Livro De Métodos_springer.pdf

Ulysses Paulino Albuquerque Reinaldo Farias Paiva de Lucena Luiz Vital Fernandes Cruz da Cunha Rômulo Romeu Nóbrega Alves Editors

Methods and Techniques in Ethnobiology and Ethnoecology Second Edition

SPRINGER PROTOCOLS HANDBOOKS

For further volumes: http://www.springer.com/series/8623

Methods and Techniques in Ethnobiology and Ethnoecology Second Edition

Edited by

Ulysses Paulino Albuquerque Departamento de Botânica, Universidade Federal de Pernambuco, Recife, Brazil

Reinaldo Farias Paiva de Lucena Departamento de Sistemática e Ecologia, Universidade Federal da Paraiba, João Pessoa, Paraíba, Brazil

Luiz Vital Fernandes Cruz da Cunha Departamento de Ciências Biológicas, Universidade Católica de Pernambuco, Recife, Brazil

Rômulo Romeu Nóbrega Alves Departamento de Biologia, Universidade Estadual da Paraíba, Campina Grande, Brazil

Editors Ulysses Paulino Albuquerque Departamento de Botaˆnica Universidade Federal de Pernambuco Recife, Brazil

Reinaldo Farias Paiva de Lucena Departamento de Sistema´tica e Ecologia Universidade Federal da Paraiba Joa˜o Pessoa, Paraı´ba, Brazil

Luiz Vital Fernandes Cruz da Cunha Departamento de Cieˆncias Biolo´gicas Universidade Cato´lica de Pernambuco Recife, Brazil

Roˆmulo Romeu No´brega Alves Departamento de Biologia Universidade Estadual da Paraı´ba Campina Grande, Brazil

ISSN 1949-2448 ISSN 1949-2456 (electronic) Springer Protocols Handbooks ISBN 978-1-4939-8918-8 ISBN 978-1-4939-8919-5 (eBook) https://doi.org/10.1007/978-1-4939-8919-5 Library of Congress Control Number: 2018959858 © Springer Science+Business Media, LLC, part of Springer Nature 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Humana Press imprint is published by the registered company Springer ScienceþBusiness Media, LLC part of Springer Nature. The registered company address is: 233 Spring Street, New York, NY 10013, U.S.A.

Overview Ethnobiology and ethnoecology have become very popular in recent years. Particularly in the last 25 years, several manuals of methods have been prepared and comprised the most classical approaches to the subject. However, there have been many advances in research because of interaction with different disciplines but also due to new, original, and interesting questions. When we published the first edition of Methods and Techniques in Ethnobiology and Ethnoecology (Springer/Humana Press, 2014), we were focused on presenting to the reader the most popular and usual approaches as well as the methods of disciplines that interact with ethnobiology, such as ecology, microbiology, and phytochemistry. The intention was that each chapter should be a script that would allow the researcher to know each of the methods described in the literature as well as to make the best choices for their own research. The vision for this handbook is to provide the current state-of-the-art methods and techniques that are applied in the research and related fields of anyone interested in ethnobiology and ethnoecology. This new volume, besides bringing new and original aspects of what is found in the literature, fills some of the gaps not covered in volume 1 (first edition). We divided the book into 4 parts covering a total of 21 new chapters. In the first part, we approached the most systematic treatment of methods and techniques in qualitative research. The chapters cover everything from the initial stages of preparing a research to the initial methods of treating and analyzing the data. In the second part, we delve into quantitative approaches from a more detailed discussion on the use of the hypothetico-deductive method and univariate and multivariate statistical approaches in ethnobiology research. In the third part, the chapters address the theoretical and methodological challenges of ethnobiology and its interaction with specific fields of knowledge, such as historical ecology. In the latter part, the chapters provide a description of methods used in other disciplines such as phytochemistry, ecology, zoology, and conservation biology. Along with the various methods covered in each chapter, the handbook also includes an extensive bibliography that details the current literature available in the field. Recife, Brazil ˜ o Pessoa, Paraı´ba, Brazil Joa Recife, Brazil Campina Grande, Paraı´ba, Brazil

Ulysses Paulino Albuquerque Reinaldo Farias Paiva de Lucena Luiz Vital Fernandes Cruz da Cunha Roˆmulo Romeu No brega Alves

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Acknowledgments A debt of gratitude is owed to many people who assisted on the preparation of this book. We thank all the authors who accepted our invitation to write the chapters for this new edition. We are especially grateful to the National Council for Scientific and Technological Development (CNPq) for financial support in the form of scholarships for scientific productivity provided to RRNA and UPA. Some of the chapters included were supported by the National Institute of Science and Technology in Ethnobiology, Bioprospecting and Nature Conservation, certified by CNPq, with financial provision from FACEPE (Foundation for the Support of Science and Technology of the State of Pernambuco - APQ-0562-2.01/17).

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Contents Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

PART I

METHODS AND QUALITATIVE TECHNIQUES

1 Preparation of Qualitative Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Joelson Moreno Brito Moura, Risoneide Henriques da Silva, Nylber Augusto da Silva, Daniel Carvalho Pires de Sousa, and Ulysses Paulino Albuquerque 2 Implementing Ethnobiological Research: Pretests, Quality Control, and Protocol Reviews. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Temoteo Luiz Lima da Silva, Joelson Moreno Brito Moura, Juliane Souza Luiz Hora, Edwine Soares de Oliveira, Andre´ dos Santos Souza, Nylber Augusto da Silva, and Ulysses Paulino Albuquerque 3 Participant Observation and Field Journal: When to Use and How to Analyze . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Juliana Loureiro Almeida Campos, Taline Cristina da Silva, and Ulysses Paulino Albuquerque 4 Audio and Video Recording Techniques for Ethnobiological Research . . . . . . . . Simone de Hek and Ana Ladio 5 Qualitative Data Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ˜ es, Daniel Carvalho Pires de Sousa, Henrique Fernandes Magalha Edwine Soares de Oliveira, and Ulysses Paulino Albuquerque 6 Discourse of the Collective Subject as a Method for Analysis of Data in Ethnobiological Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Izabel Cristina Santiago Lemos, Gyllyandeson de Arau´jo Delmondes, Diogenes de Queiroz Dias, Irwin Rose Alencar de Menezes, George Pimentel Fernandes, and Marta Regina Kerntopf

PART II

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3

15

25

35 45

55

METHODS AND QUANTITATIVE TECHNIQUES

7 Going Back to Basics: How to Master the Art of Making Scientifically Sound Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thiago Gonc¸alves-Souza, Diogo B. Provete, Michel V. Garey, Fernando R. da Silva, and Ulysses Paulino Albuquerque 8 Multidimensional Analyses for Testing Ecological, Ethnobiological, and Conservation Hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thiago Gonc¸alves-Souza, Michel V. Garey, Fernando R. da Silva, Ulysses Paulino Albuquerque, and Diogo B. Provete

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9 The Use of Multivariate Tools in Studies of Traditional Ecological Knowledge and Management Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Cristina Baldauf and Nivea Dias dos Santos 10 The Spatiotemporal Scale of Ethnobiology: A Conceptual Contribution in the Application of Meta-Analysis and the Development of the Macro-Ethnobiological Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Tania Vianney Gutie´rrez-Santilla´n, David Valenzuela-Galva´n, Ulysses Paulino Albuquerque, Francisco Reyes-Zepeda, Leonardo Uriel Arellano-Me´ndez, Arturo Mora-Olivo, Luis-Bernardo Va´zquez 11 Collection and Analysis of Environmental Risk Perception Data . . . . . . . . . . . . . . 149 ˜ es, Regina Ce´lia da Silva Oliveira, Henrique Fernandes Magalha Ivanilda Soares Feitosa, and Ulysses Paulino Albuquerque

PART III

METHODOLOGICAL AND THEORETICAL CHALLENGES

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Ethnoecology in Pluricultural Contexts: Theoretical and Methodological Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Julio A. Hurrell, Pablo C. Stampella, Marı´a B. Doumecq, and Marı´a L. Pochettino 13 Ethnobotany and Ethnoecology Applied to Historical Ecology . . . . . . . . . . . . . . . Mariana Franco Cassino, Rubana Palhares Alves, Carolina Levis, Jennifer Watling, Andre´ Braga Junqueira, Myrtle P. Shock, Maria Julia Ferreira, Victor Lery Caetano Andrade, Laura P. Furquim, Sara Deambrozi Coelho, Eduardo Kazuo Tamanaha, Eduardo Go es Neves, and Charles R. Clement 14 Challenges in Ethnozoological Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Roˆmulo Romeu Nobrega Alves and Wedson Medeiros Silva Souto 15 Biocultural Collections and Participatory Methods: Old, Current, and Future Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Viviane Stern da Fonseca-Kruel, Luciana Martins, Aloisio Cabalzar, Claudia Leonor Lopez-Garce´s, Ma´rlia Coelho-Ferreira, Pieter-Jan van der Veld, William Milliken, and Mark Nesbitt 16 Protocols and Ethical Considerations in Ethnobiological Research . . . . . . . . . . . . Sofia Zank, Rafaela Helena Ludwinsky, Graziela Dias Blanco, and Natalia Hanazaki

PART IV 17 18

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187

209

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229

METHODS AND TECHNIQUES OF RELATED AREAS

Methods in the Extraction and Chemical Analysis of Medicinal Plants . . . . . . . . . 257 Akram M. Salam, James T. Lyles, and Cassandra L. Quave Evaluation of the Antibacterial and Modulatory Activities of Zootherapeutics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 Dio genes de Queiroz Dias, De´bora Lima Sales, Felipe Silva Ferreira, Izabel Cristina Santiago Lemos, Gyllyandeson de Arau´jo Delmondes, Renata Evaristo Rodrigues Silva, Jose´ Galberto Martins da Costa, Marta Regina Kerntopf, Henrique Douglas Melo Coutinho, Roˆmulo Romeu Nobrega Alves, and Walte´cio de Oliveira Almeida

Contents

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Population Ecology of Plant Species Subjected to Extractivism: Collection and Data Analysis Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293 Juliana Loureiro Almeida Campos, Ivanilda Soares Feitosa, and Ulysses Paulino Albuquerque 20 Noninvasive Sampling Techniques for Vertebrate Fauna . . . . . . . . . . . . . . . . . . . . . 309 Leonardo da Silva Chaves, Christini Barbosa Caselli, Rafael de Albuquerque Carvalho, and Roˆmulo Romeu No brega Alves 21 Techniques to Evaluate Hunting Sustainability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 Leonardo da Silva Chaves, Christini Barbosa Caselli, Andre´ Luiz Borba Nascimento, and Roˆmulo Romeu No brega Alves Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contributors ULYSSES PAULINO ALBUQUERQUE  Laboratorio de Ecologia e Evoluc¸a˜o de Sistemas Socioecologicos (LEA), Departamento de Botaˆnica, Centro de Biocieˆncias, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil RAFAEL DE ALBUQUERQUE CARVALHO  Department of Genetics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil RUBANA PALHARES ALVES  Programa de Pos Graduac¸a˜o em Ecologia, Instituto Nacional de Pesquisas da Amazoˆnia (INPA), Manaus, Amazonas, Brazil VICTOR LERY CAETANO ANDRADE  Department of Archaeology, Max Planck Institute for the Science of Human History, Jena, Thu¨ringen, Germany GYLLYANDESON DE ARAU´JO DELMONDES  Department of Biological Chemistry/CCBS, Regional University of Cariri (URCA), Crato, Ceara´, Brazil LEONARDO URIEL ARELLANO-ME´NDEZ  Instituto de Ecologı´a Aplicada, Universidad Autonoma de Tamaulipas, Ciudad Victoria, Tamaulipas, Mexico CRISTINA BALDAUF  Department of Biosciences, Federal Rural University of Semiarid Region (UFERSA), Mossoro, Rio Grande do Norte, Brazil GRAZIELA DIAS BLANCO  Laboratorio de Ecologia Humana e Etnobotaˆnica, ECZ/CCB, Universidade Federal de Santa Catarina, Florianopolis, Santa Catarina, Brazil ALOISIO CABALZAR  Programa Rio Negro, Instituto Socioambiental, Sa˜o Paulo, SP, Brazil JULIANA LOUREIRO ALMEIDA CAMPOS  Laboratorio de Ecologia e Evoluc¸a˜o de Sistemas Socioecologicos, Departamento de Botaˆnica, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil CHRISTINI BARBOSA CASELLI  Biology Department, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil MARIANA FRANCO CASSINO  Laboratorio de Arqueologia, Instituto de Desenvolvimento Sustenta´vel Mamiraua´ (IDSM), Tefe´, Amazonas, Brazil CHARLES R. CLEMENT  Coordenac¸a˜o de Tecnologia e Inovac¸a˜o, Instituto Nacional de Pesquisas da Amazoˆnia (INPA), Manaus, Amazonas, Brazil SARA DEAMBROZI COELHO  Programa de Pos Graduac¸a˜o em Ecologia, Instituto Nacional de Pesquisas da Amazoˆnia (INPA), Manaus, Amazonas, Brazil ´ MARLIA COELHO-FERREIRA  Coordenac¸a˜o de Botaˆnica, Museu Paraense Emı´lio Goeldi, Bele´m, Para´, Brazil HENRIQUE DOUGLAS MELO COUTINHO  Regional University of Cariri, Crato, Ceara´, Brazil JOSE´ GALBERTO MARTINS DA COSTA  Regional University of Cariri, Crato, Ceara´, Brazil MARI´A B. DOUMECQ  Laboratorio de Etnobota´nica y Bota´nica Aplicada (LEBA), Facultad de Ciencias Naturales y Museo (FCNM), Universidad Nacional de La Plata (UNLP), La Plata, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Cientı´ficas y Te´cnicas (CONICET), La Plata, Buenos Aires, Argentina IVANILDA SOARES FEITOSA  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil FELIPE SILVA FERREIRA  Federal University of San Francisco Valley, Senhor do Bonfim, Bahia, Brazil

xiii

xiv

Contributors

MARIA JULIA FERREIRA  Programa de Pos Graduac¸a˜o em Botaˆnica, Instituto Nacional de Pesquisas da Amazoˆnia (INPA), Manaus, Amazonas, Brazil LAURA P. FURQUIM  Museum of Archaeology and Ethnology (MAE), University of Sa˜o Paulo (USP), Sa˜o Paulo, Brazil GEORGE PIMENTEL FERNANDES  Regional University of Cariri (URCA), Department of Education/CE, Crato, Ceara´, Brazil VIVIANE STERN DA FONSECA-KRUEL  Instituto de Pesquisas Jardim Botaˆnico do Rio de Janeiro, Rio de Janeiro, Brazil MICHEL V. GAREY  Laboratorio de Ecologia de Metacomunidades, Instituto LatinoAmericano de Cieˆncias da Vida e da Natureza, Universidade Federal da Integrac¸a˜o Latino-Americana, Foz do Iguac¸u, Parana´, Brazil THIAGO GONC¸ALVES-SOUZA  Laboratorio de Ecologia Filogene´tica e Funcional (ECOFFUN), Departamento de Biologia, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil TANIA VIANNEY GUTIE´RREZ-SANTILLA´N  Instituto de Ecologı´a Aplicada, Universidad Autonoma de Tamaulipas, Ciudad Victoria, Tamaulipas, Mexico NATALIA HANAZAKI  Laboratorio de Ecologia Humana e Etnobotaˆnica, ECZ/CCB, Universidade Federal de Santa Catarina, Florianopolis, Santa Catarina, Brazil SIMONE DE HEK  Department for Information Management and Communication, National Institute for Agricultural Technology (INTA), San Carlos de Bariloche, Rio Negro, Argentina JULIANE SOUZA LUIZ HORA  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil JULIO A. HURRELL  Laboratorio de Etnobota´nica y Bota´nica Aplicada (LEBA), Facultad de Ciencias Naturales y Museo (FCNM), Universidad Nacional de La Plata (UNLP), La Plata, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Cientı´ficas y Te´cnicas (CONICET), La Plata, Buenos Aires, Argentina ANDRE´ BRAGA JUNQUEIRA  International Institute for Sustainability, Rio de Janeiro, Brazil MARTA REGINA KERNTOPF  Department of Biological Chemistry/CCBS, Regional University of Cariri (URCA), Crato, Ceara´, Brazil ANA LADIO  INBIOMA-Instituto de Investigaciones en Biodiversidad y Medio AmbienteCONICET-National Council of Scientific Research of Argentina, National University of Comahue, San Carlos de Bariloche, Rio Negro, Argentina IZABEL CRISTINA SANTIAGO LEMOS  Department of Nursing/CCBS, Regional University of Cariri (URCA), Crato, Ceara´, Brazil; Federal Rural University of Pernambuco, Recife, Pernambuco, Brazil CAROLINA LEVIS  Programa de Pos Graduac¸a˜o em Ecologia, Instituto Nacional de Pesquisas da Amazoˆnia (INPA), Manaus, Amazonas, Brazil CLAUDIA LEONOR LO´PEZ-GARCE´S  Coordenac¸a˜o de Cieˆncias Humanas—Antropologia, Museu Paraense Emı´lio Goeldi, Bele´m, Para´, Brazil RAFAELA HELENA LUDWINSKY  Laboratorio de Ecologia Humana e Etnobotaˆnica, ECZ/CCB, Universidade Federal de Santa Catarina, Florianopolis, Santa Catarina, Brazil JAMES T. LYLES  Center for the Study of Human Health, Emory University, Atlanta, GA, USA HENRIQUE FERNANDES MAGALHA˜ES  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil

Contributors

xv

LUCIANA MARTINS  Cultures and Languages, Birkbeck, University of London, London, UK IRWIN ROSE ALENCAR DE MENEZES  Department of Biological Chemistry/CCBS, Regional University of Cariri (URCA), Crato, Ceara´, Brazil WILLIAM MILLIKEN  Royal Botanic Gardens, Kew, Surrey, UK ARTURO MORA-OLIVO  Instituto de Ecologı´a Aplicada, Universidad Autonoma de Tamaulipas, Ciudad Victoria, Tamaulipas, Mexico JOELSON MORENO BRITO MOURA  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil ANDRE´ LUIZ BORBA NASCIMENTO  Laboratorio de Ecologia e Evoluc¸a˜o de Sistemas Socioecologicos, Department of Botany, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil MARK NESBITT  Royal Botanic Gardens, Kew, Surrey, UK EDUARDO GO´ES NEVES  Museum of Archaeology and Ethnology (MAE), University of Sa˜o Paulo (USP), Sa˜o Paulo, Brazil ˆ ROMULO ROMEU NO´BREGA ALVES  Departamento de Biologia, Universidade Estadual da Paraı´ba, Campina Grande, Brazil EDWINE SOARES DE OLIVEIRA  Laboratorio de Ecologia e Evoluc¸a˜o de Sistemas Socioecologicos, Departamento de Botaˆnica, Centro de Biocieˆncias, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil WALTE´CIO DE OLIVEIRA ALMEIDA  Regional University of Cariri, Crato, Ceara´, Brazil MARI´A L. POCHETTINO  Laboratorio de Etnobota´nica y Bota´nica Aplicada (LEBA), Facultad de Ciencias Naturales y Museo (FCNM), Universidad Nacional de La Plata (UNLP), La Plata, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Cientı´ficas y Te´cnicas (CONICET), La Plata, Buenos Aires, Argentina DIOGO B. PROVETE  Laboratorio de Sı´ntese em Biodiversidade, Setor de Ecologia, Instituto de Biocieˆncias, Universidade Federal de Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul, Brazil DIO´GENES DE QUEIROZ DIAS  Federal Rural University of Pernambuco, Recife, Pernambuco, Brazil CASSANDRA L. QUAVE  Dermatology and Human Health, Emory University, Atlanta, GA, USA FRANCISCO REYES-ZEPEDA  Instituto de Ecologı´a Aplicada, Universidad Autonoma de Tamaulipas, Ciudad Victoria, Tamaulipas, Mexico AKRAM M. SALAM  Program in Molecular and Systems Pharmacology, Emory University, Atlanta, GA, USA DE´BORA LIMA SALES  Regional University of Cariri, Crato, Ceara´, Brazil NIVEA DIAS DOS SANTOS  Department of Botany, Federal Rural University of Rio de Janeiro (UFRRJ), Serope´dica, Rio de Janeiro, Brazil ANDRE´ DOS SANTOS SOUZA  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil MYRTLE P. SHOCK  Programa de Antropologia e Arqueologia, Universidade Federal do Oeste do Para´, Santare´m (UFOPA), Santare´m, Para´, Brazil FERNANDO R. DA SILVA  Laboratorio de Ecologia Teorica: Integrando Tempo, Biologia e Espac¸o (LET.IT.BE), Departamento de Cieˆncias Ambientais, Universidade Federal de Sa˜o Carlos, Sa˜o Paulo, Brazil

xvi

Contributors

NYLBER AUGUSTO DA SILVA  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil RENATA EVARISTO RODRIGUES DA SILVA  Regional University of Cariri, Crato, Ceara´, Brazil RISONEIDE HENRIQUES DA SILVA  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil TALINE CRISTINA DA SILVA  Universidade Estadual de Alagoas, Recife, Pernambuco, Brazil TEMO´TEO LUIZ LIMA DA SILVA  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil LEONARDO DA SILVA CHAVES  Department of Biology, Post-graduation Program of Ethnobiology and Nature Conservation, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil REGINA CE´LIA DA SILVA OLIVEIRA  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil DANIEL CARVALHO PIRES DE SOUSA  Departamento de Biologia, Programa de Pos-graduac¸a˜o em Etnobiologia e Conservac¸a˜o da Natureza (PPGEtno), Universidade Federal Rural de Pernambuco (UFRPE–Brasil), Recife, Pernambuco, Brazil WEDSON MEDEIROS SILVA SOUTO  Laboratorio de Etnobiologia e Ecologia Vegetal (LEEV), Departamento de Biologia, Universidade Federal do Piauı´, Teresina, Piauı´, Brazil PABLO C. STAMPELLA  Laboratorio de Etnobota´nica y Bota´nica Aplicada (LEBA), Facultad de Ciencias Naturales y Museo (FCNM), Universidad Nacional de La Plata (UNLP), La Plata, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Cientı´ficas y Te´cnicas (CONICET), La Plata, Buenos Aires, Argentina EDUARDO KAZUO TAMANAHA  Laboratorio de Arqueologia, Instituto de Desenvolvimento Sustenta´vel Mamiraua´ (IDSM), Tefe´, Amazonas, Brazil DAVID VALENZUELA-GALVA´N  Departamento de Ecologı´a Evolutiva, Centro de Investigacion en Biodiversidad y Conservacion, Universidad Autonoma del Estado de Morelos, Cuernavaca, Morelos, Mexico PIETER-JAN VAN DER VELD  Programa Rio Negro, Instituto Socioambiental, Sa˜o Paulo, SP, Brazil LUIS-BERNARDO VA´ZQUEZ  Departamento de Agricultura, Sociedad y Ambiente, El Colegio de la Frontera Sur Unidad San Cristobal de Las Casas, San Cristobal de Las Casas, Chiapas, Mexico JENNIFER WATLING  Museum of Archaeology and Ethnology (MAE), University of Sa˜o Paulo (USP), Sa˜o Paulo, Brazil SOFIA ZANK  Laboratorio de Ecologia Humana e Etnobotaˆnica, ECZ/CCB, Universidade Federal de Santa Catarina, Florianopolis, Santa Catarina, Brazil

Part I Methods and Qualitative Techniques

Chapter 1 Preparation of Qualitative Research Joelson Moreno Brito Moura, Risoneide Henriques da Silva, Nylber Augusto da Silva, Daniel Carvalho Pires de Sousa, and Ulysses Paulino Albuquerque Abstract In this chapter, we present a brief discussion about qualitative research, an approach widely used in social sciences to understand the phenomena that involve humans. Due to the importance given to the subjective perspective of the researcher and the participants being studied, this approach proved to be an important tool to understand the social relations of the most varied human groups. First, a brief history of qualitative research and its main features are presented. Then, we show the steps that the researcher must follow before starting his research. Finally, we have outlined some of the main methods used in qualitative research— ethnography, phenomenology, action research, grounded theory and case study—with some practical examples of how they can be used in ethnobiological studies. Key words Ethnobiology, Ethnography, Social-ecological systems, Ethics

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Introduction Qualitative research is a widely used approach, especially in social sciences, to understand any phenomenon that involves human beings and their social relations in the most varied environments. Since the 1920s, the fields of Psychology and Social Sciences have been applying qualitative methods [1]. In the sociology applied in the USA, for example, biographical methods, case studies, and descriptive methods—all employed in qualitative research—were central throughout the 1940s. However, as the complexity of the phenomena studied by that science increased, the use of the qualitative approach decreased and there was a greater demand for quantitative methods [1]. It was only in the 1960s that there was a strong criticism of the use of quantitative methods, due to its lack of subjectivity to understand human beings, which made the relevance of qualitative methods reemerge (see [1]).

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_1, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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Some of the most striking features of qualitative research are the use of different theoretical methods and perspectives, as well as the importance given to the subjective point of view of the researcher and the people being studied. The qualitative approach is often used in descriptive studies that investigate the human populations of a given region. These descriptions may be related to the customs, beliefs, and language of some social group. In addition, qualitative research can help in describing how people are dealing with events and circumstances in which they are involved, such as lack of food due to some catastrophe (see [2, 3]). Once the decision to implement a qualitative research is made, the novice researcher must have a considerable understanding of existing approaches to identify which one is best applied to their questioning. By doing this, the common mistake of not knowing where to start or not knowing what data to collect can be avoided. In this sense, we will show the main methods and the steps necessary to execute a qualitative and robust qualitative research.

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Preparation and Execution of Qualitative Research The preparation and execution of a qualitative research requires that some steps be followed to avoid difficulties during its accomplishment. Thus, we show below two important steps to perform a quality research.

2.1 Bibliographic Review and Research Question

Before beginning a qualitative research, an essential step is the accomplishment of a robust bibliographical review to understand the state of the art of the phenomenon to be studied. According to Flick [1], a common mistake in qualitative research textbooks is not to address in their chapters the relevance of using existing literature to address the researcher’s questions. This is a reflection of an old understanding of qualitative research, which occurred more specifically in its emergence, where any studied aspect of a human population was new. It is a misconception to think that there are completely new areas of knowledge to explore, where nothing has been published previously. However, even considering that not everything has been researched, almost everything one wants to research will probably be intertwined with an existing scientific field [1]. Performing a literature review is essential, as it helps the researcher to understand: the concepts used and discussed; the theoretical and methodological debates or controversies existing in the approach used; what has not yet been investigated; the social situation of the population that is intended to be interviewed or observed, and other advantages [1].

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Understanding the state of the art makes it possible to identify gaps—open questions—and with this, it is possible to formulate a research question that is relevant and pertinent to the advancement of its field of interest. This is a fundamental step that will determine the success and guide the entire study [1]. In all research, in order to be successful, the research question must determine the best approach to be used—whether qualitative or quantitative, for example, because the chosen method must fit the question that we intend to address as scientists [4]. 2.2 Choice of Research Location and Ethical Issues

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Studying humans demands special attention to ethical issues. Before beginning the study, the researcher must obtain all the necessary legal authorizations to execute the research in a certain location. Authorizations may vary according to the region or country, but in the ethical sphere, something that the researcher cannot fail to obtain is the consent of the people who agree to participate in their study, a universal requirement [5]. In Brazil, for example, to execute a research involving human beings, it is necessary: elaboration of a research protocol; approval of the protocol by a Research Ethics Committee (REC); obtaining the consent of the participant through an Informed Consent Form (ICF) that clarifies the purpose of the research, risks, benefits, permission to disclose the results, among other clarifications. In view of the different requirements for obtaining certain authorizations, in addition to the time required, when choosing a research location one should consider the feasibility of obtaining the relevant authorizations. Certain human populations, such as the indigenous ones, have particularities that require specific authorizations different from those required to study a population of traditional fishermen, for example, and this may invalidate all research. Thus, the question of how to gain access to the field—that is, to the research site—and to people, is crucial in a qualitative study [1].

Methods to Develop Qualitative Research

3.1 Action Research Method

Action research is a method of the social sciences that uses a cyclical way in reflecting on the improvements and/or solutions to the practical problems that occur during a research activity [6]. Thus, because it has interventionist characteristics, it is usually used by researchers who seek to understand and overcome the difficulties that arise in the learning process [7–9]. This tool involves the participation of various types of social actors and can be considered very useful in solving “immediate” problems that require “urgent” solutions [10].

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The objectives of this method can be characterized in two different perspectives: (1) assisting the researcher in the organization of a set of steps to guide the improvement of field practices [11]—for example, to adapt the manner of conducting the interviews to improve the collection of data on a particular domain of knowledge; and (2) as a tool for social change in the human group studied, critically analyzing their power structures and investigating the best ways of empowerment and social transformation [12]. After identifying a “problem”, the practitioner,1 either using or not using research techniques already established in the literature, plans the best alternatives of action that must be performed, monitors the results obtained from these actions, and then evaluates which are the most efficient and why they tend to be so. Thus, after reflecting on which changes were best or not, they use or recommend a “solution” (see [7, 11, 13]). This process involves the use of systematic approaches in the identification of information for decision-making, and therefore may assist some ethnobiological studies in the construction of practical solutions that may arise during the exercise of research activities. According to Tripp [11], there are three main types of action research: (1) technique, in which the solution is tested by borrowing another methodological tool, applying it directly in the actual sphere in which it is sought to effect improvement; (2) practice, which uses the action research cycle in the development of the changes made to reach the determined goal, being the practitioner stimulated to question what, how and when to make and apply these changes, always seeking to include all social actors involved; and (3) politics, when the objective is to have the intention of transforming the knowledge or beliefs of the group in relation to changes in their cultural systems—for example, the re-signification of social prejudices. The choice of the best approach depends on the situation of the research and how researchers articulate the questions cooperatively with each other or between the object of study [9]. 3.2

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Ethnography

Ethnography can be understood as a method for collecting data based on the direct contact of the researcher with the target individuals or groups of people, during a given period, in which participant observation and/or interviews are used to investigate and describe phenomena in a given context [14, 15].

In this chapter, “practitioners” are the actors involved in performing any research, teaching, or extension practice.

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The term, originated from the fusion of the words “people”— ethnos—and “written representation”—graphe—appeared in the late nineteenth and early twentieth centuries, from the need of researchers of that period to investigate the habit and customs of populations considered exotic [16]. Ethnography is a method that requires a lot of time to be performed properly. Usually a year or more of field work and an equal period for the maturation process with the people being studied [17, 18]. In this period, the researchers involved in the study are expected to approach the phenomenon analyzed in an effort to obtain a richer view, as experienced by individuals in the investigated context [19, 20]. During this period, the desired information can be obtained through the integration of other methods—such as participant observation and interviews—these being guided by the research objectives and by the researcher’s methodological positioning, regarding the manner the research questions can be answered [21]. Among the other techniques used to obtain data with the ethnographic method, researchers can also use methods such as focus groups, life histories, photographic records, video recordings, mapping, among others [22]. Through the triangulation of these methods, the researcher can provide a representation and reliably interpret what the participants say in their own words and in the ways in which they behave [23]. 3.3

Phenomenology

Phenomenology is a word of Greek origin composed by the words phainomenon, which means a thing as it appears, an appearance, and logos, which means what it unites, unifies, among others [24]. The term has wide use and can assume different meanings depending on the context it finds. For example, in the philosophical perspective, phenomenology is associated with a philosophical movement on how to look at the world. However, in the methodological sense, the term provides aspects of how to conduct qualitative research [25]. The phenomenological approach in qualitative research is intended to describe the meaning of a concept or phenomenon from the lived experience by several individuals [26]. Thus, the adoption of this approach offers the researchers the possibility of reducing individual experiences of an “X” phenomenon to a description of its universal essence [27]. In order to achieve this goal, the researcher will conduct the research employing the following steps: (1) identification of a phenomenon to study; (2) collecting information about how people experience this phenomenon; and (3) description of what is common in these experiments, which is considered the essence of the phenomenon

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studied [28]. Access to such information can be obtained from other methods, including interviews, conversations, participant observation, action research, focus meetings, diary analysis, and other personal texts [29]. Overall, the phenomenological method is designed to be less structured and more open, in order to encourage the participants to share details about their experience. In other words, phenomenology emphasizes subjectivity. The objective of this method is to maximize the depth of the information collected and, therefore, less structured interviews are more effective [29]. An example of the adoption of the phenomenological method can be found in the study by Anggerainy et al. [30]. This method was used for understanding the phenomena related to the use of traditional medicine by the Davak tribe in Borneo, Indonesia. In order to reach their objectives, these authors developed their research by employing the following steps: 3.3.1 Identification of a Phenomenon to Study

They sought to identify the factors that lead people in the Davak tribe to adopt traditional medicine to treat sick children at home instead of seeking conventional medical care.

3.3.2 Collection of Information About How People Experience This Phenomenon

The researchers intentionally selected and interviewed Dayak caregivers who treated sick children at home using traditional medicine before deciding to seek care in modern health facilities. Information about this practice was obtained through comprehensive interviews and voice recording, and these data were analyzed through content analysis—it is an analysis that quantifies the frequency of occurrence of a given term in a text.

3.3.3 Description of the Similarities Between These Experiences (Essence of the Phenomenon)

Based on the report of ten selected informants, the authors identified six main themes in the use of traditional medicine by the Dayak tribe to treat sick children: (1) traditional medicine as first aid; (2) ease of access and cost-effectiveness; (3) traditional medicine has not always been effective; (4) a combination of natural ingredients and beliefs; (5) the importance of “communicating” with plants; and (6) involvement with metaphysical forces. Thus, the authors conclude that the recurring themes identified in Davak’s traditional medicine for the treatment of children may help to reconcile their use with conventional medical care when necessary.

3.4

Grounded theory (GT) is a method of analysis and collection of constant comparison between categories of study, which allows the researcher to know in advance the “emergent properties” of a phenomenon, before beginning the inductive process of formulating the research questions [31]. These properties

Grounded Theory

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are the first relationships verified between different levels of experience between actors and social environments, systematically orienting qualitative research in the process of creation of theories [32–34]. In GT, after the collection of material related to the world views, experiences, feelings and intentions of the studied social actors—through interviews, audio and video recordings, participant observation, etc.—the steps to develop a theory based on data can take several paths that depend on the objectives of the research, but always begin after the first categorizations. The end of the process occurs in the identification of codes and social structures and the possibility of theorizing about the relations between them. For example, in the study of D’Avigdor et al. [35], the authors sought to understand the current state of knowledge about plants and medicinal herbs of a community in Ethiopia. For this, they conducted 15 interviews integrating methods of life history, focus groups, open and semi-structured questionnaires. The open questions sought to understand, for example, “how do you use this plant?” “With whom did you learn to prepare these remedies?” “What do you call that plant?” After transcription and analysis of the data through the GT logic, some main themes that were similar between the interviewees were identified. Among the themes identified by the authors are: “awareness of the decrease of vegetation,” “the need to conserve herbs and medicinal plants,” and “safety in the manner of preparing medicines.” In Box 1 we show the steps that must be followed to develop the GT.

Box 1 Steps to Develop the Grounded Theory: Imagine that you want to study the factors that influence the sharing of information among the firewood collectors of a given location using GT. The necessary steps would be: 1. Exploratory stage. After defining the questioning of the study, the first step of GT is exploratory, conducting pilot interviews with the first informants of the study to collect reports of personal experiences about the use of firewood—the selection of participants is intentional and directed to the context and the question investigated in the study [36]. Interviews can be individual or in focus groups. Questions should be open, such as “tell me a little bit about how you collect firewood,” “for how long have you been collecting?” “What are the major difficulties in collecting?” “How do you solve these difficulties?” “Which places have the greatest amount

(continued)

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Box 1 (continued) of firewood?” The use of audio recorders and memorandum writing, field notes and reports of participant observations are strongly recommended to enrich the analysis of codes [1]. 2. Coding stage. After the transcription of the information obtained, the second step of the GT is the initial coding, focused line-by-line (see Seidel and Recker [37]). The information goes through a process of codification and comparison of categories that indicates possible speeches on main themes that are similar among the participants. For example, the following topics can be identified: how the knowledge about firewood is acquired from the previous generation, awareness about the reduction of firewood availability, collection safety, among other topics (see the study of D’Avigdor et al. [35]). 3. Theoretical sampling stage. In the theoretical sampling stage, the coded information is now analyzed and the relationships between the discourses begin to indicate the first categorical relationships, assisting the researcher in the construction of possible explanations of the data [38]. For example, “the skills of firewood collectors” would be influencing the “way that knowledge is being passed on” because “those who have more skill do not like to share information.” These could be the first questions of the research and the theoretical sampling that would direct new collections in order to saturate these categories and concretize the relations in that social group. 4. Theorizing stage. In this last stage, the researcher finds at a possible explanation of the relations found between the categories. This step is the result of a thorough process of collecting and analyzing the phenomenon and presents a structured set of relationships about the environment, allowing the researchers to discuss their characteristics or propose improvements to problems identified in the data. At the end of our research with firewood collectors, we could conclude, for example, that skill and time of experience are the main factors that influence the little interaction between collectors.

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Identification of the topic or question of interest

Careful analysis of information about "the case"

Narration of results

Information gathering

Fig. 1 Stages of the case study, adapted from Hancock and Algozzine [42]

3.5

Case Study

The case study allows the exploration and understanding of complex issues, especially when a deep investigation is necessary, consisting of a detailed investigation of groups or organizations, with the purpose of providing an analysis of the context and processes involved in the phenomenon under study [39–41]. This method allows the researcher to go beyond the quantitative results and to understand for example behavioral conditions [40]. The case study can present four steps, represented in Fig. 1 according to Hancock and Algozzine [42]. Within the ethnobiological context, for example, the researcher can represent knowledge and cultural practices associated with health and disease cure in a medical system, providing a comprehensive guide of the behavior adopted by the members of the society studied. According to Zainal [40], there are three categories for the case study: exploratory, descriptive, and explanatory.

3.5.1 Exploratory Case Study

It explores any phenomenon that serves as a point of interest to the researcher. For example, a researcher conducting an exploratory case study on the use of a particular natural resource may ask the following general questions: “Is there a strategy for the use of this resource by the population?” If so, “how often?” General questions like these should be the starting point for a more thorough examination of the phenomenon to be studied.

3.5.2 Descriptive Case Study

It is used to describe the phenomena observed during the study. For example, it is employed to describe the different strategies that are used by a given population in the use of a particular natural resource. The goal set by the researcher is to describe the data as they occur. However, the challenge of the descriptive case study is that the researcher must begin with a descriptive theory to support the description of the phenomenon or history. Failing with that may lead to a not rigorous description.

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3.5.3 Explanatory Case Study

It examines the data closely, both superficially and in depth, to explain the phenomena. For example, a researcher can explain why a population uses a particular strategy for collecting a resource. In addition, it can be used to explain more complex phenomena that may arise during the case study.

References 1. Flick U (2014) An introduction to qualitative research, 5th edn. Sage, Thousand Oaks, CA, p 616 2. Kelly K (2016) A different type of lighting research: a qualitative methodology. Light Res Technol 49(8):933–942 3. Paley J (2014) Heidegger, lived experience and method. J Adv Nurs 70(7):1520–1531 4. Leppink J (2017) Revisiting the quantitative— qualitative-mixed methods labels: research questions, developments, and the need for replication. J Taibah Univ Med Sci 12(2):1–5 5. Hammersley M (2014) On the ethics of interviewing for discourse analysis. Qual Res 14 (5):529–541 6. Hannigan GG (1997) Action research: methods that make sense. Med Ref Serv Quar 16 (1):53–58 7. Bath C (2009) When does the action start and finish? Making the case for an ethnographic action research in educational research. J Educ Action Res 17(2):213–224 8. Laudonia I, Mamlok-Naaman R, Abels S, Eilks I (2017) Action research in science education – an analytical review of the literature. J Edu Action Res 26:480–495. https://doi.org/10. 1080/09650792.2017.1358198 9. Wilson V (2013) Research methods: action research. Evid Based Libr Info Pract 8 (4):160–162 10. Engel GI (2000) Pesquisa-ac¸˜ao. Educ Rev 16 (16):181–191 11. Tripp D (2005) Pesquisa-ac¸˜ao: uma introduc¸˜ao metodolo´gica. Educ Pesq 31(3):443–466 12. Oliveira RD, Oliveira MD (1990) Pesquisa social e ac¸˜ao educativa: conhecer a realidade para poder transforma´-la. In: Branda˜o CR (ed) Pesquisa participante. Editora Brasiliense, Sa˜o Paulo, pp 17–33 13. Beal XV (2011) ¿Co´mohacer investigacio´n cualitativa? Una guı´a pra´tica para saber que´ es la investigacio´n en general y co´mo hacerla, con e´nfasis en las etapas de la investigacio´n cualitativa. ETXETA, Jalisco, p 138 14. Almagor E, Skinner J (2013) Ancient ethnography: new approaches, 1st edn. Bloomsbury Publishing Pic, London, p 296

15. Creswell JW (2013) Research design: qualitative, quantitative, and mixed methods approaches, 4th edn. SAGE, Thousand Oaks, CA, p 273 16. Jones JS (2010) Origins and ancestors: a brief history of ethnography. In: Jones JS, Watt S (eds) Ethnography in social science practice. Routledge, London, pp 13–27 17. Humphreys M, Watson T (2009) Ethnographic practices: from ‘writing-up ethnographic research’ to ‘writing ethnography’. In: Ybema S, Yanow D, Wels H, Kamsteeg F (eds) Organizational ethnography: studying the complexity of everyday life. Sage Publications, Los Angeles, pp 40–55 18. Waal K (2009) Getting going: organizing ethnographic fieldwork. In: Ybema S, Yanow D, Wels H, Kamsteeg F (eds) Organizational ethnography: studying the complexity of everyday life. SAGE, Los Angeles, pp 23–39 19. Sandberg J, Tsoukas H (2011) Grasping the logic of practice: theorizing through practical rationality. Acad Manag Rev 36(2):338–360 20. Bass AE, Milosevic I (2018) The ethnographic method in CSR research: the role and importance of methodological fit. Business Soc 57 (1):1–42 21. Whitehead TL (2004) What is ethnography? Methodological, ontological, and epistemological attributes, 1st edn. CEHC, New York, p 30 22. Adams KM (2012) Ethnographic methods. In: Dwyer L, Gill A, Seertaram N (eds) Handbook of research methods in tourism: qualitative and quantitative methods. Edward Elgar/Ashgate, Northampton, MA, pp 339–351 23. Taylor SJ, Bogdan R (2010) Introduccio´n a los me´todos cualitativos de investigacio´n. La bu´squeda de significados, 1st edn. Paido´s, Barcelona, p 239 24. Silva CC, Medina P, Pinto IM (2012) A feno˜es para a pesquisa menologia e suas contribuic¸o em educac¸˜ao. InterMeio 18(36):50–63 25. Dowling M (2007) From Husserl to van Manen: a review of different phenomenological approaches. Int J Nurs Stud 44(1):131–142 26. Anthea WA (2015) Guide to phenomenological resource. Nurs Stand 29(34):38–43

Preparation of Qualitative Research 27. Creswell JW (2007) Qualitative inquiry and research design: choosing among five traditions, 2nd edn. SAGE, Thousand Oaks, p 448 28. Shi Z (2011) Dilemmas in using phenomenology to investigate elementary school children learning english as a second language. In Educ 17(1):3–13 29. Mayoh J, Onwuegbuzie AJ (2015) Toward a conceptualization of mixed methods phenomenological research. J Mix Methods Res 9 (1):91–107 30. Anggerainy SW, Wanda D, Hayati H (2017) Combining natural ingredients and beliefs: the Dayak Tribe’s experience caring for sick children with traditional medicine. Compr Child Adolesc Nurs 40(1):29–36 31. Lingard L, Albert M, Levinson W (2008) Grounded theory, mixed methods, and action research. BMJ 337(567):1–7 32. Markey K, Tilki M, Taylor G (2014) Reflecting on the challenges of choosing and using a grounded theory approach. Nurs Res 22 (2):16–22 33. Urquhart C, Lehmann H, Myers MD (2010) Putting the “theory” back into grounded theory: guidelines for grounded theory studies in information systems. Info Syst J 20 (4):357–381 34. Kenny M, Fourie R (2014) Tracing the history of grounded theory methodology: from

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formation to fragmentation. The Qual Rep 19 (52):1–9 35. D’Avigdor E, Wohlmuth H, Asfaw Z, Awas T (2014) The current status of knowledge of herbal medicine and medicinal plants in Fiche, Ethiopia. J Ethnobiol Ethnomed 10(38):1–32 36. Charmaz K (2006) Constructing grounded theory: a practical guide through qualitative analysis, 1st edn. Sage Publications Ltd, London, p 224 37. Seidel S, Recker J (2009) Using grounded theory for studying business process management phenomena. 17th European conference on information system 1–13 38. Charmaz K (2008) Grounded theory as an emergent method. In: Hesse-Biber SN, Leavy P (eds) Handbook of emergent methods. The Guilford Press, New York, pp 155–170 39. Meyer CB (2001) A case in case study methodology. Field Methods 13(4):329–352 40. Zainal Z (2007) Case study as a research method. J Kemanusiaan 5(1):1–6 41. Baxter P, Jack S (2008) Qualitative case study methodology: study design and implementation for novice researchers. Qual Rep 13 (4):544–559 42. Hancock DR, Algozzine B (2006) Doing case study research: a practical guide for beginning researchers, 1st edn. Teachers College Press, New York, p 121

Chapter 2 Implementing Ethnobiological Research: Pretests, Quality Control, and Protocol Reviews Temo´teo Luiz Lima da Silva, Joelson Moreno Brito Moura, Juliane Souza Luiz Hora, Edwine Soares de Oliveira, Andre´ dos Santos Souza, Nylber Augusto da Silva, and Ulysses Paulino Albuquerque Abstract In this chapter, we present the importance of pretests and pilot studies to identify practical problems in relation to data collection instruments. We also present recommendations for writing and structuring research instruments, as well as ways to test and revise them to ensure their validity and reliability. These stages cannot be neglected and must precede the beginning of the research to ensure that the information that will be obtained can reliably measure the phenomenon studied. Key words Validity, Reliability, Cognitive interview

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Introduction Once defined the hypotheses and research questions, researchers choose the methods that can provide the necessary information to evaluate their ideas. In the field of ethnobiology, interviews are one of the most commonly used basic techniques for obtaining information (details on the various types of interviews, their applications, advantages and disadvantages can be found in Albuquerque et al. [1]). However, before beginning data collection, researchers need to make sure that their data collection protocols (forms and/or questionnaires) will serve their purposes well by providing quality, replicable data that will answer their questions research. In this sense, the validity and replicability of the protocols are important, mainly when different researchers will use them simultaneously, or when one intends to use a protocol already validated for a new context.

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_2, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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Thus, we will focus on steps that can not be neglected in the ethnobiological research. They are pilot studies, pretests, and reliability and protocol validity evaluations. The pilot study involves the simulation of the formal process of small-scale data collection, aiming to identify practical problems in relation to the instruments, steps, and methods of the study [2]. It is in these studies that the pretests of the protocols occur. At this point, we can analyze whether our research instruments are adjusted to the local reality and the objectives of the study.

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Designing the Research Protocol The elaboration of the protocol is the ideal stage to ensure its quality and replicability. Aaker et al. [3] consider that the process of constructing a protocol corresponds to an “imperfect art,” precisely because there are no specific procedures that guarantee the quality of the instruments. However, there are some recommendations that, when followed, can facilitate this process and decrease the time and effort devoted to the future steps of evaluating the validity and reliability of the research instruments. In order to elaborate the questions that will compose the protocols, besides consulting the literature and researchers in the thematic area [4], it is recommended to visit the communities where the study will be developed to talk with local leaders and experts. This can contribute to make the writing and content of the questions more appropriate to the local reality. Clear and comprehensible language should be used, as well as a short and simple structure. This way the researcher can conduct the research with fluidity, simplicity and, mainly, does not confuse the participant. Other recommendations relevant to the elaboration and types of questions can be found in Albuquerque et al. [1]. In addition to thinking about the formulation of questions, the researcher needs to look at the order in which they will be organized, especially for self-administered questionnaires. The initial questions should be closed, simple, and need to catch the attention of the participant [5]. Avoid starting with emotional or controversial questions as they may cause discomfort in the participant [4]. Questions related to the socioeconomic profile (monthly income, age, etc.) may be placed at the end to avoid causing an initial impression of intrusion and because they are generally easier to respond [5]. More general questions should precede more specific questions, and questions that suggest a chronological order should be presented following that order [5]. Besides that, avoid including questions that are not directly related to your research goals as this may increase interview time and exhaust the participant, which would lead them to give unreliable answers.

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Pilot Study and Pretests By definition, a pilot study can be considered as a small-scale study of the proposed procedures, as well as of the techniques chosen [6]. They are mainly performed to discover flaws and/or weaknesses in research methods and tools, as well as to examine its validity and replicability [5]. Although many researchers consider that the preparation and prior planning are sufficient for the research to succeed, the execution of a pilot study is crucial because it can reveal subtle flaws in project design that would be difficult to reveal during the research planning stage. We may ask, what is the sample size that we should incorporate for a pilot study? Considering that each study presents its peculiarities, it depends on the researcher to define the number of people and how much time will be available for its accomplishment. According to Canhota [7], the number of participants in the pilot study does not need to be higher than 10% of the target sample defined for the complete study. This design would be enough to ensure results that can answer the research questions and test the instruments. In the pilot studies are performed the pretests of the research protocols, which consist in the testing and application of them to verify the accuracy and reliability of the information that will be obtained. In ethnobiological research, the main instruments that are tested in pilot studies are the questionnaires and/or forms used in the interviews. In general, the intention is only one: to test the validity of the instruments that will be used to gather information. Depending on the type of interview used in the research (structured, unstructured, or semi-structured), there are recommendations to be followed as means of assessing whether the questions used in the pretest are understood and interpreted correctly by the people. In the case of semi-structured interviews—the most used in the collection of ethnobiological data—it is recommended to use an interview guide, containing main points that can not be unnoticed at the interview [8]. Finally, providing the research protocols for other professionals of the same research field to analyze is a good recommendation that can favor their quality [5]. Thus, many of the problems with the elaboration of the questions can be discovered even before the pretest. The main advantage is that the information obtained from the pretest can be used for the main study if the research protocols elaborated do not present problems during the pilot studies, as long as they are collected by applying exactly the same approach.

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Quality Control of Protocols Research protocols need to be analyzed for reliability and validity to ensure the quality of the information that will be obtained. Reliability is related to the replicability of the research instrument, that is, its ability to obtain consistent or stable results over time or in cases it is used by two or more different researchers [9]. Validity is the degree to which the research instrument measures what it proposes to measure, that is, its ability to obtain reliable and accurate information about the phenomenon studied [10]. These two concepts are distinct and independent. Thus, search protocols can be reliable, and still not be valid, and vice versa. The reliability of the protocols can be tested by their stability and equivalence, depending on the specific characteristics of each research. Stability measures how stable the protocol is over time (assuming that what is being measured should remain constant) [9, 11] and can be verified by the test–retest technique [6]. The technique consists of the application of the protocol with the same individuals in two different moments [6], and can be performed with the entire initial n sample or with a fraction group chosen by means of randomization. The application of retest allows the researchers to observe the consistency of the responses that were obtained in the first application of the protocol (test), checking if they are similar or comparable [12]. The interval between test and retest should be well planned, especially for protocols that seek to measure information that may change due to changes in performance and/or learning over time. However, the technique presents as a limitation the fact that the previous experience of the participants of the research in the first test influences the retest responses. Equivalence is more directly related to the replicability of the protocols and can be tested by using alternative forms of a question with the same meaning during a single interview [11], or by the simultaneous application of two or more different researchers using the same protocol [9]. A reliable protocol should provide the same information even if executed by different people. There are two types of validity that can be tested in research protocols. The content validity is the most basic of them and is related to the protocol’s ability to measure the phenomenon studied. This can be achieved by inviting “competent judges” in the thematic area to review the content of the protocol items and determine if the instrument measures the phenomenon of interest [9]. The judges may be specialists in the subject area as well as members of the human population that will be studied. Considering the suggestions of these judges, changes can be made to the protocols that will increase their content validity. Criterion-related validity is determined when a research protocol can be compared with other validated measures of the same

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phenomenon [13] or with a standard established in the literature [10]. However, this type of comparison is not always possible because of the lack of valid measures for comparison. It is important to highlight that an instrument is valid for a certain group of people, and it is necessary to determine the validity again when the protocol is used in different groups.

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Review of Protocols The review of the protocol is an important step that must be performed before starting the research, as it assists the researcher in understanding if its protocol is appropriate to cover the entire phenomenon that is intended to study. Due to the peculiarities that certain human populations may possess, the structuring and vocabulary of the protocols may not be adequate, compromising the quality of the information collected. In this sense, a tool that can assist in the adequacy of a protocol for the reality of a given population is the application of the technique known as cognitive interview [14]. This technique is mainly characterized by the use of verbal probing questions to observe informants’ responses more completely. It assists in the evaluation of the quality of the response or in the determination whether the question is generating the information desired by the researcher (see [15, 16]). In Box 1, we describe an example of how to diagnose problems in a protocol using the cognitive interview. Box 1 Example of the Use of Cognitive Interview to Review Protocols, Adapted from Willis [16]: 1. In a hypothetical situation a scientist sought to understand the criteria of the inhabitants of a certain place to collect plants for medicinal use. Let us present a question of the protocol of this scientist followed by questions of verbal probes:

Question: How often do you collect plants to treat diseases? Verb probes used to test the question: (a) Tell me more about this... (b) How often do you collect plants in general? (c) What is “illness” for you? (d) Do you look for plants with specific characteristics or choose plants that someone has told you about which treat diseases? 2. Comments of the scientist based on the cognitive interview: (a) Some participants report that they only collect wood. (continued)

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Box 1 (continued) (b) Some participants report that they only collect fruits. (c) Some participants are not sure what “illness” is and confuse it with “hunger” or “sting”. (d) Participants reported selecting plants that could serve to treat diseases, rather than checking specific characteristics. (e) The period that the participant usually collects plants was not specified in the question. Because of this, the interpretations among interviewees regarding the frequency of collections varied widely. (f) Asking about the frequency of plant collections is impractical because people may not reliably report the exact frequency of such practice. 3. Suggested changes to improve this protocol issue: (a) In the last 12 months how many times have you collected plants? None, five times, or more than ten times? (b) If collected, in the last 12 months, did you choose it because of some specific characteristic? (c) If yes, what characteristic? (d) What part of the plant do you collect? (e) In general, how often do you collect plants with specific characteristics: often, once a month, or two or three times a year?

The cognitive interview provides information on how participants formed their answers, explanations on how they interpreted the questions, and reports of some difficulties they presented in responding to them. In addition, the use of this technique does not require large samples—usually 8–12 individuals is sufficient— because when testing the viability of a protocol, small samples quickly evidence if its structure is faulty [16]. Although it is commonly used as a pretest method, the use of the cognitive interview can occur at other stages of the research, and may provide information that allows the adequacy of the protocol for the phenomenon studied. There may be other situations in which information gathering remains difficult or participants are unable to answer to the questions, even if the researcher develops a protocol taking all necessary precautions. In these cases, the researcher can use the recruitment of third parties who live in the studied area to assist during the interviews. According to Quetulio-Navarra et al. [17], in some stages of the interview, other family members of the interviewees, as well as

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friends or neighbors, may be allowed to assist in the recall of the information requested. This approach presents the advantage of favoring the collection of information in which the participants have difficulties to remember, such as names of community leaders or specific dates, or in situations where the local language makes the research impossible. For example, in a study in the Bolivian regions of Cha´cobo and Pacahuara implemented by Zambrana et al. [18], the authors recruited and trained 12 residents living in the region to conduct interviews with participants because of the local language barrier. However, this method has limitations, since such assistants may not be able to identify important information that participants can provide during the interviews. Thus, according to Quetulio-Navarra et al. [17], precautions should be taken to reduce possible biases that the third-party recruitment method may generate: 1. Field survey to observe who can assist in interviews. 2. Only people who share the information targeted by the survey can be chosen to assist. 3. The participation of third parties should be controlled and allowed only for non-threatening questions, such as in the case of actual dates in which basic services were initiated—for example, electricity supply services. 4. Third parties may be allowed to make suggestions, but only the respondent/interviewee can provide the definitive answer. 5. The assistant’s name and relationship with the respondent should be recorded and the sections where assistance was provided should be marked. 6. Instruct assistants to leave the interview when assistance is no longer needed. In case the main problem of the protocol is related to the collection of information for sensitive issues—for example, questions about details of the woman’s/man’s health when the interviewer is of the opposite sex—a solution to avoid that the collected data are doubtful or invalid is the use of a self-administered questionnaire (SAQ). The SAQ refers to a questionnaire specifically developed to be completed by a respondent without the feedback of the researchers. However, since the SAQ is completed without the feedback of a trained interviewer, the questions should be written carefully to avoid measurement errors [19]. The main advantage of SAQ is that this tool eliminates the possible influence of the interviewer’s presence on respondents’ responses, since such privacy removes people’s inclination to provide socially desirable responses to sensitive issues [19]. However, even if this method makes the participant more comfortable, it does

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not ensure that the answers will always be true and honest. Besides that, this method requires participants to be literate, which makes it unfeasible for use in certain social contexts.

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Final Considerations Throughout this chapter we present a series of techniques for researchers to ensure the quality of their protocols. Box 2 summarizes key recommendations for readers and can be consulted whenever a researcher develops a new research protocol or migrates to a new area of study. Box 2 Recommendations to Verify the Validity and Reliability of the Research Protocols: l

Use 10% of the sample desired for the final research to execute the pilot study.

l

Be aware of the order in which the questions are organized in the protocols.

l

Develop the protocols in a short, simple, clear and comprehensive structure.

l

Elaborate and review the protocols with the help of researchers who have previous knowledge and experience with the subject area.

l

Verify the veracity of the data obtained in the pilot study by test-retest.

l

Conduct a cognitive interview with 8 or 10 people before beginning the survey.

References 1. Albuquerque UP, Ramos MA, Lucena RFP, Alencar NL (2014) Methods and techniques used to collect ethnobiological data. Humana, New York, NY, pp 15–37. https://doi.org/10. 1007/978-1-4614-8636-7_2 2. Hurst S, Arulogun OS, Owolabi AO et al (2015) Pretesting qualitative data collection procedures to facilitate methodological adherence and team building in Nigeria. Int J Qual Methods 14:53–64. https://doi.org/10. 1038/nbt.3121.ChIP-nexus 3. Aaker DA, Kumar V (2001) Day GS (2001). Wiley, Marketing research 4. Rattray J, Jones MC (2007) Essential elements of questionnaire design and development. J Clin Nurs 16(2):234–243. https://doi.org/ 10.1111/j.1365-2702.2006.01573.x

5. Slattery EL, Voelker CCJ, Nussenbaum B, Rich JT, Paniello RC, Neely JG (2011) A practical guide to surveys and questionnaires. Otolaryngol Neck Surg 144(6):831–837. https:// doi.org/10.1177/0194599811399724 6. Mackey A, Gass S (2015) Second language research: methodology and design. Routledge, London 7. Canhota C (2008) Qual a importaˆncia do estudo piloto. In: Silva EE (ed) Investigac¸˜ao Passo a Passo: Perguntas e Respostas Para Investigac¸˜ao Clı´nica. APMCG, Lisboa, pp 69–72 8. Combessie J-C (2004) O Me´todo Em Socio´ , Como Se Faz. Loyola, Paris, logia: O Que E p 2004

Implementing Ethnobiological Research 9. Salmond SS (2008) Evaluating the reliability and validity of measurement instruments. Orthop Nurs 27(1):28–30. https://doi.org/ 10.1097/01.NOR.0000310608.00743.54 10. Long T, Johnson M (2000) Rigour, reliability and validity in qualitative research. Clin Eff Nurs 4(1):30–37. https://doi.org/10.1054/ cein.2000.0106 11. Brink PJ (1991) Issues of reability and validity. In: Morse JM (ed) Qualitative nursing research: a contemporary dialogue. Sage, Thousands Oaks, CA, p 344 12. Sousa VEC, Matson J, Dunn Lopez K (2017) Questionnaire adapting: little changes mean a lot. West J Nurs Res 39(9):1289–1300. https://doi.org/10.1177/ 0193945916678212 13. Roberts P, Priest H, Traynor M (2006) Reliability and validity in research. Nurs Stand 20 (44):41–45. https://doi.org/10.7748/ns.20. 44.41.s56 14. Gray M, Blake M, Campanelli P (2014) The use of cognitive interviewing methods to evaluate mode effects in survey questions. Field Methods 26(2):156–171. https://doi.org/ 10.1177/1525822X13492703

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15. Beatty PC, Willis GB (2007) Research synthesis: the practice of cognitive interviewing. Public Opin Q 71(2):287–311. https://doi.org/ 10.1093/poq/nfm006 16. Willis G (2006) Cognitive interviewing as a tool for improving the informed consent process. J Empir Res Hum Res Ethics 1(1):9–23. https://doi.org/10.1525/jer.2006.1.1.9 17. Quetulio-Navarra M, van der Vaart W, Niehof A (2015) Can third-party help improve data quality in research interviews? A natural experiment in a hard-to-study population. Field Methods 27(4):426–440. https://doi.org/ 10.1177/1525822X15572096 18. Zambrana NYP, Bussmann RW, Hart RE et al (2018) To list or not to list? The value and detriment of freelisting in ethnobotanical studies. Nat Plants 4(4):201–204. https://doi. org/10.1038/s41477-018-0128-7 19. Rodriguez LA, Sana M, Sisk B (2015) Selfadministered questions and interviewer–respondent familiarity. Field Methods 27 (2):163–181. https://doi.org/10.1177/ 1525822X14549315

Chapter 3 Participant Observation and Field Journal: When to Use and How to Analyze Juliana Loureiro Almeida Campos, Taline Cristina da Silva, and Ulysses Paulino Albuquerque Abstract Studying the relationship between humans and nature requires a lot of fieldwork dedication from researchers. In order to understand phenomena related to human behaviors and their link to nature, ethnobiologists often use qualitative and descriptive methods and techniques, such as participant observations and field journals. In this chapter, we define these two methods and discuss the manners for collecting, analyzing, and presenting the information collected. Moreover, we discuss the advantages and disadvantages of using these methods in ethnobiological research. Key words Ethnobiology, Ethnography, Qualitative research

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Introduction Qualitative research originates from the Social Sciences and constitutes an interpretative approach that is concerned with understanding the meanings that people give to certain phenomena that occur within their social contexts [1]. The anthropological tradition of qualitative research has often been known as ethnographic research [2], which seeks to understand and describe a social group, their beliefs, and cultural practices through the immersion of the researcher in the social context to be investigated [1]. However, other authors prefer to consider ethnography as part of and not a synonym of qualitative research [3, 4]. In qualitative research, data collection and analysis should preferably be carried out simultaneously, so that analysis can accompany the information gathering process from the outset, and thus, guide the fieldwork [5]. It is common for concepts and hypotheses to be developed and revised throughout the research process. The qualitative methods used to collect data are diverse and involve

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_3, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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interviews, participatory methods, oral history, historical archive research, interpretation of photographs and videos, among others. In this chapter we focus on the approach of two methods widely used in this type of research: participant observation and field journal. We discuss when these methods should be used and how the collected data can be analyzed and presented, as well as the advantages and disadvantages of using each method.

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Participant Observation Before we define participant observation, we believe it is pertinent to briefly introduce the concept of observation. According to Richardson et al. [4] observation is the thorough examination about a phenomenon as a whole or a sum of its parts; it accurately captures the object being examined. There are two ways of observing within a qualitative research approach: non-participant observation and participant observation. In non-participant observation, also called direct observation, the researcher does not fit into the social group as if he were a member of the observed group, instead they act as an attentive spectator, observing and recording the maximum occurrences that matter to their work [4]. On the other hand, in participant observation the observer is not just a spectator. The researcher joins the studied culture to record actions, interactions, or events that occur, not only allowing the phenomena to be studied as they arise, but also offering the researcher the opportunity to obtain information themselves through the experience of the phenomena [6]. The participant observer is better able to understand the habits, attitudes, interests, personal relationships, and characteristics of daily community life than the non-participant observer [4]. Within this context, Bernard [7] emphasizes the importance of the researcher to deeply immerse themselves in the studied group and establish trusting relationships that can facilitate the participant’s observation work. For Minayo et al. [8], the technique is important as it allows the researcher to capture different situations or phenomena that are not obtained through using only questions, since the researcher experiences the day-to-day lives of the studied culture. An important issue in regards to participant observation is that many researchers believe in the notion that, during fieldwork, there is a need to act and behave in the same way as the cultural group studied. For example, it is not because you are studying an indigenous group that you should behave like an indigenous person. On the contrary, this type of behavior may sound artificial and even cause detachment from the social group. It is most important to be accepted in the research environment and acquire the confidence of the group to be studied. Whyte [9] provides a great example of this kind of attitude. In trying to adjust to the behavior of an urban

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group in Boston, USA, the researcher entered a round of conversation in which the group spoke obscene and vulgar words. The researcher then began to act and speak in a similar fashion as the group. Whyte [9] reports that everyone looked at him in surprise, and one of the group members did not expect him to speak like that, insisting that the group wanted him to remain different from them. The researcher realized that there was no expectation that he would become someone exactly like the studied cultural group, and that people were satisfied with him because they saw him differently. In his study, Whyte [9] argues that in participant observation, one must learn when to ask and when not to ask a question, just as one must know what kind of question to ask. Richardson et al. [4] point out that the researcher can “participate too much,” leading them to forget about their research goals, and unintentionally neglect them, losing the objectivity of the scientific work. Often this lack of objectivity leads the researcher to observe the phenomena not from an academic perspective (of a researcher), but from the member of the culture with which he interacts, skewing his interpretations. 2.1 Collecting Data Through Participant Observation

Bernard [7] believes that the greatest challenge of participant observation is the beginning, that is, the arrival and installation of the researcher within a culture. The author suggests that choosing a group that is open and easy to access will facilitate the data collection process. Moreover, Richardson et al. [4] emphasize the obligation of the researcher to previously present the objectives and justification of the research, so that there are no questions about the objectives of the study and the degree of acceptance of the researcher by the group. The length of time required to perform a good participant observation can vary greatly depending on the research objectives. Bernard [7] argues that it will probably take a long time for the researcher to establish themself in a social group, learn and master the language if appropriate, establish a good relationship of trust, so that they can ask good questions and receive good answers. For example, for Berreman [10] it took 6 months for the residents of the Sirkanda village in India to feel comfortable and to make animal sacrifices in front of them, a practice commonly held by the group. On the other hand, Yu [11] spent 4 months as a participant observer at a Chinese restaurant to observe the differences in perceptions of Chinese and non-Chinese employees with regard to good service, adequate compensation, and administrative functions. In order for the participant observation to rigorously reach the objectives of the research, it is important that the researcher carefully elaborate his notes on the phenomenon observed, describing in maximum detail all the perceived events [12]. Therefore, before beginning observation, the first step is to choose the ways in which

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the observations will be recorded. Later we will discuss the field journal and field notes as very suitable instruments for recording these perceptions, allowing the organization of the data in a way that is more convenient for the observer. Photography is a great recording instrument and represents part of the photographer’s world experience from their initial perception, which later can assume new interpretations of the social group that is photographed [13]. Thus, photographs not only help the researcher understand the culture studied, but also allow the studied people to interpret the behavior or phenomenon that is the subject of the researcher’s study [14]. A great example of the use of photography to record data and social behavior is Malinowski’s work, “The Argonauts of the Western Pacific,” published in 1922, which consists of reporting the anthropologists fieldwork in studying human groups who lived on the Trobiand Islands (see [15]). Another form of recording includes the use of sound recorders and camcorders, always remembering to request permission to use them from those being observed. We recommend the use of recorders whenever there is a need to register a conversation or dialogue, since its use allows the conversation to flow freely without interruption. Video, in turn, provides a record of details that are not captured by photographs or sound recorders [16]. Additionally, the video allows the studied practice to be observed at other times, and can be interpreted after the fieldwork [17]. However, it is necessary that the researcher have the financial resources to produce the video, since there is a high cost to equipment and filming staff.

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The Field Journal The field journal is a personal document and consists in recording observations, comments, and reflections for the researcher’s indi˜ os [2], in the social sciences, vidual use [18]. According to Trivin the notes made in the field journal can be understood as the whole process of collecting and analyzing information, that is, they would include descriptions of social phenomena, explanations about them, and understanding of the study’s situation as a whole. It is a document that has both a “descriptive-analytical character” and an “investigative and increasingly interim and reflexive” character, that is, it consists of “an inexhaustible source of construction, deconstruction, and reconstruction of professional knowledge and action through quantitative and qualitative records” [19]. We emphasize that the field journal can be used in different types of investigations, with different objectives and forms of registration. In social sciences, for example, this tool consists of the complete and accurate recording of observations of concrete facts,

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events, feelings, verified relationships, personal experiences of the professional/researcher, and their reflections and comments. Therefore, it should be used daily to ensure a greater systematization and possible detailing of all situations occurring during the day and between the lines of the subjects speech during the investigations or interventions. The ethnographic study is the construction of a field journal. It is an exercise that is based on direct observation regarding the cultural behaviors of a social group. It is important to emphasize that an ethnographer can have, besides the field journal, several field notes for annotations on the interviews and observations in the course of everyday life. While the observations recorded in the field journal present a freer essay, in the field notes the researcher records observations in order to facilitate data analysis [20]. Spradley [21] suggests two types of field notes: condensed and extended. The condensed field notes involve small phrases and words, becoming a practical and quick way of recording data. On the other hand, the extensive field notes should present more detailed texts in which the researcher should highlight the maximum amount of observations that were not recorded in the condensed field notes. Bernard [22] recommends that field notes be coded in order to reduce complex information to a smaller set of ideas, making it possible to locate patterns within the collected data set. In the natural sciences, the field journal, which is used with less and less frequency, can be useful to provide a permanent record of what is happening in the natural world. As an example, there are the journals of famous naturalists who provided information on biodiversity, such as Charles Darwin (see [23]). An intimate field journal is one that reflects the field researcher’s experiences [24]. A view of the field journal as material portraying the investigator’s intimacy can be seen in the publication of Malinowski’s personal journal [25], published by his wife Valetta Malinowski. In this book we can find a very human Malinowski who did not hide his feelings of antipathy and even the aggression by natives with whom he worked. Undoubtedly, the publication of the anthropologist’s intimate material has generated many discussions about fieldwork, but also led to the discussion of subjectivity from the researcher who faces the challenge of studying other cultures bearing the “burden” of his humanity, and therefore, of their weaknesses, desires, vices, and virtues. 3.1 How to Use the Field Journal

The field journal facilitates the habit of observing, describing, and reflecting carefully on the events of the working day; therefore, it is considered one of the main scientific instruments of observation and recording. The facts should be recorded in the journal as soon as possible after being observed to ensure the reliability of what is observed [18].

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It is necessary that the researcher know what type of information will be recorded in the field journal in order to structure it accordingly. For example, it may be important to record information that describes where the fieldwork is taking place, what information will help you understand what is being observed, and what other information would a researcher like to have when analyzing their notes after a week, a month, or a year. Angrosino [26] emphasizes the importance of recording the data in an organized manner that contains as much detail as possible, such as the description of the chosen scenario, the number of participants in the research and their socioeconomic characteristics, the chronology of events (take notes on dates, locations and time of events), descriptions of behaviors and interactions, records of conversations and other verbal interactions. The field journal is important for the ethnographic process, so that several components of the research are not forgotten. Continuous writing in the field journal is also important because the ethnographer’s perspectives and interpretations often change over the duration of the fieldwork process. This occurs because early interpretations are often guided by paradigms that the researcher brings to the field. As researchers learn about the cultural system under study, they often find that later interpretations of the same phenomena differ from those earlier interpretations. For example, Malinowski [15] recorded in his book: “Imagine yourself then, making your first entry into the village, alone or in company with your white cicerone. Some natives flock round you, especially if they smell tobacco. Others, the more dignified and elderly, remain seated where they are. Your white companion has his routine way of treating the natives, and he neither understands, nor is very much concerned with the manner in which you, as an ethnographer, will have to approach them. The first visit leaves you with a hopeful feeling that when you return alone, things will be easier. Such was my hope at least.” (p. 4).

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Analyzing the Data Collected After collecting data, it is time to analyze. Minayo [27] recommends reflection on the purposes of the analysis phase, which are: to establish an understanding of the data collected, confirm or not the research assumptions, respond to questions asked, and broaden knowledge on the researched subject, articulating it to the social context of which it is a part. Angrosino [26] suggests two main forms of data analysis: the descriptive analysis consisting of decomposing the data, checking for patterns and regularities, and the theoretical analysis composed of the explanation of the patterns and regularities from a theoretical perspective adopted by the researcher.

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As a first step, we suggest that the researcher transfer their field notes, audio recordings, and any other record to a computer. This allows the researcher to have a copy of their data, as well as to facilitate the location of any word or expression that they wish to review or analyze. In the following sections we present some ways to analyze the collected data, which is at the discretion of the researcher to choose the most appropriate form of analysis, either in function of the research objectives or in function of the types of data that were collected. 4.1

Categories

Working with categories implies grouping elements, ideas, or expressions around a concept that is able to encompass all of these [8]. It is a classification of field notes, grouping them into themes [26]. Categories may be established prior to fieldwork or at the time of data collection. However, Minayo et al. [8] suggest that the choice of categories is made before the fieldwork, but also soon after this, so the categories can be compared. The categories established prior to data collection are more general and abstract concepts requiring a solid theoretical foundation on the part of the researcher [8]. For example, imagine that you, the reader, are investigating the concept of nature from the members of a fishing community. Before data collection the established category could be “environmental representation,” understood as the way in which individuals externalize what is perceived, influenced by biological and cultural aspects [28]. After the fieldwork, suppose that the following excerpts from the fishermen’s speech have been recorded: 1. Nature is the river and the animals that are in it; 2. Nature is beautiful, without it we would not exist; 3. It is the trees with fruits, such as mango, avocado, papaya, banana. . .; 4. Nature is everything that was created by God. If we were to establish categories for the above phrases, we could say that excerpts 1 and 2 could fall into the category of “romantic vision,” excerpt 3 may belong to the category “utilitarian vision,” and excerpt 4 may belong to the category “sacred vision” of nature. The next step is to relate these categories to those defined before the fieldwork, which in this case was the general category “environmental representation.” Thus, the researcher can strive to understand how the concepts of nature are determined by the biological and cultural filters held by fishermen, seeking to deepen the contradictions between the ideas presented. This categorical analysis can be presented in tables or charts. The categories can be found in the first column, the excerpts from speeches or dialogues that cover such categories in the second

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column, and the interpretations of these excerpts related to the listed categories in the third column, as well as the discussion of findings based on theoretical references. If you prefer, the information in the third column can also be transposed into a running text just below the table or chart. 4.2 The Hermeneutic-Dialectic Method

The hermeneutic-dialectic method, discussed by Rychlak [29] and Stein [30] and proposed by Minayo [27], is a qualitative interpretation of data that suggests that the actors’ speech should be situated within their socioeconomic and political context to be better understood, and that the categories are formulated from this context. Minayo [27] suggests three steps to execute the proposed method: the first step is organizing the data, where a map of the collected data is made, involving the transcription of the text, rereading of the material, and organization of the reports; the second step is to classify the data by rereading the texts and identifying relevant information that will give rise to the categories; the third step is the final analysis, that is, the moment of articulating the data and theoretical references related to the research topic, responding the research questions based on the objectives.

4.3

The content analysis methodology is a set of communication analysis techniques aiming to obtain indicators through the description of the content of the information that allow the inference of knowledge about the conditions of production/reception of these messages [31]. The technique of content analysis can be summarized as a treatment of information contained in messages and texts and can be applied to the most diverse types of content, such as speeches, documents, books, magazines, and newspapers. Given the diversity of information to which this analysis can be applied, we will focus on the techniques used to analyze contents collected through participant observation and field journals. Richardson et al. [4] emphasize the importance of looking at characteristics, such as objectivity, systemization, and inference when analyzing content. For example, in a content analysis in the form of categories, presented in Sect. 4.1 of this chapter, the authors suggest that in order to achieve objectivity, one must have homogeneity (not mixing classification criteria), completeness (classifying the entire text), exclusion (the same element should not be classified in more than one category), and objectivity. Systematization consists in applying consistent rules and inference is related to the act of seeking to clarify the causes of the message or the consequences that it can cause. The criteria for organizing an analysis are a pre-analysis, assessment of material and data processing, inference, and interpretation [31]. In the pre-analysis phase, the researcher should organize the material, elaborate hypotheses and objectives, and define the field

Content Analysis

Participant Observation and Field Journal: When to Use and How to Analyze

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of research. During the analytical description, the material collected and the information recorded will be analyzed based on hypotheses and theoretical references. This phase involves the coding and categorization of recorded units, which can be a theme, a word, or a phrase. It is a phase of exploring the material, which involves exhaustive readings, and is also when what is defined in the previous phase is applied, inserting the discourse into categories of analysis. Lastly, the inferential interpretation phase is to unveil the content, focusing on the search for common trends among the data. The results are treated in a significant and valid manner, and can be submitted to statistical tests, which does not exclude the qualitative interpretations [4]. The forms of treatment are diverse, and can involve the calculation of frequencies and percentages, factor analysis, contingency analysis, among others [4]. In this phase, inferences and interpretations of results are proposed. For further study ˜ os [2], Richardson et al. of the content analysis method, see Trivin [4], and Bardin [31].

5

Final Considerations As we have seen in this chapter, the use of a field journal and notes in association with participant observation are important research tools for ethnobiology, since it deals directly with human groups and phenomena from nature. These methods allow the researcher to observe and record in depth useful information for their research. It is important to note that these techniques can easily be complemented with other qualitative or quantitative data collection methods, which can be found in subsequent chapters and volume one of this production. Lastly, we recommend attention, caution, and dedication in the use of these methods by the researcher so that the results of their ethnobiological research can be successfully achieved.

References 1. Snape D, Spencer L (2003) The foundations in qualitative research. In: Ritchie J, Lewis J (eds) Qualitative research practice: a guide for social science students and researchers. Sage Publications, London ˜ os ANS (1987) Introduc¸˜ao a` pesquisa em 2. Trivin cieˆncias sociais: a pesquisa qualitativa em edu´ tica, Sa˜o Paulo cac¸˜ao. A 3. Krefting L (1991) Rigor in qualitative research: the assessment of trustworthiness. Am J Occup Ther 45(3):214–222

4. Richardson RJ, Peres JAS, Wanderley JCV, Correia LM, Peres MHM (2012) Pesquisa social: me´todos e te´cnicas. Atlas, Sa˜o Paulo 5. Pineda MC, Leyva-Moral JM, Moya JLM (2011) El ana´lisis de los datos cualitativos: un proceso complejo. Index Enferm 20 (1–2):96–100 6. Ritchie J (2003) The applications of qualitative methods to social research. In: Ritchie J, Lewis J (eds) Qualitative research practice: a guide for

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social science students and researchers. Sage publications, London 7. Bernard HR (2006) Research methods in anthropology: qualitative and quantitative approaches. Altamira Press, Oxford 8. Minayo MCS, Deslandes SF, Neto OC, Gomes R (2002) Pesquisa social: teoria, me´todo e criatividade. Editora Vozes, Petro´polis 9. Whyte WF (1943) Street Corner Society: the social structure of an Italian slum. University of Chicago Press, Chicago 10. Berreman GD (1962) Behind many masks: ethnography and impression management in a Himalayan village. Ithaca, New York 11. Yu X (1995) Conflict in a multicultural organization: an ethnographic attempt to discover work-related cultural assumptions between Chinese and American co-workers. Int J Confl Manag 6:211–232 12. Selltiz W, Wrightsman LS, Cook SW (1987) ˜ es sociais. Me´todos de pesquisa nas relac¸o EPU, Sa˜o Paulo 13. Soilo AN (2012) A arte da fotografia na antropologia: o uso de imagens como instrumento de pesquisa social. Habitus 10(2):72–79 14. Harper D (2002) Talking about pictures: a case for photo elicitation. Vis Stud 17(1):13–26 15. Malinowski B (1922) Argonauts of the Western Pacific. Routledge & Kegan Paul Ltd, London 16. Brigard E (1995) The history of ethnographic film. In: Hockings P (ed) Principles of visual anthropology. Mouton de Gruyter, New York 17. Fuller RJ (2007) Guidelines for using video to document plant practices. Ethnobot Res Appl 5:219–231 18. Falkembach EMF (1987) Dia´rio de campo: um instrumento de reflexa˜o. Context Educ 7 (2):19–24 19. Lewgoy AMB, Arruda MP (2004) Novas tecnologias na pra´tica profissional do professor

universita´rio: a experieˆncia do dia´rio digital. Rev Tex Cont 2:115–130 20. Arthur S, Nazroo J (2003) Designing fieldwork strategies and materials. In: Ritchie J, Lewis J (eds) Qualitative research practice: a guide for social science students and researchers. Sage publications, London 21. Spradley JP (2016) Participant observation, Reissue edn. Waveland Press, Long Grove, IL 22. Bernard HR (1988) Research methods in cultural anthropology. Sage Publications, Newbury Park 23. Darwin C (1989) The voyage of the Beagle. Penguin Classics, London 24. Weber F (2009) A entrevista, a pesquisa e o ´ıntimo, ou por que censurar seu dia´rio de campo? Horiz Antropol 15(32):157–170 25. Malinowski B (1967) A diary in the strict sense of the term. Routledge & Kegan Paul Ltd, London 26. Angrosino M (2007) Doing ethnographic and observational research. Sage Publications, London 27. Minayo MCS (2000) O desafio do conhecimento: pesquisa qualitativa em sau´de. Hucitec, Sa˜o Paulo 28. Silva TC, Chaves LS, Albuquerque UP (2016) What is environmental perception? In: Albuquerque UP, Alves RRN (eds) Introduction to ethnobiology. Springer, London 29. Rychlak JF (1996) An enquiry into the hermeneutic-dialectic method of inquiry. J Soc Distress Homeless 5(3):305–317 30. Stein E (1987) Diale´tica e hermeneˆutica: uma controve´rsia sobre me´todo e filosofia. In: Habermas J (ed) Diale´tica e hermeneˆutica. L&PM, Sa˜o Paulo 31. Bardin L (1977) Ana´lise de conteu´do. Persona, Lisboa

Chapter 4 Audio and Video Recording Techniques for Ethnobiological Research Simone de Hek and Ana Ladio Abstract The aim of this chapter is to foster enthusiasm and provide basic knowledge and guidelines for making the use of audio and especially video recording techniques an integral part of ethnobiological research. Key words Video, Minimal video techniques, Participatory video, Ethical considerations

1

Introduction There is increasing recognition of the positive effect in ethnobiological investigations when attitudes, emotional meanings, beliefs, and preferences of the people using natural resources are considered. These aspects are both linguistically and corporally expressed among humans. The need of including community perspectives in ethnobiological research has encouraged the development of a range of methodologies that require diverse levels of community involvement, where audio and video are becoming more and more important. In ethnobiological research the use of audio and video recorders is considered common practice for the collection of data during fieldwork. Digital recording has provided an evolution in best practices for collecting, archiving, and communicating data. Video and audio recording of linguistic and ethnographic data in ethnobiology, for example, is now the norm [1]. Tape recorders are part of a standard recommended package of equipment for ethnobiological field research. Even digital cameras, although not often used for filming interviews and/or recording other audiovisual data (more likely the cameras are used to reproduce visual data), are in the “ideal basic kit” of materials and tools that are considered useful and/or essential [2] when going to the field. Using digital

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_4, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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recording techniques in research does not only make it easier to collect data, it also provides the ability to more easily share the data. Not just share the data among scientists, it also provides great opportunities to share data with different kinds of partners and public. More and more ethnobiologists are interested in returning data from ethnobiological research to the communities they work with, as these communities are not just simple objects of study, they are partners in an inclusive process of sharing knowledge and creating new knowledge [3]. Using audio and/or visual techniques some very creative and effective ways for communication have emerged from ethnobiological researchers. Talking Books, developed by Nathaniel Bletter [4] is one of those. See Box 1. Box 1 Talking Books: Nathaniel Bletter, an ethnobotanist, created the first talking books studying ethnobotany with the Asha´ninka community of Paititi, Peru, and the Malinke of Kita, Mali. In both communities an unwritten local language is utilized. As the communities requested him to return to them some documentation of the research that the communities could refer to, Bletter realized that books with pictures and text in Spanish or French were only useful for the small part of the communities who could read in those languages. They were useless for those who only spoke the local language. With using just pictures it is difficult to represent complex and abstract ideas like names, emotions, and relationships. Bletter decided that the optimal solution would be a talking picture book that plays short audio clips of the names and uses of the plants in the pictures in the native language. The book had to be water-resistant, it should run on rechargeable solar power so that it could be used in communities without electricity and batteries; and it had to be inexpensive enough to produce copies for all families. The books turn out to be effective tools for retaining and returning traditional knowledge of many kinds to remote, nonliterate communities; and to preserve and stimulate new interest in this knowledge within and among communities.

In processes of development communication video has been used for more than 30 years [5]. In ethnobiology video in participatory research is known as an important tool for creating local impact [6]. However, the variety of ways in which video can be applied has been poorly documented, with very few descriptions of the methodologies used [5, 7]. Video can be used in many different ways, for a high diversity of objectives. Lie and Mandler [5] present a typology of video in development communication that helps in

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creating a better knowledge and understanding of this diversity, and to choose what technique fits best the objective. We think this typology might also serve as a useful framework for ethnobiological researchers who wish to use video in their communication: – Video for data collection and reporting. Video can be used for primary data collection as well as for secondary data analysis. This type of videos can be used as input for monitoring and evaluation processes and/or for encouraging end-user participation and donor convincing. – Video for capacity building and learning. This type of videos is commonly used in extension activities to facilitate the introduction of new practices, methods and techniques, and in training sessions. They are also useful for the exchange of experiences and for stimulating reflection and shared learning. – Video for awareness raising (general public) and advocacy (specific audience): This type of videos is often a persuasive documentary style, produced to alert people to certain issues, ideas, concepts, or problems. Videos for awareness raising and advocacy are most effective when they are part of a well-designed communication strategy. – Video for stakeholder engagement and discovery. This type of videos are focused on sharing stakeholders’ knowledge, experiences and perceptions and for learning, mediation, negotiation, conflict resolution, and encouraging action. Video can be one of the tools in a participatory process. Particularly, video ethnographies can vividly show what plants, animals, objects and/or events mean to people, which depends on what they are emotionally and corporeally experiencing at that moment, as a result of their past experiences. Video is an important contribution to this end in the understanding of local knowledge, practices and decision making related to natural resource use and management. Natural resource management is part of a socioculturally specific context, and video could be the best tool to identify local values and emotional reactions of the people participating in our studies. Working with video helps us to meticulously record the expressive resources (such as facial expressions) used in the conversations in interviews and/or workshops.

2

The Minimal Video Technique Using tape recorders for audio is relatively easy and does not require specific expertise or a high financial input to obtain the equipment. More than obtaining new technical skills to be able to use this technique, researchers need to internalize/naturalize it so that there is no shame or fear to create understanding for using

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recording devices when working with communities. This is considered different though with the use of video. It is often thought that including audiovisual recording, one requires very specific technical and artistic skills and highly expensive equipment to be able to produce material of high quality. Including video in research creates enthusiasm, but often is seen as another “problem”. When a video is included as a planned result of a research project, a video production company is being hired to do so. Users of cameras working with local communities have been criticized for using a sophisticated technology in a rural setting, overwhelming the communities who make part of the research. However, with the advancement of the digital era and the quick development and democratization of communication tools like the internet, smartphones, high quality nonprofessional cameras, and easy-to-use free software for editing and sharing videos, video has become a widely used, easy access, low-cost, high-impact technique. It is recognized that working with video in communities attracts people’s curiosity, it overcomes the hurdles of local languages and illiteracy and it sits comfortably with the narrative culture that prevails in many indigenous communities where oral traditions predominate [6]. Minimal video, as a concept first mentioned by Lie and Mandler [5], but mainstream among mobile journalists worldwide (for an example, see the mobile journalism handbook: http://www.mojo-manual.org), is a strategy to include video communication based on the digital equipment and the experiences and skills locally available. With little effort people learn the basics of making a video and use their smartphones to make and/or show them. As most smartphones have high quality cameras, the quality of the video will mainly depend on the experience and skills of the video maker. Researchers can decide to depend on their own experience and skills, or they can tap from an ever-growing source of nonprofessionals with highly developed skills, also within local communities researchers work in. For a good start some basic tips for using a smartphone for making video are presented in Box 2. Box 2 Tips for Filming with a Smartphone: 1. Think before filming. Make a film plan, however small your video will be. In this plan respond the following questions: With what OBJECTIVE is the video made? WHAT is the message? For WHOM is the message? What images do I need to tell the story right? What is the context in which I wish to film and is this context right for filming? WHERE is the video shown and HOW? 2. Always ask for the approval of the persons you wish to film. Accept and respect it when people do not want to be filmed.

(continued)

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Box 2 (continued) 3. Put the settings of you smartphone camera on the highest quality available (often HD) and experiment with/understand the different settings of the film software that is on your phone. 4. Make sure you have enough memory available for the videos. Filming occupies much more space then taking pictures. 5. During filming, put your phone in airplane mode, so you will not be called while filming. 6. Film horizontally. 7. Film stable images; do not move the camera too much, film what is moving from a stable position. It is best to use a tripod. 8. Be aware of the light and the direction of the light. Try to film with the light source being behind the camera. 9. NEVER use the digital zoom. Get as close as possible to your subject. 10. If the filmed material will be edited in a separate editor later on, film short clips of minimal 3 up to 10 s. This will also force you to film the essential. 11. Film a diversity of shots, from total shots to details. In video, rhythm is in the variety. It is rhythm that makes video attractive to watch. 12. The sound is important in video. Be aware that the microphone of a smartphone is good enough for recording sound when placed near the source, but creates low quality sound while filming. Best is to record sound with a second device and later unite this audio with the visuals. 13. If you have no experience with any editing software, plan your images and their sequence well and use the pause button (this is where you cut one scene to move on to the following scene) on your phone to create a logical sequence of a variety of clips. 14. Simple editing of video can be done with apps on the smartphone. For more advanced editing, using editing programs on desktops or laptops, like imovie or moviemaker, are recommended. There are also online programs for simple editing.

Minimal video as a technique in research and development processes is seen as a strategy to produce mainly low-quality videos, not apt for wider screening, but useful for collection of raw data, internal communication processes, networking, pretesting of ideas, monitoring of local processes and for extension/education material. However, a lot of the material produced during research and

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development processes could be reformatted for wider screening, independent of the technical quality of the videos filmed under nonprofessional circumstances. The message and the story often have more impact than the quality of the image. Apart from some technical skills and the equipment, the quality of a video depends mainly on the understanding of how audiovisual language, one could see video as another language, works. The camera does not tell the story. It is the one behind the camera. With video, it becomes possible to: “talk” a universal language, be quick and immediate, easily synthesize, relate to emotions and intuitions, collectively create, reutilize materials, and reach a larger public. There are several cinematic tools to help you do so. A good first step to grab audiovisual language is to know the basics of shot composition, so on how you arrange the framing of your shot, depending on the effect you want to create. In Table 1 the main composition techniques and their effects are presented. Working along the presented basics will improve the quality of the images and the story.

Table 1 Basic shot composition techniques Composition technique

Effect

1. Rule of thirds: divide the image in equal thirds Creates depth and senses of kinesis and movement with two horizontal and two vertical lines (many cameras have a function with which these lines can be visualized in your visor). Place the subject of interest along one or more of the horizontal or vertical lines, or on one of the four intersections; never in the center of your image. Using the imaginary diagonal lines is also an option 2. Contrast between subject and background

Creates depth and orientation towards the subject

3. Angle of the camera

Normally the camera is places at eye height of the subject. Filming from below (looking up) creates a sensation of power of the subject, filming from a higher point (looking down) creates a sense of power of the public

4. Frame (what is within the borders of your image) A: gives a broad perspective and an overview of a situation your subject in different ways depending on what the public needs to know and feel from that shot. B: more personal and good for conversation and emotions Three basic shot types: (A) wide shot, C: for focus on emotions and details (B) medium shot (C) close-up shot 5. Include visual well-known symbols

The symbol will tell it all without words

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Creating a video is divided into three, sometimes two if one decides to not edit the material, production phases (followed by a post-production phase for showing, sharing, and using the video), with every phase being a process on its own: 1. The preparation phase—from idea to a working plan. During this phase, a simple plan that includes a visual plan is being created. Creating a plan guides the content. It focuses on specifying the objective, the public, the message, the resources and skills needed, and the list of images to be shot (and how these should be shot). For one video only one specific objective, one specific public, and one specific message should be defined. The more specific these are, the more impact the video will have. Working according to a plan helps in avoiding irrelevant information, the repetition of information and diluting the key message, as there will be so many interesting things to film while in the field. Having a plan also makes it easier to share, discuss, and obtain approval for the idea. See Box 3 for basic guidelines of a simple video plan. Box 3 Guidelines for a Video Plan: the chapters of the plan Chapter 1: Description of the context and the general idea Chapter 2: The objective of the video. Is it for reporting and/or data collection, for capacity building and learning, for awareness raising and advocacy, or for stakeholder engagement and discovery (remember the typologies as presented in Box 3) Chapter 4: Description of the public for whom the video is meant to be. The more general the public, the less specific the effect of the video Chapter 5: The message. Description of what it is exactly that has to be communicated with the video Chapter 6: Resources and sources needed to make this video. Here it is defined what equipment will be used, who will be involved doing what, if financing is needed and where it will come from, what authorizations have to be given, what is the best time of the year for certain characteristics of a plant and/or depending on seasonal or climatic conditions (both influencing plant and human activity) Chapter 7: A script that includes at least a detailed list of the shots necessary to film. Including a story board, which is common method for a visualizing the shots and the sequence of the shots, facilitates sharing, discussing, and analyzing the plan

2. The recording phase. This is the phase in which the planned shots are being made. Following the plan developed in the first phase will not only help to focus, it will make the whole process from filming to post-production much more efficient. Still, be flexible and open to unplanned situations and possibilities. Make sure that the filmed material is well archived, with at least one copy on a separate device.

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3. The edition phase. This is the phase in which different sources of sound, like a voice-over or music can be added. Texts can be added. Images can be digitally corrected in color and framing. This is also the moment in which it will become clear if the plan works. During editing the whole plan can be changed. During editing one can, with the same material, produce different videos with different objectives and for different types of public. Even simple video clips profit from a good preparation. Apart from ethnobiologists being able to produce quality videos with minimal equipment and expertise, it might be worthwhile to consider including filmmakers in the research process making part of interdisciplinary work. Combining science and art creates wonder, and wonder is a strong motor for curiosity and change.

3

Video in Participatory Research Documentation and data collection is often done in an extractive way, but the demand for a more effective interaction between different knowledge bodies, like local knowledge and scientific findings, is growing. Participatory video provides a way for local communities to communicate their ideas, innovations, theories and decisions not only to each other but also to researchers. The videos produced give totally different insights, going beyond statistics and reports. There is an interesting trend in research and development processes, in which the use of video is growing, towards farmer-led (or local-led) documentation and data collection for effective change and learning [8]. The creation of simple audio and/or visual material by local actors is very powerful, not just for the, often, unexpected data and local perspectives the videos can provide, but more for the process of interaction it creates. Using video facilitates the interaction between researchers and their counterparts in the community, but also among community members, and among communities. In participatory video the quality of the product is definitely not as important as the quality of the process [9]. Minimal video techniques can very well provide for the objective defined. With minimal training anyone can learn how to use a video camera to tell their story in their own local context. First of all, one has to realize that there is a high diversity in participatory video methods and approaches, and there is no single

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accepted way of doing it [9]. At the same time there is little documentation about processes of participatory video in research and literally no scientific publications can be found in ethnobotanical journals describing, discussing or analyzing in detail the process of development or resulting participatory videos [7, 10]. “Insightshare” (see insightshare.org) is the leading organization pioneering the use of participatory video for empowering individuals and communities. Box 4 shows an adapted overview of participatory video in a nutshell, as presented by Insightshare. Insightshare shows experiences with the use of video techniques that combine the iterative and highly responsive nature of video with the more systematic structures of research, providing a rigorous but engaging process that includes triangulation of different evidence sources [11]. Box 4 Participatory Video in a Nutshell: 1. Identify the digital equipment, video abilities and enthusiasm/interest available locally. 2. Organize a workshop in which participants rapidly learn how to use video and/or editing equipment through games and exercises. 3. The researcher/facilitator help groups identify and analyze important issues in their community by adapting a range of participatory research tools with participatory video techniques. 4. Short videos and messages are directed and filmed by the trained community members. 5. Footage is shared with the wider community at daily screenings. 6. A dynamic process of community-led learning, sharing, and exchange is set in motion. 7. Communities are involved to varying degrees in editing their films, but they always have full editorial control. 8. Completed films can be used for horizontal and vertical communication.

4

Ethical Issues to Consider Digitalization and the quick development and democratization of communication tools provide the possibility to create an ethnobiological knowledge base that is increasingly being shaped by more open and participatory documentation, which can include more bottom-up content [1]. However, we wish to repeat here the recommendations made by Fuller [10]: pay attention to the ethical and practical issues involved in the planning of documentation

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regarding practices that involve the use of plants; discussing the ethical issues relative to ethnobiological research with the involved community, including obtaining informed consent; and assessing commercial implications in case the video is exhibited to large audiences, including the discussion of the intellectual property rights. The Code of Ethics as developed by the International Society of Ethnobiology (see www.ethnobiology.net) and adopted by its members in 2006 has been a reference for many pioneers working with video in research and development.

5

Conclusions Audio and Video Recording Techniques are rarely used alone; they are typically part of a series of ethnobiological methods and procedures. These techniques might represent a valuable tool to analyze ethnobiological data because they allow a given practice or local voice to be captured in its minute and subtle details. It seems to be paradoxical that within a discipline such as ethnobiology that deals with local perceptions that involve emotions, feelings and subjectivities, and that recognizes the value of words and actions as a modus operandi to reproduce traditions, these techniques are not being formally privileged. In our opinion, with the help of audio and video recording we can identify the various forms of conceiving biocultural diversity, and consequently, add more multiculturalism in our investigations.

References 1. Harrison KD, Sariahmed K (2014) Linguistic and audio-video collections in ethnobiology. In: Salick J, Nesbitt M, Konchar K (eds) Curating biocultural collections: a handbook. Royal Botanic Gardens, Kew 2. Albuquerque UP et al (2014) Methods and techniques in ethnobiology and ethnoecology, Springer protocols handbooks. Springer, New York. https://doi.org/10.1007/978-14614-8636-7_2 3. Pe´rez-Ojeda del Arco A et al (2011) What have we forgotten? Returning data from ethnobiological research to local communities. Bioremed Biodivers Bioavail 5(Special Issue 1):22–27 4. Bletter N (2006) Talking books: a new method of returning ethnobiological research documentation to the non-literate. Econ Bot 60 (1):85–90 5. Lie R, Mandler A (2009) Filming for rural change. Video for development. © CTA and FAO 2009

6. Garrett BL (2011) Videographic geographies: using digital video for geographic research. Prog Hum Geogr 35:521–541 7. Grasser S et al (2016) Children as ethnobotanists: methods and local impact of a participatory research project with children on wild plant gathering in the Grosses Walsertal Biosphere Reserve, Austria. J Ethnobiol and Ethnomed 12:46 8. Ru¨ter D, Piepenstock A (2008) Farmer-led documentation. GTZ-participatory-web 9. Chowdhury A H, Hauser M (2010) The potential of moving pictures: does participatory video enable learning for local innovation? Author manuscript, published in ISDA 2010, Montpellier 10. Fuller RJ (2007) Guidelines for using video to document plant practices. Ethnobot Res Appl 5:219–231 11. Lunch N, Lunch C (2006) Insights into participatory video: a handbook for the field. www.insightshare.org

Chapter 5 Qualitative Data Analysis Daniel Carvalho Pires de Sousa, Henrique Fernandes Magalha˜es, Edwine Soares de Oliveira, and Ulysses Paulino Albuquerque Abstract In this chapter, we describe the main tools of qualitative analysis, from the approach used for a representative sampling to transcription of information, coding and triangulation of the obtained data. Transcription consists of a pre-analysis of the material in which the researcher systematizes the information for further analysis, while coding consists of the treatment of qualitative data by naming passages of text and categorizing their contents. Finally, the triangulation of data seeks to confront results, with the purpose of evaluating the reliability and generalizations of interpreted information. With this, we hope to provide methodological support to ethnobiologists who choose to direct their investigations from a qualitative approach. Key words Ethnobiology, Qualitative analysis, Qualitative methodology

1

Introduction Qualitative research uses a variety of data collection methods (interviews, memorandums, field notes, participant observation, etc.). However, in order to transform the reports into usable data, all the information obtained by these tools need to be transcribed, and these texts are the fundamental data sources for coding and analysis [1]. The analysis of qualitative data can offer rich complementary explanations about the characteristics of the systems of knowledge studied by ethnobiology. Thus, we will describe the main tools and stages of the qualitative analysis, such as how a representative sampling is to be performed, the forms and guidelines of transcription of the data collected in the field, the methods of coding and categorizing of the information collected (grouping and relating discourses and behaviors). Finally, we show the main methods to triangulate this information to avoid misinterpretation of reality or to explore perceived contradictions in the material.

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_5, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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Population Sampling The qualitative researcher usually does not know a priori the quantity and total characteristics of the people that are part of the observed social context, and the ideal sample for the research questions are based on the exhaustion of the information about the categories of analysis, or the so-called theoretical saturation. Theoretical saturation, a concept first discussed in 1967 by Glaser and Strauss [2], is a form of “sample design” of qualitative research. Once the question of the study has been developed, the researcher goes to the field and begins to intentionally interview the informants involved in the phenomenon, initiating the data collection of the study [3]. This collection will supplement the first information banks and allow for the codification of the first discourses and responses of the people involved,1 and it is finalized when new people (new discourses) do not reveal new “codes” about the phenomenon [4]. This approach for participant selection is commonly applied in qualitative research and shows the importance of coding as a sampling guide. However, in general, how many people are necessary to exhaust the thematic information? This question is widely discussed in the social literature. Accomplishing a representative sample in qualitative studies generally focuses on three main assumptions: knowledge of the past, would basically look at the published literature and follow the selection of participants used by previous studies; researcher experience, in which the number of people sufficient to saturate the categories of analysis is defined according to the “complexity” of the social context, and the theoretical and practical knowledge of the researcher or research group is the “final decision” about the participants of the study; and the quasi-empirical basis, in which the number of participants is determined by a series of researches that directly studied the characteristics of theoretical saturation (see [5]). The first two are critical as to the subjectivity of the sample selection. However, the latter is based on studies that have used the quantitative analysis methodology to investigate which population sampling is ideal in the surveys. Several studies of qualitative sampling have shown that the theoretical saturation of several topics and research topics is achieved with relatively small samples, which vary practically between 10 and 50 people [6]. Guest and colleagues [7] sought to raise data for the development of HIV and sexual health information for communities in Nigeria and Ghana. They interviewed 60 women over 18 with active sexual life using standardized questionnaires and semi-structured interviews, enquiring their

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Coding is to identify passages of different people that relate to the same “code” developed by researchers, see Sect. 3 of this chapter.

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behaviors, prevention and knowledge about topics related to their intimate lives. After intense coding and analysis, they found that only 12 informants were required to saturate 100 codes (92%) and 80 of them (73%) by the first six informants. Hagaman and Wutich [6], investigating the order of appearance of the research categories of four populations from different social contexts (related to water management, income, and access to drinking water), showed that 12–16 interviews were necessary to record the common themes within each culture, while 20–40 interviews were necessary to record the themes shared by all the people in the sample. These authors also argue that this number of interviews is sufficient when the phenomena studied are local and well contextualized, while large and heterogeneous groups of people require a greater effort to collect and select the sample units [6]. Based on this discussion, understanding that qualitative methods are different from quantitative ones, ethnobiological investigations that choose to use inductive research approaches should follow the same qualitative research assumptions for sample selection, namely, delimit well the phenomenon to be investigated, define a minimum limit of interviews for intracultural surveys and qualitatively select the informants, as well as systematically encode the information collected (see [8] for example of qualitative analysis in social-ecological systems).

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Data Transcription After finalizing the data collection (see Chap. 1), it is necessary to proceed for analysis of the information. Transcription then becomes a pre-analysis of the material. Its guidelines assist researchers to organize information systematically (regardless of analytical techniques and tools that will be used) for further analysis [9]. It is noteworthy that the transcription of the data is an important step of the research and not just a technical detail that precedes the analysis. Therefore, it is of utmost importance to define what the rules and criteria will be that will lead to the transcriptions, so that they contain all the elements necessary to transform the information into usable data. Depending on the purpose of the research, it is interesting that the transcripts are performed only as required by the study question. Thus, the time and energy that would be invested in the process of transcribing unnecessary elements (such as interruptions or random subjects that come up in the conversation with the interviewee) would be invested in the interpretation of the data. There are cases, however, in which it is important that all elements are transcribed, allowing for further detailing of subsequent analysis [10]. In this sense, the transcription can be complete (all the context and discourse, including pauses, interruptions, etc.), partial or summarized (only extracts that are relevant to the research).

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Because there is no general pattern and because it is a process that requires a lot of time from the researcher, it is important to determine a standard so that all transcripts present the same structure, such as the word processor that is used, the most adequate fonts, specific formatting for certain situations, among other elements (exemplified in Box 1). This standardization in the structure minimizes the time consumed in locating the elements in the interviewees’ speeches. Throughout the process, it is fundamental that the researcher is guided by the research question that the analysis seeks to answer [9]. It should always be considered that everything that is transcribed and the form that this transcription is structured, influences the process of data analysis [9]. Box 1 Example of Useful Elements for Structuring a Transcript (Adapted from Flick [10]): Structure Word processor Microsoft Word 2016 Font

Times New Roman 12

Margins

Left 2 cm, Right 5 cm

Spacing

1.5 cm

Numbering

Above and right of each page

Interviewer

Sı´mbol: Entrdor

Interviewee

Sı´mbol: Entrdo

Transcript conventions used Type of Complete transcription

4

WORD

Caps Lock: indicates increased sound amplitude

Word

Underlined: indicate stress

(1, 2, etc.)

Pauses: in the speech of the interviewee or between interviewees, in seconds

[...]

Text cutting: Speech considered unnecessary for research

(words...)

Incomprehensible words: transcription breaks and “best chance” of the transcriber

Coding The identification and refinement of important concepts are fundamental steps in qualitative research. These processes often begin with simple observations interpreted separately and then grouped and organized into research categories [11], which can result in a large

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volume of material. Thus, methods that allow for the organization of this data in a practical and didactic manner need to be adopted [10]. Codification consists in the treatment of qualitative data by naming text passages, categorizing their contents [12]. Thus, the researcher can establish a structure of thematic ideas, directing their reasoning in the text and, consequently, making possible the interpretations of its content [11]. This process can be classified, according to Gibbs [13], based on three criteria, exemplified as follows (Box 2): (1) descriptive coding, in which we use similar words or even original terms of the text under analysis, repeating briefly the primary idea conveyed by the data; (2) analytical codification, in which we seek to apply a code to refine the interpretation of the text, aiming at a deeper understanding of its content; and (3) theoretical coding, which intends to elaborate a theory that makes possible the explanation of the analyzed data. Box 2 Example of Encoding Process, Inspired by Gibbs [13]: Qualitative data

Coding

Classification

“Whenever it rains we plant: the pasture becomes green and beautiful”

Landscape

Descriptive

“Whenever we have the flu, we go quickly Adaptive for the lemon balm or mint tea” response

Analytical

“The foxes that invade our yard and eat our Trophic Theoretical chickens do not even serve to eat: we just competition kill them”

The way the researcher encodes a given qualitative data depends on the type of filter that is applied. In other words, the same data can be codified based on different classification criteria, depending on the view of the researcher who interpret and analyzes the information [14]. For example, qualitative research on the medical practices of a particular local community can identify reports as in the following passage: Normally I water my plants every morning as soon as I get out of bed (...), but watering should be one of the first things I think when I wake up. I come back and check once again if the plants that were very wilted in the morning had already regained the vigor that I know they have, which indicates that the water was well used by them (. . .). It’s such a joy to see them [the plants in the yard] at this period because I feel good and I know that taking good care of them always will have them close to me.

The habit of worrying about backyard plants can be categorized as “concerns about the loss of medicinal plants,” “leisure activities” or even “occupational therapies.” It depends, of course, on the purpose of the study that investigates this social activity, and therefore, the importance of the detailed explanation of the whole process of analysis and categorization of textual information [10].

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Among the main coding techniques used by researchers in different areas, two deserve special mention because they are especially simple and useful. The first of these is line-by-line coding, in which each line of text is encoded, even if it does not correspond to complete sentences. The second is the case-by-case comparison, in which parts of the text of the same document, or excerpts of different documents, are compared (examples of these two types of coding in Box 3) [13]. Box 3 Example of Line-by-Line Coding and Case-by-Case Comparison: Line-by-line Text

Coding

Have always raised “I’ve raised my goats since I was a boy. (...). animals I do not like to depend on others, (...). (. . .) the whole problem is when the weather changes Considers himself/ herself independent greatly, the droughts are terrible.” Climate change is a problem Case-by-case comparison Informant Biography

Attitude towards raising animals

Sir x

He has been raising goats since childhood. He has many. Lives alone and does not rely on anyone’s help

Full dedication

Mrs y

She raises chickens at home. She is a full- Partial dedication time teacher. The animals are unconfined all day and confined in the night

Sir x

He does not raise animals, despite having No dedication parents farmers. He is a full-time driver. Lives with the parents

Regarding the first technique, we can note how complex and detailed a coding process can be. In the second, conversely, the researcher seeks divergences and/or similarities that enable them to identify relationships and patterns, inspiring the creation of codes for the various compared cases [10]. After coding, the researcher can systematically access the coded texts, comparing how these variations occur [11]. Manual coding is ideal for collections whose samples are relatively small. However, if the research contains large samples, the use of specialized software in the qualitative data analysis (CAQDAS— Computer Assisted Qualitative Data Analysis Software) is essential [14]. Besides the sample size, the time available and the researcher’s experience should be evaluated in order to choose the type of method to be used in the analysis of the collected data [15].

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Tables are one of the most used resources, since they assist in the organization of the thought during the creation of the codes, making possible the comparison between them [13] (see example of codification of a textual passage in Box 4). Memorandums are also very didactic and accessible coding tools, and correspond to field notes used by the researcher to record the names of each developed code. Besides that, additional information can be inserted, such as the dates each coding was made, and a description of the idea directed to codes [14]. The CAQDAS, conversely, offers the researcher a series of resources, helping them evaluate characteristics and relationships between texts [14]. However, many experts recommend using these software programs combined with manual resources (e.g., print or handwritten texts). Thus, the researcher can develop a greater familiarity with the data, assisting in the interpretation and the creation of analysis codes. Box 4 Hypothetical Example of Coding a Passage of an Informant About His Health History Regarding the Preference for Plants in the Treatment of Diseases. Encoding Allows for Summarizing an Idea of the Texts Analyzed in a Concept That Facilitates the Comparison with the Others Developed During the Research: “Here at home when we get sick, we only use the Coding: same plant remedy.1 (...) and medicine of 1. Exclusive preference pharmacy is for this new people,2 who were for plants born in this modern time, so do not 2. Influence of age understand medicine from the bush, right?3 3. Influence of (...). And the plants are very good, better than modernity/globalization 4. Efficacy/healing the pharmacy remedies (...).4 Now when the power weather is dry, a lot of plants are gone, there Lack of choice are the pharmacy remedies left, right?5 6. Adaptation strategy Sometimes we get a little more leaf and keep it, so when the drought comes we are not left without our medicine from the bush”6

5

Triangulation Triangulate the information to evaluate the data collected and analyzed in the field is perhaps one of the main steps of the qualitative analysis. Here, the objective is to confront results, seeking to reflect on the reliability and generalizations of the interpreted information (e.g., to verify whether the reported behavior matches the practice or to analyze different points of view of a given phenomenon). This process occurs simultaneously with the development of the study and helps researchers to resolve conflicts and/or search for evidence on the validity of the observed data [16]. Data triangulation practices occur through tools such as biographical analysis, interviewee validation, constant comparisons, and

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textual review. Analyzing the biographies offers the researcher varied information about how people organize their understandings of the world [10].2 These narrative texts are a particular view of the world and constitute a set of important information for qualitative analyzes, describing people’s life experiences with the studied phenomena. The validation of the interviewee is to compare the responses and behaviors of the interviewees at different moments of collection to validate them in different research situations [10]. Verbal validation is a common tool of this process, consisting of repeated interviews with the same informants, with their discourses investigated and systematized, to check the information through the analysis results [13]. According to Flick [10], to validate information in this manner, three considerations must be followed: (a) validate whether the discourse is correct, comparing old and current answers, for example; (b) whether its content is related to socially shared information; and (c) whether the content is sincere in terms of selfrepresentation of the respondent. This process assists in the inspection of the research findings and in the qualitative analysis, essential as a method of data triangulation (see forms of data validation in Box 5). Divergences are highly context dependent and should always be considered for questioning what factors influenced these changes of ideas and opinions (new cultural events, pressures external to the interview, conflicts of interest, etc.) [16]. Constantly comparing research codes to investigate their relationships is the most important approach for analyzing qualitative research [10]. After the first interviews and the codification of all textual information,3 the researcher starts the process of hierarchizing the collected codes, relating the discourses, practices or field notes to create categories, information that will be associated and investigated about a certain observed social phenomenon [13]. In this sense, it is important to structure the codes and related textual passages in a way that allows for a more efficient systematic comparison between the information presented [3]. Using tables or flowcharts can be a good strategy, assisting in the construction of matrices that allow to relate different categories of analysis,4 searching for differences and similarities between the reports of the people in the process of categorization [16]. Structuring information in this manner prevents errors and duplications in the codebook and

2

“Tell a little about the “x” relation to your life story?” e.g., the “x” being the observed phenomenon, usually lead to chronological narratives that reflect individual and shared experiences of people with their collective contexts (institutional, political, etc.) and socioeconomic (childhood, professional training, marriage, paternity, etc.) [13]. 3 E.g., developing a book listing all the codes used in the analysis and descriptions of their meanings, helping to identify and adjust the categorizations of the research [17]. 4 Here we emphasize the importance of using computer software to organize this large amount of data, see Sect. 3 of this chapter.

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allows for a general view of the interpretations of all actors involved in the observed phenomenon [13]. Post analysis, interviews and field observations can be thought to fill in explanatory gaps or to make new questions that arise from the analysis of these categories, and this process is fed back until the theoretical saturation of the phenomenon. Finally, the textual review consists literally of revising the textual data for irregularities. This practice allows for a review of informants’ expressions and updates in the codebook, as well as revisiting the general information of the collected data, establishing opportunities for a dense analysis of the relations from the first research questions [13]. Box 5 Constant Validation Checking (Extracted from Bernand [1]): 1. If you are interviewing people, look for consistencies and inconsistencies among knowledgeable informants and find out why those informants disagree about important things 2. Whenever possible, check people’s reports of behavior or of environmental conditions against more objective evidence. If you were a journalist and submitted a story based on informants’ reports without checking the facts, you would never get it past your editor’s desk. Why not hold anthropologists to the standard that journalists face every day? 3. Be open to negative evidence rather than annoyed when it pops up. When you run into a case that does not fit your theory, ask yourself whether it is the result of: (a) normal intracultural variation, (b) your lack of knowledge about the range of appropriate behavior, or (c) a genuinely unusual case 4. As you come to understand how something works, seek out alternative explanations from key informants and from colleagues, and listen to them carefully. American folk culture, for example, holds that women left home for the work-force because of what are widely called “feminism” and “women’s liberation.” That is a popular emic explanation. An alternative explanation is that feminist values and orientations are supported, if not caused, by women being driven out of their homes and into the workforce by the hyperinflation during the 1970s that drove down the purchasing power of their husbands’ incomes (Margolis 1984). Both the emic, folk explanation and the etic explanation are interesting for different reasons 5. Try to fit extreme cases into your theory, and if the cases will not fit, do not be too quick to throw them out. It is always easier to throw out cases than it is to reexamine your own ideas, but the easy way out is hardly ever the right way in research

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References 1. Bernard HR (2006) Research methods in anthropology. Qualitative and quantitative approaches, 4th edn. Altamira, Oxford 2. Glaser BG, Strauss AL (1967) The discovery of grounded theory: strategies for qualitative research. Aldine Transaction, Piscataway, NJ 3. Charmaz K (2006) Constructing grounded theory: a practical guide through qualitative analysis. Sage Publications Ltd, London 4. Ando H, Cousins R, Young C (2014) Achieving saturation in thematic analysis: development and refinement of a codebook. Compr Psychol 3:1–7 5. Galvin R (2015) How many interviews are enough? Do qualitative interviews in building energy consumption research produce reliable knowledge? J Build Eng 1:2–12 6. Hagaman AK, Wutich A (2017) How many interviews are enough to identify metathemes in multisited and cross-cultural research? another perspective on Guest, Bunce, and Johnson’s (2006) landmark study. Field Methods 29:23–41 http://journals.sagepub.com/ doi/10.1177/1525822X16640447 7. Guest G, Bunce A, Johnson L (2006) How many interviews are enough? Field methods, vol 18, pp 59–82 http://journals.sagepub. com/doi/10.1177/1525822X05279903 8. D’Avigdor E, Wohlmuth H, Asfaw Z, Awas T (2014) The current status of knowledge of herbal medicine and medicinal plants in Fiche, Ethiopia. J Ethnobiol Ethnomed 10:1–32

9. McLellan E, MacQueen KM, Neidig JL (2003) Beyond the qualitative interview: data preparation and transcription. Field Methods 15:63–84 10. Flick U (2009) An introduction to qualitative research. Sage Publ, London 11. Chambliss DF, Schutt RK (2013) Making sense of the social world: methods of investigation, 4th edn. Sage, Thousand Oaks 12. Creswell JW (2007) Projeto de pesquisa: me´todos qualitativo, quantitativo e misto, 2nd edn. Artmed, Porto Alegre, RS 13. Gibbs G (2008) Analyzing qualitative data. The SAGE Qualitative Research Kit London. SAGE, London ˜ a J (2009) The coding manual for quali14. Saldan tative researches. Sage Publications Ltd, Los Angeles, CA 15. Basit TN (2003) Manual or electronic? The role of coding in qualitative data analysis. Educ Res 45:143–154 16. Beal XV (2011) ¿Co´mo hacer investigacio´n cualitativa? Una guı´a pra´tica para saber que´ es la investigacio´n en general y co´mo hacerla, con e´nfasis en las etapas de la investigacio´n cualitativa. ETXETA, Jalisco, MX 17. MacQueen KM, McLellan-Lemal E, Bartholow K, Milstein B (2008) Team-based codebook development: structure, process, and agreement. Handb Team Based Qual Res 2008:119–135

Chapter 6 Discourse of the Collective Subject as a Method for Analysis of Data in Ethnobiological Research Izabel Cristina Santiago Lemos, Gyllyandeson de Arau´jo Delmondes, Dio´genes de Queiroz Dias, Irwin Rose Alencar de Menezes, George Pimentel Fernandes, and Marta Regina Kerntopf Abstract Collective subject discourse (CSD) is a systematic method of organization and tabulation of qualitative data, anchored in the theory of social representations, combining methodological rigor and the search for the essence of thought expressed in a given social context. Some advantages of the CSD include the possibility of working with numerically more representative samples, as well as contemplating quantitative aspects of the studies directed to the most diverse academic areas of knowledge. Our objective is to highlight the principles for the operationalization of the DSC, its main characteristics and shed light on its use in the field of research in ethnobiology. Key words Ethnobiology, Research methods, Discourse of the collective subject

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Discourse Analysis: Initial Concepts What we consider today as studies of a qualitative approach, they emerged in the nineteenth century in the social sciences. In 1932, the book Methods of Social Investigation was published, by Sidney and Beatrice Webb, leading names in English sociology. In this work, the Webb couple disseminated the use of interviews, documents and personal observations as instruments to collect data on the empirical reality of human beings [1]. However, there was no methodological clarity regarding the treatment of data and the massive comparison with the quantitative methods proclaimed by the natural sciences left the qualitative studies obfuscated in the academic environment, being restricted, almost exclusively to anthropology—due to the influences of Malinowsky and Boas and their ethnographic studies. At least, this was until the 1960s, with the emergence of journals dedicated exclusively to qualitative methods, as well as the defense of the qualitative

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_6, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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approach by exponents of the studies of the natural and exact sciences [2]. Besides ethnographic studies that are notoriously recognized as qualitative, there are case studies (life histories) and documentary research (reports, films, photos, drawings) that can be appropriately considered as qualitative research. Thus, currently, the qualitative approach is widely used and recognized in the academic environment, having gradually consolidated as a formidable way of producing data. Regarding the treatment of these data, there are two classic ways of conceiving analysis in qualitative research, although they are not the only ones: content analysis and discourse analysis [3]. Content analysis (CA) arose even before the consolidation of qualitative studies, and therefore it is traditionally a quantitative method, anchored in processes that guide its application in a logical and sequential way. This type of method was originally used to analyze journalistic material transmitted during periods of armed conflict, pointing out variables and citation frequencies. That is, it was applied to the written text. Currently, some authors have given a qualitative approach to CA, recognizing the need to go beyond the written word and adopting theoretical conceptions to better base the analyses [4]. On the other hand, discourse analysis (DA) is based on three main historical axes: linguistics, Marxism, and psychoanalysis with Michel Peˆcheux as the main representative of the traditional French DA. Thus, the DA proposed a more thorough analysis, associating internal and external elements in the production of discourses, and for that reason, inseparable from the social reality that created it, supported by an ideology. According to Peˆcheux [5], ideology is the representations of a certain class. Thus, once there are several classes, a society will express ideological differences, capable of expressing different discursive formations in a concrete way, with “what can and must be said in a certain epoch” as the discursive formations. In this way, “there is no discourse without subject and there is no subject without ideology”. Thus, anchored in the precepts of qualitative research— although not restricted to this approach, as we shall see—and from DA, the proposal of the Collective Subject Discourse—CSD of Lefe`vre and Lefe`vre [6] arises as a method of organization and tabulation of qualitative data, allying the search for the essence of thought expressed in a given social context and methodological rigor in the treatment of research data, enabling to “make the community speak directly” ([6], p. 16). Therefore, our objective is to highlight the principles for the operationalization of CSD, highlighting its main characteristics and shedding light on its use in the field of research in ethnobiology as an important resource for data analysis.

Discourse of the Collective Subject as a Method for Analysis of Data in. . .

2

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The Method The CSD consists in the search for the representation of collective thought, from the construction of a discourse-synthesis originated from the discursive contents of different individuals. Simply stated, the CSD is the junction of individual discourses, generated through an open question that effectively expresses the thought of a collectivity [6]. In this sense, through this CSD proposal to tabulate qualitative data from a verbal nature, it becomes possible for each individual interviewed in the study to contribute to the construction of collective thinking. This methodological procedure is supported by the empirical perspective that the collective character of social thought can be measured by the number of choices of a particular group of people belonging to a given community, so it can be considered socially shared, although expressed individually [7]. According to Lefe`vre and Lefe`vre [6], the CSD is based on the hypothesis that when individuals in society, they share beliefs, values, and social representations. Consequently, a methodological process was developed capable of managing an organization of the verbal expressions generated by the social research that use open instruments for the data collection. This methodological process is systematically oriented through specific elements for its development, called operators, being the Central Idea, the Anchorages, the Key Expressions and the CSD as the final product of this process [6]. According to Lefe`vre and Lefe`vre [6], key expressions (KE) are literal transcriptions of the discourse that reveal the essence of the statements, leading to their signification, properly speaking, evidencing the central idea that permeates a certain thought. For this reason, the authors also point out that there is no way to dissociate the KE from the central ideas (CI), and these operators are indispensable for the formation of the CSD. In the case of central ideas, they are defined as a description of the meaning of the statements. According to the authors: “The central idea has. . .the important function of individualizing a given discourse or set of discourses, positively describing its semantic specificities” ([6], p. 25). It is further emphasized that an individual may present in his speech, for the same issue, more than one CI. In turn, anchorages (AC) are explicit manifestations of a belief that the author of the discourse professes and that is used to frame a specific situation. They can be generalist comments, guided by common sense, markedly notorious in speeches and usually easy to identify. It should be emphasized that ACs, contrary to what happens with KE and CI, are not mandatory to compose the CSD. Therefore, identifying the methodological figures cited above (KE, CI, and AC), they will be the CSD, considered as the main

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methodological figure expressed from the method. According to Lefe`vre and Lefe`vre ([6], p.18): “The the collective subject discourse is a discourse-synthesis. . .composed of KEs that have the same CI or AC.” [6]. As exemplified in the schemes below:  CI1 Representation A : CSD1 ¼ KEðn2Þ þ KEðn5Þ þ KEðn8Þ þ KEðnx Þ  AC1 Representation B : CSD 2 ¼ KEðn3Þ þ KEðn7Þ þ KEðn9Þ þ KEðnx Þ Source: Schemes proposed by the authors. where: CSD ¼ Collective subject discourse KE ¼ Key expression CI ¼ Central idea AC ¼ Anchorage n ¼ Participant in the survey Another feature of the CSD is the fact that it is evidenced in the discursive mode. These authors argue that representation by charts, tables, and categories is characterized as farther from reality as concrete individuals think, and therefore the use of discourse is more appropriate as a more vivid and real form of representation of collective thought, providing a clearer picture of the thought of a collectivity [6]. Nevertheless, it is emphasized that the representation of adjuvant data—such as number of informants, gender, profession—as well as the prevalent CI present multivariate forms of presentation and can be expressed either using simple descriptive writing, as an auxiliary resource for organization and general visualization of the data. In this context, it is highlighted that to reach the desired collective thought, a representative sample of a population considered for the study is necessary. Only in this way, it will be possible to have the representation of internalized ideas in the set of opinionating individuals, that is, the collective subject [8]. However, to trigger collective thinking, the use of an essential object is required: the open question. The open question will be responsible for producing the thought, and it is still considered as the research procedure that stimulates the expression of the thoughts of individuals in a more intensely discourse [9]. It is important to emphasize the guiding question in the presentation of the results. The following is an example of organization and presentation of data that can be used in ethnobiological studies (Box 1).

Discourse of the Collective Subject as a Method for Analysis of Data in. . .

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Box 1 Relationship between central ideas of question X, the proportion of responses according to the participants of the research and CSD for question X: Question X: What is your opinion about [. . .]? Central ideas

Community informants N %

A B C ... Total of informants ¼ a Collective subject discourse CSD—Central idea A: [. . .] CSD—Central idea B: [. . .] CSD—Central idea C: [. . .] Source: Data organization proposed by the authors a A discourse may present more than one central idea

Consequently, each CSD is made up in the first person singular, so the thought of a group or collectivity will be expressed as an individual discourse. This is the qualitative variable of the CSD. However, after the construction of the speech-synthesis, it becomes possible to identify the quantitative variable for each CSD. This variable has two attributes: intensity and amplitude [8]. Thus, Lefe`vre and Lefe`vre [8] characterize intensity as the number or percentage of individuals who contributed with KE and CI that sketched similarities or complement each other at a given time for the preparation of the different synthesis speeches. Regarding to amplitude, it can be understood as the measure of the presence of the CSD considering the field or universe. Therefore, the CSD is appropriately a qualitative and quantitative technique, since the search for the rescue of social representations is qualitative in the sense of its object of investigation, that is, the search for collective thought, which cannot immediately be identified by purely quantifiable resources [8]. However, after the identification of the central ideas, key expressions, anchorages and confection of the CSD, a quantitative treatment can be applied, since the quantitative dimension of opinion is based on an inseparable integration with the qualitative dimension, considering that they concern the quantity of individuals or responses that contributed to the making of each discourse-synthesis [6].

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Therefore, contrary to what some researchers claim, quantity and quality are complementary and not mutually exclusive concepts. In the CSD technique, for example, there is an inherent merger between quality and quantity, as the authors argue [6]. Thus, the CSD emerges as a proposal that inserts a significant change in the field of qualitative research, which through this methodological procedure assume the status of qualitative research or mixed approach, since it is possible to know and measure the representations of collective discourses about the most diverse topics that interact at the core of their social reality with methodological rigor [10]. Thus, for the correct application of the CSD technique, it is necessary to recover the meaning of the collective opinions of a given group, at the heart of these collective opinions will be originated numerous CSD, being a complex process, that must be subdivided into several moments [9], respecting a hierarchical order of well-established steps, performed through operations that will be performed on the collected material.

3

Software for the Construction of the CSD: Qualiqunatisoft and CSDsoft Subsequently, the data collected should be appropriately transcribed for analysis. At this point, the researcher can choose to perform the technique manually or use the Qualiquantisoft as an aid to analysis. The use of the software is encouraged, considering the particular aspects of the organization of the records and valuation of the mixed approach. Thus, it is emphasized that the purpose of this program is to enable a remarkable optimization of the technical work for the analysis of the research data. Also, the software allows to effectively relating the qualitative and quantitative aspects of studies using the CSD for data analysis [11]. The software is composed of registers (allowing the archiving of data and databases related to interviewees, surveys, and questions, among others); analyses (they are tables and processes that enable the accomplishment of the pertinent stages to the construction of the Collective Subject Discourses); tools (responsible for the export and import of data, as well as the results of research) and reports (performing the organization and allowing the printing of the results of the research) [11]. However, it is noted in particular by the Collective Subject Discourse Research Institute (CSDRI), that QualiQuantiSoft can be correctly classified as a facilitator and not substitute, in any instance, for the work that must be performed by the researcher. In fact, this software is a relevant aid for the researcher. Thus, Qualiquantisoft allows producing CSD adopting more reliable, systematic, explicit and standardized procedures, building

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the social speech through the speech of individuals, aimed by the researcher. This process carried out with the use of the software represents a greater effectiveness of the investigative activity, besides the saving of time for the researcher. Moreover, the use of Qualiquantisoft enables to carry out the research work with relatively numerous samples—when considering the reality of qualitative research—besides important data registers and the application of filters according to the different variables considered. It should be noted that other research software is currently available with the CSD, DSCsoft, considered the new software of the Collective Subject Discourse. It should be noted that DSCsoft has been idealized by the same creators of Qualiquantisoft and the trend is to replace it gradually, as it is presented as improved software compared to its predecessor and with new features and breadth of analysis of the samples. Therefore, besides the tools of Qualiquantisoft of the operational and visual advances, it is useful to point out that DSCsoft presents a greater capacity for the registration of the speeches, allowing the analysis with numerically more representative samples. It also allows for a more effective association of the qualitative and quantitative aspects of the studies, producing the intersection of subjective and objective variables, such as “beliefs” and “age”, for example [12]. Nevertheless, although the transition from Qualiquantisoft to DSCsoft is a natural and expected trend, Qualiquantisoft is still widely used by several higher education institutions with the license, being adopted as a standard program in public and private institutions that use the CSD, which justifies its relevance in the application of the method.

4

The CSD and the Research with Ethnobiological Approaches As discussed previously, the thought is collected from the use of open questions, which allows the internalized thought to be expressed through a discursive behavior, enabling to externalize a social fact of interest to the researcher. Thus, the CSD enables to employ a data analysis capable of allying the voices of the individuals who participated in the research in different representative discourses, not excluding their subjectivity, characteristic of qualitative research, while making feasible a reliable and quantitative evaluation of the ideas, based on a specific method, clear and reproducible. Therefore, considering all the reasons presented, starting from the genesis of discourse analysis, firmly as a method, the theoretical basis of the CSD, as well as the applicability of the technique, it is

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reinforced that the CSD is appropriate for data analysis in ethnobiological research. Let us see a few examples in this sense. In a study conducted in the municipality of Igarassu, in the Atlantic Forest, state of Pernambuco, Brazil, Silva et al. [13] sought to identify the perceptions of the local landscape by the vision of students from the fifth to the eighth grade. The collective subject discourse was used as one of the methodological approaches for the analysis of the data, probably being the pioneer publication in the use of CSD in the field of research in ethnobiology. Thus, in this study, 12 central ideas were identified, together with the corresponding key expressions, presented in tables, and it is possible to draw a panorama of children’s collective thinking about the local landscape. Some important CI were: I love the forest; We are happy because we have forests, they have many types of life; We are killing the forests, we have to preserve; People are destroying the forests and that is bad. We have to have preservation. These CI were expressed by fifth, sixth, seventh, and eighthgrade students, respectively [13]. Sensitive key expressions indicated by the authors are also highlighted, such as: “We are destroying the green of our forest. . .trees cut down and animals hunted. . .deforestation is a crime against nature. We, humans, have to cut down trees and then plant others” ([13], p. 204) and, “I think of the riches that the forest gives us. I am afraid that the day will come when we will not see these landscapes anymore. . .People should take care of the forest” ([13], p. 205). Something that became evident through the CSD was the conservationist view in all the grades considered in the research. In the dissertation of Lemos [14], the technique was also used. The objective of the study was to learn about traditional knowledge about the use of natural resources to treat acute respiratory infections, diarrhea, and anemia in children living in a traditional community located in the northeast of Brazil. The qualitative focus of the study was achieved through the search for an understanding of the meaning attributed to the use of these traditional resources by mothers or caregivers of children, as well as the reflection of this practice for conventional medicine. In the data analysis with the CSD, there were 46 central ideas identified for five questions, which revealed an appreciation of the use of natural resources to treat common childhood diseases. A relevant aspect to be highlighted was the organization of the data prioritizing the mixed approach allowed by the CSD, exposing qualitative and quantitative aspects of the discourses. The data were organized into tables and charts [14]. One of the questions asked was: Have you ever talk to a health professional about how you use plants or parts of animals to treat your child’s illness? Tell me how it was. Only for this question, there were nine CI, such as: Yes, but I was shy and I did not talk any more; No, because I was afraid and/or ashamed; I tried, but they

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did not pay attention; No, because they do not ask, they do not show interest and No, because they do not believe in the effectiveness of this type of treatment [14]. Thus, according to the author, the results from the CSD analysis showed that considering cultural aspects in the child health care approach is relevant, since they are resources widely used by families and regarded as effective therapeutic options for a range symptoms and health situations in the context of diseases prevalent in childhood [14]. In the article by Sousa et al. [15], conducted in a quilombola community in northeastern Brazil, the CSD was also the method of choice for organization and data analysis, the objective of the research was to investigate the forms of use and storage of plants found in the community. Differently from the previous examples mentioned, the data for this study were listed emphasizing only the CSD as the main operators of the method and focusing exclusively on the qualitative analysis of the discourses. Some particularly interesting passages from the study by Sousa et al. [15] and that can be punctuated in the speeches represented are: “I learned from the older ones here [. . .] My grandmother was a blesser; blessed people here and in Coqueiro. My aunt prayed here and my mother is [. . .] a healer for the children here”—about who from whom he learned to use plants ([15], p. 233); “I plant it here in the yard. I plant it and take care of it so it does not die with the drought. When there is no one around the house, I look for it at my mother’s house or the neighbor’s house”—about how she gets the plants mentioned ([15], p. 234) and “It does good and it does not do any harm. Medicine from a plant is better than medicine from a drugstore. It makes us better. So, it does good and not harm. It does not harm at all”—about adverse effects and contraindications related to plant use ([15], p. 235). In Alves research [16], the author sought to analyze the relationship between the use of plants, their meanings, and conventional and traditional treatment for diagnosed people with systemic arterial hypertension (SAH) in a quilombola community in northeastern Brazil. In this study, it was possible to evidence a number of CI, from the application of the CSD technique with six subjective questions. Therefore, in the study of Alves [16], some peculiar points were the accomplishment of the analysis in agreement with the theory of social representations—what allows for a more critical and ample vision of the processes investigated—the identification of anchorages to back up and validate a widespread thought in the community and the interdisciplinary approach that permeated the whole study, bringing together relevant discussions at the heart of the biological sciences and health sciences. The data were presented through written representation of the speeches and organized in tables, prioritizing the qualitative approach of the method.

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In this sense, according to the author and through the speeches, it was possible to understand the meaning given to hypertension and its direct relationship with culture and psychosocial aspects, factors that will directly reflect the forms of treatment and the therapeutic scheme adopted by different populations. In the case investigated, this was evident through the use of plants over conventional treatment, as reported by some residents [16]. It is worth mentioning the research by Brasil et al. [17] who sought to evaluate the preference between drugs or plants for pain management in a quilombola community. In this aspect, the study adopted the CSD as a method of analyzing the verbal expressions of the participants, combining qualitative and quantitative variables, with an expressive sample—in the context of qualitative methods for analysis—of fifty-two residents. Thus, the research of Brasil et al. [17] concluded that most study participants used teas for pain management, and although some of them used conventional medications, they attributed to plants a greater efficacy in pain management. One notable aspect of the research was the use of classical representation in data expression, with all CI listed for each question and all CSD expressed for a more reliable view of the thoughts represented by the community. It should be noted that there were 26 CI distributed in four subjective questions. For example, for the question about the opinion of the residents regarding the home preparation with plants for the treatment of pain, the prevalent CIs were: “It is good because it’s effective,” expressed by 61.54% and “It’s good, but it depends on the type of pain,” indicated by 21.15% of the participants [17]. For the question about the residents’ view regarding conventional drugs, the most significant CI was: It is effective, but tea is better, for 38.46% of the sample. Regarding the use in association of plants and drugs, 88.46% reported that they do not use it because it can cause poisoning. Concerning the substitution of drugs by plants, 51.92% expressed they do not substitute them, but they could not identify the reasons for this [17]. It is worth mentioning some important discourses in the research of Brasil et al. [17], such as: “[. . .] the medicine from the pharmacy did not work, with faith in God I became good with medicine from the plants. I already had the acetaminophen once and it did not work [. . .] I took the tea and solved it.” ([17], p. 777); “No!” “God!” You cannot take both because you can poison. Everyone here knows that you cannot take the two together: the plant and the drug; it is too risky” ([17], p. 776) and “I do not change my tea, I drink tea first. I see the people going to the health centers, to the hospital, I’m not going. I think it is a waste of time because I have everything here [. . .]” ([17], p. 775). However, some aspects should be discussed on the use of CSD in ethnobiological research, aiming at an improvement in the use of

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the technique, enabling better analysis and, consequently, a higher quality of published research. Thus, at least two aspects are noteworthy: the presentation of the data and the case of the theory of social representations. One of the great advantages of the CSD is to enable the representation of subjective data in a precise way, drawing a general picture of the expressed thoughts of a given population. When we do not show some of the basic operators of the method in presenting our results, such as KE and CI, we can distort or blur the general understanding of the results achieved, with a meticulous organization of the basic operators, which in simple textual writing, or using tables and charts. In part, this problem is due to the internalization of the most common forms of analysis of qualitative data, as well as their presentation. However, this fact may jeopardize the understanding of the results, as well as not to showing specific characteristics of the method, which would be regrettable. This problem is also related to the lack of control over the operation of the CSD. Another fact that contributes to an inefficient organization and presentation of the data is the nonuse of the specific software for the CSD. Although this is not a requirement, it is highly advisable to use Qualiquantisoft and, more recently, CSDsoft as auxiliary tools in the CSD analysis process, allowing a better organization and tabulation of results, combining objective and subjective aspects. Another aspect that needs to be improved in the publications that use the CSD is the consideration of the theoretical basis of the method, anchored in the Theory of Social Representations [18]. When it is left out of the context of the analyses, these become superficial and not elucidating, providing only a pragmatic view descriptive of the findings. Thus, the CSD cannot be dissociated from the theoretical considerations that permeate the method. Otherwise, we would be analyzing only content in a classical perspective, and not speeches.

5

Final Considerations Thus, the studies cited during the chapter are only a few practical examples of how CSD can be effectively applied in the context of ethnobiological research, regardless of the ethnobiological aspect considered. Therefore, the CSD goes beyond the simple mechanical representation of discourses or written representation of verbal expressions allocated in a given category in an impersonal and random manner, as observed in other methods widely used in the context of qualitative research. As a method of organizing, tabulating, and analyzing data based on the theory of social representations, the CSD is particularly interesting because it allows to ally different representative

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voices of a given collective thought in clear sentences and consonants, drawing a vivid, real and tangible panorama of the discourses of different individuals, assisting in the more thorough analysis of the results obtained in the field. Its systematic operationalization—besides the aid of software developed specifically for analysis by the CSD—assists in the construction of well-delineated and precise sentences, however, without losing the inherent subjectivity of thought and enabling through the expressed discourses, to scan the core of the representations imbued in each sentence, which lies at the heart of DA. Another advantageous aspect is that the CSD is applicable to samples of wide amplitude and this is due to the methodological process adopted for it, allowing even the subsequent intersection of objective and subjective variables. Consequently, according to the authors of the method, the CSD not only allows this type of qualitative and quantitative association but it also evidences the need for a mixed treatment of the data [7]. Thus, with all the characteristics highlighted for the CSD and its uniqueness in the analysis of the data of the qualitative studies, it is reinforced that its use in ethnobiological research has the potential to enrich the subjective analyses of thoughts, beliefs, and concepts. Therefore, when we go to the field to carry out our surveys, our notes, and records, there is always a presence that goes through these objective data, before the research, during the study or after initial impressions and impact assessments. That presence is the human presence, rich in subjective accounts, experiences, and values. These qualitative aspects, which are historically confused with the very emergence of ethnographic studies with Boas and, most notably, Malinowski, may be explicit or implicit, and disregarding them does not bring us closer to a more robust and scientific analysis, but distances us from a one of the central aspects of our ethnobiological studies and that rests in the cradle of Anthropology: human relationships and representations. References 1. Turato ER (2005) Me´todos qualitativos ˜ es, e quantitativos na a´rea da sau´de: definic¸o diferenc¸as e seus objetos de pesquisa. Rev Saude Publ 39:507–514 2. Godoy AS (1995) Introduc¸˜ao a` pesquisa qualitativa e suas possibilidades. Rev Adm Empres 35:57–63 3. Bauer MW, Gaskell G (2015) Pesquisa qualitativa com texto, imagem e som: um manual pra´tico (Pt.). Editora Vozes, Petro´polis

4. Krippendorff K, Bock MA (eds) (2009) The content analysis reader. Sage Publications, Thousand Oaks, CA, pp 234–242 5. AAD PMA d (1990) In: Gadet F & Hak H. Por uma ana´lise automa´tica do discurso (Uma introduc¸˜ao a` obra de Michel Peˆcheux). Pontes, Campinas 6. Lefe`vre F, Lefe`vre AMC (2005) O discurso do sujeito coletivo: um novo enfoque em pesquisa qualitativa (desdobramentos). EDUSC, Caxias do Sul

Discourse of the Collective Subject as a Method for Analysis of Data in. . . 7. Lefe`vre F, Lefe`vre AMC (2012) Pesquisa de Representac¸˜ao Social: um enfoque qualiquantitativo. 2 Ed. Lı´ber Livro Editora, Brası´lia 8. Lefe`vre F, Lefe`vre AMC (2006) O sujeito coletivo que fala. Interface (Botucatu, Online) 10:517–524 9. Lefe`vre F, Lefe`vre AMC (2005) Depoimentos e Discursos: uma proposta de ana´lise em pesquisa social. Lı´ber Livro Editora, Brası´lia 10. Figueiredo MZA, Chiari BM, Goulart BNG (2013) Discourse of collective subject: a brief introduction to a qualitative-quantitative research tool. Distu´rb Commun 25:129–136 11. Lefe`vre F, Lefe`vre AMC (2014) O que e´ o DSC/Qualiquantisoft. IPDSC – Instituto de Pesquisa do Discurso do Sujeito Coletivo. Disponı´vel em, Sa˜o Paulo http://www.spi-net. com.br/manual-qqsoft.pdf 12. DSCsoft (2015). Disponı´vel em. http://www. tolteca.com.br/dscSoft.aspx 13. Silva TC, Medeiros PM, Sousa TA, Albuquerque UP (2010) Northeastern Brazilian students’ representations of Atlantic Forest fragments. Environ Dev Sustain 12:195–211 14. Lemos ICS (2015) Uso de recursos naturais para o tratamento de doenc¸as prevalentes na ˜ es da Etnomedicina ao infaˆncia: contribuic¸o estudo da Medicina Tradicional. Dissertac¸˜ao

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(mestrado em Bioprospecc¸˜ao Molecular). Departamento de Quı´mica Biolo´gica, Universidade Regional do Cariri, Crato 15. Sousa GM, Fernandes GP, Kerntopf MR, Barbosa R, Lemos ICS, Alves DA, Oliveira DR (2017) Ethnobotanical study of Arruda quilombo community in the State of Ceara´, Brazil. J Med Plants Res 11:232–238 16. Alves DA (2017) Utilizac¸˜ao de plantas medicinais em pessoas com hipertensa˜o arterial sisteˆmica: estudo etnobotaˆnico em uma comunidade quilombola. Dissertac¸˜ao (mestrado em Enfermagem). Departamento de Enfermagem, Universidade Regional do Cariri, Crato 17. Brasil AX, Barbosa MO, Lemos ICS, Lima CNF, Delmondes GA, Lacerda GM, Monteiro AB, Dias DQ, Silva AA, Fernandes GP, Barbosa R, Menezes IRA, Coutinho HDM, Felipe CFB, Kerntopf MR (2017) Preference analysis between the use of drugs and plants in pain management in a quilombola community of the state of Ceara´, Brazil. J Med Plants Res 11:770–777 18. Lefe`vre F, Lefe`vre AMC (2014) Discurso do ˜es sociais e interSujeito Coletivo: representac¸o ˜ es comunicativas. Texto Context Enferm venc¸o 23:502–507

Part II Methods and Quantitative Techniques

Chapter 7 Going Back to Basics: How to Master the Art of Making Scientifically Sound Questions Thiago Gonc¸alves-Souza, Diogo B. Provete, Michel V. Garey, Fernando R. da Silva, and Ulysses Paulino Albuquerque Abstract Inspired by the famous quote of Leonardo da Vinci, this chapter builds upon the idea that practice without theory is blind and unpredictable. Indeed, theory without practice can be idle. Accordingly, progress in science is made through approaches that integrate hypothesis testing and falsifiability or that investigate weight of evidence for multiple hypothesis, such as the hypothetico-deductive method (HDM) and Bayesian techniques. Here, we provided a straightforward way to combine the HDM with statistical thinking to create a diagram that links variables by causal links, which can improve the scientific method and statistical literacy. Key words Hypothetico-deductive method, Scientific flowchart, Prediction, P value

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Introduction He who loves practice without theory is like the sailor who boards ship without a rudder and compass and never knows where he may cast.—Leonardo da Vinci

Tell me what your question is. Perhaps this is the phrase that most young researchers listen to when they begin their scientific activities. Apparently simple, answering this question becomes one of the biggest challenges in scientific training. Whether in qualitative or quantitative research, the entire knowledge-seeking process starts from a question/problem formulated by the researcher at the beginning of the process. This question will guide the researcher in all stages of the research. In the specific case of quantitative research, the question will begin one of the most powerful ways of thinking scientifically: the hypothetico-deductive method (HDM) championed by Karl Popper [1]. This chapter proposes a way of thinking about scientific hypotheses (generated within the HDM) to improve statistical Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_7, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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thinking by using a flowchart that relate variables by causal links. In addition, we argue that you can easily use flowcharts to (1) tease apart relevant variables and how they affect each other; (2) improve (when necessary) experimental/observational design; (3) facilitate the selection of statistical analyses; and (4) boost data interpretation and communication.

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Questions Must Precede Statistical Analyses

2.1 A Bestiary of Hypothesis Testing (Are You Asking the Right Question?)

Most students and professors in the biological sciences have an aversion to the word “statistics”. Not surprisingly, whereas most academic disciplines in STEM (Science, Technology, Engineering, and Mathematics) have a strong statistical background in their undergraduate level, courses in the biological sciences have poor curricula in how to integrate statistical thinking within a biological context [2]. These courses have been frequently taught without any practical baseline to integrate students in a problem-solving platform [3]. Unfortunately, ethnobiology, ecology, and conservation (hereafter EEC) are not exceptions. More importantly, a major concern during the statistical training of EEC students is the need of working with complex, multidimensional problems, which demand analytical solutions even more complicated to a public without a background in statistics and mathematics. Hence, some researchers consider statistics as the most problematic part of their scientific research. We argue that the difficulty of using statistics in EEC is associated with the absence of a problem-solving platform stating clear hypotheses derived from a theory. However, we agree that there is a great challenge in ethnobiology to integrate this hypothesis-driven approach, because it was introduced only recently (see [4–6]). In view of the lack of a problem-solving platform, we frequently notice that students/researchers in EEC usually have a hard time answering basic questions for a scientific research, such as: 1. What is the main theory or logical reasoning of your study? 2. What is the main question of your study? 3. What is your hypothesis? What are your predictions? 4. What is the sampling unit, independent and dependent variables of your work? Is there any covariate? 5. What is the control group? How can one select any statistical test without answering those five questions? The frequentist statistical framework provides a way to go by progressively supporting or falsifying a hypothesis [1, 7]. The decision to reject a null hypothesis is made using a probability value (usually P < 0.05) calculated by comparing

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observed events with repeated observations that generate a null distribution. Now, let us teach by example and introduce a “guide to statistical thinking,” which connects some essential elements needed before running any multivariate (or univariate) analysis (Fig. 1, see also Fig. 1.3 in [8], and Fig. 1 in [9]). First, imagine you observed the following phenomena in nature: (1) “local people selecting some plants for medical purposes,” and (2) “monodominant patches of the tree Prosopis juliflora, an invasive species in several regions.” On the ethnobiology side, to understand how and why traditional knowledge is constructed, there is a theory or hypothesis (e.g., apparency hypothesis: Gonc¸alves et al. [10]) explaining the main processes dictating plant selection (Fig. 1a). Then, you can ask one or more questions related to those observed phenomena (Fig. 1b). For example, how does urbanization affect people knowledge about medicinal plant use in different biomes? On the ecological/conservation side, to understand why introduced species affect local native species, you need to understand the ecological niche and evolutionary theories [11, 12]. You can ask, for instance, how does exotic plants affect native plant community structure? Complex or vague questions difficult the construction of the research flowchart (see description below) and the selection of statistical tests. Instead, a useful question should indicate the relevant variables of your study, such as independent and dependent variables, covariate, sampling unit, and the spatial scale of interest (Fig. 1b). In the provided ethnobiological example, urbanization and people knowledge are the independent and dependent variables, respectively. Also, this study has a broad scale, as it compares different biomes. The next step is constructing the biological hypothesis (Fig. 1c), which will dictate the association between independent and dependent variables. In the ethnobiological example, the hypothesis is that (1) “urbanization affects people knowledge about medicinal plant use,” while the ecological hypothesis is that (2) “exotic species affect native community structure.” Note this is very similar to the main question. But you can have multiple hypotheses [13] derived from one theory. After stating the biological (or scientific) hypothesis, it is time to think about the corollary (logic derivation) of the hypothesis, which is called prediction (Fig. 1d). The predicted patterns are a very important step, because after defining it you can operationalize your variables and visualize your data. For example, the theoretical variable “Urbanization” can be measured as “urbanization grade along urban, peri-urban, and rural areas,” and “people knowledge” as “the number and type of useful plant species used for different diseases.” Thus, the prediction is that urbanization grade decreases the number and type of known plant species utilized for medicinal purposes.” In the ecological example, “Exotic species” can be

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Fig. 1 A guide to statistical thinking combining the hypothetico-deductive method (a–d, i) and frequentist statistics (e–i). See also Fig. 1 in Underwood [9], Fig. 1 in Ford [15], and Fig. 1.3 in Legendre and Legendre [8]

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measured as “the density of the exotic plant Prosopis juliflora” and “Community structure” as “native species richness and composition”. After you have operationalized your work in the light of the hypothetico-deductive method (HDM), the next step is “thinking statistically” about the formulated biological hypothesis (see Figs. 1e, f). Then, you need to define the null (H0) and the alternative (H1) statistical hypotheses. Two different “statistical hypotheses” can be derived from a biological hypothesis (Fig. 1e). Therefore, we are using the term “statistical hypothesis” in quotation marks, because the so-called statistical hypotheses are predictions sensu stricto, and often confound young students. The null statistical hypothesis represents an absence of relationship between the independent and dependent variables. After defining the null statistical hypothesis, you can derive one or multiple alternative statistical hypotheses, which demonstrate the expected association(s) between your variables (Fig. 1e). In our example, the null hypothesis is that “urbanization grade does not affect the number of useful plant species known for local people.” In turn, the alternative hypothesis is that “urbanization grade does affect the number of useful plant species known for local people.” After you operationalized your variables and defined the null and alternative hypotheses, it is time to plot the expected result (Fig. 2, Box 1) and choose an adequate statistical method. For example, if you want to compare the difference in the composition of useful plants between urban, peri-urban, and rural areas, you can run a PERMANOVA (Chap. 8, in this book) that uses the pseudo-F test statistics. Then, you have to choose the probability threshold (the P value) of the statistical test to decide whether the null hypothesis should or should not be rejected [14]. If you find a P < 0.05, you should reject the null statistical hypothesis (urbanization does not affect the number and composition of plants). Conversely, a P > 0.05 indicates that you cannot reject the null statistical hypothesis. Thus, the test statistics and the P value represents the last part of the statistical hypothesis testing, which is the decision and appropriate conclusions that will be used to feedback to the main theory (Figs. 1g–i). By generalizing your results and falsifying (or not) your hypotheses, the study is seeking to refine the conceptual construction of the theory, which is constantly changed (Fig. 1i, [15]). However, there is a critical point in this last statement, because statistical significance does not necessarily mean biological relevance (see discussion in Gotelli and Ellison [14], Martı´nez-Abraı´n [16]). In the words of Ford [15]: “statistics is used to illuminate the problem, and not to support a position.” Also, the hypothesis-testing procedure has some uncertainty, which can influence “false-positive” (type 1 error) and “false-negative” (type 2 error) results [17].

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Box 1 Type of Variables and Data Visualization: As described in Sect. 3, the flowchart is essential for connecting relevant variables for the research. To take advantage of this approach, you can draw your own graphical predictions to help you think about different analytical possibilities. Here, we provide a full description of types of variables that you must know before running any statistical analysis and plotting results. Also, we show a brief gallery (Fig. 2) with examples of good practices in data visualization (Fig. 3b, see also Fig. 8.1 in Chap. 8 in this book). Besides connecting different variables in the flowchart, you should distinguish the type of variable. First, you must identify the independent (also known as explanatory or predictor) and dependent (also known as response) variables. The independent variable is the one (or more) that predicts or affects the response variable (e.g., soil fertility is the independent variable that affects the abundance of a focal plant species, the dependent variable). Additionally, a covariate is a continuous variable that can affect the response or the independent variables, or both, but usually is not of interest of the researcher. After defining those variables and connecting them in the flowchart, it is time to differentiate their type: (1) quantitative or continuous, and (2) categorical or qualitative (Fig. 2a, Box 1). The type of variable will define what kind of plot you may select. For example, if you are comparing two continuous variables or one continuous and a binary variable, the best way to visualize them (Fig. 2b) is a scatterplot (Fig. 2c, d). The line represents the values predicted by the statistical model used (e.g., linear, logistic). If you are interested in comparing the range of different traits (or the description of any numerical variable) between categorical variables (e.g., species or local populations), a dumbbell plot is good option (Fig. 2e). Histograms can be also used to show the distribution of two continuous variables of two groups or factors (Fig. 2f). However, if you want to test the effect of an independent categorical variables (like an ANOVA’s design) on a numerical variable, boxplots (Fig. 2g) or violin plots can summarize them elegantly. Multivariate datasets, in turn, can be visualized with ordination (Fig. 2h) or cluster plots (not shown). There is a comprehensive website presenting several ways for visualizing data called datavizproject.com.

For the sake of simplicity, we will not further discuss the pros and cons of frequentist statistics, alternative methods (e.g., Bayesian and Maximum Likelihood), and philosophical issues regarding the “p value” (for a discussion on these topics see the forum in Ellison et al. [18]).

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Fig. 2 Type of variables (a) and data visualization (b) to represent the expected relationship between dependent and independent variables, or covariates

3 Flowchart: Connecting Variables to Improve Experimental Design and Statistical Analysis McIntosh and Pontius [19] stated that statistical thinking (represented in Fig. 1) includes four important steps: (1) what questions you would investigate (Sect. 4), (2) how and where to collect the data [20], (3) what factors should be considered and how they affect your variables of interest (and how they affect each other), and (4) what statistical analysis you should use and how to interpret and communicate results (Section 4). However, step (3) must be done before collecting the data. For example, if you are interested in investigating the benefits of riparian forests to native fish species, what variables should be included in the study? If you choose rivers with and without riparian forest as the single predictor variable, your sampling design will omit other confounding variables, such as river order and upstream soil organic carbon. Vellend [21] named this issue the “three-box problem” (see also [20]), which is the problem in inferring that X (independent variable) causes Y (dependent variable) when other variables create or magnify the

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Fig. 3 Example of how to use a flowchart to improve the understanding of the studied system. The theoretical question “What is the impact of invasion on native community and ecosystem properties? can generate two predictions: (1) the exotic plant Prosopis juliflora reduces beta diversity of native plant communities, and (2) Prosopis juliflora modifies plant composition, and reduces carbon stock and decomposition rates. After stating your predictions, you can construct a flowchart connecting the relevant variables and the expected associations between them (a). Also, you can use the information in Box 1 to identify which type of variable you will collect and what plot(s) can be used (b)

correlation between X and Y (see Fig. 2 in [20]). A useful tool for understanding the relationship among every relevant variable for your study is a flowchart. In the “research flowchart” (see also [22]) proposed here, dependent (also known as response) and independent (or predictor) variables, as well as covariates are depicted as boxes (with distinct shapes: Fig. 3). In addition, you can use an arrow to represent a (possible) causal pathway indicating strength and sign (positive or negative) of the predictor variable on the dependent variable (Fig. 3). By doing so, you could improve the experimental or observational sampling design including or controlling for confounding variables, which help you tease apart the contribution of different predictor variables in your system. Importantly, making connections among variables improve your ability to visualize the “big picture” of your research, which in turn affect your experiment, statistical analysis, and literature review. In fact, Arlidge et al. [23] argued that flowcharts facilitate the construction of scientific narratives by improving: (1) the definition of multiple working hypotheses, (2) gathering, interpreting, and spreading data, and (3) the communication of the study content. You can also refer to

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Magnusson et al. [22] for how to use flowcharts in statistical analysis. Furthermore, Ford [15] recommended the use of an analytical framework to foster research development. More importantly, the research flowchart can be used as a strong tool to accomplish Ford’s advices, which were: (1) define the asked question, (2) define the theory to be used, (3) define the technique of investigation (e.g., experiment, field observation), (4) define the measurements, (5) define how to make inference, and (6) interpret, generalize, and synthesize from data, which feedback to refine theory and modify (when necessary) future questions (Fig. 1).

4

Fundamental Questions in Ethnobiology, Ecology, and Conservation Theories are generalizations. Theories contain questions. For some theories the question(s) are explicit and represent what the theory is designed to explain. For others the questions are implicit and relate to the amount and type of generalization, given the particular choice of methods and examples used by researchers in constructing the theory. Theories continually change, as exceptions are found to their generalizations and as implicit questions about method and study options are exposed.—E. David Ford [15]

As we argued before, a relevant, testable question precedes statistical analysis. Thus, we present below 12 questions that can stimulate future research in EEC. Note, however, that we do not mean they are the only relevant questions to be tested in EEC (see, e.g., Sutherland et al. [24] for a full evaluation of cutting edge research avenues in Ecology; and Box 6.1 in Pickett et al. [25]). Specifically, these questions are very broad and can be further developed into narrower questions, hypotheses, and predictions. After each theoretical question, we presented an example of a study testing it and the relevant variables that can stimulate future studies. (a) How does land use affect biodiversity maintenance and spatial distribution of species at different spatial scales? Example: Several studies on different ecosystems and scales investigated how land use affects biodiversity. However, we highlight a study comparing global effects of land use (e.g., human population density, landscape to human uses, time since forest conversion) on terrestrial species (e.g., net change in local richness, average compositional dissimilarity) [26]. (b) What is the impact of biotic invasion on native communities and ecosystem properties? Example: Investigating how the establishment of exotic species affects species richness of the recipient, native communities, as well as how it impacts the delivery of ecosystem services. Previous studies have controlled the presence of invasive species or compared historical records (observational

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study) of these species and how they impact biodiversity. In addition, there is some effort in understanding the predictors of invasibility (e.g., gross domestic product of regions, human population density, coastal mainland and islands) [27]. (c) How does top predator decline affect the delivery of ecosystem services? Example: Investigating how the removal of large carnivores affects the delivery of ecosystem services, such as carbon sequestration, disease, and crop damage control. Previous studies have investigated this question by controlling the presence of top predators or comparing historical records (observational study) of species and several predictors (e.g., habitat loss and fragmentation, conflict with humans—hunting, utilization for traditional medicine, and depletion of prey) [28]. (d) How does ocean acidification affect primary productivity and food webs in marine ecosystems? Example: Recent studies tested the individual and interactive effects of ocean acidification and warming on trophic linkages across a food web. Acidification and warming have been manipulated by changing levels of CO2 and temperature, respectively. Previous studies demonstrated that elevated CO2 and temperature boosted primary productivity and affected the strength of top down control [29]. (e) How do we reconcile societal needs for natural resources with nature conservation? Example: There is a growing literature using landscape approaches to improve land management to reconcile conservation and economic development. The studies have mixed objectives, but in general they used stakeholder engagement, institutional support, effective structures of governance as predictor variables, and environmental (e.g., soil and water conservation, vegetation cover) and social-economic (income, social capital, public health, employment) improvements as dependent variables [30]. (f) What is the role of protected areas (PAs) for the maintenance of biodiversity and ecosystem services? Example: There has been considerable work in the last decade comparing the effectiveness of PAs for biodiversity conservation. Although this question is not completely separated from question E, the design of studies is relatively distinct. In general, researchers contrast the number of species and the delivery of ecosystem services (e.g., water and soil retention, carbon sequestration) between protected and unprotected areas [31].

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(g) How to integrate scientific and local people knowledge to mitigate the negative impacts of climate change and land use on biodiversity? Example: Extreme climatic events can have strong impact on agricultural yield and food production. Recent authors have argued that this effect can be stronger for small farmers. Future studies can investigate how rainfall and temperature affect agricultural yield and how traditional farmers or indigenous people deal with this negative impact. Traditional farming systems have lower soil erosion, and N2O/CO2 emissions than monocultures, and thus can be seen as a viable mitigating activity in a changing world [32, 33]. (h) How does climate change affect the resilience and adaptive strategies in social-ecological systems? Example: The changing climate alters both fisheries and agriculture worldwide, which in turn enforces humans to change how they grow crops. Recent studies have argued that agriculture in some countries will face risks under climate change. These studies compare different production systems, from conventional agriculture to other types made by local people. For example, there is a strong connection between (1) threatened and overfished species, (2) human development index (HDI) and average dependence on fisheries and aquaculture. Also, there is evidence that biodiversity may buffer climate change impacts by increasing land resilience [32, 34]. Also, an interesting approach is to investigate how local people deal with these challenges in terms of their perceptions and behavior. (i) How does biological invasion affect spatially and temporally the structure and functionality of social-ecological systems? Example: Many studies demonstrated that invasive species have negative biological, economic, and societal consequences. Here, similarly to question B, researchers controlled the presence of invasive species or compared historical record. However, recent works quantify not only native species richness and composition, but also animal/plant traits that directly affect the delivery of ecosystem services, such as provisioning (food, water), regulating (climate, flood control), supporting (nutrient cycling, soil formation), and cultural (ecotourism, cultural heritage) services [35]. But, invasive species can provoke positive effects on social-ecological systems by incrementing the availability of natural resources, impacting how people manage and use local biodiversity. (j) What is the relationship between phylogenetic and taxonomic diversity with biocultural diversity?

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Example: Recent studies have shown that there is a phylogenetic and taxonomic pattern in the resources that people incorporate into their social-ecological systems, especially medicinal plants. There is a tendency for people, in different parts of the world, to use phylogenetically related plants for the same purposes. Here, researchers can test how much this affects the diversity of practices in a social-ecological system, considering the environment, as well as its structure and functions [36, 37]. (k) What environmental and social-political variables change the structure and functionality of tropical social-ecological systems? Example: Testing the influence of human-driven environmental changes (e.g., fire, logging, warming) on keystone species and, consequently, how this effect cascade down to other species and ecosystem services (e.g., carbon storage, water cycle, and fire dynamics) [38]. (l) Do species traits influence how local people distinguish useful from useless plant or animal species? Example: Investigating whether local people have a nonrandom preference when selecting animal or plant species. You can evaluate whether different groups (e.g., tourists) or local populations (e.g., fishermen) select species based on similar traits. Recent studies have shown a potential link between plant (e.g., color, leaf, flowering) and bird (e.g., color, vocalization) traits and some cultural ecosystem services, such as aesthetic, recreational, and spiritual/religious [39]. As you have noticed, the questions were more theoretical and, consequently, you can derive testable predictions (using operational variables) from them (Figs. 1 and 3). For example, from the question “How does land use affect biodiversity maintenance and spatial distribution of species at different scales?” we can derive two different predictions: (1) population density (land use operational variable) changes species composition and reduces species richness at the landscape scale (prediction derived from the biotic homogenization hypothesis [40]); (2) the composition of plant traits is different in forest remnants with different matrices (sugarcane, cattle, city, etc.).

5

Final Considerations Tell me your secrets And ask me your questions Oh let’s go back to the start Running in circles, coming up tails Heads on a science apart

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Nobody said it was easy (...) Pulling the puzzles apart Questions of science, science and progress —The Scientist, Coldplay This is an excerpt of a song by the British rock band Coldplay from their 2002 album “A Rush of Blood to the Head.” The lyrics are an amazing comparison between science and the ups and downs of a broken relationship. The band made an astonishingly clear statement that, as a scientist, we (should) frequently ask questions, go back to the start after discovering they were wrong (or not) and run in circles trying to improve our knowledge. The band described in such an accurate way how cyclical (but not repetitive) is the scientific method. As the song goes: it is not easy, but learning how to ask good questions is an essential step toward knowledge consolidation. By including hypothesis testing in EEC we can be more precise. Definitely, this does not mean descriptive science is useless at all. On the contrary, the development of EEC, and mainly ethnobiology, was built upon a descriptive frontline, which means it was valuable to the foundation of Ethnobiology as a consolidated discipline [41, 42]. However, recent studies advocate that ethnobiology should dialogue with disciplines with stronger theoretical background, such as ecology and evolutionary biology to improve research on biodiversity [43]. In turn, incorporating local knowledge into ecology and evolution will certainly refine their own development, which ultimately benefits biological conservation [44]. In addition, (ii) there is an urgent need for training young researchers in the philosophy and methodology of science, as well as scientific communication and production [45]. As a concluding remark, we believe that the training of students in EEC needs a reappraisal that necessarily goes back to basic concepts and methods. Accordingly, researchers can combine the hypothetico-deductive method with statistical thinking using a research flowchart to go beyond description.

Glossary1 Assumption Hypothesis Mechanism

1

After Pickett et al. [25].

Conditions needed to sustain a hypothesis or build the theory. Testable statement derived from or representing various components of a theory. Direct interaction of a causal relationship that results in a phenomenon.

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Pattern Phenomenon Prediction

Process

Repeated events, recurring entities or replicated relationships observed in time or space. An observable event, entity or relationship. A statement of expectation deduced from the logical structure or derived from the causal structure of a theory. A subset of phenomena in which events follow one another in time or space, which may or may not be causally connected. It is cause, mechanism or constraint explaining a pattern.

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Going Back to Basics: How to Master the Art of Making Scientifically Sound. . . 24. Sutherland WJ, Freckleton RP, Godfray HCJ, Beissinger SR, Benton T, Cameron DD, Carmel Y, Coomes DA, Coulson T, Emmerson MC, Hails RS, Hays GC, Hodgson DJ, Hutchings MJ, Johnson D, Jones JPG, Keeling MJ, Kokko H, Kunin WE, Lambin X, Lewis OT, Malhi Y, Mieszkowska N, Milner-Gulland EJ, Norris K, Phillimore AB, Purves DW, Reid JM, Reuman DC, Thompson K, Travis JMJ, Turnbull LA, Wardle DA, Wiegand T (2013) Identification of 100 fundamental ecological questions. J Ecol 101:58–67 25. Pickett ST, Kolasa J, Jones CG (2007) Ecological understanding: the nature of theory and the theory of nature, 2nd edn. Elsevier, Amsterdam 26. Newbold T, Hudson LN, Hill SLL, Contu S, Lysenko I, Senior RA, Bo¨rger L, Bennett DJ, Choimes A, Collen B, Day J, De Palma A, ˜o S, Edgar MJ, Dı´az S, Echeverria-London Feldman A, Garon M, Harrison MLK, Alhusseini T, Ingram DJ, Itescu Y, Kattge J, Kemp V, Kirkpatrick L, Kleyer M, Correia DLP, Martin CD, Meiri S, Novosolov M, Pan Y, Phillips HRP, Purves DW, Robinson A, Simpson J, Tuck SL, Weiher E, White HJ, Ewers RM, Mace GM, Scharlemann JPW, Purvis A (2015) Global effects of land use on local terrestrial biodiversity. Nature 520:45–50 27. Dawson W, Moser D, Mvan K, Kreft H, Pergl J, Pysˇek P, Weigelt P, Winter M, Lenzner B, Blackburn TM, Dyer EE, Cassey P, Scrivens SL, Economo EP, Gue´nard B, Capinha C, Seebens H, Garcı´aDı´az P, Nentwig W, Garcı´a-Berthou E, Casal C, Mandrak NE, Fuller P, Meyer C, Essl F (2017) Global hotspots and correlates of alien species richness across taxonomic groups. Nat Ecol Evol 1:0186 28. Ripple WJ, Estes JA, Beschta RL, Wilmers CC, Ritchie EG, Hebblewhite M, Berger J, Elmhagen B, Letnic M, Nelson MP, Schmitz OJ, Smith DW, Wallach AD, Wirsing AJ (2014) Status and ecological effects of the world’s largest carnivores. Science 343:1241484 29. Goldenberg SU, Nagelkerken I, Ferreira CM, Ullah H, Connell SD (2017) Boosted food web productivity through ocean acidification collapses under warming. Glob Change Biol 23:4177–4184 30. Reed J, Vianen JV, Barlow J, Sunderland T (2017) Have integrated landscape approaches reconciled societal and environmental issues in the tropics? Land Use Policy 63:481–492 31. Xu W, Xiao Y, Zhang J, Yang W, Zhang L, Hull V, Wang Z, Zheng H, Liu J, Polasky S,

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44. Saslis-Lagoudakis CH, Clarke AC (2013) Ethnobiology: the missing link in ecology and evolution. Trends Ecol Evol 28:67–68 45. Albuquerque UP (2013) How to improve the quality of scientific publications in ethnobiology. Ethnobiol Cons 2:1–5

Chapter 8 Multidimensional Analyses for Testing Ecological, Ethnobiological, and Conservation Hypotheses Thiago Gonc¸alves-Souza, Michel V. Garey, Fernando R. da Silva, Ulysses Paulino Albuquerque, and Diogo B. Provete Abstract This chapter outlines the commonest multidimensional analysis used in ecology, ethnobiology, and conservation. After mastering how to create a scientific research workflow based on a problem-based platform (Chap. 7, in this book), readers will learn how to visualize complex datasets (e.g., species or ethnospecies lists, several social-political or environmental variables, and so on), and test multivariate hypotheses. We provide a full reproducible example of every analysis discussed in this chapter as an Online Material. We further encourage students and researchers to move from a “description-based multidimensional analysis” (such as using unconstrained ordination, like PCA) to an explicit hypothesis-testing framework that can greatly improve learning and research programs. Key words Data analysis, Hypothesis testing, Scientific research workflow, Ordination

1

Introduction Multivariate methods can be roughly divided into two types: ordination and clustering. The first kind tries to sum up relationships of one (or more) matrices and find the major axis of variation, while the second tries to find groups in a dataset. Additionally, ordination methods can be further divided into constrained and unconstrained. In this chapter, we will cover the most commonly used ordination methods in ethnobiology, ecology, and conservation (EEC) studies. In addition, we provided a full reproducible example that you can run every analysis mentioned here in your computer (Online Material). We organized this chapter in the following structure: first, we present how we can standardize/transform datasets before applying the analysis, and also briefly the pairwise association measures (i.e., distance or similarity/dissimilarity measures). After that, we present two unconstrained methods used in exploratory data analysis

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_8, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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applied to a single data matrix (e.g., environmental variables) such as principal component analysis (Sect. 2.1), and principal coordinate analysis (Sect. 2.2). Then, we divide analyses into four groups associated with the type of hypotheses: (1) test the effect of several predictors (e.g., environmental features) on one dependent variable (e.g., species richness) (Principal Component Regression in Sect. 3); (2) analyze the effect of categorical independent variable (e.g., biome) on several dependent variables (e.g., species traits) (Permutational Multivariate Analysis of Variance and CommunityWeighted Mean in Sect. 4); (3) test how several predictor variables (e.g., social-political characteristics) affect several response variables (e.g., medicinal plant used by local people) (Redundancy Analysis in Sect. 5); and (4) test associations between each dependent variable (e.g., traits) and one categorical independent variable (e.g., habitat type) using the Indicator Value index (Sect. 6).

2

Exploratory Data Analysis and Visualization

2.1 Association Measures

Before going deep into analytical methods, we must first understand the concept of similarity, which forms the basis for any clustering or ordination method. Association coefficients measure the resemblance between objects (Q mode) or descriptors (R mode). With a few exceptions, EEC studies are interested in knowing the resemblance between objects (e.g., species), and less often between descriptors (e.g., environmental variables). Association measures for Q mode are the (dis)similarity between objects, whereas those for the R mode are one of dependence, such as correlation or covariance coefficients. For the remaining of this Section, we will discuss dissimilarity coefficients used in ordination techniques [1, 2]. Sections 4.2 and 5 will briefly discuss methods to analyze the relationship between traits and environment that use the R mode (e.g., RLQ, [3]), for more details on the Q mode see Legendre & Legendre [4]. Dissimilarity measures can be classified based on how they treat double zeros, type of data (binary or quantitative), and their symmetry. A (dis)similarity varies from 0 (minimum similarity) to 1 (maximum similarity), while a distance measure is the opposite and has no upper bound. Therefore, objects that are shown closer together in the reduced space are more similar to each other, regarding their characteristics (e.g., species that have similar distributional pattern). Distance measures can be calculated as D ¼ 1  S, but can also be normalized to range between 0 and 1 by dividing it by their maximum value. Yet distance coefficients can be metric, semimetric, or non-metric. EEC studies only use metric and semimetric coefficients. The kind of data will guide the choice of a distance measure (see Table 7.4 in Legendre and Legendre [4]).

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Accordingly, observational EEC studies usually collect species incidence or abundance in the field to make correlations with environmental data. The main theory behind those studies is the ecological niche concept [5], which states that individuals of species are distributed in the environment such that their abundance is highest at optimal values of a given environmental variable, lowering in both ends (maximum and minimum) of that variable following a Gaussian distribution. This pattern means that species absent from two sites cannot be taken as evidence of the similarity between those sites, since their environmental characteristics may be outside the species niche (i.e., represent ecological extremes not occupied by individuals of that species). Therefore, ideal similarity coefficients for use in EEC studies should disconsider double zeros. Such coefficients are called asymmetrical, and they can handle binary (incidence) or quantitative data (e.g., abundance). The most commonly used binary asymmetrical coefficients (or indices) are the Jaccard and Sørensen. The basic difference between them is that Sørensen gives a double weight to joint presences, but at the same time it is sensitive to variation in species richness between sites, differently from the Jaccard index. Similarly, coefficients for quantitative data can be symmetrical, such as the Gower coefficient, or asymmetrical, such as the percentage difference (also known as Bray–Curtis coefficient). The Gower coefficient is useful because it can deal with descriptors with different mathematical properties. Because of this, it has been increasingly used in the functional trait literature (see Sect. 4.2), since a trait matrix can contain a mixture of continuous, categorical multistate, binary variables, etc. Conversely, the percentage difference coefficient deals with raw abundance data, raw meaning not requiring previous normalization. This is a useful property because species abundance is usually very skewed in ecological communities, with a few abundant and many rare species. A number of ecologically meaningful dissimilarity coefficients are available in the functions vegdist of vegan [6], dist.ldc of adespatial [7], and dist.ktab of the ade4 [8] package. 2.2 Transformations for Abundance Data

Ordination methods require that distance coefficients have a Euclidean property (i.e., metric), so objects are adequately displayed in the reduced space according to their shared characteristics. However, distance coefficients that deal with species abundance data are not Euclidean. In the case of incidence data, binary indices are also not Euclidean (Table 1). This is problematic because a PCoA (see Sect. 2.4) run with those data can produce eigenvectors with complex or negative eigenvalues, which are not readily interpretable. In those cases, one must transform the raw dataset before computing the distances (Table 1). The recommended transformation in this situation is the Hellinger transformation [9], but a recent study has combined the Box–Cox with the

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Table 1 Schematic representation of the main matrices used in EEC studies, with appropriate transformation (when necessary), dissimilarity, and ordination methods applied to each one

Matrix Y represents the abundance (or presence/absence) of species (columns) at different sampling units, such as sites (rows). Matrix T combines species in rows and traits in columns. Matrix X represents environmental or social-political predictor variables (columns) at different sampling units (rows). Matrix E contains ecosystem properties (columns) of different sampling units (rows). Notice that values in matrices T, X, and E can be of different types, such as numeric, nominal, ordinal, binary, and fuzzy, or any combination of them

chord transformations for species abundance data [10]. In this situation, a PCoA is done in two steps: first raw data undergo Hellinger transformation, and then it’s calculated the distance coefficient of interest (tb-PCoA, [4]). 2.3 Principal Component Analysis (PCA)

The aim of any ordination technique is to position objects (or descriptors) in a reduced space compared to the original dataset. To accomplish that, an ordination method computes eigenvalues and eigenvectors from a variance–covariance matrix of variables (descriptors). Space is limited to explain the concept of eigenanalysis, but a good visual introduction that you can play with is available at http://setosa.io/ev/eigenvectors-and-eigenvalues/. But briefly, an eigenvector is the principal axis of the variance–covariance matrix, while an eigenvalue represents the amount of

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variation captured by an eigenvector (see [4]). This procedure inherently implies a loss of information. The first of these ordination techniques was proposed by Karl Pearson [11] and is called Principal Component Analysis, which is based on the Euclidean distance. It was initially used to analyze human morphometric measurements, and it has been extensively used for a number of purposes ever since. As it uses Euclidean distance, it accepts any continuous descriptor, for example measurements of size and shape, climatic, and edaphic variables. The advantage of PCA is that it produces new variables (principal components) are that orthogonal (i.e., independent to each other). This is useful when one is dealing several variables collected in the field that are possibly correlated to each other, for example. As always, the research question dictates the kind of data that will be collected and, consequently, the kind of association measure and the ordination method that will be used. Below, we discuss an application of PCA for exploratory data analysis of plant morphological traits. Despite being descriptive, notice that there is an a priori expectation for the results. Example 1: l

Theoretical question: Does species traits influence how local people distinguish useful from useless plant or animal species?

l

Example: Morphological traits of plants preferred vs. nonpreferred by local people for medicinal uses.

l

Question: how morphological traits of plants preferred vs. nonpreferred by local people are distributed in the multidimensional space? Which traits are more important for determining this sorting?

l

Hypothesis: Preferred species will be more similar to each other and cluster together in the reduced ordination space, but different from the nonpreferred ones.

l

Variables: Specific leaf area, proportion of bark area, leaf thickness, potential plant height, seed mass.

l

Sampling unit: plant species.

Here, we took the trait dataset recently published by Rodrigues et al. [12] for tree species of Southern Brazil to illustrate this question. This dataset contains traits of leaf, branch, maximum potential height, seed mass, and dispersion syndrome of 117 tree species. For the sake of simplicity and to illustrate how the method works, we will use just a few traits and categorize half of the species as being used by local people and the other half not used. We then run a PCA on this dataset. Since the variables were measured in different scales, we had to standardize them before running the PCA (see Appendix for more details). Contrary to our initial hypothesis, we found that preferred and nonpreferred species

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had similar morphological characteristics and sampling units overlapped in the ordination space (Online Material). Plant height and proportion of bark area were not very useful for the formation of the axes. In the plot, the angle of the arrows informs about the correlation of that variable with a given axis. For example, SLA is closely related to axis 1, meaning that this variable contributed very much to the formation of the axis and to distinguish species arranged along it, but not much to the second axis. Interestingly, plant height is contributing equally to the formation of both axes. This means that data points (species) arranged to the right of the ordination plot (positive side) have a large SLA and are tall. Similarly, those to the left are small trees and have small SLA, but have thick leaves, large seeds, and high proportion of bark area. The correlation of original variables with the principal components is their loadings, which vary from 1 to +1 and are interpreted as Pearson correlation coefficients. Accordingly, the position of individual sampling units (in this case species) along the axis is their score. For more details on interpreting PCA biplot, see Chap. 9 of Legendre and Legendre [4]. As a final note, the sampling unit of this example are species, which points to the need to incorporate the phylogeny in order to account for the dependence among them. We will not cover such phylogenetic comparative methods in this book, but solutions to this specific problem with PCA exists [13, 14]. 2.4 Principal Coordinate Analysis (PCoA)

PCA is a useful method to sum up information in a data table, but an important limitation is that it only uses Euclidean distance. Usually, researchers in EEC are interested in understanding how species abundance changes along environmental gradients or between different discrete areas. Abundance is count data, and as such violates the triangle inequality of metric distances (see [4]). To overcome this limitation of PCA, Gower [15] created a new eigenfunction analysis called Principal Coordinate Analysis (or PCoA), which can deal with any coefficient of association. PCoA is an eigenanalysis that works similarly to PCA. Thus, the terms, interpretation of outputs and biplots are the same. The only difference is that semimetric coefficients (see Sect. 2.1) tend to produce eigenvectors with negative or complex eigenvalues. Therefore, after calculating the distance coefficient, one has to test if the distance matrix is Euclidean before running a PCoA. This can be easily done with functions is.euclid of package ade4, and dist.ldc of package adespatial. Another way to overcome the problem is to use a correction method to get rid of negative eigenvalues. There are two methods that distort the distance matrix, forcing it to be Euclidean: Lingoes and Cailliez [4].

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Example: l

Theoretical question: How does land use affect biodiversity maintenance and spatial distribution of species at different spatial scales?

l

Question: How the relationship between morphological and reproductive plant traits varies along an urbanization gradient?

l

Hypothesis: Generalists (ruderal) species will be more common in urban areas due to their high reproductive output (r strategy).

l

Variables: 31 morphological and reproductive variables for 136 plant species along an urbanization gradient in France. In the example below, we will use just diaspore mass (mg), seed bank longevity, flowering duration, plant height, time of first flowering, mycorrhizas, aerial vegetative propagation, and mechanism of seed dispersal.

l

Sampling unit: Species.

Since trait data were in different formats: three quantitative, four semiquantitative (ordered factor), and one binary (dichotomous), we used the Gower coefficient to calculate the distance between species. Since this distance matrix is not Euclidean (see above), we calculated the square-root of the distance matrix, which turned out to be Euclidean (see Online Material). Thus, no correction method for negative eigenvalues was needed. In the Online Material, we show the PCoA biplot with scaling 1, we can see that species clustered into four distinct groups in the ordination diagram. Accordingly, the presence of mycorrhiza and the mechanism of seed dispersal were important to this sorting. Another common application of PCoA in EEC studies is to analyze species abundance matrices to explore patterns of species distribution in space and time. In this case, instead of a morphological trait matrix as in the example, one would have incidence or abundance data of species (rows) along sites (or time periods; columns). In order to conduct a PCoA onto this kind of matrix, one would have to calculate an appropriate distance coefficient. For example, Jaccard or Sørensen for incidence data or percentage difference for abundance. Notice however the need to take the square-root of the distance matrix before running a PCoA, because none of those coefficients are metric. An interesting point in this kind of study is that species are usually the sampling unit (object) to which one wants to know the distributional pattern. Thus, the same problem with phylogenetic autocorrelation arises as in the PCA example above. Again, methods have been recently proposed to deal with that situation [16], called Double Principal Coordinate Analysis (see function dpcoa in package ade4).

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Testing the Effect of Several Predictors on One Dependent Variable

3.1 Principal Component Regression

Principal Component Regression (PCR) combines multiple regression analyses with Principal Component Analysis (PCA, Online Material). Instead of directly performing a regression analysis using the dependent variable on the independent variables, PCR uses a set of eigenvectors as predictor variables [17]. One of the advantages of PCR is that it decreases the effective number of parameters of the model (Fig. 1a). This is relevant in situations in which there are many predictor variables, and relatively few samples—a common situation in EEC studies. Furthermore, one problem of many statistical analyses, particularly linear models, is dealing with numerous correlated predictor variables, i.e., multicollinearity [18]. When two or more of the explanatory variables are collinear (existence of correlation between covariates), they add redundant

Fig. 1 Schematic representation of four approaches to test multidimensional hypotheses. Different approaches were accompanied by operational questions and a graphical output to illustrate how to generate testable predictions. (a) The first approach is used to investigate the effect of several predictors (that can be raw environmental variables (X) or PCA scores (Xpc)—Page 12) on one dependent variable (e.g., body size, Fig. 2). (b) The second approach investigates group differences with PERMANOVA (Page 14). (c) The third approach tests how environmental gradients changes species or trait compositions (Page 20). (d) Lastly, you can identify indicator taxa or traits with IndVal (Page 24)

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information to the model, skewing the results by inflating standard errors of coefficients [17, 18]. In these cases, a PCR can be useful because we can reduce a large number of correlated variables down to a smaller number of orthogonal components. One limitation of PCR is that the components that explain most of the variance in the predictor variables might not be the most important in explaining the variance in the response variable in a multiple regression model [19]. Other important point is that there is no single best method to determine how many components to keep [1, 17]. For example, the decision can be completely arbitrary (number of axes necessary to represent 75% of the variance of the data), or using one of several approaches to choose how many axes that represent interesting variation of the data (e.g., Broken-stick model) and axes that merely display the remaining, essentially random variance (see Borcard et al. [17] for examples). Example 1: l

Theoretical question: How do environmental gradients affect geographic variation of species traits?

l

Question: How do environmental gradients drive intraspecific body size of Boana faber?

l

Hypothesis: Boana faber have larger body size on colder sites.

l

Dependent variable: body size of different individuals of Boana faber.

l

Independent variable: environmental variables (e.g., temperature and precipitation).

Here, we used data from Boaratti and da Silva [20] who tested how environmental gradients affect the variation in B. faber body size. They measured the body size of B. faber from specimens deposited in scientific collections and downloaded temperature and precipitation variables from the WorldClim database [21]. Boaratti and da Silva [22] performed a PCA and used the first two axes as predictor variables of body size in a PCR model. The authors prepared a matrix containing the localities as rows and average body size of B. faber populations and environmental variables as columns. Then, we generated PCR models with different combinations of predictor variables. Boaratti and da Silva [23] found that in cold and moist localities, individuals of B. faber are larger than in warm and dry localities (F2,23 ¼ 14.76; R2 ¼ 0.36; P < 0.001; Fig. 2). Example 2: l

Theoretical question: How do we reconcile societal needs for natural resources and nature conservation?

l

Question: What is the relationship between the number of fish species known by fishermen and their personal experiences?

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Fig. 2 Relationship between body size (snout–vent length—SVL) of 25 Boana faber populations and the first principal component. In cold and moist localities, individuals of B. faber are larger than in warm and dry localities l

Hypothesis: personal experience of fishermen increases their knowledge about fish species.

l

Dependent variable: number of fish species.

l

Independent variable: personal experience (e.g., time as fisherman, number of fishing techniques used, whether or not his father was a fisherman).

l

Covariate: age.

We tested the prediction that personal experience increases the number of fish species known by native fishermen living in islands. We randomly selected 30 local fishermen, between 16 and 60 years old, to evaluate their knowledge about fish species. For each fisherman interviewed, we obtained the following information: (1) number of fish species known; (2) fisherman’s age; (3) number of fishing techniques used to capture fishes; and (4) if fisherman’s father was also a fisherman. We created a matrix with personal experiences as columns and each fisherman as rows. Then, we performed a PCA onto this matrix. We generated PCR models with different combinations of predictor variables. We found that fishermen whose fathers were also fishermen and are working for a long time with fishery know more fish species than fishermen whose fathers were not fishermen and are working for a short time with fishery (F2,28 ¼ 141, R2 ¼ 0.83, P < 0.001; Online Material).

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Finding Differences in Species (or Trait) Composition Between Groups Permanova

Permutational multivariate analysis of variance (PERMANOVA) is used in EEC studies to test hypotheses concerning differences in the composition and/or relative abundances of different species (i.e., dependent variables) between different groups or treatments (i.e., independent variable). It is a nonparametric method that uses any measure of dissimilarity (therefore we can use numeric, nominal, ordinal, and binary datasets as dependent variables) and compares variability of multivariate datasets within groups versus within groups, using a permutation test with pseudo-F ratios [22, 23]. For example, we can use PERMANOVA to test if species composition is different among three distinct environments: mature forest, secondary forest, and pasture (Figs. 1b and 4). PERMANOVA partitions the sums of squares analogous to a traditional multivariate analysis of variance (MANOVA) and calculated as follows: (1) the within-group sum of squares as the sum of squared distances from individual replicates to their group centroid; and (2) the amonggroup sum of squares as the sum of squared distances from group centroids to the overall centroid. One of the advantages of PERMANOVA is that, it does not assume that the data come from a multivariate normal distribution (which is an unrealistic assumption for most ecological data sets) differently from a MANOVA. Although there is no explicit assumption regarding homogeneity of variance within each group [22], PERMANOVA is sensitive to differences in spread among groups and a separate permutation test for significant differences in homogeneity of multivariate dispersions is recommended [22, 24]. Example 1: l

Theoretical question: How does land use affect biodiversity maintenance and spatial distribution of species at different spatial scales?

l

Question: How does land use affect arthropod species composition in the Brazilian Cerrado?

l

Hypothesis: urbanization grade increases beta diversity of arthropods.

l

Dependent variable: arthropod species composition.

l

Independent variable: urbanization grade (pastures, sugarcane, and Cerrado protected areas).

We evaluated arthropod species composition collected in 5  5 m plots allocated in ten pastures, ten sugarcane fields, and ten Cerrado protected areas. Considering the ecological niche theory [5], our predictions are that (1) protected areas in the Cerrado will harbor distinct arthropod species composition from pasture and sugarcane areas, and (2) there is no difference in terms of

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Fig. 3 nMDS plots illustrating similarities in species composition among arthropods in pasture (green color), sugarcane (pink color), and Cerrado protected areas (blue color)

species composition between pastures and sugarcane. First, we need to create a matrix with arthropod species as columns and areas in rows). Then, we use the function adonis available in the vegan package [6] to perform the analysis. Lastly, we performed a nonmetric multidimensional analysis (NMDS, [4]) to graphically represent arthropod species composition of the three treatments. We found that species composition of arthropods is influenced by land use (F2,27 ¼ 24.37, R2 ¼ 0.64, P ¼ 0.001) with pasture, sugarcane and Cerrado protected areas showing distinct arthropod species composition (Fig. 3). Example 2: l

Theoretical question: What are the environmental drivers changing the structure and functionality of tropical social-ecological systems?

l

Question: How does urbanization affect local knowledge about medicinal plant species?

l

Hypothesis: Urbanization modifies the type (quality) of medicinal plant species recognized by local people.

l

Dependent variable: plant species composition.

l

Independent variable: people living in different areas (rural, periurban, and urban areas).

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We tested the hypothesis that the knowledge about plant species decreases along an urbanization gradient. Considering that rural exodus and the transformation of rural areas into small cities and villages have increased in the last century, and consequently the dependency on local plant resource and the lower access to medicinal resources. Thus, our prediction is that people living in rural areas will know more plant species with medicinal uses than people living in peri-urban and urban areas. Also, they know different plant species. We randomly selected 1000 local people, between 18 and 70 years old, living in rural, peri-urban and urban areas. We asked people if they used local plants as medicine or if they recognized plants with medicinal uses. Based on the answers, we created a matrix with plant species in columns and each person in rows. Then, we use the function adonis available in the vegan package [6] to perform the analysis. Lastly, we performed a nonmetric multidimensional analysis (NMDS) to graphically represent the results. We found that local knowledge about species of plants with medicinal uses is different along the rural-urban gradient (F2,27 ¼ 12.25, R2 ¼ 0.47, P ¼ 0.001). People living in rural areas had different knowledge about species of plants with medicinal use than those living in peri-urban and urban areas, but there is no difference between people living in peri-urban and urban areas (Online Material). 4.2 CommunityWeighted Mean (CWM)

A long-standing question in EEC is the association between environmental features or social-political characteristics and species traits. There are several methods developed for testing it, such as RLQ [3], Fourth-Corner [25] and Community-Weighted Mean of trait values (CWM, [26]). Conceptually, the CWM measures the most probable attribute of a randomly sampled individual. This method integrates trait and abundance distribution and, thus calculates the dominant attribute found in the most common species (i.e., dominant trait composition). CWM is calculated with the following formula: CWMt ¼

n X

pi  traiti ,

i¼1

where pi represents the relative abundance of species i in the site m (i.e., the number of individuals of species i divided by the total number of individuals in site m), traiti is the trait value of species i, and n is the number of species in site m [26]. Therefore, the CWM needs two different matrices: (1) site by species matrix (Y, where rows represent m sites and columns n species: Table 1) and (2) species by trait matrix (T, where rows represent n species and columns t traits: Table 1). Then, the CWMt (for multiple traits) calculates the most common value for each trait t per site m. The CWMt matrix (Fig. 1) can be used as a multivariate dependent variable considering m sites as rows and t traits as columns. The

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Fig. 4 Ordination diagram of principal coordinate analysis (PCoA) of the plant traits selected by local people in different water scarcity regimes

environmental features (matrix X: Table 1), in turn, can be used as predictor variables affecting trait composition (Table 1). Lavorel et al. [27] argued that this method demonstrates little sensitivity to different experimental methods used to estimate abundance and trait value (but see limitations and improvements in Peres-Neto et al. [28] and ter Braak et al. [29]). To test the effect of predictor variables (e.g., land use, climate) on trait composition, it is possible to combine CWM with PERMANOVA (Sect. 4.1, application in Rigal et al. [30]), RDA (Sect. 5.1, see Kleyer et al. [31]) or dbRDA (example in Sole´-Senan et al. [32]). By combining CWM with PERMANOVA you can test whether different groups/treatments have distinct trait composition (Fig. 4). However, if you are interested in investigating how trait expressions change along environmental gradients, you should use RDA or dbRDA combined with CWM (Fig. 1b, d, [31]). In the first approach, you need to calculate the CWM matrix to represent dominant traits per site with the function functcomp (package FD). This function accepts different types of variables, such as numeric, nominal, and binary [33]. Then, we need to use an appropriate distance coefficient (see Sect. 2.1) to measure trait compositional distances. Similarly to Sect. 4.1, we used function

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adonis to run a PERMANOVA and test whether trait composition varies between different treatments/groups. The dependent variable must be a distance matrix and independent variables can be numerical (e.g., age), nominal (urban, peri-urban, or rural), or mixed. Also, you must check the heterogeneity of multivariate dispersions [24] when combining CWM with PERMANOVA. Example 1: l

Theoretical question: What are the environmental drivers of the structure and functionality in tropical social-ecological systems?

l

Question: How does climate variability affect plant traits selected by local people?

l

Hypothesis: water scarcity modifies plant traits preferred by local people.

l

Dependent variable: plant trait diversity and composition.

l

Independent variable: water scarcity (wet and dry years) and temperature.

l

Covariate: yearly unemployment rates, family income, number of people per settlement.

We created an illustrative dataset in which one researcher investigated whether water availability affects plant selection by local people (as a secondary resource) for fuelwood and feeding along 10 years. We selected six rural settlements with varying socialpolitical conditions, and ~300 households within ten families per settlement. We repeated local inventories two times per year. We conducted interviews and in situ inventories (for simplicity, methodological details about them are omitted here) asking the following information: (1) family income, (2) types of fuel used for cooking (natural gas, fuelwood, and mixed), origin of wood and vegetable/fruits (native plant collected in loco vs. commercial wood or vegetables/fruits), plant traits selected for using as fuelwood (e.g., wood density) or food (e.g., fruit type). We used three different matrices: matrix Y (species per sites), matrix X (predictor variables per sites) and matrix T (trait per species) (Table 1). First, we use the function functcomp (FD) to calculate the CWM. After, we calculated the Euclidean distance between sites. Then, we tested which variables affected trait composition combined with betadisper (vegan) to check betweengroups variance. Lastly, we can use PCoA to visualize possible differences in trait composition between groups of interest (Fig. 4). It is important to note that the variance of trait matrix and predictor variables may affect the relevant traits/variables in many analyses. Thus, some authors recommend transforming (e.g., log) or standardizing (e.g., unit variance) values before applying the CWM and PERMANOVA analyses (Online Material). In our example, we found that the most important predictor variable was water scarcity (R2 ¼ 0.503, P < 0.001, Fig. 4), whereas

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temperature (R2 ¼ 0.0004, P ¼ 0.328), unemployment rate (R2 ¼ 0.03, P ¼ 0.001) and family income (R2 ¼ 0.002, P ¼ 0.001) had a negligible effect. The dominant traits correlated with the PC 1 were (1) preference for commercial wood (r ¼ 0.931), (2) preference for commercial fruit/vegetables (r ¼ 0.972) and wood density (r ¼ 0.829). These results indicate that local people prefer dense fuelwood in the dry season, while commercial wood, fruits, and vegetables are the preferred traits in the wet season (Fig. 4).

5

Testing How Environmental Gradients Affect Species (or Trait) Composition

5.1 Constrained Ordination

Redundancy Analysis (RDA) is mainly used in ECC studies for testing hypotheses concerning environmental or social-political factors (i.e., independent variables) that affect species distribution among sites (i.e., dependent variable). Canonical analyses (a synonym for constrained ordination) are called direct gradient analysis because, unlike indirect gradient analysis (e.g., principal component analysis - PCA: Sect. 2.3), the ordination of species matrix is constraint to the predictor variables [4]. They can do so in two different ways: symmetric and asymmetric [4]. Symmetric analysis does not distinguish between independent and dependent variable matrices, generating the same result. Thus, this analysis searches for common patterns between those matrices. Conversely, in asymmetric analysis, results differ when inverting matrices, because its mathematical procedure quantifies the variation of response matrix explained by the predictor matrix. RDA assumes a causal relationship between the dependent variable (we can use numeric or binary datasets) and independent (numeric, nominal, ordinal, binary, or mixed datasets: Table 7.1, Figs. 7.1 and 7.2 in Chap. 7 in this book. First, RDA apply a multiple regression to each variable Y (composition or local knowledge matrix) with all variables X (exploratory variables matrix), resulting in a constrained ˆ . Then, a PCA is made onto the Y ˆ matrix to obtain the matrix Y matrix of eigenvectors U. Finally, a multiple linear correlation is applied between matrix Y and U. The results are linear combinations between Y and X, in which the axes are linear combinations of the environmental variables (gradient), and the species are the response to this gradient [34]. Optionally, a permutation method can be used to test the null hypothesis that the observed F statistics is different from random or not. This F statistics is calculated for each axis and environmental variable, which means that you can test the relative importance of each predictor variable. Thus, you can work with multiple hypothesis concerning each predictor variable (e.g., temperature, family income) or groups of environmental variables (e.g., soil characteristics, Fig. 1c). In addition, you can obtain the variance explained (R2adj) by each variable (Fig. 5) and contrast how environmental and spatial variables affect the

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Fig. 5 Results of redundancy analysis (RDA) comparing environmental variables affecting the spatial distribution of anurans Table 2 Summary of redundancy analysis (RDA), showing eigenvalues, percentage of explained variance, and P values of each axis Canonical axes

Eigenvalues

Proportion explained

P

RDA1

0.178

0.243

0.001

RDA2

0.040

0.055

0.733

RDA3

0.031

0.043

0.787

RDA4

0.013

0.017

0.970

dependent variables by combining RDA with variance partitioning (analysis not presented in this chapter: see, e.g., Dray et al. [35]). As part of the results, we obtain a triplot graph to visualize the data, where site scores are plotted in their centroid in the ordination space and environmental variables are plotted as correlations with site scores. Also, factor loadings, which represent the correlation between variables and canonical axis should ideally be reported (Table 2). There is an essential difference between RDA and CCA: whereas the first is used when the matrices X and Y have linear relationships, the latter is based on chi-square distance, which assumes that Y is related to X in a unimodal way. Therefore, a CCA should be preferred when environmental gradients are long, whereas RDA should be used for short gradients [4].

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Example 1: l

Theoretical question: how does land use affect biodiversity maintenance and spatial distribution of species at different scales?

l

Question: how does urbanization affect anuran species composition?

l

Hypothesis: land use intensification modifies anuran beta diversity.

l

Dependent variable: the abundance of different anuran species.

l

Independent variable: environmental descriptors of habitat associated with urbanization.

To understand how environmental gradients affect the distribution of anurans in anthropogenic landscapes, we sampled anuran species composition in 20 lentic water bodies in urban and periurban areas. In each water body, we measure four environmental descriptors: (1) surface area, (2) percentage of pond canopy cover, (3) amount of floating aquatic vegetation, and (4) urbanization grade within a 200 m radius around the water body. Our prediction is that urbanization grade is the main driver of the variation in species composition. It is important to note there are other confounding variables that should be considered, such as climate [36] and water chemistry [37]. First, we elaborate a matrix with anuran species abundances in columns and water bodies in rows and a matrix with environmental variables in columns and water bodies in rows. Then, we use the function rda in the vegan package [6]. We found that environmental variables influenced anuran species composition among water bodies (RDA global model: F4,15 ¼ 2.09, P ¼ 0.001; Table 3). The degree of urbanization was the most important environmental variable (Table 3, Fig. 5). Example 2: l

Theoretical question: What are the environmental and socialpolitical drivers of the structure and functionality in tropical social-ecological systems?

Table 3 Factor loadings showing the correlations between environmental variables and the axes of the redundancy analysis (RDA) RDA1

RDA2

RDA3

RDA4

P

Urbanization

0.986

0.151

0.062

0.019

0.001

Area

0.079

0.757

0.097

0.641

0.425

Vegetation

0.041

0.406

0.595

0.693

0.462

0.384

0.142

0.773

0.485

0.527

Canopy cover

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l

Question: How does the knowledge about cultivated medicinal plants change in response to social-economic characteristics?

l

Hypothesis: medicinal plants cultivated vary according to socialeconomic characteristics of local people.

l

Dependent variable: plant species known by local people.

l

Independent variable: social-economic characteristics.

l

Covariate: size of forest remnants.

We test the hypothesis that social-economic characteristics of households influence the knowledge about cultivated plant species with medicinal effects affecting the composition of plants cultivated. We randomly sampled 20 households that had medicinal plants in their gardens, and recorded plant species composition. We obtained information on social-economic characteristics by applying local inventories. Questions asked pertained to family structure (i.e., numbers of household members), number of years attending school, family income, and how long have performs rural activities. We know that forest remnant size could be associated with the availability of medicinal plants. Thus, forest remnant area in each property was considered as a covariate. We created a matrix with plant species composition in each garden in columns and household in rows. Based on the answers of the local inventory, we created a matrix with social-economic characteristics in columns and household in rows. Then, we performed an RDA, as described above. We found that social-economic characteristics influenced the medicinal plants cultivated by people that live in rural areas (RDA global model: F5,14 ¼ 1.7313, P ¼ 0.017; Table 4). The variation in literacy among households was the most important variable (Table 4).

Table 4 Summary of the redundancy analysis (RDA) showing eigenvalues and percentage of explained variance by four axes, as well as the correlations (loadings) between social-economic characteristics of household and axes RDA1

RDA2

RDA3

RDA4

Eigenvalue

0.473

0.157

0.095

0.019

Proportion explained

0.199

0.066

0.040

0.008

0.161

0.669

0.595

0.416

Literacy

0.942

0.256

0.096

0.193

Income

0.206

0.365

0.351

0.837

Rural activity

0.207

0.5190

0.803

0.207

Family

Significant values are in bold

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Identifying Indicator Taxa or Trait

6.1 Indicator Value Index

The indicator value index (IndVal) is most commonly used in studies to test associations between species (dependent variable) with habitat type (independent variable). In other words, IndVal can find indicator species [38]. IndVal is based on the degree of species specificity with the site (i.e., exclusivity in terms of presence/absence or species abundance within a habitat type) and its fidelity to that site (i.e., the frequency of occurrence of species in the same habitat type) [39]. IndVal generates a value (in percentage) whose maximum is 100%, when all individuals of species i occur in all available sites within a single site group (Fig. 1d). The significance of IndVal is obtained through a randomization procedure (e.g., Monte Carlo) and confidence intervals are obtained by applying bootstrap methods [39]. Usually, two criteria are used to say that a given species is an indicator of a habitat type: P-value (P > 0.05) and an IndVal higher than 70% (see [40, 41]). Example 1: l

Theoretical question: How to integrate scientific and local people knowledge to mitigate the negative impacts of climate change and land use on biodiversity?

l

Question: Are there indicator species of environmental quality in Ephemeroptera?

l

Hypothesis: Habitat contamination affects species occurrence among streams.

l

Dependent variable: Ephemeroptera species.

l

Independent variable: preserved and anthropized streams.

We evaluated Ephemeroptera species sampled using a dip net in 15 preserved and 15 anthropized streams in the Atlantic Forest. Our prediction is that aquatic pollution will negatively affect the occurrence of more sensitive species while favor other species, which could be used as indicators of environmental quality. We created a matrix with Ephemeroptera species in columns and areas in rows. We then used the function indval in the labdsv package [42]. Among the 13 Ephemeroptera species collected, three were classified as indicators of ecological condition (Table 5). Two species were indicators of preserved areas (B. prosculus and F. carioca), and one anthropized streams (R. trichobasis). Example 2: l

Theoretical question: How do we reconcile societal needs for natural resources with nature conservation?

l

Question: Is there any difference in the medicinal plants used between indigenous and indicator species of environmental quality in Ephemeroptera?

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Table 5 Indicator value (IndVal) for different Ephemeroptera species in anthropized and preserved streams. The Monte Carlo test was performed using 9.999 runs Anthropized

Preserved

P

Americabaetis alphus

0.462

0.438

0.868

Aturbina georgei

0.299

0.552

0.162

Baetodes prosculus

0.000

0.800

0.001

Camelobaetidius juparana

0.000

0.267

0.110

Paracloeodes eurybranchus

0.400

0.187

0.277

Rivudiva trichobasis

0.401

0.0188

0.045

Tupiara ibirapitanga

0.000

0.267

0.100

Caenis cuniana

0.027

0.213

0.262

Campylocia anceps

0.023

0.043

1.000

Tricorythodes hiemalis

0.230

0.236

0.994

Tricorythopsis gibbus

0.101

0.099

1.000

Farrodes carioca

0.003

0.445

0.008

Needhamella ehrhardti

0.281

0.010

0.082

l

Hypothesis: indigenous populations and immigrants use different medicinal plants.

l

Dependent variable: medicinal plant species.

l

Independent variable: populations (indigenous and European immigrants).

We tested the hypothesis that indigenous and immigrant populations use the same medicinal plants species to treat illnesses, due to cultural exchange, especially when dealing with exotic plants. We worked with a Guarani tribe and small farmers living nearby in southwestern Brazil. We randomly selected 100 individuals reported as specialists in medicinal plants in each population, ranging from 30 to 70 years. The information was obtained using the free list technique. We elaborated a matrix with medicinal plant species in columns and areas in rows. We then used the function multipatt available in indicspecies packages [37]. Among the 15 medical plants species, nine are used more specifically by a single population, and six are used by both populations. Four species were used commonly by immigrants: Cynara scolymus (IndVal ¼ 0.83, P ¼ 0.0001), Cinnamomum aromaticum (IndVal ¼ 0.632, P ¼ 0.003), Polianthes tuberosa (IndVal ¼ 0.620, P ¼ 0.038), and Plumeria lancifolia (IndVal ¼ 0.592, P ¼ 0.009). Five species of medical plants were used mainly by indigenous people: Joannesia

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heveoides (IndVal ¼ 0.975, P ¼ 0.0001), Luehea divaricata (IndVal ¼ 0.923, P ¼ 0.0001), Eichhornia crassipes (IndVal ¼ 0.922, P ¼ 0.0001), Carapa guianensis (IndVal ¼ 0.751, P ¼ 0.0007), and Impatiens balsamina (IndVal ¼ 0.632, P ¼ 0.003). Most species are used by specific populations, indicating that illnesses treatment in many cases is done with distinct medicinal plants species, evidencing a small cultural exchange in relation to medicinal plants.

7

Concluding Remarks While it is important to learn about the methods developed by previous generations of scientists, do not let yourself be silenced by their aura. If you think you have a good idea, work on it, develop it, listen to criticisms, and publish it, thus contributing to the advancement of the field. Do not let people tell you that everything is known, or that you are too young or not good enough to contribute to this field—or any other field of science [P. Legendre and L. Legendre 2012]

Pierre and Louis Legendre wrote in the preface of their pivotal book on multidimensional analyses [4] how important it is for students to advance the field with new (fresh!) ideas. Importantly, this sentence is also motivational because working with complex data require solutions that are not so obvious. Thus, we urge that readers, specially students, face the fact that biological hypotheses in EEC are complex and, consequently, testing them with multidimensional methods can be the best choice for advancing the field. However, you should be aware that using some methods, such as unconstrained ordination (PCA) and hierarchical clustering to discuss a posteriori hypothesis do not represent an appropriate way to go. Actually, we are an advocate for the integration of the hypothetico-deductive method with multidimensional statistics to test multiple predictions in order to promote the theoretical advance of ethnobiology, ecology, and conservation. To achieve this literacy on statistical thinking and multidimensional analysis we encourage reading Legendre and Legendre [4], Mayo [43], Taper and Lele [44], and Salsburg [45], that will open up a brave new world for your scientific research. References 1. Borcard D, Gillet F, Legendre P (2018) Numerical ecology with R, 2nd edn. Springer, New York 2. Gower JC, Legendre P (1986) Metric and euclidean properties of dissimilarity coefficients. J Classif 3:5–48 3. Dole´dec S, Chessel D, ter Braak CJF, Champely S (1996) Matching species traits to

environmental variables: a new three-table ordination method. Environ Ecol Stat 3:143–166 4. Legendre P, Legendre L (2012) Numerical ecology, 3rd English edn. Elsevier, Amsterdam 5. Chase JM, Leibold MA (2003) Ecological niches: linking classical and contemporary approaches. University of Chicago Press, Chicago

Multidimensional Analyses for Testing Ecological, Ethnobiological, and. . . 6. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MH, Szoecs E, Wagner E (2018) Vegan: community ecology package. R package version 2.5-1. https://CRAN.R-project.org/package¼vegan 7. Dray S, Blanchet G, Borcard D, Clappe S, Guenard G, Jombart T, Larocque G, Legendre P, Madi N, Wagner HH (2017) Adespatial: multivariate multiscale spatial analysis. R package version 0.0-9. https://CRAN.Rproject.org/package¼adespatial 8. Dray S, Dufour AB (2007) The ade4 package: implementing the duality diagram for ecologists. J Stat Softw 22:1–20 9. Legendre P, Gallagher ED (2001) Ecologically meaningful transformations for ordination of species data. Oecologia 129:271–280 10. Legendre P, Borcard D (2018) Box-Cox-chord transformations for community composition data prior to beta diversity analysis. Ecography 41:1–5 11. Pearson K (1901) On lines and planes of closest fit to systems of points in space. Philos Mag 2:559–572 12. Rodrigues A, Bones F, Schneiders A, Oliveira L, Vibrans A, Gasper A (2018) Plant trait dataset for tree-like growth forms species of the subtropical Atlantic Rain Forest in Brazil. Data 3:16 13. Revell LJ (2012) Phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol 3:217–223 14. Jombart T, Dray S (2010) Adephylo: exploratory analyses for the phylogenetic comparative method. Bioinformatics 26:1907–1909 15. Gower JC (1966) Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53:325–338 16. Pavoine S, Dufour AB, Chessel D (2004) From dissimilarities among species to dissimilarities among communities: a double principal coordinate analysis. J Theor Biol 228:523–537 17. Quinn GP, Keough MJ (2002) Experimental design and data analysis for biologists. Cambridge University Press, Cambridge 18. Zuur AF, Ieno EN, Elphick CS (2010) A protocol for data exploration to avoid common statistical problems: data exploration. Methods Ecol Evol 1:3–14 19. Hadi AS, Ling RF (1998) Some cautionary notes on the use of principal components regression. Am Stat 52:15–19 20. Boaratti AZ, Silva FR (2015) Relationships between environmental gradients and geographic variation in the intraspecific body size

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of three species of frogs (Anura). Austral Ecol 40:869–9765 21. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978 22. Anderson MJ (2001) A new method for non-parametric multivariate analysis of variance. Austral Ecol 26:32–46 23. McArdle BH, Anderson MJ (2001) Fitting multivariate models to community data: a comment on distance-based redundancy analysis. Ecology 82:290–297 24. Anderson MJ, Ellingsen KE, McArdle BH (2006) Multivariate dispersion as a measure of beta diversity. Ecol Lett 9:683–693 25. Legendre P, Galzin R, Harmelin-Vivien ML (1997) Relating behavior to habitat: solutions to the fourth-corner problem. Ecology 78:547–562 26. Garnier E, Cortez J, Bille`s G, Navas ML, Roumet C, Debussche M, Laurent G, Blanchard A, Aubry D, Bellmann A, Neill C, Toussaint JP (2004) Plant functional markers capture ecosystem properties during secondary succession. Ecology 85:2630–2637 27. Lavorel S, Grigulis K, McIntyre S, Williams NSG, Garden D, Dorrough J, Berman S, Que´tier F, The´bault A, Bonis A (2007) Assessing functional diversity in the field – methodology matters! Funct Ecol 22:134–147 28. Peres-Neto PR, Dray S, ter Braak CJF (2017) Linking trait variation to the environment: critical issues with community-weighted mean correlation resolved by the fourth-corner approach. Ecography 40:806–816 29. ter Braak CJF, Peres-Neto P, Dray S (2017) A critical issue in model-based inference for studying trait-based community assembly and a solution. PeerJ 5:e2885 30. Rigal F, Cardoso P, Lobo JM, Triantis KA, Whittaker RJ, Amorim IR, Borges PAV (2018) Functional traits of indigenous and exotic ground-dwelling arthropods show contrasting responses to land-use change in an oceanic island, Terceira, Azores. Divers Distrib 24:36–47 31. Kleyer M, Dray S, Bello F, Lepsˇ J, Pakeman RJ, Strauss B, Thuiller W, Lavorel S (2012) Assessing species and community functional responses to environmental gradients: which multivariate methods? J Veg Sci 23:805–821 32. Sole´-Senan XO, Jua´rez-Escario A, Conesa JA, Recasens J (2018) Plant species, functional assemblages and partitioning of diversity in a Mediterranean agricultural mosaic landscape. Agric Ecosyst Environ 256:163–172

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33. Laliberte´ E, Legendre P, Shipley B (2014) FD: measuring functional diversity from multiple traits, and other tools for functional ecology. R package version 1, pp 0–12 34. ter Braak CJF (1987) Ordination. In: RHG J, CJF T, OFR V (eds) Data analysis in community and landscape ecology. Cambridge University Press, Cambridge, pp 91–173 Pudoc, Wageningen, The Netherlands. Reissued in 1995 35. Dray S, Pe´lissier R, Couteron P, Fortin M, Legendre P, Peres-Neto PR, Bellier E, Bivand R, Blanchet FG, De Ca´ceres M, Dufour A, Heegaard E, Jombart T, Munoz F, Oksanen J, Thioulouse J, Wagner HH (2012) Community ecology in the age of multivariate multiscale spatial analysis. Ecol Monogr 82:257–275 36. Vasconcelos T, Santos T, Haddad C, RossaFeres DC (2010) Climatic variables and altitude as predictors of anuran species richness and number of reproductive modes in Brazil. J Trop Ecol 26:423–432 37. Hecnar SJ, M’Closke RT (1996) Regional dynamics and the status of amphibians. Ecology 77:2091–2097 38. de Ca´ceres MD, Legendre P (2009) Associations between species and groups of sites: indices and statistical inference. Ecology 90:3566–3574

39. Dufreˆne M, Legendre P (1997) Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol Monogr 67:345–366 40. McGeoch MA, Van Rensburg BJ, Botes A (2002) The verification and application of bioindicators: a case study of dung beetles in savanna ecosystem. J Appl Ecol 39:661–672 41. Tejeda-Cruz C, Mehltreter K, Sosa VJ (2008) Indicadores ecolo´gicos multi-taxono´micos. In: Manson RH, Herna´ndez-Ortiz V, Gallina S, Mehltreter K (eds) Agroecosistemas cafetaleros de Veracruz: Biodiversidad, Manejo y Conservacio´n. INECOL – INE-SEMARNAT, Me´xico, pp 271–278 42. Roberts DW (2016) labdsv: ordination and multivariate analysis for ecology. R package version 1.8-0. https://CRAN.R-project.org/ package¼labdsv 43. Mayo DG (2018) Statistical inference as severe testing: how to get beyond the statistics wars. Cambridge Univ. Press, Cambridge 44. Taper ML, Lele S (2004) The nature of scientific evidence: statistical, philosophical, and empirical considerations. University of Chicago Press, Chicago 45. Salsburg D (2002) The lady tasting tea: how statistics revolutionized science in the twentieth century. Holt, New York, NY

Chapter 9 The Use of Multivariate Tools in Studies of Traditional Ecological Knowledge and Management Systems Cristina Baldauf and Nivea Dias dos Santos Abstract The use of multivariate analyses in diverse ethnosciences has greatly increased in recent decades, allowing for quantitative studies of different questions related to traditional knowledge and its applications. The potential use of those analytical tools, however, has still been modest in terms of the field of ethnoecology. Within that context, the present chapter begins with a panoramic view of the use of multivariate analyses in ethnobiology and ethnoecology and the principal themes and questions that have been recently addressed in scientific publications. We discuss here the principal types of data, matrices, and techniques of multivariate analysis, as well as data transformation, the construction of multivariate matrices, and the choice of appropriate analytical techniques for each type of data set. Finally, we provide examples of the application of those multivariate methodologies in ethnoecology. Key words Ordination analysis, Multivariate analysis, Indirect analyses of gradients, Canonic analyses, Quantitative ethnoecology

1

Initial Contextualization Traditional knowledge comprises detailed information concerning local biodiversity as well as information about the ecological, hydrological, pedological, climatic, and astronomical phenomena in a given region. That knowledge is organized in at least three dimensions: a belief system (kosmos), information (corpus), and a set of management or productive practices (praxis)—known as the KC-P complex [1]. In light of those characteristics, some authors have suggested an analogy between traditional knowledge and multivariate statistics [2, 3], as both are characterized by simultaneously considering numerous variables. Multivariate analyses are useful in many areas of science, and their use in ethnobiology and ethnoecology has greatly increased in recent decades. One of the pioneering uses of multivariate techniques to analyze ethnobiological data was published by Kaplan and

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_9, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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Levine [4], entitled “Cognitive mapping of a folk taxonomy of Mexican pottery: a multivariate approach.” That paper sought to analyze the different forms of classification and subjacent cognitive structures involved in the (traditional) folk classification of the ceramic cooking utensils in Valley of Puebla, Mexico. The authors argue for the use of multivariate analyses throughout that article as a powerful tool to aid in the identification of cognitive structures together with ethnotaxonomic data. Numerous studies since that time have employed multivariate analyses to characterize systems of traditional biological classification, often comparing those systems to formal scientific classifications [5–7]. The use of multivariate analyses in ethnobiology is not, however, limited to classification systems. Numerous expressions of traditional knowledge and its applications have been studied using multivariate statistics. Ho¨ft et al. [8] presented a very clear synthesis of the use of multivariate analyses in ethnobotany, and we recommend it for reading. Themes such as the traditional use of medicinal [9, 10], edible [11], and woody plants [12], or the identification of species for priority in terms of their conservation [13], and the identification of new species through “genomic ethnobotany” [3, 6], are just a few examples of the application of those mathematical techniques in ethnobotany. Those tools have been less used in ethnozoology (but consult [14, 15] until now, although they retain the same potential reported for ethnobotany.

2

The Use of Multivariate Analyses in Ethnoecology Multivariate analyses have been employed in ethnoecology to characterize ecological knowledge and the use and management of natural resources by traditional or local populations. One of the themes examined through that perspective concerns comparative studies of traditional ecological and scientific knowledge. The questions addressed by those studies have generally been related to the existence, or not, of similarities within and between each of those knowledge systems. Miller [16], for example, compared the folk knowledge of fishermen with that of scientists specialized in fishing technologies in terms of the relationship between fish abundance and fishing stock structures in Hawaii using multivariate tools, and discovered significant overlaps in the knowledge bases of both groups. Another topic that has been examined in the field of ethnoecology in recent years considers the multiple factors that mold folk knowledge and natural resource use. Multivariate analyses have been employed in those cases to understand how social, ecological, and economic factors influence human perceptions of timber and non-timber resources and their harvesting. Many of those studies, however, have been published in journals more directly related to

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ethnobotany (economic botany, ethnobotany research and applications), as they focus on plant resources. Even so, their themes can be considered to fall within the realm of ethnoecology, as they represent scientific studies of traditional ecological knowledge [17]. Some ethnoecological studies examine the management of a specific resource and, in these cases, the use of multivariate analyses could help reveal the diversities of management systems used by traditional populations in their exploitation of that species—which could represent the first stages of its domestication process [18, 19]. Traditional management and domestication have been studied from ethnobiological/ethnoecological points of view with the support of multivariate analyses [20–22] as researchers seek to investigate in what manner traditional management (human selection of phenotypes) has caused morphological and genetic differences between managed and unmanaged populations. Finally, from the point of view of landscape management, the use of multivariate techniques allows one to address historic ecological questions concerning the domestication of landscapes and anthropogenic influences on them. A case study by Zurita-Benavides [23] recorded differences in diversity, equitability, and plant species richness between managed and unmanaged forests—indicating the roles of human populations in modifying natural areas within the Amazon region. We will examine in this chapter how multivariate analyses and can aid our understanding of traditional ecological knowledge and folk management practices with animal and plant species and landscapes. We will discuss the principal types of analyses applicable to ethnoecological questions and how data gathered from interviews or bibliographic material can be transformed into multivariate data.

3

Constructing a Matrix of Ethnoecological Data Studies concerning ecological knowledge and traditional management systems generally work with complex data tables and incorporate different variables to be correlated for given sets of samples. In multivariate analyses, those tables are organized into matrices that contain information concerning variables/descriptors (columns) that qualitatively or quantitatively describe the samples (lines)—which are the units we wish to compare. In elaborating a multivariate matrix, it is important to define what samples and what types of descriptors will be used. To that end, it is critical to specifically formulate the question to be asked, as that will define the organization of the data matrix. For example, in a situation in which we are gathering information from farmers concerning native plant species in the Caatinga domain and are interested in knowing if certain groups of farmers preferentially use certain plants, those farmers represent the “samples” and the plant species

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are the “variables/descriptors.” As such, if our question is related to whether there are certain groups of plants with distinct uses (e.g., as food resources, for decoration, or in rituals) by a subset of a given rural population, those plants should be considered samples and the interviewees as descriptors—as we are interested in how the plants are classified according to their uses. It is worth noting that there are two principal modes of analyzing a multivariate matrix: mode Q—when we wish to understand the relationships between the samples; and mode R—when we are interested in the relationships between the descriptors. This chapter will address analyses related to the Q mode (comparisons between samples). Numerous types of matrices have been used in ethnoecological studies: matrices focusing on the knowledge and use of different species among different social or ethnic groups; matrices with floristic data from different areas with different degrees of human intervention; matrices containing morphometric or genetic data of ethnospecies or ethnovarieties; or matrices of the socioeconomic data of interviewees. That diversity of data and matrix types allows the use of different multivariate tools. Additionally, those matrices can be analyzed individually or be related to two or more matrices from the same study. We will return to that point later. As mentioned above, it is essential to precisely define the question(s) to be asked before initiating data collection and its organization, because it is often possible to gather specific information concerning a given group of samples (e.g., socioeconomic and ethnoecological matrices) and evaluate the relationships between those variables (refer to the direct analysis of gradients in topic 4). 3.1 Types of Descriptors

The descriptors of a multivariate matrix can be classified as binary or multistate (Fig. 1). Binary data has only two possible states (e.g., present
absent, yes
no, live
dead), as, for example, when we note that a given interviewee knows a given species, normally hunts a given animal species, or uses a given management practice.

Fig. 1 Types of descriptors used in a multivariate matrix

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Multistate data can be “nonordered” (i.e., qualitative) or “ordered” (semiquantitative or quantitative). In some situations, we might wish to compare knowledge between individuals belonging to different social or ethnic groups concerning a certain resource or set of resources. In those cases, the social or ethnic group constitutes a multistate nonordered (qualitative) datum. Qualitative data represent nominal descriptors that do not have a numerical order among the categories. As such, for that qualitative data to be used in a multivariate analysis, it must be transformed into binary data (0–1)—a subject that we will address in the following section. There is also a third type of data that is quite frequently encountered in ethnoecological studies—multistate ordered (semiquantitative) data. In those cases, there are also categories, but they demonstrate an ordering. For example, plant populations subjected to management can be classified (in a simple way) as wild, semi-domesticated, or domesticated. Those categories demonstrate an order, as they represent a gradient of greater or lesser degrees of domestication. Quantitative data can be continuous—measurable variables within a continuous scale (e.g., units of time, size, or height), or discrete—measurable variables that assume only entire values, generally obtained from counting (e.g., the abundance or use-frequency of a resource), with the latter data type being more common in studies of traditional ecological knowledge. There are situations where the researcher needs to transform the data before the analysis. Data transformation are usually undertaken for a variety of reasons, such as: [24]. 1. Make comparable descriptors that have been measured in different units (e.g., distance in km, wide in cm, weight in kg); 2. Normalize the variables data and stabilize their variances; 3. Code non-ordinated multistate (qualitative) variables into binary variables. We provide below an example of how to proceed with this transformation. For more information on data transformation consult [24–26]. 3.2 How Can Qualitative Data Be Transformed?

Non-ordinated multistate (qualitative) data must be transformed/ codified into binary data before it can be used in multivariate analyses. In these cases, each category of a variable must be transformed into a descriptor. For example, assume that we are working with populations of different ethnic groups (A, B, and C). In that case, the descriptor cannot be “ethnic group”, but rather each group must be transformed into a descriptor (Table 1). We must therefore always be aware of the quantity of qualitative data included in a multivariate analysis, as its incorporation generally results in large numbers of descriptors and (it is important to

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Table 1 Example of a homogenized matrix containing a binary variable (sex),a a nonordered multistate variable (ethnic group), and quantitative continuous data (frequency of firewood collecting) transformed into binary data Frequency of firewood collecting (up to two times/ Individual Sex Group A Group B Group C month)

Frequency of firewood collecting (between three and four times/ month)

Frequency of firewood collecting (more than four times/month)

1

0

0

1

0

0

1

0

2

0

1

0

0

1

0

0

3

1

0

0

1

0

0

1

a

In the case of binary variables, we recommend that the authors use only one of the possible states in the analysis matrix

note) in some types of analyses (e.g., principal component analysis) the numbers of descriptors cannot exceed the numbers of samples. The term heterogeneous matrix is used to describe a matrix that contains different distinct types of descriptors (binary, semiquantitative, quantitative). The use of that type of matrix is not recommended for many multivariate analyses, however. If you do come to work with a high number of binary descriptors, one option to uniformize your matrix is to convert the quantitative descriptors into binary forms (Table 1). Two problems associated with that transformation, however, are the loss of distinctions between the samples (which then assume the same category), and the loss of amplitudes of difference between the samples. If the transformation of a heterogeneous matrix into a homogeneous matrix results in a large loss of information, one option might be to employ a similarity coefficient for the mixed data (Gower coefficient). The general coefficient of similarity proposed by Gower [27] allows the combination of different types of descriptors into the same matrix, processing each descriptor according to its own mathematical characteristic. More detailed information concerning that coefficient can be found in [25]. After calculating the Gower coefficient, it is possible to use the resulting triangular matrix (matrix of similarities between the samples) in grouping analyses and in some types of ordination, as will be demonstrated in the following section. We recommend that the authors always advise the readers about the types of data used as descriptors, as well as the criteria used in its collection, as demonstrated in the following example (Table 2). Now that we have considered the theme of the matrix, we will now examine what are the principal types of multivariate analysis, what exactly they are and do, and how they are classified.

Age Profession

Socioeconomic

Discrete quantitative Multistate non-ordinated Discrete quantitative Continuous quantitative

Type

Discrete quantitative Discrete quantitative Multistate ordinated Multistate ordinated

Quality of the resource

Collection intensity Resource management

Landscape management

Ethnoecological Distance to the collection Continuous area quantitative Quantity of the resource Discrete quantitative

Schooling Income

Variable

Context

Criteria and values

Distance (in km) to where the species is collected Number of individuals of the target species in the collection area Percentage of individuals affected by pests or disease Number of collections per week Type of management practice used with 1 ¼ tolerated; 2 ¼ protected; populations of the target species 3 ¼ promoted; 4 ¼ cultivated Degree of landscape management 1 ¼ promoted; 2 ¼ managed; 3 ¼ cultivated

Number of years of study Monthly wage (US$)

Age of interviewee (years) Principal professional activity

Description

Table 2 Suggestions of descriptions of the data matrices used in multivariate analyses Multivariate Tools in Studies of Traditional Ecological Knowledge. . . 117

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Multivariate Analyses: Types and Principal Methods Multivariate analyses can be classified into two large groups: dependence techniques and interdependence techniques [28]. Dependence techniques assume, a priori, that one or more of the variables are dependent on the behaviors of other variables, that is, there are predictor variables that act upon response variables. Examples of techniques of dependence are multiple regression, canonic correlation analysis, linear models of probability, and structural equation modeling. Interdependence techniques are used to explore the interrelationships of multiple variables to evaluate possible associations or correlations between them. Within that group are classification/grouping analysis and ordination analysis, and they will be examined primarily in the present chapter. Techniques of interdependence are widely utilized in exploratory analyses and aid investigations focusing on the structure of the data and the identification of patterns as well as grouping among samples. Classification analyses group samples according to the descriptors utilized. To perform grouping, the multivariate data matrix must initially be submitted to an analysis of similarity or dissimilarity that will generate indices of similarity or difference between the samples based on the descriptors utilized. Ordination analyses arrange samples along gradients based on two or more descriptors. In such an ordination, each descriptor of the data matrix represents a dimension. The central objective of an ordination analysis is, therefore, to reduce a large number of variables to just a few dimensions (with a minimum loss of information), therefore permitting the detection of the principal patterns of similarity, association, and/or correlation between those variables [29]. The samples are ordinated within a bidimensional or three-dimensional space according to the similarities between them. Ordination does not, however, force the formation of groups (as do classification analyses). In an ordination diagram, the groups can be defined using two principal criteria: cohesion (the degree of proximity of the samples within a given group) and isolation (the distance between two or more groups). One advantage of ordination analyses over classification analyses is that when examining a biplot of an ordination is possible to evaluate which descriptors are responsible for the groups that were formed. Biplots express the scores of the samples and descriptors (Figs. 2, 3, and 4). We will therefore focus on the use of ordination analyses in ethnoecology in the present chapter. Ordination analyses can be divided into indirect analyses of gradients, when there is only a single data matrix, and direct analyses of gradients (or canonic analyses), when there are two or more data matrices to be correlated. Among the principal indirect analyses of gradients used in ethnobiology/ethnoecology

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Fig. 2 Biplot diagram of a principal component analysis (PCA). In PCA the descriptors are quantitative and visualized as vectors and the samples as circles

studies are: principal component analysis (PCA) and correspondence analysis (CA), which are based on auto-analyses and the utilization of rectangular matrices (samples x descriptors), and non-metric multidimensional scaling (NMDS) and principal coordinate analyses (PCoA or PCO), which are performed using distance matrices between samples (triangular matrices). Few publications, however, have so far used direct analyses of gradients such as canonic correspondence analysis (CCA). Examples will be given in the next section of the use of some of those analytic techniques, and we will discuss still other possibilities of comparing matrices, such as the Mantel Test. Box 1 Pay Attention!: The most important thing to consider when choosing an adequate analysis for your research is the type of matrix being used (heterogeneous x homogeneous) and the behavior of the data in that matrix (linear or unimodal). In order to determine if the data demonstrates linear or unimodal responses, one must know the size of the gradient that the data set describes, which is related to the heterogeneity of that data set (i.e., how distinct your samples are from each other). As such, the first step to be

(continued)

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Fig. 3 Biplot diagram of a correspondence analysis (CA). In this CA the descriptors were transformed into binary data for homogenization of the matrix. Descriptors are showed as asterisks and samples as circles. The colors of circles denote the sex female (red) or male (blue)

Box 1 (continued) taken (which must be done before any ordination analysis) includes the quantification of the gradient expressed along the first ordination axis of a Detrented Correspondence Analysis (DCA). DCA is an ordination technique derived from CA that was created to reduce the “arc effect” generated by extensive data gradients [30]. In a simplified view, we can consider this analysis to detrend, along the first ordination axis, the gradient that a CA would exhibit along axes 1 and 2. As such, the first axis of a DCA is scaled in standard deviation units (SD) and displays, at its extremities, the most widely separated samples. The length of the axis indicates whether the data of the matrix demonstrates a linear/monotonic response (SD < 1.5) or unimodal (SD > 3) behavior. Matrices that describe gradients between 1.5 and 3.0 (SD) are generally used in analyses processing either linear or unimodal data. More detailed information concerning DCA can be obtained in [26, 31].

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Fig. 4 Triplot diagram of a canonic correspondence analysis (CCA), with information about the samples and descriptors of the primary matrix (ethnoecological), visualized as asterisks, and secondary matrix (socioeconomic), visualized as vectors

The box below (Fig. 5), adapted from Palmer [32], describes which multivariate analyses are adequate for what types of data. Legendre and Legendre [25] and McCune et al. [26] also provide valuable information concerning that subject.

5

Ethnoecological Applications We present here examples of studies that employed indirect multivariate analyses (a single data matrix) and direct analyses of gradients (two or more matrices).

5.1 Principal Component Analysis (PCA)

Blanckaert et al. [21] combined ethnobotanical, genetic, phytochemical, and morphological data to test for possible differences between managed and non-managed populations of an edible Mexican species (Chenopodium ambrosioides) using different multivariate techniques. Those authors used PCA to compare the morphological data of the two types of populations; the samples consisted of individuals of C. ambrosioides, while the descriptors were morphometric characters (17 continuous and three non-ordinated multistate). Those descriptors were measured in different treatments based on two factors: (A) the plant variety, and (B) management technique, as identified by the ethnobotanical data. Five individuals of each of the two treatments were measured: (1) the red variety + wild type, (2) red variety + incipient

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Fig. 5 Choosing the appropriate analysis for your data type. Adapted from Palmer (2009)

management, (3) white variety + wild type, (4) white variety + incipient management, and (5) white variety + intense management. As such, the morphometric matrix contained data of 25 samples and 20 descriptors (see Table 1 of the article). The data obtained from the ordination diagram revealed the existence of morphological varieties associated with the gradient of management intensity. Those results, combined with genetic and phytochemical data, suggest that the focal species is demonstrating the effects of incipient domestication. 5.2 Partial Canonic Correspondence Analysis (pcca)

Rangel-Landa et al. [22] investigated how the types and intensities of management of edible, medicinal, and ceremonial species used in Ixcatla´n (Oaxaca, Mexico) are influenced by sociocultural and ecological factors. To that end, those authors used a method of direct analysis of gradients—partial canonic correspondence analysis (PCCA). PCCA is a special type of CCA that is used to correlate two matrices while controlling the effects of a third matrix on the first two (see [25] for more information). Those analyses therefore considered three matrices: a matrix of sociocultural data; a matrix of ecological data; and a management matrix (response matrix). It is important to note that whenever canonic analysis is employed, it compares two or more matrices related to the same set of samples.

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In the case of that study, the three matrices contain distinct descriptors for the same samples (plant species). For more details concerning the matrices, consult Table 2 of that article. A CCA was performed for each type of use in order to identify which fraction of the relative variations of management is explained by the sociocultural and ecological predictors, and what are the effects of the interactions of those two factors. As such, partial analyses were performed on the different combinations of those three matrices: (1) CCA with the ecological matrix; (2) CCA with the management matrix explained by the sociocultural matrix; (3) CCA with the management matrix explained by the ecological matrix; and (4) CCA with the management matrix explained by the combined effects of the sociocultural and ecological matrices. The results of those analyses revealed that the sociocultural variables influenced the type and intensity of management more heavily than the ecological variables for the interactions between ecological and sociocultural variables. That pattern was identified in all three use categories. We stressed the word “how” in the example above, as the type of question posed is directly linked to the type of multivariate analysis to be chosen. CCA provides information about how the descriptors in the second matrix are correlated with the data of the first matrix, so that it is possible to know if those descriptors are responsible for the formation of the groups. That result constitutes one of the principal advantages of canonic ordination analyses. Those analyses allow us to understand, in an exploratory way, how the variables relate to each other (collinear variables) and with the sample set (how they explain the formation of groups)— thus allowing one to better understand the internal functioning of the system. If the researcher is only interested, however, in knowing if a data matrix is correlated (or not) with a second matrix, the Mantel test can be used. That test correlates (for the same sample set) two similarity or distance matrices, in a partial Mantel test format in which the effects of a third matrix can be controlled [26]. 5.3

The Mantel Test

Alves et al. [33] analyzed the resource harvesting strategies used by itinerant apiculturists in the semiarid region of Brazil. Those apiculturists are generally organized into family groups and move their beehives from one place to another during the dry season to areas with more abundant flowering. One of the hypotheses raised by the authors refers to the influence of social factors on the strategies used for obtaining resources. They sought to determine whether the apiculturists tended to collect resources in certain areas according to the social group to which they belonged. To that end, two similarity matrices were constructed using the Jaccard index. The first matrix evaluated the similarities of the participants in regard to their social relationships. In that case, the authors were interested in knowing if there was any correlation between the social

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relationships of the apiculturists and the foraging areas they used. The two matrices were correlated using the Mantel test, with a resulting high and significant value (r ¼ 0.861; p < 0.001), indicating that the choices of the foraging areas were strongly associated with the social relationships between the apiculturists.

6

Final Considerations This chapter presents a view of the universe of multivariate analyses available, and their potential for analyzing ethnoecological data. We strongly recommend that readers who might wish to use them acquire more information about these types of analyses. To learn more about the possibilities introduced here, as well as other multivariate methodologies, there is considerable literature available that was used in preparing this chapter, and which we recommend for study [24–26, 28, 34]. In addition to those books, the site prepared by Palmer [35] supplies tips and important information about the different methodologies presented here. It should be stressed that the appropriate use of multivariate analysis in ethnoecology will depend on well-formulated questions, adequate methods of data collection and, obviously, correct interpretations of the results—so that the human dimension is not lost within the matrices.

References 1. Toledo VM (2002) Ethnoecology: a conceptual framework for the study of indigenous knowledge of nature. In: Stepp JR (ed) Ethnobiology and biocultural diversity. International Society of Ethnobiology, Gainesville, FL, pp 511–522 2. Moller H, Berkes F, Lyver POB, Kislalioglu M (2004) Combining science and traditional ecological knowledge: monitoring populations for co-management. Ecol Soc 9(3):2 3. Newmaster SG, Ragupathy S (2009) Ethnobotany genomics-use of DNA barcoding to explore cryptic diversity in economically important plants. Indian J Sci Technol 2 (5):1–8 4. Kaplan FS, Levine DM (1981) Cognitive mapping of a folk taxonomy of Mexican pottery: a multivariate approach. Am Anthropol 83(4):868–884 5. Peroni N, Martins PS, Ando A (1999) Diversidade inter e intra-especı´fica e uso de ana´lise multivariada para morfologia da mandioca (Manihot esculenta Crantz). Sci Agric 56 (3):587–595 6. Ragupathy S, Newmaster SG, Murugesan M, Balasubramaniam V (2009) DNA barcoding

discriminates a new cryptic grass species revealed in an ethnobotany study by the hill tribes of the Western Ghats in southern India. Mol Ecol Resour 9(s1):164–171 7. Maloles JR, Berg K, Ragupathy S, Nirmala BC, Althaf KA, Palanisamy VC, Newmaster SG (2011) The fine scale ethnotaxa classification of millets in southern India. J Ethnobiol 31 (2):262–287 8. Ho¨ft M, Barik S, Lykke A (1999) Quantitative ethnobotany—applications of multivariate and statistical analyses in ethnobotany. People and plants working paper 6:1–49 9. Leduc C, Coonishish J, Haddad P, Cuerrier A (2006) Plants used by the Cree Nation of Eeyou Istchee (Quebec, Canada) for the treatment of diabetes: a novel approach in quantitative ethnobotany. J Ethnopharmacol 105 (1–2):55–63 10. Obo´n C, Rivera D, Verde A, Fajardo J, Valde´s A, Alcaraz F, Carvalho AM (2012) ´ rnica: a multivariate analysis of the botany A and ethnopharmacology of a medicinal plant complex in the Iberian Peninsula and the Balearic Islands. J Ethnopharmacol 144 (1):44–56

Multivariate Tools in Studies of Traditional Ecological Knowledge. . . 11. Rivera D, Obo´n C, Inocencio C, Heinrich M, Verde A, Fajardo J, Palazo´n JA (2007) Gathered food plants in the mountains of CastillaLa Mancha (Spain): ethnobotany and multivariate analysis. Econ Bot 61(3):269 12. Rodrı´guez Lo´pez S, Toledo BA, Galetto L (2015) Use of wood resources in Central Argentina: a multivariate approach for the study of phytogeography and culture. Ethnobot Res Appl 14:381–392 13. Awas T, Asfaw Z, Nordal I, Demissew S (2010) Ethnobotany of Berta and Gumuz people in western Ethiopia. Biodiversity 11(3–4):45–53 14. Garcı´a del Valle Y, Naranjo EJ, Caballero J, Martorell C, Ruan-Soto F, Enrı´quez PL (2015) Cultural significance of wild mammals in mayan and mestizo communities of the Lacandon Rainforest, Chiapas. Mexico J Ethnobiol Ethnomed 11(1):36 15. Quinlan RJ, Rumas I, Naiskye G, Quinlan M, Yoder J (2016) Searching for symbolic value of cattle: tropical livestock units, market price, and cultural value of maasai livestock. Ethnobiol Lett 7(1):76–86 16. Miller ML, Kaneko J, Bartram P, Marks J, Brewer DD (2004) Cultural consensus analysis and environmental anthropology: yellowfin tuna fishery management in Hawaii. CrossCult Res 38(3):289–314 17. Marques JG (2001) Pescando pescadores: cieˆncia e etnocieˆncia em uma perspectiva ecolo´gica. NUPAUB-USP, Sao Paulo 18. Baldauf C, Hanazaki N, MSd R (2007) Caracterizac¸˜ao etnobotaˆnica dos sistemas de manejo de samambaia-preta (Rumohra adiantiformis (G. Forst) Ching-Dryopteridaceae) utilizados no sul do Brasil. Acta Bot Bras 21(4):823–834 19. Baldauf C, Dos Santos FAM (2013) Ethnobotany, traditional knowledge, and diachronic changes in non–timber forest products management: a case study of Himatanthus drasticus (Apocynaceae) in the Brazilian Savanna. Econ Bot 67(2):110–120 20. Casas A, Caballero J (1996) Traditional management and morphological variation in Leucaena esculenta (Fabaceae: Mimosoideae) in the Mixtec Region of Guerrero, Mexico. Econ Bot 50(2):167–181 21. Blanckaert I, Paredes-Flores M, Espinosa-Gar˜ ero D, Lira R (2012) Ethnobotanicı´a FJ, Pin cal, morphological, phytochemical and molecular evidence for the incipient

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Chapter 10 The Spatiotemporal Scale of Ethnobiology: A Conceptual Contribution in the Application of Meta-Analysis and the Development of the Macro-Ethnobiological Approach Tania Vianney Gutie´rrez-Santilla´n, David Valenzuela-Galva´n, Ulysses Paulino Albuquerque, Francisco Reyes-Zepeda, Leonardo Uriel Arellano-Me´ndez, Arturo Mora-Olivo, and Luis-Bernardo Va´zquez Abstract From local level ethnobiological research, patterns have been identified in the relationships between human groups and natural resources. Although these patterns are consistent, they are unknown at a wider spatiotemporal scale, as well as the variables and the causal mechanisms that originate them. One of the factors that could be influencing the lack of study of social-ecological patterns is the ignorance of new macro-scale analysis perspectives; as well as the absence of a semantic, conceptual, and analytical framework. For this reason, it is proposed to establish a semantic-conceptual framework of areas in which ethnobiology can be developed at a macro-scale, which is the application of meta-analysis and the development of macroethnobiology. Both perspectives develop larger-scale research (space-time) and are based on the analysis of local information (primary information), identify variables, use statistical analysis, and determine processes and patterns by analyzing data heterogeneity. However, both disciplines have different goals, as well as the use of analysis tools. For the adequate development of any of these two approaches in ethnobiology, it is essential to conceptually know the discipline, select the primary information under quality criteria, fulfill with the theoretical assumptions of statistical tests, make an adequate interpretation of data variation and have the support of experts. It is not about proposing new disciplines, but broadening the study approach of ethnobiology, revaluing primary information, analyzing variables together and identifying social-ecological processes and patterns. We consider that on a broader scale, the analysis is workable for the understanding of social-ecological relationships. Key words Ethnobiology, Meta-analysis, Macro-ecology, Social-ecological relationships

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Introduction Ethnobiology is a multifactorial and interdisciplinary research field [1] which seeks to understand the relationship of cultural, social, biological, and environmental factors [2] by obtaining and

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_10, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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accumulating data that can be studied at different spatiotemporal scales; allowing for the identification of social-ecological patterns. From ethnobiological research, social-ecological patterns have been identified at the local level, for example at the level of traditional classification [3–7], plant species domestication and manipulation [8, 9], the use of wildlife [10] and edible fungi [11], among others. However, although such patterns are evident at a local level [12, 13], few larger scale studies analyze them. Ethnobiological data study at different spatiotemporal scales allows to define the social-ecological patterns, as well as the variables that originate them. For example, Molares and Ladio [14] study Mapuche ethnobotany (Argentina and Chile) demonstrating that there is a set of common knowledge, but with through time cultural erosion. One of the identified social-ecological patterns is that of biocultural diversity, recognized as the spatial co-occurrence between biological, cultural, and linguistic diversity [15–17], which has been related to the Rapoport rule as a statistical explanation between these similarities [18] generating an overlapping among the zones with the greatest biodiversity and “hotspots” conservation priority, and the most diverse cultural regions of the planet [19]. Other data on social-ecological patterns are: I. Human populations genetic variation as an effect of geographic isolation and dynamics [20]. II. Evolutive and adaptive processes on geographic distribution and dynamics of language generated by migration phenomena [21]. III. The support given by natural resources to the development of human societies complying with the laws of physics and energy [22]. IV. Biodiversity loss and the disproportionate growth of human societies with an effect of ecosystem homogenization [23–25]. V. Current distribution modification of some species due to anthropogenic factors [26]. VI. Influence of macro-ecological patterns in agricultural settlement systems [27]. VII. Or the biophysical constraints of land on development, sustainable consumption and its effect on macro-economics [28–32]. The identification of many of the aforementioned patterns is mainly due to approaches from other research disciplines different from ethnobiology, especially from human macro-ecology. However, the analysis of this type of interrelations is viable from ethnobiology; because it is a growing, multidisciplinary orderliness,

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combining both biological and cultural information. This leads to taking concepts and methods in order to generate new theoretical bases [33], as well as to restructure its approach and strengthen a research program not yet completed [2]. And it is one of the most promising alternatives, for its conceptual and methodological construction, adopting procedures already in use in consolidated fields, such as ecology [34] and also studying in detail the already accumulated (ethnobiological) data set, which can be analyzed from the meta-analytical or macro-ethnobiological approach for the understanding of social-ecological patterns. As evidence of conceptual growth at different spatiotemporal scales of ethnobiology, we can see that new research perspectives have emerged, such as: I. Evolutionary ethnobiology (EE) which studies the history of patterns between human behavior and biological resources [2, 35]. II. Niche construction theory (NCT) as an integrating scenario for studies that investigate the effect of human activities on the environment [36]. III. Macro-ethnobiology as a macroscopic statistical analysis for phenomena that tend to repeat in different places [12]. IV. Or the application of meta-analysis in the evaluation of traditional knowledge [37]. Therefore, we will focus on two of these approaches: metaanalytical and macro-ethnobiological, contributing with a conceptual framework that allows for ethnobiological analysis at other scales and with it the identification of processes, patterns, and social-ecological variables that underlie them; as well as its consolidation and development.

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Application of Meta-Analysis or Meta-Analytical Approach in Ethnobiology Albuquerque and Medeiros [12] propose macro-ethnobiology as a research stream focused on macroscopic level study approach, focusing its analysis on the statistical understanding of socialecological phenomena, through meta-analysis application. However, the term macro-ethnobiology may cause confusion if it is related to macro-ecology, because they are two totally different approaches and analyses. Therefore, it is suggested for the general framework of its conceptualization to be the application of meta-analysis or the meta-analytical approach of ethnobiology. Having as main goal to develop an integrative research by combining disparate research components (concepts, methods, and data) that is, by adding primary information (previous works) for the construction of large

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data sets (“big-data”), characterized by presenting high levels of complexity, diversity, and heterogeneity. These large data sets present variables which, quantitatively analyzed, based on the a priori construction of hypotheses and through systematic reviews and meta-analyses, explain processes and patterns. Systematic reviews are used in the synthesis of information guided by a predefined research question or by a previously delimited problem. They use simple methods to evaluate and filter information, creating a replicable review [38] but which is generally qualitative, although they can also include statistical analyses and should show clarity in the selection criteria for the included studies. Systematic reviews often focus on defining a general research landscape [39]. However, they may present limitations to contrast the found evidence, in order to generalize processes and patterns or to identify information gaps ([39, 40]; Fig. 1). In contrast, meta-analyses are based on sophisticated statistical analysis procedures, which bring benefits to the understanding of the development of the research disciplines in which they have been applied [41]. These integrate multiple independent studies, quantify effects or describe processes structure, through large data sets variation. They are recognized for increasing confidence and data synthesis, as well as identifying information gaps ([40–46]; Fig. 1; Box 1). They are used in large-scale patterns determination, allowing for the construction of generalizations and evidence-based assumptions [41]. It is also considered that they generate transformative research, because the solidity patterns of the integrated data are able to identify causal factors [39].

Fig. 1 General schematization of systematized reviews and meta-analysis. I. Systematic review. II. Metaanalysis

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Box 1 Generalities to Be Considered in the Application of Meta-Analysis in Ethnobiological Researches: Meta-analytical approach development I

A priori hypothesis or delimited problem: General and wide questions should be avoided. Instead, questions should be concrete and be based on a previous review of data availability. They should describe a challenge that can be addressed with the concentrated effort of a small working group

II

Primary information or literature inclusion: A thorough literature review should be carried out. In addition, some authors recommend including only literature from impact factor journals in order to avoid bias in the data analysis. However, due to the nature of “ethnodisciplines,” characterized by multiple methodologies in generating primary information, it is possible to be flexible and include information that is available in libraries, or that does not have an impact factor, or that take advantage of high accessibility to online documents. Much of this information has gone through a rigorous process, for example, establishment of research objectives, monitoring of a methodological framework in its development and has been reviewed by expert academics. However, we do not consider adequate for inclusion information derived from sources such as abstracts from congresses or posts on personal websites

III Inclusion criteria: To provide greater methodological robustness and avoid biases in the inclusion of primary information, search filters must be established, for example, a set of keywords IV Variables or variable coding: These depend directly on the research question and on the available information, since sometimes the primary sources of information do not use the same methodology. If so, a categorization framework of variables can be established to homogenize the primary data. The categorization of variables should corroborate the influences of the primary information on the processes or patterns sought. It is essential to take into account, when categorizing the variables, that the primary information data are all accessible V

Effect size or data heterogeneity: In order to integrate the results of the primary information, an indicator applicable to all independent results must be defined. This reflects the magnitude of the relationship among the involved variables. Different indices can be used; in this way the primary information is represented in the metaanalysis by an index of the effect size Statistical analysis and its interpretation: Descriptive, parametric, nonparametric, and even multivariate statistics can be used. For ethnobiological data, since they usually do not fulfill the norms of data normality, the application of nonparametric tests is recommended. It is indispensable to consider the application of the statistical tests to comply with the theoretical suppositions

VI Processes and patterns: The obtained results must answer the research objective, focusing on the a priori hypothesis, on the processes or trends that were expected, or on those that the data reflect

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Meta-analysis application is new and robust; however, it has the disadvantage of overestimating or underestimating results if criteria are not met during the primary information selection, data validation, theoretical assumptions of chosen statistical tests, or because of an inadequate interpretation of these ([42, 43, 47, 48]; Box 2). To minimize this effect, it is proposed to standardize the primary data search methods as a quality control, establishing limitations during primary information selection, as well as to evaluate data variation through heterogeneity tests and to fulfill theoretical assumptions of the statistical tests ([46, 49]; Box 3). Box 2 Criticisms on Ethnobiology Meta-Analysis Development and Its Similarity with Other Disciplines: General critics on ethnobiology applied meta-analysis I

Effect size overestimation: This happens when including primary ethnobiological information published with negative data or in favor of the prevalence of some paradigm. This effect can be minimized by conducting a systematic and controlled review

II

Heterogeneous data inclusion: It depends on the similarity among ethnobiology studies so they are significant when combined, in ethnobiology there is usually a variety of ethnographic sampling types, informants, ethnographic tools and in the ethnospecies identification at a taxonomic level. These barriers can be passed by applying hierarchical methods

III Poor quality studies inclusion: When adding studies which do not fulfil the minimum methodological criteria or that the parameters have not been adequately measured IV Variable correlation (co-variables): it is a variable that is not controlled in the data taking; it shows a high correlation with the dependent variable, and therefore the higher the correlation value, the greater the error

Meta-analysis application in ethnobiology is justified by the contribution and growth of research at local, regional and global levels in most of the ethnobiological sub disciplines; in the methodological research standardization, in the combination of both cultural and biological data, as well as in the availability and access to online publications. However, its performance will depend directly on the research question or the raised a priori hypothesis. Therefore, we propose to design protocols in which it is established that the data necessary for its application are available in the primary information.

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The variables establishment must be focused on phenomena explanation as a result of social-ecological characteristics and interactions [12], in turn the variables are integrated by data sets, which are the basis for the application, development and success of the meta-analysis. However, primary information in ethnobiology does not exclude methodological problems, as seen in other areas [39, 41]. One of the main problems is its origin, since these data come from both qualitative and quantitative research, they have been obtained from multiple ethnographic and biological methods, gathered from a variety of ethnographic tools, analyzed or not by means of some statistical or multivariate analysis. Box 3 Primary Information Selection Criteria and MetaAnalysis Data Treatment: Criteria I

Primary information standardization: Set of key words [46], it is possible to include the sets that are considered necessary l Framing the discipline (e.g., ethnosciences) l Defining the object of study (e.g., taxonomic group, ethnic group) l Central research theme (e.g., traditional knowledge, classification systems, traditional medicine, perception, management) l Geographic scale (e.g., local, regional, global)

II

Data heterogeneity: Analyzing the null hypothesis that the included studies are evaluating the same effect * Cochran Q: it is a nonparametric statistical test, which examines whether k treatments have identical effects [50] l I2: Provides a measure of the inconsistency degree in the studies’ results [38]

III Bias evaluation: The primary data contribution should preferably be available in Web of Science [44] l At indexed journals [43] l Publications preferably in English because it is the universal language of science [43] l Gray literature inclusion (congresses, theses, briefs) can generate biases in the conjunction of big-data [43]. However, it can be considered as long as criteria are established for its inclusion and that the necessary information is available in each one of the researches l Availability of online publications l That all the included studies have similar characteristics or that they evaluate the same effect

Sometimes the variables can be integrated from the primary information and in other occasions we could opt for their coding. Therefore, variables may be numerical or categorical, dependent or independent, depending on the trend used to evaluate. In the case

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of categorical variables, these can be coded by assigning an ascending numerical value by importance of the subcategories that make up the variable, where the values depend directly on the subcategories amount; or by ordering them randomly or alphabetically. It is important not to attribute more or less relevance to any subcategory, in order to reduce the bias in the value assignment. Despite the methodological problems that may arise during the development of the meta-analytical approach in ethnobiology, the benefits of its application are greater allowing for the establishment of validated protocols, randomized and controlled trials, evaluation of random data, sensitivity, and identification of heterogeneity factors (biological, methodological, social, cultural, economic, etc.) in the analysis [43]. It also allows for framing researches at an a priori assumption or hypothesis, and that the studies are replicable. It also contributes to the identification of information gaps, consolidating the critical recommendations making in favor of the maturation of ethno disciplines. However, it should not be forgotten that the development of the meta-analytic approach in ethnobiology is complex due to the primary data nature, mainly because of the variety of methods applied for its generation. Therefore, it is essential to recommend the ethnobiological community to work under standardized methods in the generation of primary information, as well as to establish research agendas and networks at a regional and international level.

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Macro-Ethnobiology The comparison at different spatiotemporal scales of socialecological relationships has theoretical and practical relevance for ethnobiology. Its systematic study helps to understand the principles that underlie between human beings and their environment [2], in addition to the increasing concern from ecologists, conservation biologists, and macro-ecologists to integrate large-scale analyses of cultural, social, and economic factors [12], mainly to evaluate the human impact and influence on biodiversity, and generate adequate conservation strategies [22, 28–30, 34, 51–55]. This approach has been addressed by crossing the boundaries between natural and social sciences, through human macroecology; focused on the study of the interactions between human groups and the environment at different spatiotemporal scales, which binds small-scale interactions by identifying emerging patterns and their underlying processes; using the same macroecological conceptual framework, its analytical rigor, methodological approach, and technological tools [29, 30]. In turn, human macro-ecology can use ethno biological concepts and data to

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Fig. 2 Macro-ethnobiological approach spatiotemporal scales. (a) Space (I. Global scale, II. Regional scale; and III Local scale). (b) Time (t ¼ present, t ¼ past, +t ¼ future)

incorporate social-ecological factors in greater detail, making a conjunction between both disciplines. Therefore, we can talk about macro-ethnobiology just as long as, besides being based on the principles of human macro-ecology, its interest is to study the statistical properties of a great amount of “ethnobiological particles” (ethnobiological data at a local level) comparable at any level of organization [56]. Where the emergent properties of the conjunction of a large number of “ethno biological particles” are described in the large-scale analyses [57], thus evaluating the complete system (Fig. 2). Multispecific methods have been designed to understand the processes behind the patterns. In addition, one of the current prerogatives of macro-ecology is to create networks among researchers [58] with the goal of developing methods and concepts for evaluating macro-ecological patterns with current biotic and abiotic conditions [57], emphasizing diversity analysis and its conservation [59] in which it is essential to include its relationship with human groups [51]. This type of analysis is possible thanks to the increase in data accumulation and informatics resources [60]. In the main, macro-ecology studies the patterns expressed by ecological systems through extensive spatial and temporal scales, by statistically analyzing the processes that determine these patterns ([56, 61–64]; Box 4), by emphasizing central points such as (a) integration of the past to current macro-ecological patterns, (b) explicit consideration of local patterns that lead to observed large-scale patterns, (c) large-scale data dependence and their quality; and (d) statistical analysis sophisticated methods for explaining the inherent bias in large-scale sampling [65].

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From macro-ecological perspective, the influence of humans on the environment, climatic changes produced by anthropogenic activities; as well as biodiversity loss due to pollution, land use practices, and ecosystem fragmentation have been studied [30, 57]. Although there is a variety of macro-ecological approaches, these studies do not explicitly distinguish human activities as processes that can give shape or cause patterns variation, such omission can be an error [51]. Since in macro-ecology it has been little studied, the influence of the environment on human groups, the biotic and abiotic conditions of culture, society, demography, health, or on the use of natural resources or at an economic level [30] it is in here where linking with ethnobiology can contribute significantly, by generating data on social-ecological relationships at the local level. Box 4 Macro-Ecology: Macro-ecology studies the relationship between organisms and their environment, characterizing and explaining organization patterns such as distribution, abundance, and diversity; to analzse processes that occur at a regional, global, and/or temporal level [61–63, 66–68]. It emphasizes its research in the quest for emerging statistical patterns [29, 69, 70] seeks to deepen the knowledge about the structure and functioning of ecological systems [63] characterizing its study in two aspects: large scale and multispecificity [65]. It is a discipline that answers hypotheses about systems which are too large to be manipulated experimentally [61] providing new knowledge and ways to understand them [22, 30]. In its beginnings, macro-ecology based its research on the correlative approach, associating a response variable (species richness) and a predicting variable (environmental, geographic, ecological variable, etc.). A clear example is the analysis of the latitudinal gradient/species richness [29, 68, 69], the distributions of the ecological attributes as a way of understanding the distributions causal processes [72] and the covariation among attributes [61]. However, it is a discipline characterized by constant revolutionizing without losing interest in determining ecological patterns and the causal variables that generate them. Currently, based on large datasets management, simulation models and technological implementations have generated new research trends, such as macro-evolution [73–75], application and development of the niche concept [76–78], phylo-macroecology [79], metabolic theories development [80], unifying theory [81], beta diversity analyses [82, 83], and sustainability and human macro-ecology [22, 30], among other approaches. A broader understanding of macro-ecology, its objectives and its methods helps to consider large-scale questions and

(continued)

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Box 4 (continued) research [84], responding every time to more complex questions, one of them being the contribution to one of the greatest challenges of the twenty-first century, to ensure a sustainable future for humanity, by combining cultural evolution as a main human characteristic, related to the role of energy availability and natural resources [29]. Macro-ecology is a discipline worldwide characterized for having a great development, until reaching today’s situation [65]. As a discipline that counts with more and more research groups that contribute to its study, due to its spectacular advance in the generation and availability of information [85]. Proposing new research questions, advancing in the understanding of the processes and mechanisms that underlie these patterns [29].

A macro-ethnobiological pattern recognized from the ethnobiological framework and studied through human macro-ecology is that of biocultural diversity, understood as the spatial co-occurrence between the areas of greatest biological, cultural, and linguistic richness, which are located in the intertropical region throughout the planet [15–17, 55, 86–88]. This has allowed us to identify that these regions have high levels of energy availability, complying with the macro-ecological rule of productivity [89]. Other macro-ethnobiological patterns, are the area–diversity relationship; since it has been seen that the mountainous areas harbor a high cultural diversity, areas that also have a high biological diversity [15]; or the positive relationship between the regions size (islands) and their linguistic variation [88] as a mechanistic phenomenon in the geographical arrangement. In order to develop the macro-ethnobiological approach it is imperative to consider in its application the search for correspondence with some of the macro-ecological rules, from the perspective that we wish to study. Going into: I. The species–area relationship, where a positive relationship is established between the species richness and the area size; II. The latitudinal and altitudinal gradients, in the first case we have seen that there is a greater species richness in areas close to the tropics, and in the second there is a greater diversity in the near regions at sea level. III. The species–diversity habitats relation, which assumes that the more heterogeneous a region is, the greater the biological diversity it will present. IV. The biodiversity–productivity relationship, which proposes that the most productive ecosystems will sustain greater

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biological diversity; among other described macro-ecological rules (Table 1). This is possible by designing research to assess whether these rules apply in social-ecological relationships. Exploring if: I. The bigger the area, the bigger the species use and knowledge. II. If human groups include more biodiversity in their socialecological systems by getting closer to the intertropical zones. III. If people use more resources at a lower altitude. IV. If human groups in territories with larger environmental heterogeneity develop larger species use and knowledge. V. If at more productive regions there is an increase in the traditional systems of biodiversity use and knowledge, among other macro-ethnobiological patterns (Table 1). It is important to consider that the suggested macroethnobiological patterns are not always fulfilled in the same way for all biological groups, since these in turn are determined by macro-ecological patterns. The exploration of macroethnobiological rules is necessary, through the establishment of more specific investigations for each biological group and at different spatial and temporal scales. Proposing the hypothesis exploration as: I. In the case of wild fauna there is a greater use of species in the number of uses and parts used and their relation with size. II. For edible fungi there is a greater diversity of species that are harvested in temperate regions (pine, oak, mixed forests) compared to tropical areas. III. Wild flora species with medicinal and edible potential are those that have been domesticated the most. IV. Floristic species that show certain secondary compounds are more likely to be part of social-ecological systems. V. Large and medium-sized species have a greater number of uses and parts used, than smaller ones. In addition, social-ecological systems can be explored by adding cultural, social, economic, and environmental variables. Explaining phenomena like: I. Human groups belonging to the same linguistic family (cultural origin) possess greater similarity in their social-ecological systems. II. There are convergent patterns of traditional ecological systems among culturally unrelated human groups, originated by the biological characteristics of the species.

There is greater species diversity at altitudes closer to sea level, decreasing as altitude increases

Altitudinal gradient

Human groups use more resources when at lower altitude

The greatest species richness is found Human groups established in the intertropical zone include greater in latitudes close to the equator, recognition and use of diversity in establishing that as we move away their socioecological systems than (N/S) the wealth gradually those established in higher latitudes decreases

Latitudinal gradient

The greater the cultural area, the greater biocultural diversity (richness of known and used species)

Suggested macro-ethnobiological patterns

Species richness in an area is a potential function of the area size

Description

Species–area relation

Macro-ecological pattern Visualization

Table 1 Macro-ecological patterns and examples in which macro-ethnobiological approach research can be carried out

(continued)

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Suggested macro-ethnobiological patterns

There is a greater number of species with a cultural identifier in species of medium and small size compared to large size species

Body size distribution

More small body size species have been described in relation to large size species

I. The areas with greatest biocultural diversity are located in the areas with the highest productivity on the planet II. In regions with higher productivity there is an increase in traditional systems of knowledge and use of biodiversity

The greater the habitat diversity, the Human groups whose territories have greater environmental greater the species richness, a heterogeneity will present greater response to landscape heterogeneity diversity of species use and knowledge

Description

Biodiversity–productivity The higher the energy flow rate in a relation system (productivity), the greater the biological diversity

Species–habitat diversity relation

Macro-ecological pattern

Table 1 (continued)

Visualization

140 Tania Vianney Gutie´rrez-Santilla´n et al.

Species abundance decreases with body mass among species within any great taxon

Species abundance–body size relation

Species cultural assignment increases in relation to their body size

I. Cultural recognition at the regional level increases with species distribution II. Species with restricted distributions have a local cultural assignment III. Species with broad distribution ranges have greater cultural relevance than those with smaller or restricted distribution

The original idea was designed by Stephens and collaborators [71], who explore the macro-ecological rules that operate for wild and parasitic species

Local species abundance increases with wide distribution

Species abundance distribution relation

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III. Species traditional use and knowledge at ethnohistorical documents prevail at some regions in the present. IV. Current macro-economy and globalization phenomena generate cultural homogenisation conditions. V. Traditional social-ecological conservation.

systems

favor

biodiversity

In addition to considering compliance with macro-ecological rules, attention must be paid to the data set and the analysis variables. Macro-ecology bases its studies on geography and demography, a link between these two variables is the correlation between species diversity in the sites and the average range of species that occur in there; reflecting mathematical and biological relationships, being sites diversity and species distribution the fundamental pieces [90]. Similar attributes are found in the ethnobiological data, taking as analysis units the species lists published in the ethnobiological works, with which it is possible to generate incidence matrices (presence–absence) constituting the integrating variables with sites and species descriptors. Regarding the variables, environmental, geographical, and ecological variables can be used, to which cultural, social, and economic variables can be added, taking care that these are not correlated. By combining data and variables from human macro-ecology, it has been suggested to analyze patterns such as the energy exchange between humans and the biophysical environment, human nutrition ecology, life history, geographical space use, human population structure, disease ecology, industrial and urban systems [30]. However, we still need to include some fundamental aspects such as the traditional systems of knowledge, use and management of the species, because it is considered that there is little information about it; but these variables can be included from the macroethnobiological perspective. As a central point of research, it considers that the Earth’s most biodiverse areas are occupied by native groups [15–17, 87].

4 Why Asking Research Questions for Meta-Analytical and Macro-Ethnobiological Approach Development? For the success and good development of the meta-analytical and macro-ethnobiological approach, it is essential to draw a frame of reference. This type of exercise has been applied in ecology by seeking to list its main challenges and means to solve them [91–93]. This is possible by highlighting key issues, designing a series of questions that identify ethnobiological areas that have the potential to significantly advance and provide a working agenda; emphasizing that the main objective of these research approaches is to determine processes, patterns, and variables of the relationships

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between human groups and biological diversity; analyzing the influence of those relationships on ecosystems and species conservation, and community development; integrating the ecological, environmental, social, cultural, and economic problems. The goal of designing a framework is to generate important questions with answers for the different ethnobiological disciplines. General and broad questions should be avoided; instead it is recommended to develop questions that describe a challenge that can be addressed with a focused and concentrated effort of a small group of researchers or through a research program receiving adequate financial support. The proposal questions must be rigorous, democratic, and transparent, without the aim of favoring a particular research group, and lacking a desire to develop only one or another ethnobiological discipline, as well as to choose to work with a specific human group or geographic region. To carry out this process of question development and selection, one could start, for example, with a search for international authors inviting them to join a collaborative working group. This search would focus on researchers who have a greater number of citations, the editors of important journals in the area, as well as a representative from each of the countries that have the greatest contributions to the discipline at an international level. The search should be seeking a balanced representation of researchers who work on different ethnobiological areas. It is also important to look for financing at institutional and governmental levels, and also to establish collaborations with other nonethnobiological disciplines with the purpose of creating a working group and collaborative networks that seek to promote meetings in which the relevant topics and possible issues are discussed. As well as the selection of thematic areas of predominant research that reflect the ethnobiological context and that generate a critical discussion about the possible results, in order to reformulate the questions and approaches. The questions should take into consideration their expected importance and impact. For example, nowadays some of the premises of ecology and ethnobiology are conservation, sustainable management and development, and integrating social actors. This is due to the fact that environmental and cultural changes are strongly affecting local communities and biodiversity. It is important to let the ethnobiological community know that new research perspectives, in this case the meta-analytical and macroethnobiological approach, are not proposed as new ethnobiological subdisciplines. Rather, they seek to have a broader view of the variables, processes, and patterns that are integrating the discipline. Thus, conceptual and methodological gaps are explored, designing inclusive research programs of a large scientific community that significantly contributes to their scientific maturity (Table 2).

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Table 2 Questions examples for meta-analytical and macro-ethnobiological approach Focus

Questions

Meta-analysis

Is it possible, with the availability of “big-data” primary information, the development of meta-analytical approach? Does the meta-analysis application allow for the identification of information gaps? Critically contributing to its scientific consolidation Is a methodological standardization and a quantitative growth of ethnobiology possible? Which are the most culturally relevant species at a regional and global level? What should be the central lines of research in ethnobiology, facing the accelerated loss of biological and cultural diversity? What is the difference in the discipline growth and maturation between the qualitative and quantitative contributions?

Macroethnobiology

What is the relationship between the biocultural diversity loss and the ecosystems homogenization? What is the effect of overexploitation of natural resources in the different indigenous regions at a regional and global level? Can biocultural patterns be identified by applying the macro-ethnobiological approach? Is the biodiversity management at indigenous regions optimal?

Shown questions do not necessarily indicate an importance order, some may contribute disciplines development in a theoretical, conceptual, methodological, practical, or developmental way

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Chapter 11 Collection and Analysis of Environmental Risk Perception Data Henrique Fernandes Magalha˜es, Regina Ce´lia da Silva Oliveira, Ivanilda Soares Feitosa, and Ulysses Paulino Albuquerque Abstract People perceive and represent the environment that surrounds them through physical, psychological, and cultural filters, which enables them to understand the scenarios and environmental changes that occur in their environment. Many of these changes, however, can be interpreted as potentially adverse situations, that is, as risks. The analysis of risk perception can be a very useful tool in ethnobiological studies, in the search for a better understanding of environmental problems perceived and faced locally. Different methods and techniques can be used in the collection and analysis of environmental risk perception data. In this chapter, we present the interview, the stimulus with drawings, participatory risk mapping and the richness indexes and risk sharing perceived as resources that can be used to evaluate the environmental risks perceived by a particular social group. Key words Ethnobiology, Environmental risk perception, Data collection

1

Introduction Human perception is responsible for the organization and interpretation of reality by people, thus, they attribute meaning to their environment. We perceive the environment through our senses. The manner we perceive it, in turn, can be influenced by physical, psychological [1] and cultural filters [2]. Thus, we move to the concept of environmental perception that corresponds to the representation that individuals make of their environment, which allows them to understand the scenarios and environmental changes that surround them [3]. Many of the environmental changes that people perceive can be interpreted as potentially unfavorable or harmful circumstances, which can be defined as risk [4]. Other definitions point to

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_11, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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environmental risk as the likelihood of adverse effects occurring as a consequence of an environmental phenomenon [5–7]. Faced with variations and connotations for the same term, it is important that the researcher be careful to define well what he is considering as environmental risk in his research. In ethnobiological research, the analysis of risk perception can be a very useful tool in the search for a better understanding and search for solutions to problems perceived and faced locally [4, 8]. In the collection and analysis of environmental risk perception data, different methods can be applied, depending on the research objectives. In this chapter, we will detail some of these methods, conceptualizing them and showing their applicability in different types of environmental risk perception studies.

2 Methods of Data Collection and Analysis in Environmental Risk Perception Research 2.1

Interviews

One of the most commonly used techniques to access the local perception of environmental risks is interviews [9, 10]. Among the vast options of interviews, what is more frequently observed in these types of studies are the semi-structured ones. They are based on a script containing flexible questions, considering issues that may arise during the interview [11]. This technique also enables the informants to feel free to express themselves on their own terms and according to their own convictions. However, the researcher must be aware that the focus of research is not lost due to this flexibility [11]. Although this method is performed face-to-face with the informant, and any questions can be clarified at the time, depending on how the question is asked different interpretations may occur. For example, if we ask the informants “How do you perceive and adjust to climate change?” It may occur that they do not understand what it is because of the way the question was elaborated. In this case, they can take one of these two attitudes: answer that they do not know, or that they do not understand. In face of the situation reported above, the researcher must rephrase the question so that it becomes clearer to the informant. In some cases, they may act differently from these two situations, trying to answer based on their understanding, which is often not based on the full understanding of the issue of interest of the investigator. Generally, the interviews feature two main sections. The first one consists of socioeconomic information of the informants, such as name, age, gender, profession, among others. The second part

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aims to identify the specific issues of the study, such as people’s perception of environmental risk, what are the potential impacts generated by these risks, how they can affect their daily activities, and what measures do they take to adapt, or prevent locally perceived risks [10]. Thus, people can inform the researcher about their ways of managing risks according to the current climate, which can be done, for example, by diversifying agricultural crops, by cultivating the species that are more resistant to drought in times of scarcity of rainfall, the use of irrigation to supply the water demand of plantations [9], among others. 2.2 Stimulus with Drawings

The drawing stimulus method is a tool that can be used with people of different age groups. However, it is most commonly used to integrate children into environmental risk perception studies, since evidence indicates that in the face of extreme environmental changes, such as drought and flooding, children are more exposed and vulnerable to these risks [12]. In addition, drawing is considered a way of communicating and expressing feelings and a way of representing how the individual perceives the events of the external world [13, 14]. Therefore, through drawing, children can represent their understanding of the natural world, becoming an effective way of learning how disasters affect their lives, and how hazards can be minimized [15, 16]. However, it is important to advise that this method requires more time for execution, and a possible lack of ability of children with drawing may be a limitation that must be considered by the researcher [17]. In fact, the drawings are an important tool to access local environmental perception and/or knowledge. However, there are still a few studies that work with this perspective, and when it comes to children, studies are still scarcer [15]. In addition, it is important to note that compared to older generations, children may have a more up-to-date view of local environmental conditions, and such information may be useful to understand the current environmental reality compared to the past [16]. As an example, we present the study of Taylor and Peace [15] in Indonesia. Among multiple methods, the authors used the design to assess children’s perception of risk and their ability to respond to flood impacts (Box 1). Taylor and Peace [15] noted that children presented their own ideas and perspectives for action in the face of environmental risks, suggesting that the drawing can provide important information about children’s resilience to environmental disasters.

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Box 1 Steps, with Adaptations, Used by Taylor and Peace [15] to Access the Environmental Perception of Children and Understand How They Act in the Face of Flood Events in the Local Community: Phase 1 Elaboration of key questions to direct the children at the moment of the research that are directly related to the objective of the research. Phase 2: Environmental risk perception “How do you see the floods here in the community (. . .)” “Draw on the flood that occurs here in the community (. . .)” Phase 3: Perception on the adaptation on the perceived risk “What do you know about flood prevention (. . .)” “What do you do during floods (. . .)” “What prevents you from doing this action (. . .)”

Pellier et al. [16] indicated that, through drawings, children were able to convey their perceptions about current and future environmental conditions. Children can also make associations on local fauna and flora conditions that are useful in studies aimed at sustainable management of natural resources in the face of global environmental change (see [16]). Thus, for a better understanding of how to direct and analyze information obtained in this type of study, in Box 2 we present a hypothetical case, elaborated from an adaptation of the methodology used by Silva et al. [17] in a study of environmental perception with children. Box 2 Steps to Analyze the Contents of the Drawings, Adapted from Silva et al. [17]: Consider the Fig. 1 as example, and see the steps described below: (a) Create categories to analyze the information contained in the drawings, for example, category to insert biotic and abiotic components; (b) Create category for perceived risk evidenced by the child, for example, deforestation caused by the human being; (c) Count of each element contained in the drawing and subsequent grouping in their respective categories; (d) The researcher may choose to see the frequency of citation by gender, age, schooling and/or comparison of different communities. This step will depend on the guiding question of the study.

2.3 Incidence and Severity of the Perceived Risk

An approach to quantitatively assess risks is through the application of some techniques proposed in the literature. In this topic, we will discuss Participatory Risk Mapping (PRM), a method originally developed by Smith et al. [4] and then adapted by Baird et al. [19] that is used to access the perception of environmental risks.

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Fig. 1 Illustration of the environmental reality related to the local flora, made by a child from a rural community near the Chapada Diamantina National Park, Bahia, Brazil. Adapted from Oliveira et al. [18]

In relation to other methods used for this same purpose, PRM has the advantage of being a very precise method in its application, which facilitates the identification and classification of the factors that cause the risks perceived by the people [20]. The PRM also allows the researcher to evaluate the potential that a certain risk has of affecting people’s way of life [8]. First, the researcher should ask through interviews that people name the risks they perceive. Soon after, people are invited to sort and classify the risks they cited according to the level of impact they cause in their lives, which Smith et al. [4, 21] names severity. A great advantage of the PRM is that it allows people themselves to decide which risks most affect their quality of life [4, 19, 21], that is, the researcher does not influence the responses of the informants. As researchers, we should pay attention to two situations that may occur when people classify risk: different people may use different terms for the same risk [4, 21]; and the same person can cite more than one factor causing a certain risk [20, 22]. In this case, some questions such as “In which situation can this risk occur?” and “How can this risk be avoided?” can help us to obtain more accurate answers, which will facilitate the subsequent classification of risks. Subsequently, the researcher should measure the frequency with which the risk is perceived and identified, and the risks that are perceived as more serious, respectively: risk incidence (I) and severity index (S). If the researcher decides to adopt the model of Smith et al. [4] in the study, they should classify the risks according

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to the severity attributed by the informant, representing them by numbers on a decreasing scale (the number 1 represents the most serious risk, number 2, the second most serious risk; and so on). Soon after, people should be encouraged to present ways of resolving or mitigating each of the cited and classified risks (adaptive strategies). The proportion of people who identified a source of risk will correspond to the incidence index (Ij), which will be calculated by the equation Ij ¼ nr/nj, where nr represents the number of times the risk was cited, and nj represents the total number of informants. The values of I represent the risk dimension in the context of the studied population, and can vary from 0 (lower frequency of citations) to 1 (all interviewees cited). The Severity Index (S) represents the number and classification of risk factors cited by each person, and its value can vary from 1 (most severe) to 2 (less severe). Sj is calculated by the equation Sj ¼ 1 + (r – 1)/ (n – 1), where r represents the risk classification based on the order indicated by the informant, and n represents the number of risk factors cited by the people. After completing the calculation, we will have: the most severe risk (r ¼ 1) for Sj ¼ 1; the least severe risk (r ¼ n > 1) for Sj ¼ 2; and the remaining risks for equally distributed intermediate amounts. In Box 3, we present a hypothetical example of the calculation of severity index (S) and risk incidence (I).

Box 3 Hypothetical Example of Calculation of Severity Index (S) and Risk Incident (I ), According to Smith et al. [4]:

Informants Classification (r) Risk factors

Factors number (n) Sj

I

4

II

III

1

Food scarcity

2

Water shortage

1.33

3

Agricultural pests

1.66

4

Lack of sanitation

2

1

Lack of sanitation

2

Water shortage

1

Food scarcity

2

Water shortage

1.5

3

Lack of sanitation

2

2

1

1 2

3

1

Risk factors

Severity index (S) Risk incidence (I)

Food scarcity

1

0.66

Water shortage

1.61

1

Lack of sanitation

1.66

1

Agricultural pests

1.66

0.33

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After calculating the two measures, they can be combined to compose a third index: Total Risk (R), represented by the equation Rαβ ¼ αI/βS, where α represents the value of the Incidence Index, and β corresponds to the value of Severity Index. It is interesting to note that, if α ¼ 1 and β ¼ 1, we would have the measure represented by the formula R11 ¼ I/S, which represents a variance from 0 (zero incidence) to 1 (most severe risk). In case the PRM model modified by Baird et al. [19] is applied, the calculation of the incidence index (Ii) will follow the same steps as the original model proposed by Smith et al. [4], as we have discussed earlier. The difference is in the calculation of the severity index (Sj), which should be calculated in two steps. First, the researcher has to obtain the individual value of the risk severity index (Rij), whose formula is Rij ¼ 1 – rij - 1/ni, where nj represents the total number of risks (nj) mentioned by each informant (i), while r represents the classification of each risk individually. Then, all the results found individually for Rij should be summed and divided by the number of times the risk was cited as the most severe (Nj). Thus, we obtain the severity index, by the equation Sj ¼ ∑i  1Nj ¼ 1  Rij / Nj. In this model, Sj has values between 0 (risks that are not considered severe) and 1 (severe risks). The results can be represented by means of a risk map, which is a graph that allows the researcher to determine the space and the distribution of the incidence and severity of the risk. For this purpose, the PRM according to Baird et al. [19] is recommended, since the type of classification of the severity index (Sj) used in this model, as we have discussed in the previous paragraph, facilitates both the elaboration process and the interpretation of risk maps [19]. As a practical example, we present below (Fig. 2) an environmental risk map model developed with data obtained from a study implemented in a rural community in the Brazilian Northeast [23]. In the Fig. 2, we observe the following: two risks considered by the population as severe, but not as incidents (lack of religiosity, unemployment); one risk perceived locally as severe and incidental (drought); risks that are not considered severe or incidental (violence, native flora decreases, wildlife decreases, agricultural pests); and, finally, a risk perceived as an incident, but not as severe (soil nutrient deficiency). In ethnobiological studies, risk mapping can be very useful, for example, to evaluate the risk factors that can affect the way of life of people living in areas of socio-environmental conflicts. In addition, they may also assist in the identification of social groups or strata that perceive certain environmental risks as more severe [20]. 2.4 Richness and Sharing of Perceived Risks

Originally, the knowledge wealth index (KWI) and the knowledge sharing index (KSI) emerged as a suggestion for a new quantitative simple measure, focused on the people and the knowledge they have, and in the sharing and uniqueness of the information

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RL

1

UE 0.9

DROUGHT

0.8 0.7

Severity

0.6 0.5 0.4 IVC

0.3 0.2 0.1 0

NRF YPW WR WC

0

0.1

PNS

PLG

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Incidence

Fig. 2 Example of perceived environmental risk map (RL religiosity, UE unemployment, DROUGHT—uncontrolled drought/winter/absence of rain/low rainfall, IVC insecurity/violence/crime, YPW young people who do not want to work, WR wildlife reduction, WC warm climate, NFR native flora reduction, PLG plagues, and PNS soil poor in nutrients). Source: Oliveira et al. [23]

obtained [24]. Thus, these measures allow the researcher to make decisions and test hypotheses about the distribution of knowledge in a community, as well as estimate the richness and sharing of information among people [24], considering the similarity between people within the same social group [23]. On this topic, we will discuss the use of richness and sharing of perceived risks indexes, adapted by Oliveira et al. [23] from the model proposed by Arau´jo et al. [24]. The KWI represents a distance measure whose values range from 0 to infinity. The lower the KWI value, the greater the perceived risks and the corresponding adaptive strategies cited by the informants [23]. This relation is determined by the equation KWIi ¼ 1/∑Ji2, in which Ji ¼ Pi/Ci.Pi:Pi represents the number of risks and adaptive strategies cited by each participant; and Ci represents the total adaptive risks and strategies cited by the local community. In order to simplify these calculations, we recommend, following Arau´jo et al. [24], that more than one informant is interviewed for each house, considering that the family is the sample unit of the research. The KSI is also a measure of distance, and its values can vary from 0 to 1. The index is expressed by the equation KSI ¼ KWIi/ KWImax, where KWIi represents the degree of information sharing between each participant, and KWImax represents the degree of information sharing among components of the local community in question [24]. The lowest degree of sharing is represented by the value 1.

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In order to facilitate the analysis of the data obtained, we recommend that they are organized into categories. As an example, we present the study by Oliveira et al. [23] who chose to organize their data into two categories: environmental risk perception, which included the perceived risks related to environmental changes; and sociocultural risk perception, which encompassed the perceived risks related to the impacts of environmental changes on people’s livelihoods (Box 4). Box 4 Forms of Perceived Risk Categorization, by Oliveira et al. [23]: Perceived risks

Number of citations

Categories

Sub-categories

Environmental risk perception (n ¼ 7)

54 Climatic phenomena Drought/absence of rain/uncontroled winter/long summer Warmer climate

Sociocultural risk perception (n ¼ 5)

Population abundance (fauna/ flora) Native flora reduction Native flora growth Wildlife reduction

27

Soil quality Soil poor in nutrients

30

Agriculture Pests

2

Sociocultural Insecurity/violence/crime Young people unmotivated to work in the field Weakened health Unemployement Religiousness (lack of faith, lack of commitment to the church)

9

In the study exemplified above, Oliveira et al. [23] assessed the relationship between the degree of religiosity/spirituality of a rural population in the Brazilian Northeast and the richness and sharing of locally perceived risks, and the adaptive strategies developed. In order to test this relationship, the authors used generalized linear models (GLM) with Gaussian distribution, where the values obtained for degrees of religiosity/spirituality were used as explanatory variables and the measures of richness index and index of perceived risk sharing—and of adaptive strategies—were used as response variables. As a result, the authors did not find a significant relationship between the degree of religiosity/spirituality and richness and risk sharing, and with adaptive strategies [23].

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The same methodology used by Oliveira et al. [23] can be applied in any ethnobiological study that aims to evaluate the relationship between any explanatory variable (level of schooling, for example) and the richness and sharing of locally perceived risks. Thus, the use of KWI and KSI in ethnobiological studies can be very useful to obtain information about how richness and the sharing of information—in our case, risk perception—arise among families, communities and/ or different social groups [24]. References 1. Bell S (2001) Landscape pattern, perception and visualization in the visual management of forest. Lands Urb Plan 54:201–211 2. Okamoto J (2002) Percepc¸˜ao ambiental e comportamental. Mackenzie, Sa˜o Paulo 3. Garcı´a-Mira R, Real JE (2005) Environmental perception and cognitive maps. Int J Psychol 40(1):1–2 4. Smith K, Barrett CB, Box PW (2000) Participatory risk mapping for targeting research and assistance: with an example from east African pastoralists. World Dev 28:1945–1959 5. Sjo¨berg L (2000) Factors in risk perception. Risk Anal 20:1–11 6. Sjo¨berg L (2000) The methodology of risk perception research. Qual Quant 34:407–418 7. United Nations Office for Disaster Risk Reduction (2009) Global assessment report on disaster risk reduction: risk and poverty in a changing climate. UNISDR, Geneva, Switzerland 8. Quinn CH, Huby M, Kiwasila H, Lovett JC (2003) Local perceptions of risk to livelihood in semi-arid Tanzania. J Environ Manag 68:111–119 9. Campos M, Vela´squez A, Mccall M (2014) Adaptation strategies to climatic variability: a case study small-scale farmers in rural Mexico. Land Use Policy 38:533–540 10. Wang S, Cao W (2015) Climate change perspectives in an Alpine area, Southwest China: acase analysis of local residents’ views. Ecol Indic 53:211–219 11. Albuquerque UP, Ramos MA, Lucena RFP, Alencar NL (2014) Methods and techniques used to collect ethnobiological data. In: Albuquerque UP, da Cunha LVF C, RFP L, RRN A (eds) Methods and techniques in ethnobiology and ethnoecology. Springer protocols handbooks. Humana Press, New York, pp 15–37 12. United Nations Children’s Fund (2008) Climate change and children: a human security challenge. Policy Review Paper. UNICEF

Innocenti Research Centre, Florence. Available from: http://www.unicef-irc.org/ publications/pdf/ climate_change.pdf. Accessed 25 April 2018 13. Barraza L (1999) Children’s drawings about the environment. Environ Educ Res 5 (1):49–66 14. Hume C, Salmon J, Ball K (2005) Children’s perception of their home and neighborhood environments, and their association with objectively measured physical activity: a qualitative and quantitative study. Health Educ Res 20 (1):1–13 15. Taylor H, Peace R (2015) Children and cultural influences in a natural disaster: flood response in Surakarta, Indonesia. Int J Disaster Risk Reduct 13:76–84 16. Pellier A, Well JA, Abram NK, Gaveau D, Meijaard E (2014) Through the eyes of children: perceptions of environmental change in tropical forests. PLoS One 9(8):e103005 17. Silva TC, Chaves LS, Albuquerque UP (2016) What is environmental perception? In: Albuquerque UP, RRN A (eds) Introduction to ethnobiology. Springer International Publishing, Switzerland 18. Oliveira RCS, Schmidt IB, Conceic¸˜ao AA (2013) Uso e conhecimento do candomba´. 1ª ed, Feira de Santana, Editora UEFS 1, 38p 19. Baird TD, Leslie PW, Mccabe JT (2009) The effect of wildlife conservation on local perceptions of risk and behavioral response. Hum Ecol 37:463–474 20. Silva TC, Cruz MP, TAS A, Schwarz ML, Albuquerque UP (2014) Methods in research of environmental perception. In: Albuquerque UP, da Cunha LVF C, RFP L, RRN A (eds) Methods and techniques in ethnobiology and ethnoecology. Springer Protocols Handbooks. Humana Press, New York, pp 99–109 21. Smith K, Barrett CB, Box PW (2001) Not necessarily in the same boat: heterogeneous risk assessment among east african pastoralists. J Dev Stud 37:51–30

Collection and Analysis of Environmental Risk Perception Data 22. Silva TC, Ferreira WS Jr, Santoro FR, Arau´jo TAS, Albuquerque UP (2016) Risk perception. In: Albuquerque UP, Alves RRN (eds) Introduction to ethnobiology. Springer International Publishing, Switzerland 23. Oliveira RCS, Albuquerque UP, Silva TLL, Ferreira WS Jr, Chaves LS, Arau´jo EL (2017) Religiousness/spirituality do not necessarily matter: effect on risk perception and adaptative

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strategies in the semi-arid region of NE Brazil. Glob Ecol Conserv 11:125–133 24. Arau´jo TAS, Almeida ALS, Melo JG, Medeiros MFT, Ramos MA, Silva RRV, Almeida CFCBR, Albuquerque UP (2012) A new technique for testing distribution of knowledge and to estimate sampling sufficiency in ethnobiology studies. J Ethnobiol Ethnomed 8:11

Part III Methodological and Theoretical Challenges

Chapter 12 Ethnoecology in Pluricultural Contexts: Theoretical and Methodological Contributions Julio A. Hurrell, Pablo C. Stampella, Marı´a B. Doumecq, and Marı´a L. Pochettino Abstract This chapter is a contribution to current ethnoecology from a complex perspective, through a revision of the presuppositions that constitute its theoretical–methodological framework. The systemic approach of ecology understood as a science of synthesis based on relationships between the organism and its environment is discussed. The complex thinking applied to biocultural ecology, based on the relationships between the people and their environment is also discussed, including a reflection about the dissociation between nature and culture, and its conceptual implications. Ethnoecology as the study of local people knowledge system about their own relationships with their environment poses a discussion on sciences and ethnosciences, and its relationships with ecology and biocultural ecology. The reflection about the relationships between the observer and the observed people implies a discussion upon the researcher’s presence in his own research, and how he manages his thinking categories. The role of interviews as communication systems in which the generated knowledge is embodied in actions (discourses and behaviors) is revalued. Ultimately, three cases for the Rio de la Plata riverside (Buenos Aires province, Argentina) are presented. These cases illustrate how the local people identify and value the environmental changes in the pluricultural contexts of the urban areas, and how the obtained results have meaning in the theoretical–methodological framework developed. In conclusion, complex thinking allows us to construct adequate explanations for complex phenomena that ethnoecology tries to explain, and to avoid reductionisms. Key words Ethnoecology, Complexity, Presuppositions, Local knowledge system, Environmental changes, Rı´o de la Plata Riverside, Argentina

1

Introduction This chapter includes the theoretical–methodological framework of a research line in ethnoecology that is developed by the Laboratorio de Etnobota´nica y Bota´nica Aplicada (LEBA), Facultad de Ciencias Naturales y Museo (FCNM), Universidad Nacional de La Plata (UNLP), Argentina. The research line is supported by studies carried out for the past 30 years in different sectors belonging to Rı´o de la Plata region, oriented towards the understanding and

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_12, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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valorization of local environmental changes, according to the studied people knowledge system. The theoretical–methodological framework is defined, and some illustrative cases that link the research line theory and practice are discussed. We support the idea that the research theoretical–methodological framework is the context in which the research results acquire meaning, and in this sense the researchers must be explicit about their own presuppositions (i.e., knowledge tacitly assumed beforehand at the beginning of an argument line). For the research line context, we analyze the basic presuppositions about ecology, biocultural ecology, and ethnoecology, including the researcher’s role in the research process. In his book Mind and nature: A necessary unity, Gregory Bateson said: “Science, like art, religion, commerce, warfare, and even sleep, is based on ‘presuppositions’. It differs, however from most other branches of human activity in that not only are the pathways of scientific thought determined by the presuppositions of the scientists but their goals are the testing and revision of old presuppositions and the creation of new. In this latter activity, it is clearly desirable (but not absolutely necessary) for the scientist to know consciously and be able to state his own presuppositions. It is also convenient and necessary for the scientific judgment to know the presuppositions of colleagues working in the same field. Above all, it is necessary for the reader of scientific matter to know the presuppositions of the writer (. . .) I believe in the importance of scientific presuppositions, in the notion that there are better and worse ways of constructing scientific theories, and in insisting on the articulate statement of presuppositions so that they may be improved” [1].

2 2.1

Theoretical–Methodological Framework Ecology

In its broadest sense, ecology is the science that studies the complex set of relationships between organisms and their environments [2, 3]. This definition implies a complex thinking [4] because both organisms and environments are systems whose relationships define a higher level system (“organism–environment”). In this sense, the word system refers to a “whole” in which it is possible to distinguish “parts” or “elements” related to each other in some way. In this respect, Ramo´n Margalef remarked: “In the study of all systems, the knowledge of the relationships between the interacting elements is more important than the exact nature of these elements, which are studied by other sciences that explains their characteristics in terms of the relationships between components of a lower order” [5]. For the organisms (a part of the whole), the “other science” is biology, that studies the living systems, their origin, characteristics, and evolution. Ecology is a science of synthesis, a

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broad platform where both biology and the physical environment sciences acquires a complex meaning, especially considering the evolutionary process that as Margalef said: “does not develop in the emptiness” [5]. From the origin of the General Systems Theory, at the 1940s, the notion of system became a transdisciplinary tool that aims at a “science of the whole,” a concept many times considered vague, misty, and semi-metaphysical [6]. The Aristotelian axiom: “the whole is more than the sum of its parts,” implies that the system presents emerging properties (the properties of the whole), different from the separately considered parts properties. In ecology, this currently rooted conception has abolished the already old and reductionist definition of ecosystem as a sum of the biotic community (biocenosis) and the physical environment (biotope) [7]. However, this triumph of complexity over simplicity inside the scientific domain has not yet taken root in the ecology teaching at some educational levels: the equation “ecosystem ¼ biocenosis + biotope” is still taught. This simplifying ecosystem notion is a trivialization of the original concept of Arthur G. Tansley, who in 1935 defined the ecosystem as: “The global system (. . .) which includes not only the set of organisms, but also the complete set of physical factors, which constitute what we call ‘environment’ (. . .) It is not possible to separate the organisms from their environment with which they constitute a unique system (. . .) It is a system that formed in this way constitutes the basic unit of Nature” [8]. Towards the 1970s, biology has provided a new vision about living beings based on autopoiesis theory [9], in which organisms are considered as systems defined by their singular capacity to build themselves. This self-production is possible only if the living system is related to what surrounds it, because those relationships make possible the necessary exchanges of matter, energy, and information. Thus, by virtue of such exchanges the organism is a thermodynamically open system that organizes itself (self-organization) at the expense of generate information (a certain order), opposite concept to entropy (disorder). The introduction of these notions coming from other scientific domains, especially from the information theory and the thermodynamics of far from equilibrium systems, into ecology is due to the intellectual effort of Ramo´n Margalef [2, 3, 10–14]. As Edgar Morin said, the complexity of the living systems lies in the fact that organism organizes itself and, at the same time, depends on its own environment. The apparently contradictory concept of self-eco-organization has a new meaning in the context of a system that encompasses both an organism and its environment [15]. “It is not possible to separate the organisms from their environment,” as Tansley said [8]. In current ecology, the concept of environment has at least two meanings. On the one hand, it refers to the set of physical variables (the environment as a physical space). On the other hand, the

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environment also includes other organisms of the same species or others, with which the organism (considered as the reference system) also exchanges matter, energy, and information [16]. From the perspective of the complex thinking, the environment thus defined should not be reduced to the physical environment. Likewise, in its complex sense before delineated, an organism specifies its environment through its interactions with other living systems and the physical conditions. Life not only depends on the physical parameters but also modifies and reconfigures them. In his book Leben und Umwelt, from the early 1940s, August F. Thienemann argues that life (Leben) and its surrounding world (Umwelt) define one another and constitute a “unity.” Following these arguments, the organism lives in its environment, does not live in an environment (as an independent instance from the organism). Going a step further, it is possible to affirm that when an organism dies, its environment dies with it [17, 18]. The statement of Gregory Bateson: “If the organism ends up destroying its environment, it has in fact destroyed itself” [19] acquires a renewed relevance. If in a system one part destroys the other, the whole system disappears. This discussion is inscribed in contexts of change: the organism–environment system is dynamic, it changes over time, and it evolves. Thereby, this system constitutes not only the ecological unit but also the evolutionary one, that is, the survival unit [19]. In the ecology framework, as Margalef explains, evolution goes beyond the scope of the species level (neo-Darwinian evolution) [20]. In accord with Jordi Flos: “Definitely, the adaptability of one single species goes through its success in collaboration with the construction and maintenance of a system, in which the internal flow of information is maximized” [12]. Maximizing system information implies increasing its organization and complexity. 2.2 Biocultural Ecology 2.2.1 People and Their Environment

The concept of organism–environment system defines the ecology domain in its most general sense. But if the organism studied is human beings, we have entered into a more specific ecological domain, the so-called biocultural ecology, that is, the scientific study of complex relationships between people and their environment [17, 21–23]. The term biocultural comes from the concept of biocultural diversity, which is understood as the diversity of life both in its biological dimension (organisms, species, communities, ecosystems) and in its cultural dimension (knowledge, beliefs, language, practices). These dimensions are not separated, nor do they transit parallel paths; on the contrary, they interact in many complex ways, and coevolve [24, 25]. It is relevant to highlight that the concept of coevolution is resonant with the idea about the organism–environment system evolution. In fact, the organism and its environment (the survival unit) “do not cross at infinity,” they go “together.” The integrating vision based on the relations between people and their environment (the environment that we

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people identify as our, through our interactions), both natural and cultural, would allow to overcome the old dichotomy between nature and culture as dissociated scenarios. However, this non-dissociation that supports the theory does not always translate into the practice sphere. In the scientific domain, we often fall into the “temptation” of the simplification and we declare into theory that we accept the non-dissociation, but in practice we analyze natural and cultural variables separately. This contradiction (more frequent than it seems), which is relatively easy to understand insofar as our current way of thinking, still has deep roots in the old simplicity paradigm. As Morin said: “An illusion keeps people away from the complex thinking: believing that complexity leads to the elimination of simplicity. By the way, the complexity appears where the simplicity fails (. . .) While the simplified thinking disintegrates complexity, the complex thinking integrates as much as possible the simplifying ways of thought, but rejects their blinding and reductionists consequences” [4]. 2.2.2

Nature and Culture

If complex thinking integrates concepts that the simplified thinking dissociates (e.g., through system notion), we have to say that if biocultural ecology is a particular kind of ecology, the systemic principles of ecology also must be applied to biocultural ecology. In this frame, we must assume that people (ourselves) are organisms that live in our environment (not an environment), and as such, we are systems. As a reflection, Morin warns us: “Since Darwin we admit that we are sons of primates, but not that we ourselves are primates. We are convinced that once we descended from the tropical genealogical tree of which our ancestors are part of, and since then we have moved away from it forever, and we have built, regardless of nature an independent kingdom of culture” [26]. This simplified thought separates us from our own biology and our environment, and it immerses ourselves into the antinomy “nature versus culture.” The argument is dangerous: if nature is alien to us, we are enabled to subdue it, conquer it, to appropriate it. Against this way of thinking, Morin argues: “Man is a cultural being by nature, because he is a natural being by culture” [26]. For people, the positions that tend to dissociate nature and culture, as well as those that tend to integrate them, they have meaning in the context of our own particular culture. “Man is a cultural being by nature” because the culture is our human nature. Besides, “man is a natural being by culture” because we conceptualize our nature from our cultural background [4, 26]. Regarding nature and culture, we can start either with a concept that favors dissociation or with one that favors integration, and our explanatory models will be consistent with each starting point [17]. For the biocultural context, the dissociation between nature and culture has no meaning. The field of biocultural ecology, as noted above, supposes the broader context of ecology: if we (people) destroy our

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environment, we destroy ourselves. In this sense, we have to ask: What conceptions about “nature” and “culture” guide the strategies of environmental planners and conservationists? The idea that we can appropriate nature (as a set of available resources) is based on the nature–culture dissociation: we can appropriate something when that something is alien to ourselves. This position (that we could call against nature) opposes the other, the more romantic: “the humanity must return to nature” (against culture position). We must ask ourselves: When we have abandoned nature? This position reminds us the one mentioned by writer Michel Houellebecq: “. . . the curse of the tourist that desperately searches unspoiled places (without tourists) that his mere presence discredits, and be pushing himself to go more and more far in an increasingly useless project (...) hopeless situation, as that of man trying to escape of his own shadow” [emphasis added] [27]. In this case, an integrating approach is healthier. On this issue, it is important to reflect about our reference theoretical framework (our starting point). If we start from distinct bases, even using the same procedures, we will obtain different conclusions. Bateson said: “In fact, the problem of how to transmit our ecological reasoning to those whom we wish to influence in what seems to us to be an ecologically ‘good’ direction is itself an ecological problem. We are not outside the ecology for which we plan, we are always and inevitably a part of it” [19]. It is time to assume that we need complex reformulations for complex phenomena. Otherwise, our explanations would become reductionist [4, 28, 29]. 2.3

Ethnoecology

2.3.1 Science and Ethnoscience

The word ethnoscience appeared in 1950, in the book Outline of Cultural Materials, by George Murdock, but the first formal definition would just emerge a decade later [30]. In the 1960s, the anthropologist William Sturtevant wrote “. . . a survey and explication of a new approach in ethnography. . .” [31], called new ethnography or ethnoscience. The prefix ethno (from the Greek εθνoς, “people” or “nation”) has for Sturtevant a new meaning: “is to be understood in a special sense, it refers to the system of knowledge and cognition typical of a given culture” [31]. As Alves and Albuquerque said, it has been a new approach “. . .through which cultures were no longer seen as collections of artifacts and behaviors, but began to be considered as systems of knowledge. . .” [32] The conceptualization of knowledge as a system that gives meaning to its contents implied a step forward for the understanding of complexity in ethnoscience. The knowledge system is necessarily local, because people live in their own local environment, the one that people identify as theirs through their interactions, as discussed before. In this complex sense, environment includes other people, other kind of living systems, and the physical environment, and it should be considered

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“natural and cultural” at a time. On these bases, biocultural ecology must be considered the science that studies the relationships between people and their environment from the researcher’s perspective, whose knowledge system (it is assumed) corresponds to the scientific knowledge. Moreover, ethnoecology must be considered the ethnoscience that studies the knowledge systems of local people about their own relationships with their environment. In this definition, the term local is posed in its complex sense, based on the relationships between people and their natural–cultural environment as an explanatory core. In terms of Nazarea, it is the situated knowledge of people who participate in a net of relationships located in time and space [33]. Outside this context, the adjective local had usually been employed as a replacement to avoid other qualifiers, such as “traditional,” “indigenous,” and “native,” among others, that present significant definition problems, especially in the case of the widespread term “traditional” [32, 34]. The distinction between science and ethnoscience (e.g., “biocultural ecology” and “ethnoecology,” respectively) is based on its object of study, that is, the phenomena to be explained (“relationships” in the first case, “knowledge systems”—that emerges from those relationships—in the second). In no case does this distinction imply that the so-called ethnosciences are not sciences. In fact, the methods and techniques of ethnosciences are no different from those of ethnography, the scientific domain from which ethnoscience has emerged. In terms of the approaches, the ethnoscientific one allows for a dialogue with the non-ethnoscientific approaches within science, which would be desirable to occur more frequently. In this very scenario: “. . . a more recently accepted interpretation is that ethnoscientific procedures should be seen as scientific procedures that aim to describe and analyze the local knowledge, and occasionally to establish comparisons and articulations with that knowledge which is practiced and accepted in the academy” [32]. 2.3.2 Disciplinary Complexity

Current science is often subdivided into disciplines and subdisciplines with more and more specific objectives in relation to an increasing specialization path, what could become an excessive atomization (simplicity paradigm). However, when phenomena to be explained are complex, such as ecological or anthropological ones, it is necessary to provide explanations that avoid reductionism (complexity paradigm). Likewise, in relation to the specialization, anthropologist Marc Auge´ warns that: “[the duality] between the disciplines themselves and the terrains to which they apply (...) present a certain ambiguity, since one can ask whether it is the specific nature of the terrains that allows the specificity of the disciplines, or whether, conversely, it is the procedures that construct the terrains to which they apply” [35].

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The complexity has entered this scenario by the hand of interdisciplinarity and transdisciplinarity that try to establish exchanges between isolated disciplines. Interdisciplinarity implies that disciplines interact and obtain mutual benefits, although without losing their individuality. Transdisciplinarity implies by the way a higher level of disciplinary integration, in which the disciplines’ frontiers become diluted within a broader context [36]. Ecology, as a science of synthesis [5], is a transdisciplinary field that integrates elements from various sources, and whose contents are relevant not only for ecology but also for other sciences [17]. In this framework, what could be valid for ecology could be valid for ethnoecology too. Marques considers, for example, that ethnoecology is “. . . the transdisciplinary field of scientific research that studies the thoughts (knowledge and beliefs), feelings and behaviors that mediate the interaction between the human populations (...) and the remaining elements of the ecosystems. . .” [32, 37] The author also indicates that it is necessary to recognize ethnoecology “. . . as a field of knowledge intersection (at least an interdisciplinary field and not just one more discipline)” [emphasis added] [32, 37]. The path from interdisciplinarity to transdisciplinarity shows the increasing need for a more complex perspective. Instead, interdisciplinarity and transdisciplinarity are synonymous for other authors. This seems to be the case of Ruiz-Malle´n and others: “Ethnoecology is the interdisciplinary study—from a particularly local perspective—of the dynamic relations between human beings and the environment in which they live. . .” But at once, the same authors argue: “Ethnoecological studies hold a transdisciplinary perspective based on contributions made by natural and social sciences on different levels” [38]. For other authors, “Ethnoecology is the interdisciplinary study of the knowledge systems, practices, and beliefs of different human groups about their environment” [39–41]. Also, these consider that “transdisciplinary research” can be seen as the integration of both scientific and local knowledge systems. Angelstam and others state: “This form of research is based on the integration of multiple disciplines and the active inclusion and participation of stakeholders representing different societal sectors in the processes of problem formulation, knowledge production, and learning” [42]. In a commitment to complexity, Moraes and others add that ethnoecologists should recognize: “The importance of the interdisciplinary training and the development of a common language that allows communication between scientists of diverse disciplines, working in different contexts and cultures” [41]. Furthermore, with regard to the nature–culture complex and the local knowledge evolutionary value, they comment: “. . . the new millennium saw a turn in the way of conceiving the local knowledge systems about the environment, which became conceptualized as complex forms of adaptation to the environment, result of the coevolutionary dynamics of nature and culture” [41].

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For ethnoecologists, the phenomenon to explain is the local knowledge of the people considered as reference, the so-called observed people [32]. As we said, this knowledge refers to the relationships between local people and their natural–cultural environment, the one that the very people specify for the fact alone of living in it. The experience of the observed people in their environment is the basis from which the knowledge about their own experiences emerges. The knowledge (information, ideas, thoughts, feelings, beliefs) arises from the relationships that people experience. Once emerged, knowledge guides actions (verbal and nonverbal language, behavior patterns, practices, exchanges, selective strategies that become adaptive). In this sense, knowledge is embodied in actions [17, 43]. In turn, these actions feed-back on the knowledge that generated them, generating new knowledge that guide new actions, and thus recursively (The mechanism is a cybernetic regulation circuit based on the feedback notion, it is not a causal linear process of deterministic type.) [21, 22, 44]. Thus, the local knowledge system is a dynamic unit that changes over time in an adaptive sense, and the people–environment system evolves as a whole. In communicational terms, the relationships between people and their environment are the context in which the knowledge acquires meaning, and knowledge is the context in which actions acquire meaning. For the simplicity paradigm the observer (i.e., the researcher) is independent of the observed system (an observer absent from his own observation). In this framework, as cyberneticist Heinz von Foerster stated, the observer must meet an agreed requirement: his properties (experiences, meanings, interpretations) should not enter the description of his observations [45]. The author comments: “This attitude is clearly expressed in a style of scientific writing in which the author says: It can easily be demonstrated, or It is observed, rather than ‘I’ could easily demonstrate, or ‘You’ could observe, if you are interested (. . .) the problem of science is the illusion of being able to make affirmations with independence of the observer” [45]. For the complexity paradigm the observer is a constituent part of a system—the so-called observant system—that also includes the observed system, with which the observer interacts in different ways. The systemic principles that we apply to people in relation to their environment must apply to the observer who (such as any of us) cannot dissociate from his own environment, which includes the observed people with whom he interacts. The relationships between the observer and the observed people are the experiential context of the observer in which the knowledge emerge, and embodied in the observer actions. On the way to a complex thinking, we must assume that the researcher is in fact present, and intervenes in the research process that he himself designs and develops based on his own decisions.

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The researcher must choose the theoretical–methodological framework (which unfortunately is not always explicit) [16] because this is the context in which the proposed research has meaning. Likewise, the researcher selects the people–environment system whose knowledge he intends to explain, according to the proposed objectives. He is also present when selecting the informants or interviewees according to the criteria established by him or by other researchers that he intends to follow, when deciding on the appropriate methods and techniques suited to his purposes, and when adjusting those methods and techniques to the surveyed people particularities [46–49]. When the research process is finished, the researcher becomes visible when presenting his work results. It is relevant to highlight that in the simplicity paradigm the researcher becomes visible only when the research ends, and from the research’s beginning and during its development, the researcher believes that he is absent (invisible). This is a kind of reductionism because the invisible researcher works as a trivial machine [45], where we see both inputs and outputs without knowing what happens inside (e.g., income ¼ informants, outcome ¼ local knowledge). If we consider the researcher as a non-trivial machine (i.e., a system) [45] we know what the machine is like inside, what components it has, the relationships between the components, and finally how it works (e.g., how the local knowledge is obtained from the informants, that is, what intermediate processes take place). The way to de-trivialize the researcher’s role in his research is to make explicit the presuppositions (knowledge) that guide the procedures he uses (actions), starting with a clear definition of his theoretical–methodological framework. 2.5 The Researcher in His Research

The researcher’s presuppositions are related both to his cultural background and personal characteristics, and function as the principles that guide his explanatory models [44]. Thereby, we can have several explanations for the same phenomenon according to the researcher’s theoretical premises, or the consensual premises among the researchers in a research line. The researcher has to make explicit presuppositions that require an exercise of reflection that is not frequent in the daily research work [17]. However, the reflection on the concept of resource is a pending subject in ethnoecology, because this field aims to study the knowledge systems of local people in relation to their own relationships with their environment (as noted above). If the researcher considers natural resources as elements that environment provides people to satisfy their needs, the researcher adheres to the simplicity paradigm (although being not explicit about this matter). In this trivializing approach, the researcher considers that he is alien to the environment and the people who live in it, and presupposes that local people are alien to the same environment as well. For these people, resources would be something given, that could be obtained

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(or could be appropriated) because it is not a part of themselves. In addition, resources are considered natural, that is, provided by nature dissociated from culture of both the people studied and the researcher (cultures that are often not the same). For complexity paradigm, the concept of resource is defined by the knowledge system of the local people under study, a definition that may or may not coincide with the researcher’s definition of resource, according to his own knowledge system. These two knowledge systems (which are expected to be elucidated and compared by the researcher) depend on the cultural background and personal characteristics of each one. Therefore, it is difficult to consider how much of natural or cultural implies the concept of resource. In a non-trivializing approach, the researcher and his environment constitute a system, in relation to the system constituted by local people and their environment, people that establish what a resource is, or what is not, through their own experiences. In this context, talking about given resources has no sense. No knowledge is directly accessible, but is possible to access indirectly through the actions that the knowledge generates, like discourses and behaviors of interviewed people [16]. Actions allow the researcher to reconstruct the knowledge generated from them. Among the different techniques commonly used in ethnosciences (like free listing, participant observation, and oral history, among others) [46–49], interviews “are the main tool that researchers have to elicit information from study populations” [47]. An interview is a communicational system based on the relationships between the interviewer (researcher) and interviewees (informants), relationships that allow for diverse exchanges between the involved actors. An interview implies a conversation (in Latin, “go round together,” from cum, “with,” and versare: “go round”), in which at least two participants exchange discourses (verbal language) and behaviors (nonverbal language: gestures, postures, movements, and space use) that accompany the discourses. Together, both languages (verbal and nonverbal) reinforce the meaning of circulating mes¨ zu¨orc¸un said sages in the interview communicational context. O that: “It is obvious that a great number of people agree that nonverbal language takes up more space in communication than verbal language” [50]. This is a very relevant topic, especially for the intercultural communication to which many ethnobiologists and ethnoecologists are accustomed. “It is important to understand that every culture is unique and has its own customs, values, and characteristics. [Into nonverbal language] Misunderstandings and misinterpretations can be minimized when both sides are aware of the fact that not every behavior is appropriate or transmits the same message in every culture” [50]. Albuquerque and others comment: “. . . nonverbal language, which depending on the population studied, can be of fundamental importance for the understanding of life and the daily routine of the community. The

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misinterpretation of a simple gesture can compromise the study” [46]. However, nonverbal language is still terra incognita for many ethnoscientists. It is necessary to reflect on how this absence influences our explanations. It is reductionist to consider that the researcher copies or transfers without any kind of interpretation of what the interviewee expresses (like a medieval amanuensis monk). This only could be possible in a simplicity paradigm context that dissociates the researcher from both the interviewee (with whom he inevitably interacts) and the interview context (in which he necessarily is immersed). In the complexity paradigm perspective, an interview is the communicational context where discourses and behaviors (that allow for the knowledge reconstruction by the researcher) have meaning. In the reconstruction process of local knowledge system, the nontrivial researcher (who is present in his own research) necessarily has to make his own thinking categories explicit in order to be able to establish comparisons with those of the interviewees. In a general sense, the thinking categories of interviewers and interviewees are not equivalents, even if both belong to the same culture. The comparison requires an information exchange that allows for adjustments and readjustment (a feedback circuit) in terms of meaning. It is clearly a reflexive path (not linear but recursive). This complex situation is contrasted with that of a trivial researcher (who is absent in his own research) that considers himself separated from his environment and believes that his thinking categories are valid independently of those of the interviewees. In this framework, the researcher can award, transfer, or impose (in the worst case) his own thinking categories to the people under study. For instance, categories as “medicine” or “medicament” (according to the researcher) and “remedy” (expressed by interviewees) are not necessarily homologous, nor can they be transposed in a direct way [16, 51]. When the researcher makes his own thinking categories explicit, he avoids this interview trivialization and facilitates the reconstruction process of local knowledge.

3 3.1

Research Developed Study Area

The study area corresponds to the “Rı´o de la Plata region” that encompasses the area of influence of the Rı´o de la Plata: the lower delta of the Parana´ River and its advance front, the Martı´n Garcı´a Island, and the Rı´o de la Plata riverside from the delta to Punta Indio district in Buenos Aires province. This region includes the Buenos Aires-La Plata Metropolitan Area, the largest conurbation (in size and population) in Argentina, constituted by two contiguous urban agglomerations: the “Greater Buenos Aires” and the “Greater La Plata.” The first involves the Buenos Aires

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Autonomous City (the federal capital) and neighboring districts of Buenos Aires province. The second, further south, involves La Plata city (the provincial capital) and its neighboring districts [17, 52, 53]. This complex region contains three distinct areas: 1. Spontaneous vegetation areas, mostly riparian, as marginal forests, hydrophilic forests and shrublands, herbaceous coastal communities (denominated pajonales), and “giant bulrush” populations (called juncales), and also the forests of higher terrains on a substrate of shells parallel or subparallel to the coastline (named talares). In these areas are located several state and private protected areas. 2. Exclusively urban areas (the conurbation). 3. Peri-urban areas defined as transitional sectors between the previous areas, and also between the exclusively urban areas and peripheral rural zones (cultivated fields). Peri-urban areas have changing borders according to their historical rhythms, and include zones with development of horticultural activities (locally named La Plata horticultural belt), in commercial orchards with relatively large areas (4–10 ha) that provide fresh vegetables and fruits for conurbation inhabitants, and homegardens with small areas (0.25–0.50 ha) for family consumption, even for occasional sale in reduced scale, as a supplement to the domestic economy [54–60]. 3.2

Background

3.2.1 Immigration Flows and Pluriculturality

From the mid-nineteenth century and first half of the twentieth century, Argentina received massive waves of immigration mostly of European origin (44.9% from Italy, 31.5% from Spain, until 1940). Immigrants have decisively collaborated to build the country cultural heritage, and many current “local family traditions” have its origin in these migratory flows. Immigration from neighboring countries was more or less constant during this period, but with a major presence in border provinces. In the second half of the twentieth century, a recent and not massive immigration from neighboring countries occurred, this time directed to the Buenos Aires-La Plata Metropolitan Area. Most neighboring immigrants arrived from Paraguay and Bolivia (21.22% and 15.24% respectively, of all foreigners in 2001), and oriented themselves towards horticultural activity in the peri-urban area, as well as towards manufacturing industry, construction, and commerce in the exclusively urban areas [52, 61, 62]. By the end of twentieth century, another recent immigration to Metropolitan Area took place, corresponding to the Far Eastern countries, such as Korea, Japan, and China. The Asian immigration represented in 2001 almost 2% of all foreigners in Argentina, an exiguous value compared to 67.96% immigration from American countries and 28.22% representing that from European countries.

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However, Asian immigrants concentrated in Buenos Aires Autonomous City have a conspicuous presence, engaged in the manufacture of clothing and commerce. Japanese and Chinese immigration in the first half of twentieth century was low and they settled in the peri-urban areas, dedicated themselves to horticulture and/or floriculture. In the late twentieth century, Chinese immigrants exceeded the number of Japanese and Koreans, the groups that previously dominated [52, 63]. With regard to immigration flows to Buenos Aires-La Plata Metropolitan Area, people from other provinces of the country (the so-called internal immigrants), who settled in the conurbation searching for better life conditions and work chances, should also be considered. In this frame characterized by immigration processes, the study area constitutes a pluricultural context as in other large metropolitan areas around the world. This context implies a heterogeneous mosaic of cultural segments, each one conformed for different people who share their own worldviews and traditions, and who interact to a greater or lesser degree with people belonging to other cultural segments. It is a dynamic system that changes according to the rhythm of intercultural interactions. By its presence alone, both the external and internal immigrant segments increase the system complexity of the study area. Pluriculturality can be defined as the coexistence of different cultures in a geographical scenario which live together through very diverse sort of exchanges. On the contrary, multiculturality seems to be considered as a previous step where different cultures coexist but exchanges are not enough to “live together.” As an overcoming stage, interculturality is understood as a necessary goal pointing to the recognition and understanding of the existence of other cultures, as well as respect, communication, exchange, and mutual learning [64]. It is important to highlight that in a culturally heterogeneous context, different cultural segments can present diverse exchange levels, so that some segments can display stronger exchanges than that displayed by others segments of the same set. Also, exchanges between segments do not necessarily start at the same time, or develop in the same way. These differences are expected in regard to a pluricultural system. 3.2.2 Environmental Changes

The high current biocultural diversity of the study area is the result of its secular history of environmental changes, as shown by the data obtained in research carried out in exclusive urban, peri-urban, and spontaneous vegetation areas [53, 55, 64]. In a general sense, environmental changes refer to the identification of differences (both natural and cultural) in a temporal axis that allow to describe two environmental situations, previous and subsequent. Change magnitude can vary from small differences, perhaps not very visible, to catastrophic events, according to the valorization realized by both the researcher and local people. Most of the changes identified

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are local, and some correspond to weather conditions linked to global climate change. In the framework of local biocultural diversity, the peri-urban sector presents the most visible consequences of the environmental changes upon local people’s lives, due mainly to its characteristic mobile limits, as has been particularly evident in previous studies on local homegardens and commercial orchards [54–57]. The increasing advance of the urbanization is a continuous process in the study area, though the territorial extension of the peri-urban sector in relation to the local spontaneous vegetation areas responded to “expansion–contraction pulses,” at least in the last century. This affirmation is based on the available historical and geographical data, and on the application of ethnoscientific techniques that aim to valorize the narratives of local inhabitants about environmental changes as a methodological tool [53, 65, 66]. Towards the end of the nineteenth century, in different zones of the riverside of the Rı´o de la Plata, the lands dedicated to fruit-horticultural activity were expanded, hand in hand with European immigration, with the consequent contraction of the spontaneous vegetation areas. During this time, immigrants introduced Vitis labrusca L. (Vitaceae), and started the production of the so-called vino de la costa (“coastal wine”), because the vineyards were located near riverside (a product that is currently considered “traditional” for the area) [55, 66]. On the contrary, in the first half of twentieth century, industrial development and frequent floods of the Rı´o de la Plata conditioned many inhabitants engaged in horticulture to settle in the exclusively urban sectors (which expanded along with increasing industrialization), which led to the abandonment of the horticultural lands, and the contraction of these spaces was accompanied by a conspicuous expansion of the spontaneous vegetation areas (whose floristic composition changed with the entry of cultivated species that had become naturalized, constituting a new system different from the original one). Now, an incipient recovery of the horticultural activities, and certain expansion of vineyards encouraged by local cooperatives, with the resultant contraction of spontaneous vegetation areas are underway [65]. These “expansion–contraction pulses” of the areas, each in relation to one another, is a characteristic of local peri-urban biocultural landscape. In this way, the pulses constitute the context where environmental changes (which result from the emergence of a set of both natural and cultural variables) have meaning, and define the evolution of a local biocultural system, which adjusts to the circumstances [53]. 3.3

Local Actors

The cases presented here correspond to the peri-urban areas of the southern sector of Rı´o de la Plata region, in Buenos Aires province. These cases involve three kinds of local actors selected for the ethnoecological research because their specific activities and daily lives were influenced, both directly and indirectly, by different

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environmental changes over the last century: (1) horticulturists (locally named quinteros) of homegardens of Ensenada and Berisso districts coasts (Greater La Plata), (2) woodcutters (locally known as len ˜ ateros) of Magdalena and Punta Indio districts in implanted forests and local talares (further south Greater La Plata), and (3) giant bulrush extractors (locally called junqueros) of Magdalena district riverside. The research design, for all the cases, has been based on reconstruction of the local knowledge system related to the identification and valorization of environmental changes, that happened mainly over the second half of the twentieth century, and in some cases from the beginning of that century, when informants recalled situations narrated as part of family histories [53]. In order to access the local knowledge system, different locations in the study area were selected, where both open and semi-structured interviews were conducted [47], which made possible a major flexibility in conversations between the interviewer and the interviewee, and to pay more attention to the nonverbal language that accompanies and reinforces the verbal language. In most cases, the interview resulted in the analysis of the interviewees’ narratives, including the oral history technique [49, 67]. According to Ruth Lane, a pioneer in the study of narratives about environmental changes: “Local people accumulate knowledge (...) from their own experiences and from those of prior generations, but processes of memory are tied to life experience and it is necessity highly selective” [68]. The narratives allow to incorporate the appreciation of environmental changes from the perspective of local informants, and thus useful to rethink the conservation from an integrating biocultural perspective [65]. In Lane’s words: “By recording the local people perspectives and relating them to scientific understandings of the impact of land use change, local knowledge and scientific knowledge can be brought together” [68]. In the case of the horticulturists, the initial ethnoecological studies were oriented to horticultural practices and the management of local agrobiodiversity [53–57]. During these studies, it became evident in the interviews that different environmental variables (both natural and cultural) were interpreted as change situations by the informants with an impact on their own activities. On this basis, it was decided to reorient the interviews towards the identification and valorization of the local environmental changes. Studies about local agrobiodiversity were carried out both in homegardens and in commercial orchards [56, 57]. The study of local environmental changes was restricted to riverside homegardens where floods are a very relevant factor: 25 interviews in homegardens of three different localities were developed [53, 54]. In the case of both len˜ateros and junqueros, the studies developed were specific: 24 interviews in five different localities were realized

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[69]. Informed consent of the interviewees, comprising people of both sexes between 25 and 75 years old, was requested. All of them were selected using the snowball sampling technique [46] and were considered key informants due to their recognized experience in the activity they are currently doing or have done in the past.

4 4.1

Studied Cases “Quinteros”

Quinteros are the local actors involved in horticultural activity in homegardens, often locally so-called quintas. The homegardens local history in Berisso and Ensenada districts is immersed in the “expansion–contraction pulses” context commented above. Local environmental changes have meaning in that context. The “first pulse” recorded began at the end of nineteenth century with the arrival of European immigrants that expanded the cultivated lands to the detriment of the spontaneous vegetation areas. Homegardens with diverse vegetables, some fruit trees, and also vineyards, proliferated near the Rio de la Plata shores in Ensenada and Berisso districts. The “second pulse” at first half of twentieth century, was characterized by industrial development and frequent river floods implied abandonment and reduction of the horticultural terrains, and expansion of the spontaneous vegetation sectors. The “third pulse” corresponded to current times with a limited activity in homegardens and a rise in winegrowing activities with development of the aforementioned cooperatives. The recovery of local horticultural practices depends on the efforts of the quinteros that allow for their daily sustenance and the direct sale of some handmade products they produce. In this context, field works focused on the horticultural activities and the environmental changes identified and valued in the interviewees’ narratives. The riversides are dynamic systems, and those of the Rio de la Plata are not an exception, with frequent floods of different magnitudes that can affect houses and homegardens along the coasts. Homegardens also are dynamic systems that can change its physiognomy, microclimatic conditions, and association of cultivated species that can change in time according to the species selection criteria of different family members: some species may be no longer cultivated, other new species may be introduced, and neglected species may be recultivated (selective criteria may be adaptive for the system as a whole). Likewise, homegardens can be abandoned for some time (e.g., after a flood) and then can be reused. Isla Paulino (Berisso district) is a locality that illustrates the impact of great floods on the lives of local horticulturists. According to historical records, in 1915 a strong flood destroyed the precarious houses (ranchos) of that time, which were replaced by houses of wood and zinc. The local population was able to recover despite the destruction. A second flood of large proportion took place in 1940:

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the water exceeded the level of 4 m and devastated the homegardens and vineyards, houses, and infrastructure for tourism of relative importance. This time, reconstruction was more difficult. This last great flood is considered “catastrophic” in the quinteros narratives, who suffered the effects of the phenomenon, directly or indirectly through their familiars. The Isla Paulino depopulation was very conspicuous in the first half of the twentieth century, both due to the effects of the mentioned flood, and as a result of the increasing industrialization and urbanization. In its apogee, before the alluded changes, more than 70 families related to horticulture, fishing, and tourism lived on the island. Currently, only seven families live permanently on the island, and another five have conserved their houses for weekends. Unlike other nearby localities, Isla Paulino, with about 1300 ha, despite being located 10 km from La Plata city, is today in a precarious situation: there are no electricity, potable water, and gas services, and it has only a public telephone. There is no school, and a single health post provides a nursing service during summer. Fluvial transport presents restricted schedules and sometimes it is interrupted [53, 54]. The floods are identified and negatively valuated in the quinteros narratives as environmental changes. The same happens with the “industrialization–urbanization” complex that conditioned the abandonment that is still observed in Isla Paulino and neighboring places. In the narratives, no differences are expressed between natural and cultural environmental changes for the horticulturist’s everyday experiences (categories that correspond to the researcher). The researcher can be tempted to consider floods as natural phenomena and urbanization as a cultural one, but this is a reductionist way of thinking. Even if we consider that flood is a natural phenomenon in its origin, the moment it intervenes people’s lives, as we discussed above, it becomes also a cultural phenomenon. Urbanization (as a result of industrialization progress) could be understood as a cultural phenomenon, but urbanization intervenes people’s lives, and becomes natural to people. We must remember what Morin said: “Man is a cultural being by nature, because he is a natural being by culture” [26]. 4.2

“Len˜ateros”

Len˜ateros are the local actors involved in firewood extraction, consumption, and sale. The main use identified by interviewees is heating homes during the winter (salamanders and fireplaces), and to a lesser extent cooking (roasting, wood oven, and clay oven). Also, firewood is highly valued by brick factories of the studied area. All the interviewees indicated that the utilization of firewood complements natural or packaged gas for heating rooms and cooking. The extraction of firewood is carried out in local forests, both native (talares) and planted (mainly eucalyptus species). Talares are forests developed on a shell substrate in higher terrains that represent the ancient coastline. Dominant species is

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the “tala,” Celtis ehrenbergiana (Klotzch) Liebm. (Celtidaceae), accompanied by other native trees species, such as “coronillo,” Scutia buxifolia Reissek (Rhamnaceae), “sombra de toro,” Jodina rhombifolia (Hook. & Arn.) Reissek (Santalaceae), and “sauco,” Sambucus australis Cham. & Schltdl. (Caprifoliaceae). In the area naturalized exotic species are also found, like the “laurel,” Laurus nobilis L. (Lauraceae), “morera,” Morus alba L. (Moraceae), “acacia negra,” Gleditsia triacanthos L. (Fabaceae), and “ligustro,” Ligustrum lucidum W.T. Aiton (Oleaceae). The talares have seen a widespread destruction as a result of non-sustainable practices such as uncontrolled firewood extraction. The historical references point to an intensive early use of “tala” timber from the sixteenth century, mainly for fuel and construction of houses and fences [69]. To protect these forests in 1984 the Biosphere Reserve “Parque Costero del Sur” (“Coastal Park of the South”) was created in Magdalena and Punta Indio districts, which is a valuable biocultural heritage for the area. It consists of a 5-km wide and 70-km long fringe on the south riverside of the Rı´o de la Plata, with an area of 25,000 ha, comprising mainly private properties. It is a partial protection reserve of the International Union for the Conservation of Nature (IUCN), and allows for the sustainable use of ecosystems. Nevertheless, a municipal regulation prohibits the total use of some native tree species. Currently, activities such as livestock husbandry and shell extraction in the reserve’s private lands affect the integrity of the talares. The season for firewood collection is mainly winter. Sellers usually extract wood earlier to have a supply of dry firewood. Interviewees comment that collection of dry branches is carried out by people of both sexes and different ages, from children to elderly, from the surroundings of houses or more distant places. The municipal pruning waste and wood from clearing forests for construction are also taken advantage of. Extractions are only carried out by adult men and include collection of fallen trees, pruning in height, and cutting down planted forests. The collected firewood is transported afoot or by trucks and vans. Chainsaws, endless saws, and axes are utilized for cutting. The branches are often cut to get kindling. Most of the interviewees prefer the timber obtained from “talas” and “coronillos,” both valued as “good firewood” because of the heat generated and its enduring embers (according to the available literature the timber from these forests are dense, hard, and heavy). However, interviewees comply with the local prohibition to extract inside the Biosphere Reserve. Consequently, they use eucalyptus timber as an alternative, stating “it makes good flame and it is easier to obtain,” and because implanted eucalyptus species forests abound in the area [69]. With respect to the identification and valorization of local environmental changes, according to len ˜ ateros narratives it is not related to the lack of the resource but to the prohibition of

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extractions of native trees within the Biosphere Reserve. This is more evident in the interviewees who live within the reserve in Punta Indio district. Firewood cannot be extracted from “tala” and “coronillo,” but it can be extracted from naturalized species like “acacia negra,” “laurel,” and “ligustro,” as part of the talares conservation strategies. Outside the reserve, planted forests have extended which per se constitutes an environmental change although one of gradual effect. The creation of the reserve in the 1980s that modified the valorization of the talares is also an environmental change. Before the constitution of the protected area the talares were exploited without any control, even to facilitate the local shell extraction. In his narrative, an interviewee comments, appealing to his own family history: “my father lived his whole life fighting against the tala. That was the conception that we previously had about the tala. It had to be eliminated, it was like Indians” [69]. From elimination to current conservation there was a learning about the valorization of the talares (a contextual change that has generated a new meaning), embodied in the new timber resource selection. 4.3

“Junqueros”

Junqueros are the local actors involved in the extraction and use of “giant bulrush” ( junco), Schoenoplectus californicus (C.A. Mey.) Soja´k (Cyperaceae), and its related species. These actors are mainly extractors (cutters) and sometimes sellers and artisans, and most of them supplement their domestic economy with other jobs such as fishing or trading. The extraction is carried out in spontaneous populations ( juncales) on the Rı´o de la Plata shore. The harvest is done from late winter or early spring until late summer or early fall, when plants reach high enough for their use (1.60 m) and weather conditions allow for drying. In winter they prefer not to cut, to avoid the cold and because, as they say: “if it is cut in that season plants do not recover.” Nevertheless, some interviewees expressed that in the “good times” (e.g., the 1980s) they extract continuously all the year. The rushes are cut with sickles mainly made by hand, using scythes and knives as a base material. The cut is done at the emerged substrate level, to avoid accidents. The freshly cut rushes are piled and transported to houses, where they are “cleaned” by shaking them so that the dry and shorter ones fall away. During the process, the rush is considered “green” and some junqueros sell it in that state. However, others dry them in the sun, so that rushes become clear, and thus increase its value. The interviewees identify in their narratives different kinds of rushes according to their uses: (1) the thickest to tie tomato, chili, and eggplant plants to respective canes in commercial orchards, or for making rustic handicrafts such as mats and baskets, (2) the thinnest to tie garlic and onion plants in orchards, and also to make more delicate artisan weaves. With respect to identification and valorization of local environmental changes by the junqueros, their narratives coincide with two

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facts that they consider very negative for the development of their activities in the 1990s. “Good times” of the 1980s became “bad times” in the next decade. In the first place, most of junqueros production was sold to producers of the horticultural belt, to tie plants to canes in open-air crops. The definitive adoption of cultivation under cover (greenhouses) in the 1990s, a system that pushed its major productivity inside these controlled environments, involved the replacement of rushes by plastic supplies (polyethylene threads), which implied an abrupt decline in the demand: the beginning of the decline of the junqueros activity. Secondly, a “catastrophic” event occurred at the end of 1999: Magdalena district coast was affected due to an oil spill, the product of a collision between an oil tanker that entered a channel of the Rı´o de la Plata and a container ship heading in the opposite direction. As a consequence of the impact, 4600 m3 of crude oil was spilled. The oil slick affected 23 km of riparian wetlands, including the juncales. Once the spill reached the Magdalena district riverside, different local actors were seriously affected: junqueros, fishermen, camping sites, and supplies stores’ owners, among others. All interviewees attribute the decrease of the juncales to the oil spill, due to the death of its rhizomes: the oil “burned” the rushes, and some plants that had not died became “spotted,” lowering their quality. Some narratives acknowledge that juncales decrease is linked with the greater erosion on certain coastal areas (that impedes the sedimentation necessary for the rushes’ growth). A few narratives connect the juncales decrease with cattle-intensive breeding on the coasts, especially in winter when pastures are scarce. The junqueros activities in the area studied have not recovered yet, limited only to obtain raw material for handicraft production [69].

5

Final Remarks In this chapter we try to delineate a theoretical–methodological framework from the perspective of the complexity paradigm, following the pathway outlined by Gregory Bateson about the need to make explicit our presuppositions in our work as scientists. The theoretical–methodological framework is the context in which the research results acquire meaning. In this sense, we discuss presuppositions about ecology, biocultural ecology, and ethnoecology, the relationships between organisms and its environment and the people and their environment (and what the people think about it), about the dissociation between nature and culture, the links between knowledge and actions, as well as the place of the researcher in his own research, and the role of his own thinking categories in the research process. In this framework, we apply the complex thinking to different cases related to how people under study identify and value the

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so-called environmental changes, a relevant topic for current ethnoecology in pluricultural contexts of urban areas. Along this path, the ultimate aim is to put into practice our reflection capacity. In this respect, we agree with Humberto Maturana: “How far should the reflection go? Every human being reflects a condition of humanity. The question alludes to how many of the foundations of our doing and our world we dare to judge in the reflection. My answer is: everything” [70]. We must rethink our thinking as a contribution to a complex ethnoecology.

Acknowledgments The authors acknowledge Ulysses P. Albuquerque for his support and generosity, Alejandro C. Pizzoni for critically reading and making opportune comments on the manuscript, the interviewees that contributed disinterestedly with their knowledge during the research development, and the LEBA staff who collaborated in the field work. Universidad Nacional de La Plata (UNLP), Fondo para la Investigacio´n Cientı´fica y Tecnolo´gica (FONCyT), and Consejo Nacional de Investigaciones Cientı´ficas y Te´cnicas (CONICET), Argentina, provided financial support for the studies carried out. References 1. Bateson G (1979) Mind and nature: a necessary unity. Dutton, New York 2. Margalef R (1986) Ecologı´a. Omega, Barcelona 3. Margalef R (1991) Teorı´a de los sistemas ecolo´gicos. Universitat de Barcelona, Barcelona 4. Morin E (1994) Introduccio´n al pensamiento complejo. Gedisa, Barcelona 5. Margalef R (1981) Ecologı´a. Planeta, Barcelona 6. von BL (1968) Teorı´a general de los sistemas. FCE, Mexico City 7. Odum E (1972) Ecologı´a. Interamericana, Me´xico 8. Tansley A (1935) The use and abuse of vegetation concepts and terms. Ecology 16:284–307 9. Maturana H, Varela F (1972) De ma´quinas y seres vivos. Editorial Universitaria, Santiago de Chile 10. Margalef R (1980) La biosfera: entre la termodina´mica y el juego. Omega, Barcelona 11. Flos J (1984) Ecologı´a entre la magia y el to´pico. Omega, Barcelona 12. Flos J (2005) El concepto de informacio´n en la ecologı´a margalefiana. Ecosistemas 14(1):7–17

13. Prigogine I (1972) La thermodynamique de la vie. La Recherche 3(24):547–562 14. Prigogine I, Stengers I (1990) La nueva alianza, la metamorfosis de la ciencia. Alianza Editorial, Madrid 15. Morin E (1983) El Me´todo II. La vida de la Vida. Ca´tedra, Madrid 16. Hurrell JA, Albuquerque UP (2012) Is ethnobotany an ecological science? Steps towards a complex ethnobotany. Ethnobiol Conserv 1:4. https://doi.org/10.15451/ec2012-8-1.4-1-16 17. Hurrell JA (2014) Urban ethnobotany in Argentina: theoretical advances and methodological strategies. Ethnobiol Conserv 3:2. https://doi. org/10.15451/ec2014-6-3.3-1-11 18. Thienemann AF (1956) Leben und Umwelt. Rowohlt, Hamburg 19. Bateson G (1987) Steps to an ecology of mind. Jason Aronson, Northval 20. Margalef R (1986) Variaciones sobre el tema de la seleccio´n natural. Exploracio´n, seleccio´n y decisio´n en sistemas complejos de baja energı´a. In: Wagensberg J (ed) Proceso al azar. Tusquets, Barcelona, pp 121–140 21. Hurrell JA (1987) Las posibilidades de la etnobota´nica y un nuevo enfoque a partir de la

Ethnoecology in Pluricultural Contexts: Theoretical and Methodological. . . ecologı´a y su propuesta ciberne´tica. Rev Espa˜ ola Antropol Am 17:235–258 n 22. Hurrell JA (1990) Interpretacio´n de relaciones en ecologı´a, a partir de la nocio´n de sistema en Santa Victoria e Iruya (Salta, Argentina). Tesis doctoral 548, Fac Ci Nat y Museo, Universidad Nacional de La Plata 23. Albuquerque UP, Hurrell JA (2010) Ethnobotany: one concept and many interpretations. In: Albuquerque UP, Hanazaki N (eds) Recent developments and case studies in ethnobotany. SBEE/NUPEEA, Recife, pp 87–99 24. Maffi L (2001) Introduction. On the interdependence of biological and cultural diversity. In: Maffi L (ed) On biocultural diversity. Linking language, knowledge, and the environment. Smithsonian, Washington, pp 1–50 25. Maffi L (2005) Linguistic, cultural, and biological diversity. Annu Rev Anthropol 29:599–617 26. Morin E (1983) El paradigma perdido. Kairo´s, Barcelona 27. Houellebecq M (2002) Plataforma. Anagrama, Barcelona 28. Morin E (1984) Ciencia con consciencia. Anthropos, Barcelona 29. Morin E (1985) O problema epistemolo´gico ˜ es Europa-Ame´rda complexidade. Publicac¸o ica, Lisboa 30. Beaucage P (2000) La etnociencia, su desarrollo y sus problemas actuales. Cronos 3 (1):47–92 31. Sturtevant WC (1964) Studies in ethnoscience. In: Romney AK, D’Andrade RG (eds.) Transcultural studies in cognitione. Am Anthropol 66(3):99–131 32. Alves AGC, Albuquerque UP (2010) “Ethno what?” Terminological problems in ethnoscience with a special emphasis on the Brazilian context. In: Albuquerque UP, Hanazaki N (eds) Recent developments and case studies in ethnobotany. SBEE/NUPEEA, Recife, pp 67–79 33. Nazarea VD (1999) A view from a point: ethnoecology as situated knowledge. In: Nazarea VD (ed) Ethnoecology: situated knowledge/ located lives. University of Arizona Press, Tuscon, AZ, pp 3–20 34. McClatchey WC (2005) Exorcizing misleading terms from ethnobotany. Ethnobot Res Appl 3:1–4 35. Auge´ M (2006) Hacia una antropologı´a de los mundos contempora´neos. Gedisa, Barcelona 36. Caravantes-Garcı´a CM (1980) Sugerencias para una metodologı´a de la interdisciplinarie˜ ol Antropol (Barcedad. Acta I Congr Espan lona) 1:425–442

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Chapter 13 Ethnobotany and Ethnoecology Applied to Historical Ecology Mariana Franco Cassino, Rubana Palhares Alves, Carolina Levis, Jennifer Watling, Andre´ Braga Junqueira, Myrtle P. Shock, Maria Julia Ferreira, Victor Lery Caetano Andrade, Laura P. Furquim, Sara Deambrozi Coelho, Eduardo Kazuo Tamanaha, Eduardo Go´es Neves, and Charles R. Clement Abstract In this chapter, the reader will find guidelines and suggestions for the application of ethnobotanical and ethnoecological methods in archaeological sites and their surroundings, aiming to establish a closer dialogue between ethnobiology and archaeology for understanding the human history of past and present landscapes. The goal of such methodological proposals is to document the knowledge and practices of human populations that live on and around archaeological sites concerning the vegetation of these areas. The methods presented here can shed light on specific questions about the relationships between past human populations and their plant resources (e.g., practices of use, management, and domestication), helping to understand how people transformed the landscape and how the legacies of such relationships are visible in the present. This chapter is collectively written by ethnobiologists, botanists, ecologists, and archaeologists from several institutions working in the Amazon basin. Thus, examples presented here come mainly from research conducted in this region. Key words Archaeological sites, Useful plants, Domesticated landscapes, Landscape transformations

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Introduction Long-term human activities have modified the environment during much of the Holocene, if not earlier [1]. Through management practices, people have transformed the landscapes in which they live into more productive and secure cultural niches for human dwelling, foraging, and food production [2–4]. The emergence of food production systems, starting around 10,000 years ago, caused enduring impacts on species distributions with the promotion and expansion of populations of domesticated animals and plants [5].

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_13, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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Along with modifications in species compositions and distributions, humans have increased the complexity and heterogeneity of landscapes through changes in soil properties and hydrology [3, 6]. Thus, contemporary landscapes can be considered the result of complex interactions of multiple factors over time, including human actions and natural events [7]. Historical ecology is an interdisciplinary research program that seeks to elucidate the histories of interrelationships between human populations and their landscapes [8–11], attempting to understand the nature, the intensity, the spatial extent, and the persistence of human landscape transformations [12, 13]. Ethnobotany and ethnoecology offer methods that are useful for researching the historical ecology of landscapes. This chapter outlines these well-known methods and shows how they interact with other disciplines involved in historical ecology research. Understanding the human history of a place is necessary for understanding the landscapes of the present [6, 14]. Archaeological sites are the places where we find material evidence of past human occupations, whether from decades or millennia ago. A great variety of archaeological sites and remains exist, from many geographical regions, periods, and peoples, that result in different contexts, use histories, and, ultimately, modern landscapes (Fig. 1). Examples of archaeological sites include settlements with permanent housing, temporary campsites, and agricultural, ceremonial, and tool-

Fig. 1 The Monte Castelo shell mound archaeological site near the Guapore´ River is predominantly formed from freshwater snail shells and other materials intentionally deposited by humans since the early Holocene. This created an elevated area that is always above the level of the inundations in the seasonally flooded savannas in Rondonia State, Brazil, and supports a distinctive vegetation, including forest taxa. Credit: Myrtle P. Shock, UFOPA

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production areas. Archaeological remains include fragments of ceramic vessels, stone artifacts, glass and metal objects, animal and human bones, plant remains, as well as features such as hearths, burials, anthropogenic soils, and postholes. Archaeology, through the analysis of different material cultural remains, reconstructs the history of human populations, and includes archaeobotany, also known as paleoethnobotany, that focuses on the relationships between people and plants through the analysis of botanical remains [15]. Archaeobotanical data can provide insights into diet, subsistence strategies, and resource management practices [16–19]. A closely associated discipline, paleoecology, seeks to understand the environmental conditions that persisted during a certain period. The identification of plant remains in paleoecological records can offer insights into how and how strongly humans modified vegetation on both local and regional scales, and when combined with archaeology contributes for a thorough understanding of the historical ecology of the landscapes [20]. Since modern landscapes are the result of cultural activities in the past [6], present-day plant communities may contain information that helps to tell stories of how humans occupied and constructed their niches [21], providing a complement to archaeological remains as a tool to understand cultural changes [22], that is, they can be considered ecofacts [23, 24]. Plants are an important part of cultural niche construction of all peoples, as numerous plant species with different uses are fundamental elements to supply the material and spiritual needs of day-to-day life of all human communities [25–27]. Through intimate, long-term interaction with the landscape, people developed detailed knowledge about how to manage and transform their environment [4]. People who live near and on archaeological sites today use and appropriate the legacies of past populations, such as the anthropogenic forests and soils, and are able to identify and differentiate forest communities and resources [26, 28] and classify them according to their uses [29]. This knowledge is critical to the histories about how niche construction transforms environments into landscapes. The different cultural dimensions of people–plant interactions and the metaphorical representations embedded in this knowledge and practices can be revealed through the methodological framework developed by ethnobiology and ethnoecology [30]. In this chapter, we propose guidelines for the application of ethnobotanical and ethnoecological methods for studies of plant communities associated with archaeological sites, in order to identify legacies of plant and landscape use and management, and to investigate the ways in which local people continue to incorporate and perpetuate these legacies. Following a presentation about archaeological sites as study locations, this chapter focuses on specific methods that can be used to

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approach questions that stem from historical ecology. Most research projects combine more than one method, as they are complementary in nature.

2 Archaeological Sites as Nexuses for Investigating the History of Human–Plant Interactions The reoccupation of archaeological sites is a common phenomenon [31], as cultural, social, and symbolic motivations can lead groups of people to recognize cultural landscapes as places to settle [32]. The continuities between the scenarios of past and present populations are not always clear, especially in places with violent colonization histories. Traditionally, such continuities are sought in social structures, in settlement and demographic patterns [31]. However, the notion of continuity can also be understood as the particular ways of relating with the environment, culturally and historically constructed by peoples of the past, and constantly re-signified by current populations, whether or not they have genetic or social relationships with the prior inhabitants [31]. An archaeological site and its surroundings encompass areas with different functionalities: habitation areas, plazas, activity areas, homegardens, swiddens, trails, ritual areas, etc. Different functionalities are associated with different ways to use and manage the land and resources, and therefore can lead to different visible legacies on the landscape. When a place is reoccupied, these functionalities can be different and they are also likely to change with time (see Fig. 2 for a hypothetical superposition of past and present occupations). As a result, a complex vegetation palimpsest emerges, composed of a mosaic of useful plants introduced in different spaces and in different periods of time. Ethnobiological methods, designed for accessing the current relationships between people and their landscapes, can help disentangle the different dimensions involved in the construction of such a landscape. We recommend that, whenever possible, the collection of ethnobotanical and ethnoecological data be done in combination with archaeological research. Assessing the relationship between past activity areas and modern plant species distributions is important for understanding long-term people–plant relationships. For instance, in Amazonian archaeological sites, anthropogenic soils (such as Amazonian Dark Earths, or Terra Preta de I´ndio) (Fig. 3) are often associated with areas inhabited by people in the past, and as one moves away from the habitation areas, the degree of soil modification tends to gradually decrease due to other types of past land use [34, 35]. Surrounding areas, at greater distance, with barely or unaltered soils are interpreted as having been used with lower intensity (e.g., for hunting and plant gathering).

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Fig. 2 This hypothetical scheme shows a current riverside community (above) that has reoccupied a place previously occupied by a pre-Columbian indigenous population (below). The representation of the past occupation is inspired by the Xinguano villages depicted in Heckenberger [33]. Designed by Flavio Cassino

Recognizing the heterogeneity within and between archaeological sites is important for more accurate interpretation of present vegetation patterns in previously occupied areas.

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Selection of Collaborators The methods of ethnobiology, when applied to historical ecology studies, usually seek to understand the legacies of long-lasting histories of cultural niche construction in current landscapes. Thus, people who have lived for a long time in the study area (e.g., former residents, communities founders), are usually appropriate collaborators in surveys. The collaborators can be selected through the snowball technique [36]. According to the objectives of the researcher, other requirements besides long permanence in the region should be considered. For example, when studying the legacies of past populations on forest composition around archeological sites, extractivists, hunters, and others who frequently make use of forest resources are recommended potential collaborators. When looking for the influence of past occupations in homegardens, women who tend the gardens are the preferred collaborators [37]. For studies about vegetation diversity of fallows on anthropogenic soils, farmers who are more knowledgeable about soil types and old cultivated areas will be the most appropriate contributors (e.g., [38]). Depending on the research question, a systematic or random selection of collaborators may be required;

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Fig. 3 Profile of an Amazonian Dark Earth (Terra Preta de I´ndio) at the Hatahara site, Iranduba, Amazonas, Brazil. Note the dark brown color and numerous ceramic fragments. Credit: Val Moraes, Central Amazon Project, USP

for example, to access the general knowledge on soil–plant interactions, including—but not limited to—archaeological sites (e.g., [38]). For further general recommendations on the criteria to choose survey collaborators, see Albuquerque et al. [39].

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Free Listing of Landscape Categories and Useful Plants Free listing is an interview strategy designed to provide an inventory of a certain cultural domain, that may also contribute to identify the cultural importance and salience of items, to identify

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local specialists, and to analyze intracultural variation [40]. Free listing is a tool that has advantages and limitations, and should always be executed following the good practices recommended by Albuquerque et al. [41], Bale´e and Nolan [42], and Quinlan [40]. The employment of free lists on and around archaeological sites is a valuable approach for understanding local perceptions about different landscape domains, areas used in the present and past, and the different degrees of human influence across the landscape. As an example, the Ka’apor people of eastern Amazonia recognize a series of landscape domains, including high forests, fallow forests, swamp forests, riverine forests, old and new gardens, and patches with specific dominant tree species [42]. The Waja˜pi people, of northeastern Amazonia, recognize different types of fallow forests according to their successional stages and their species composition (closed fallow, new fallow, old fallow, and clean fallow) [43]. The Yanomami people of northern Amazonia recognize at least 25 types of vegetation in their territory, including different successional stages of swiddens and fallows, forests with different degrees of human impact and different structures and composition [44]. Free lists can also be used to help elicit the plant composition of different landscape domains [42]. Bale´e and Nolan [42] asked Ka’apor collaborators to list trees that occur in fallow forests (which would be vegetation domains with cultural history) and trees that occur in high forests. The same logic can be applied to elicit plant species occurring in archaeological areas, such as species that occur on Amazonian Dark Earths [45]. Free lists of plants that occur in different areas within archaeological sites may also provide useful information that can be fed into predictive models of the occurrence of archaeological sites. Data on the distribution of archaeological sites, especially in forested areas, is still scarce and highly heterogeneous [13]. In the Brazilian state of Acre, for example, hundreds of geometric earthworks, known as geoglyphs, were discovered only after deforestation in the last few decades [46]. In recent years, with the advances of GIS technologies and the creation of extensive databases, predictive models of archaeological sites location have been developed, helping to optimize surveys to locate new sites [47–50]. In the Amazon basin, numerous useful palms and trees (e.g., Elaeis oleifera and Bertholletia excelsa) are indicators of cultural landscapes [45, 51]. Forest patches enriched with these and other useful species are considered “cultural or anthropogenic forests,” because they are believed to be the result of past human management [24, 51] (Fig. 4). Clement et al. [52] suggested four categories of plant species that are indicators of anthropogenic soils in Amazonia: (a) species whose distribution is limited to anthropogenic soils; (b) out-of-range indicators; (c) out-of-typical-habitat indicators; (d) species with greater density, dominance, or frequency in anthropogenic soils rather than elsewhere.

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Fig. 4 A Brazil nut (Bertholletia excelsa) stand along the edge of Jutica Lake, Tefe´, Amazonas, Brazil. Most Brazil nut stands across Amazonia are anthropogenic in origin [53]. Credit: Eduardo K. Tamanaha, IDSM

Thus, free listings may be used to identify plant indicators of archaeological sites. Junqueira et al. [54] interviewed smallholder farmers about species that occur in fallows on ADE and in fallows on other types of soil. Using the lists produced, the authors applied an indicator species analysis [55], commonly used in ecological research, to identify which species can be considered indicator species of anthropogenic soils, without explicitly asking local residents. When applied across a wider area by integrated research groups, information about the occurrence of these species should contribute to determine regional patterns of distribution of plants that are considered indicators of archaeological sites. Further tools to analyze the cultural importance of the items cited during free lists can be found in Albuquerque et al. [41], Bale´e and Nolan [42], and Quinlan [40].

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Interviews About the Uses and Management of Plants Interviews are commonly used in ethnobiological studies. Semistructured interviews, in which the main questions are established by the researcher to guide the collaborator to topics sought by the researchers, provide opportunities for issues that come up during conversation to be included and explored when the researcher judges them to be relevant [41]. For further discussion of the care needed for planning and executing interviews see Albuquerque et al. [41].

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For historical ecology approaches, semi-structured interviews can draw upon the collaborators’ knowledge of the environment, the patterns in which useful plants occur in the landscape, their associations with different elements of archaeological sites, and the areas and the ways in which they are used and managed. The persistent effects on the landscape of past management practices are often recognized by modern societies. Numerous of these cultural practices are perpetuated in the present, and modified by current societies, sometimes dynamically re-signified and adapted to local demands [3]. Similar to what was proposed for free lists, interviews can be formulated in order to elicit the different landscape units recognized by local people and the plants used by them [28]. For each plant, questions can be asked about (a) the plant’s uses, (b) how it is managed, and (c) where it occurs. In addition, semi-structured interviews may provide qualitative information about the symbolic relationships between local people and the environment, and their impressions about the societies that occupied the region in the past, contributing to understanding how current societies re-signify and transform legacies from past populations. In order to facilitate data analysis, the types of use and management can be defined and grouped into categories. Uses can be grouped into categories depending on the purposes for which a species is used. An extensive literature exists on the compilation and analysis of these categories of plant uses [44, 56–59]. Management practices can be grouped into categories depending on “what people want to achieve, whether the effects of the practice are directional or not in the way they fundamentally shape plant species assemblages, and whether the practices result in similarities in terms of forest composition, abundance and distribution of useful species” ([3], p. 4). See Levis et al. [3] for a proposal of management practice categories. The places where a species can be found can be categorized into two main groups: past areas of use (e.g., irrigation canals, anthropogenic soils, mounds) and present areas of use (e.g., habitation areas, homegardens, swiddens, fallows, high forests). As mentioned previously, when ethnobiological methods are used in conjunction with archaeological surveys, previously used and/or managed areas can be defined much more accurately. Certain elements of archaeological sites are recognized by current local populations, who usually incorporate them into their daily activities. They can thus be sought during interviews as particular landscape units. By coupling this local recognition with available archaeological data, the distribution and overlaps between modern and past land uses categories can be compared across the archaeological site. Semi-structured interviews were used by Machado Mello and Peroni [60], in association with other methods, to investigate local populations’ perceptions about cultural landscapes in Araucaria

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forests of southern Brazil. Their interviews contained questions regarding local ecological knowledge, management and uses of resources on caı´vas, specific landscape units of the Araucaria forest where animals are raised and plants are harvested by local people. With this approach, they were able to identify transformations in local resource use and management over the years and highlight the role of human management for the conservation of these systems. When applied to historical ecology, interviews must capture the local understanding of the multiple temporalities present on the landscape. Thus, the approach should be informed by the local perceptions of the origins and the history of the cultural landscape being studied, and their relationships with the current distribution of plant species and communities. Forest patches dominated by useful plants, for instance, may be interpreted by local people as legacies of past human populations, as observed in our studies in Amazonia (e.g., [3]). Local people also consider animals to be responsible for the occurrence of forest patches, because they disperse the majority of tropical plant seeds and are frequently observed doing so. Our experiences in Amazonia have shown that, especially when dealing with forest patches close to habitation areas and cultivated fields, current residents can recall information about who was responsible for planting them. In areas that have been continuously occupied, historical knowledge of the landscape can be very detailed and go well beyond the memory and/or lifetime of local residents. Certain mythological narratives contain references to specific plant origins, such as the allusion to the guarana´ (Paullinia cupana) domestication event in a myth by the Satere´-Mawe´ people of Central Amazonia [61]. In addition, anthropogenic forests are not interpreted by local people in isolation from other evidence (whether material, such as ceramic fragments, or cultural, such as oral history) considered to tell stories about forests and landscapes. From these modern observations, timelines can be projected for the histories of different plant species and places in the landscape. By assessing present uses and management practices of plant resources and local perceptions about the landscape, historical ecology is able to design scenarios of how people constructed elements of the current landscape [62]. Recognizing the dynamic nature of cultural practices and eliciting information about past uses and management practices of natural resources enriches these scenarios. Careful interpretation of interviews is important when inferring the temporal depth of the use and management of plant resources observed in the present. Based on our experience in Amazonia, we mention two examples: – The current social/cultural/economic importance of the species vs. the possible importance it may have had in the past. These data can often be obtained in historical accounts and

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ethnographies. For example, manioc (Manihot esculenta) is widely cultivated and consumed by Amazonian populations in the present, but may have had less cultural importance in the diets of pre-Columbian populations [63, 64]. – The tools and management methods available in the past. In Amazonia, the absence of metal tools in pre-Columbian societies suggests that slash and burn agriculture is a postcolonial practice [65].

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Accessing Local Oral History Oral history techniques can be conducted through unstructured or semi-structured interviews with broad stimuli about the collaborators’ life story. This method reveals stories of recent times, which are per se embedded in narratives and memories of different time depths [66]. By narrating memories to others, one can create symbolic networks, which strengthen the construction of identities within a group linked by common events. In this manner, even when facts were not experienced by the speaker, they can be significant in his memory. Oral history recognizes the agency of people in cocreating present realities [67] and “is based on awakening people’s consciousness and strengthening pride in their own experience and identity” ([68], p. 3). In the case of historical ecological research, thematic oral history, in which interviews are conducted around a central theme [69], can be used to elicit the memories of the criteria used to select a certain place for settling, its landscape dynamics, the changes that have occurred in resource use and management, the presence of prior communities/peoples and their activities, etc. Moreover, this method can provide qualitative information about the symbolic dimension of the interaction between local people and their environment. By accessing the memories related to transformations and appropriations of the landscape, thematic oral history may be able to fill in gaps, through specific information from collaborators’ reports. As an example, a former resident of Caiambe´ Lake (in Central Amazonia) reported to us that when he first arrived in the region some Amazonian Dark Earths in the area were filled with concentrations of hog plum (Spondias mombin), a tree species less common today in the local landscape. When analyzing charred plant macroremains from an archaeological site in the region, we found remains of this species, indicating its use by populations in the past. By combining oral history with archaeological data, we drew a time line of activities involving the use and management this species at Caiambe´ Lake.

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Archaeological sites awaken a myriad of feelings and representations in local populations, triggering different forms of interpretation of the past. The life experiences of people living today on archaeological sites form networks, where archaeological remains gain meanings according to each one’s trajectories. The plants of the present, with all their associated symbolic universe [43, 70], are also interpreted according to personal and shared stories. By assessing these representations, oral history complements academic interpretations of archaeological sites and cultural landscapes [43, 66]. The interview is the moment of an important encounter between the researcher and the collaborator, when a relationship of complicity is created for the production of a narrative [66]. Thus, a number of rules of ethical conduct should be observed, as described by Medeiros et al. [67] and the International Society for Ethnobiology [71]. See Medeiros et al. [67] and Meihy [69] for recommendations on the transcription, validation, and analysis of the interviews.

7 Participatory Mapping of Past and Present Use Areas and Useful Plant Distributions Participatory mapping is a tool that can be used for locating the distribution of areas of past and present land use and the occurrence of plant resources. Maps elaborated using this technique are important representations of how people perceive their territory and the elements they find to be meaningful [72]. Thus, they are also a tool for community empowerment, as they emphasize local protagonism in elaborating a research product that represents the collective knowledge of the community, encompassing information from the present day to an unknown time in the past [73]. Participatory maps are particularly important for studies in historical ecology, as they are efficient tools to elicit recent landscape history, efficiently assessing changes in land use or in the distribution of plant resources, through the production of maps representing the landscape in different periods [74]. Methods of mapping, and cartographic representations in general, may be unfamiliar to members of many communities. Thus, researchers have the responsibility to discuss their objectives, the methods, the advantages and disadvantages, and basic elements of cartography to the participants before beginning the mapping [73, 75]. Further advice on researcher conduct for guiding participants in the elaboration of maps can be sought in Silva et al. [75]. There are several ways to carry out participative mapping [75]. We present two examples that we consider most suitable for collecting of data while working on archaeological sites: mental

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maps (sketches) and mapping over cartographic bases. Both can be produced by working either with individuals or with groups. In the case of the elaboration of individual maps, the researcher may also construct a final map made by compiling those produced individually. When possible, the final product should be validated in a workshop with the community. Mental maps are cartographic representations that do not require scale or formal references, such as geographical coordinates [72]. They are handmade drawings and their production requires simple material (e.g., A1 or A3 size paper and colored pencils). This method does not seek exact measurements or consistent and georeferenced scales, as the drawn representation is open to the author’s perceptions of his/her reality [72]. Elements that are more significant tend to receive greater emphasis in this kind of mapping. For historical ecology approaches, mental mappings can be applied to represent the local landscape in the recent past. The researcher can ask, for instance, that older residents represent how the landscape was organized when they were young (forested areas, cultivated areas, dwelling areas, location of the main plant resources, etc.). Another approach is to stimulate the representation of different elements of the archaeological site near or on which they live (e.g., where can one find anthropogenic soils, caves, earthworks, rock paintings, old cemeteries, etc.). For mapping with cartographic bases, a printed and georeferenced base map or satellite image (preferably on large paper), containing landscape features that can be easily identified is taken to the community. Participants use the map to locate the information they wish to represent, drawing with colored pencils over tracing paper [75]. The base map must not influence the participants’ perceptions of significant areas or features, to ensure that they represent objects/phenomena most related to their own experiences [72]. However, basic elements, such as rivers, community locations, and roads, should be indicated by the researcher to improve the informants’ understanding of the scale and the locations of reference features. Since the drawings made by participants are overlain on a georeferenced base map, all information produced can be georeferenced. This technique permits the investigation of landscape transformations up to the present, using the same logic as for mental maps. For example, Verbicaro and Nunes [74] asked residents of a rural community in the state of Para´, Brazil, to map the occurrence of ac¸aı´ (Euterpe oleracea) and miriti (Mauritia flexuosa) palm stands in their community on several maps spanning 20 years. From this procedure, the authors were able to identify changes in the abundance and distribution of these species through time. Cartographically referenced maps are also important tools to locate cultural forests, through the delimitation of patches of useful plants and the patterns of species distributions on archaeological sites and in their surroundings [3].

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Guided Tours Guided tours are also known as the field informant or “walk-in-thewoods” technique [41]. They consist of walks with local informants in community areas. Guided tours help to identify in the field plant species and landscape units, besides providing the researcher with the opportunity to observe management practices that had been previously overlooked. They also allow for the identification and recognition of elements within archaeological sites and plant species that may be associated with these elements. It is recommended that the tours are guided by local experts. Usually, these experts can be identified during free listings or interviews [39]. However, in some situations, community members themselves like to identify the guides, and they may not necessarily meet the needs of the research project. In these cases, we recommend making the tour with more than one guide. As tours can take a long time, they must be scheduled in advance according to the guide’s availability. Guided tours allow integration of numerous research activities. Researchers must record the amount of time spent on the tour; record the trajectory traveled (via GPS); collect and take pictures of plant specimens for botanical identification; georeference the specimens of interest (e.g., useful species or those collected for botanical collections); and name and characterize the landscape units visited. To characterize landscape units we recommend documenting: descriptions of the activities carried out in the area; period of use or abandonment (e.g., crop age, years of fallow); soil type; popular names and properties of useful plants; vegetation descriptions, including notes about species dominance in the landscape; and traces of recent and past occupations and activities, including paths, signs of vegetation management, archaeological artifacts, evidence of burning, anthropogenic soils, patches of useful trees and palms. Guided tours are important sources of information about the local knowledge and perceptions of landscape units and useful plant species. This method is usually a tool to complement interviews, free lists and/or participatory mappings, in order to consolidate the information obtained through other types of data collection. Machado Mello and Peroni [60], for instance, conducted guided tours with all the collaborators interviewed during their research on the maintenance of cultural landscapes in the Araucaria forest, in order to collect, identify and verify plant material mentioned during the interviews. With this method, many things that have been said and represented by research collaborators can be observed. In addition, through the perception of the guide, new information can be incorporated to understand the complexity of relationships between people, plants, and landscapes.

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Floristic Inventories Previously, we showed how ethnobotanical methods can be applied to historical ecology approaches in studies of landscapes and plant communities that occur on archaeological sites. Here, we show how the execution of floristic inventories on archaeological sites and surrounding areas can be a complementary approach to the methods presented above, in order to identify legacies of plant use and management by past societies on modern landscapes. Long-lived pioneer, useful, and domesticated species or species that incidentally coevolved with cultural landscapes can be used as indicators of human transformations [13, 45, 52]. These species’ distributions, however, are also influenced by natural conditions (e.g., climate and soil), and our capacity to detect the effect of past human influence on modern species distributions is limited by the data available (either ecological or cultural). Reliable information on the spatial distribution of plant species depends on good botanical collections and proper floristic inventories. The execution of floristic inventories provides a characterization of the structure of plant communities that can be correlated to human perceptions, values, habits, and modes of past and present resource use [76]. Thus, the dataset generated during floristic inventories in different landscape units is an important descriptor of the behavior of plant communities in areas with different human activities. Floristic inventories on archaeological sites and related areas can complement information about useful plants associated with past human activities [13, 77]. Indeed, some species that were used in the past may no longer be recognized as useful in the present, especially when one takes into account the common discontinuity between past and current human societies. Another application of systematic floristic inventories conducted in different archaeological contexts and regions is the creation of databases containing information about species that may be indicators of archaeological sites in different regions, which could lead to the identification of past cultural preferences. The identification of the plant community of a given area is necessary for fundamental ecological investigations, such as modeling patterns of species diversity and determining species distributions [78]. If the interpretation of archaeological structures/ remains can lead to the recognition of past land use patterns, floristic inventories performed on these areas can be directly related to long-term human history. Floristic inventories applied to historical ecology can follow different approaches. Here, we present some of the possibilities for vegetation surveys that can contribute to understanding the role of humans in shaping plant communities. The decision about inventory plot size depends on the possibilities offered by the study area and the analysis that will be

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performed with the data collected. Traditionally, one-hectare plots are established as a standard sample size for floristic inventories [78]. However, depending on the goal of the survey, smaller plots can be defined. Junqueira et al. [45], for instance, established 25  10 m plots, in order to avoid border effects when sampling small patches of secondary forests on anthropogenic soils. Lins et al. [79] inventoried the entire extension of homegardens, regardless of their area. For investigation across wider areas, standard 1-ha plots should be adopted (e.g., [77]) in order to facilitate comparisons with other studies [76]. Especially in tropical communities, where diversity and heterogeneity are high, when plots are small due to constraints inherent to the research questions, sampling a larger number of plots is highly recommended so that a sufficient number of individuals have been sampled for a robust quantitative analysis. The definition of the biological group (woody or herbaceous individuals, lianas, etc.) and the size of sampled individuals (minimum diameter at breast height—DBH) will depend on the objectives of the research. Usually, in 1-ha plots, all stems with DBH  10 cm are sampled. Despite the recommendation of 1-ha plots as standard, Phillips et al. [78] showed that 0.1-ha plots are more efficient in obtaining floristic information if all stems with DBH  2.5 cm are inventoried. Following any sampling strategy, rarefaction methods can be used for standardized comparisons with other floristic studies, as discussed by Arau´jo and Ferraz [76]. Subplots for the inventory of herbaceous plants can be designed when necessary. Due to the economic importance of the Arecaceae family and because they are good indicators of anthropogenic forests [45, 80], we recommend the inclusion of palms in inventories of historical ecological studies. For the correct identification of the taxa sampled, it is recommended that vouchers be collected and deposited in collections, prioritizing fertile material whenever possible. Floristic inventories per se provide a large amount of valuable data. However, when floristic information is analyzed together with environmental (e.g., soil) or ecological (e.g., functional traits, tree growth rings) data, it is possible to obtain better and more detailed insights to help reconstruct the history of the vegetation sampled. Integrated analysis of these parameters will contribute to the assessment of the human and environmental effects on plant distributions and compositions [13]. Furthermore, while performing floristic inventories, the use of scientific literature to obtain ethnobotanical data about the sampled species can provide complementary information about the species collected in the field. The information about the uses, management, and other relevant data about the history and distribution of plant species identified in floristic inventories associated with archaeological sites may constitute a basis for advances of interpreting the history of interactions between human populations and their landscapes.

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Floristic inventories can also be performed during archaeological excavations [46]. Based on the assumption that modern plant communities may also be considered archaeological remains [23, 24], floristic inventories of plots delimited around excavation areas are complementary procedures to any archaeological intervention for the systematic collection and registration of these “ecofacts.” In this situation, the establishment of the sampling plots can be determined according to the position of test pits and/or excavation units. The analysis of floristic composition around an excavation area, in combination with the analysis of other classes of archaeological remains, will allow interpretation of the current plant community in a more defined historical context. For further discussion of the sampling methods and analysis of floristic data in ethnobotanical studies see Arau´jo and Ferraz [76].

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Final Considerations: The Integration of Archaeology and Ethnobiology In the introduction of this chapter, we mentioned the contributions made by archaeobotany and paleoecology to understand the history of human–plant interactions by (a) identifying which plants were used and managed in the past, (b) identifying the environmental context in which they were used, and (c) shedding light on the scale and duration of landscape transformations. The accuracy of archaeobotanical and paleoecological studies can be enhanced by establishing a closer dialogue with ethnobiology. Drawing upon ethnobotanical knowledge is essential to (a) provide information about which species have current or historic uses in the region of study, and therefore guide the elaboration of reference collections for the identification of botanical remains; and (b) to record how plants are used and processed by people, and thereby illuminate possible scenarios of preservation and non-preservation of specific plant remains in archaeological contexts. While drawing upon ethnoecological knowledge holds numerous benefits for understanding local historical ecology [81], current human land-uses provide an important baseline from which the paleoecological record can be interpreted. In the absence of “natural” vegetation baselines, one must start from cultural landscapes and work backwards [82, 83]. Thus, in the same way that archaeological data are important for ethnobiological research to interpret cultural landscapes, the interpretation of archaeological contexts benefits from the understanding of present scenarios of management and use of landscapes and plant resources. The integration of ecological, paleoecological, and archaeological studies is revealing that most of the apparently natural areas of the planet have longer and more pronounced cultural histories than assumed in the past [1]. Case studies illustrate examples of forest recovery, forest enrichment with useful species, and the creation or

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maintenance of places that today are valued habitats, indicating that the human history of appropriation of ecosystems can have positive effects over biodiversity [25, 84, 85]. The integration of ethnosciences with archaeology can offer models for understanding the resilience of such current landscapes based upon their history [86]. Local populations are vital partners in this approach, as their knowledge and practices reinforce ecosystem health that resulted from thousands of years of human occupation [84, 87]. References 1. Ellis EC, Kaplan JO, Fuller DQ, Vavrus S, Klein Goldewijk K, Verburg PH (2013) Used planet: a global history. Proc Natl Acad Sci U S A 110(20):7978–7985. https://doi.org/10. 1073/pnas.1217241110 2. Clement CR (1999) 1492 and the loss of Amazonian crop genetic resources. I. The relation between domestication and human population decline. Econ Bot 53(2):188–202. https:// doi.org/10.1007/BF02866498 3. Levis C, Flores BM, Moreira PA, Luize BG, Alves RP, Franco-Moraes J, Lins J, Konings E, ˜ a-Claros M, Bongers F, Costa FRC, ClemPen ent CR (2018) How people domesticated Amazonian forests. Front Ecol Evol 5:171. https://doi.org/10.3389/fevo.2017.00171 4. Albuquerque UP, Gonc¸alves PHS, Ferreira Ju´nior WS, Chaves LS, Oliveira RCS, Silva TLL, Santos GC, Arau´jo EL (2018) Humans as niche constructors: revisiting the concept of chronic anthropogenic disturbances in ecology. Perspect Ecol Conserv 16. https://doi.org/ 10.1016/j.pecon.2017.08.006 5. Boivin NL, Zeder MA, Fuller DQ, Crowther A, Larson G, Erlandson JM, Denham T, Petraglia MD (2016) Ecological consequences of human niche construction: examining long-term anthropogenic shaping of global species distributions. Proc Natl Acad Sci U S A 113(23):6388–6396. https://doi. org/10.1073/pnas.1525200113 6. Bale´e W, Erickson CL (2006) Time, complexity, and historical ecology. In: Bale´e W, Erickson CL (eds) Time and complexity in historical ecology: studies in the Neotropical lowlands. Colombia University Press, New York, pp 1–17 7. Crumley CL (2007) Historical ecology: integrated thinking at multiple temporal and spatial scales. In: Hornborg A, Crumley CL (eds) The world system and the earth system: global socioenvironmental change and sustainability since the neolithic. Left Coast Press, Walnut Creek, CA, pp 15–28

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Chapter 14 Challenges in Ethnozoological Research Roˆmulo Romeu No´brega Alves and Wedson Medeiros Silva Souto Abstract Faunistic and cultural diversity reflects the range of interactions between people and animals, and thus provides numerous opportunities for ethnozoological research. However, there are several challenges associated with the development of this type of research program, which may deter researchers who are interested in the area. In this chapter we discuss the methodological challenges and difficulties commonly associated with conducting ethnozoological research, with an emphasis on the context of Brazil, and point out potential suggestions on how such difficulties can be minimized. Key words Ethnobiology, Ethnozoology, Voucher specimens

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Introduction Ethnobiological research alone represents a challenge for any researcher who intends to develop studies in this area since it is a multidisciplinary field of research, implying the need to master concepts and methods of both natural and human sciences. In the particular case of ethnozoology, there are additional factors that increase the difficulties in performing research on the subject. In the most diverse environments, of both urban and rural areas, there is a great diversity of interactions between people and animals, which provide numerous opportunities for ethnozoological work that is of great importance to several areas of knowledge [1]. Thus, it is fundamental that varied strategies be adopted to overcome the challenges that are commonly associated with the development of research in this area. In this chapter, we briefly discuss some factors associated with the challenges and difficulties of conducting ethnozoological research, and provide some suggestions as to how such difficulties can be minimized and overcome.

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_14, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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Legislation, Use, and Commerce Regarding Animals The use and commercial trade of wild animals are activities that occur on all continents, both in urban and rural areas [2–5]. Access to, and the use of, wildlife resources in each country varies according to local legislation, and is crucial for making people feel more or less comfortable in talking about the interactions they establish with them. Some of the factors that influence the acquisition of knowledge about a species include whether the animal is domestic, wild, protected by law, or a target of regulated hunting and fishing. In Brazil, for example, federal legislation establishes that an individual found killing, persecuting, capturing or using a wildlife species, native or on a migratory route, without permission of the competent authorities is subject to detention of 6 months to 2 years and a fine. Furthermore, those that commercialize, offer for sale, acquire, export, hold in captivity or transport such species may suffer the same penalties. The penalty may be increased by up to 50% if the species involved are on lists of endangered animals. In addition, abuse, mistreatment or injury of animals, wild or domestic, native or exotic, justify the detention of 3 months to a year plus a fine [6]. Thus, it can be seen that in situations such as these, obtaining information from people interacting with animals in a clandestine manner becomes more difficult. Despite the legal implications and regulations, hunting and consumption of wild animals persists on all continents [2, 7]. In this scope—a cultural socioeconomic context in which legislation regulates interactions with the fauna—there remain many cases when legislation is admittedly incapable of preventing consumption and commerce, even though it proposes to do so, eventually stimulating conflicts and causing different users of products derived from wild animals to do so clandestinely. Thus, many individuals do not admit that they use or commercialize products derived from fauna, knowing that this implies an illegal activity, which represents an additional difficulty for carrying out ethnozoological studies. The clandestine or semi-clandestine nature of the use and commercialization of wild animals is one of the factors that certainly contribute to the scarcity of detailed information on ethnozoology, especially when it comes to wild animals for which there is no free commerce [8]. The situation becomes even more difficult when research is carried out in urban areas, where commerce of wild animals commonly occurs in public markets and free fairs [9–14]. In these localities, inspections by environmental agencies are common, resulting in the apprehension of products derived from wild animals that are commercialized for different purposes, from products used as food to live animals used pets. In this way, the researcher may be

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confused with an undercover prosecutor, and so is usually viewed with suspicion by potential respondents. In addition, the advance of modern technological resources in tropical areas in recent years, such as the expansion of Internet and mobile telephone services, has made it possible to increase contact between hunters/collectors of wild fauna and other actors in the market chain (e.g., market vendors, restaurant owners, final consumers). This scenario has allowed the emergence of an intense and rapid black chain of exploitation and commercialization of fauna, making it difficult to locate and analyze the role of the agents involved in illegal trade and places researchers and organizations linked to ethnozoological research at risk. For ethnozoological studies developed in this context, the initial contact with the target population of the research is one of the most difficult stages, since several factors can influence the availability of people for interviews and follow-up activities of participant observation. As in any ethnobiological research, establishing trust in the target population is critical to the success of the research. Thus, it is recommended that interviews start by explaining the research in detail, and obtain authorization to conduct the work. The introduction of the researcher by another person, such as a local leader or a person who is respected in the community to be studied, can facilitate approaching the interviewees and obtaining information. Finally, during research involving illegal activities, discrete behavior and friendly approaches are necessary factors for guaranteeing the safety of the participants and increasing the chances of good execution of field activities.

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Obtaining Testimonial Material Voucher specimens are fundamental components of ethnobiological studies. They allow the accurate identification of the biological material upon which observations and data are recorded. Thus, for an ethnozoologist, voucher specimens are essential for the development of quality work. Popular names vary widely depending on the locale, so matching a common name with a scientific name is not a reliable method of identification. Many ethnozoological studies have only vernacular names or the identification of species through “taxonomic clues,” which, although an alternative resource for obtaining information, can often result in taxonomic errors. The absence of testimonial material is the main cause of a lack of scientific rigor for many ethnobiological studies, especially those that study invertebrates or fish, which require more careful identification. Thus, from a current and future perspective, such research, as well as the scientific journals in which it is published, must acknowledge the need for collecting testimonial specimens and

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their deposition in a scientific collection, which is one of the fundamental steps in the quest for qualitative improvement to ethnozoological studies. The correct species-level identification provides a basis for comparing biological, ecological and ethnozoological data. In addition, studies with adequate species identification allow temporal comparisons of the occurrence and patterns of fauna utilization in a given region. Compared to ethnobotanical research, in which plants can usually be obtained with relative ease, ethnozoological studies possess a higher degree of difficulty in collecting biological material. Depending on the type of study, the difficulties of obtaining specimens are diverse, especially when the study deals with a wide variety of animal species or when only parts derived from the animals listed in the research are available. Thus, the animal group to be investigated has direct influence on the ways of obtaining the testimonial material. For example, in ethnoichthyological work, fish can be purchased directly from the fishermen involved in the research [15, 16]. When the study involves different animal groups, the difficulty increases, since the methods of collection are also variable. In relation to work with hunters and fishermen, their knowledge and the techniques they use can maximize the collection of testimonial specimens [17–19]. Whenever possible, specimens of each animal recorded in an ethnozoological study should be collected, and can often be acquired directly from the interviewees through donations or purchase (in the case of commercialized species). For some animal groups, parts derived from animals may, in many cases, enable the identification of species. Very often interviewees (traders or users of wildlife products) stock products derived from animals, such as skulls and furs, used for medicinal, ornamental and magicalreligious purposes, while such parts are frequently discarded when their use is for purposes of food, as is usually the case when the product consumed is meat [20–23]. “Disposable” products can be purchased from the interviewees. Skeleton elements, shells and skins that allow the identification of many species of mammals, reptiles, birds, and fish are commonly accepted as testimonial material in zoological collections. In the case of invertebrates, shells of mollusks and exoskeletons of corals are examples of materials that can serve as testimony. Obtaining specimens of large vertebrates (e.g., whales, bovines, or large carnivores) present a high degree of difficulty both for their collection and for their maintenance in scientific collections. Normally in such cases, as pointed out by Bye Jr. [24] exceptions are made to the general rule that testimonial specimens are essential, particularly when dealing with very large animals with universally recognized identification. However, in some cases, when possible, the collection of animal parts can be used as specimen testimony. If it is not possible to obtain any part of the animal, a photograph or

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reference drawing may be sufficient. For example, a photo of a stranded whale or dolphin that permits identification can be deposited in the database of a scientific collection. Photographs of animals also allow the identification of certain species, and can be used for some studies that address live animals, such as pet birds, which obviously will not be donated by the interviewees. For animal groups that vocalize, vocalizations, if properly documented, can provide all the essential requirements of a testimonial specimen. Birds, for example, recognize each other by a variety of specific vocalizations that can be used by researchers to identify species quickly and practically, and in some cases can reveal sex, age, and even subspecies. Considering that vocalizations are important for the recognition of species of different groups, such as amphibians, insects, and even certain mammals, the use of such an approach isn’t limited to ethnoornithological investigations. In the latter case, one can resort to taxonomic procedures, for which the consultation of the specific bibliography (searching for published works on the animals that have been carried out in the region) and specialists, who work in local universities and know the composition of the fauna of the studied region, is recommended. The importance of testimonial specimens in ethnobiological research has been repeatedly emphasized. A well-developed ethnozoological work, with the collection of testimonial material, not only contributes to the quality of the research, mainly with regard to biogeography, but also makes it possible to discover new species and the expansion of the known geographic distribution of species already described. References 1. Alves RRN, Souto WMS (2015) Ethnozoology: a brief introduction. Ethnobiol Conserv 4(1):1–13 2. Alves RRN, Souto WMS, Fernandes-FerreiraH, Bezerra DMM, Barboza RRD, Vieira WLS (2018) The importance of hunting in human societies. In: RRN A, Albuquerque UP (eds) Ethnozoology: animals in our lives. Academic, London, pp 95–118 3. Baker SE, Cain R, Van Kesteren F, Zommers ZA, D’cruze N, Macdonald DW (2013) Rough trade: animal welfare in the global wildlife trade. Bioscience 63(12):928–938 4. Fernandes-Ferreira H, Mendonc¸a SV, Albano C, Ferreira FS, Alves RRN (2012) Hunting, use and conservation of birds in Northeast Brazil. Biodivers Conserv 21:221–244 5. Ferreira FS, Fernandes-Ferreira H, Leo Neto N, Brito SV, Alves RRN (2013) The trade of medicinal animals in Brazil: current

status and perspectives. Biodivers Conserv 22:839–870 6. Fernandes-Ferreira H, Alves RRN (2014) Legislac¸˜ao e mı´dia envolvendo a cac¸a de animais silvestres no Brasil: uma perspectiva histo´rica e socioambiental. Gaia Sci 8(1):1–7 7. Alves RRN, van Vliet N (2018) Wild fauna on the menu. In: RRN A, Albuquerque UP (eds) Ethnozoology: animals in our lives. Academic, London, pp 167–194 8. Alves RRN, Souto WMS (2011) Ethnozoology in Brazil: current status and perspectives. J Ethnobiol Ethnomed 7(22):1–18 9. Alves RRN, Rosa IL, Albuquerque UP, Cunningham AB (2013) Medicine from the wild: an overview of the use and trade of animal products in traditional medicines. Anim Trad Folk Med 2013:25–42 10. Albuquerque UP, Monteiro JM, Ramos MA, Amorim ELC, Alves RRN (2014) Ethnobiological research in public markets. In:

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Albuquerque UP, LVFC C, RFP L, RRN A (eds) Methods and techniques in ethnobiology and ethnoecology. Springer, New York, pp 367–378 11. Oliveira ES, Torres DF, Brooks SE, Alves RRN (2010) The medicinal animal markets in the metropolitan region of Natal City, Northeastern Brazil. J Ethnopharmacol 130(1):54–60 12. Whiting MJ, Williams VL, Hibbitts TJ (2013) Animals traded for traditional medicine at the Faraday market in South Africa: species diversity and conservation implications. In: Alves RRN, Rosa IL (eds) Animals in traditional folk medicine: implications for conservation. Springer, Berlin, pp 421–473 13. Alves RRN, Feijo´ A, Barboza RRD, Souto WMS, Fernandes-Ferreira H, Cordeiro-Estrela P et al (2016) Game mammals of the Caatinga biome. Ethnobiol Conserv 5:1–51 14. Alves RRN, Pereira Filho GA, Silva Vieira K, Souto WMS, Mendonc¸as LET, Montenegro PFGP et al (2012) A zoological catalogue of hunted reptiles in the semiarid region of Brazil. J Ethnobiol Ethnomed 8(1):27 15. Pinto MF, Moura˜o JS, Alves RRN (2015) Use of ichthyofauna by artisanal fishermen at two protected areas along the coast of Northeast Brazil. J Ethnobiol Ethnomed 11(20):1–32 16. Pinto MF, Moura˜o JS, Alves RRN (2013) Ethnotaxonomical considerations and usage of ichthyofauna in a fishing community in Ceara´ State, Northeast Brazil. J Ethnobiol Ethnomed 9(17):1–11 17. Alves RRN, Mendonc¸a LET, Confessor MVA, Vieira WLS, Lopez LCS (2009) Hunting strategies used in the semi-arid region of

northeastern Brazil. J Ethnobiol Ethnomed 5 (12):1–50 18. Bezerra DMM, Araujo HFP, Alves RRN (2012) Captura de aves silvestres no semia´rido ˜ es brasileiro: te´cnicas cinege´ticas e implicac¸o para conservac¸˜ao. Trop Conserv Sci 5 (1):50–66 19. Nordi N, Nishida AK, RRN A (2009) Effectiveness of two gathering techniques for Ucides cordatus in Northeast Brazil: implications for the sustainability of mangrove ecosystems. Hum Ecol 37(1):121–127 20. Alves RRN, Rosa IL (2007) Zootherapy goes to town: the use of animal-based remedies in urban areas of NE and N Brazil. J Ethnopharmacol 113:541–555 21. Alves RRN, Rosa IL (2010) Trade of animals used in Brazilian traditional medicine: trends and implications for conservation. Hum Ecol 38(5):691–704 22. Vieira KS, Vieira WLS, Alves RRN (2014) An introduction to zoological taxonomy and the collection and preparation of zoological specimens. In: Albuquerque UP, LVFC C, RFP L, RRN A (eds) Methods and techniques in ethnobiology and ethnoecology. Springer, New York, pp 175–196 23. Ferreira FS, Albuquerque UP, Coutinho HDM, Almeida WO, Alves RRN (2012) The trade in medicinal animals in Northeastern Brazil. Evid Based Complement Alternat Med 2012:1–20 24. Bye RA Jr (1986) Voucher specimens in ethnobiological studies and publications. J Ethnobiol 6(1):1–8

Chapter 15 Biocultural Collections and Participatory Methods: Old, Current, and Future Knowledge Viviane Stern da Fonseca-Kruel, Luciana Martins, Aloisio Cabalzar, Claudia Leonor Lo´pez-Garce´s, Ma´rlia Coelho-Ferreira, Pieter-Jan van der Veld, William Milliken, and Mark Nesbitt Abstract Biocultural collections document human–nature interactions through plant and animal-based artifacts, raw materials, herbarium voucher collections, and varied forms of documentation. They form a valuable resource for biocultural conservation, preserving and enhancing traditional knowledge, livelihoods, and the environment. They should be used through participatory methods that allow institutional researchers and local communities to share data on ethnobiological collections and artifacts, enabling new knowledge of plants and people from multiple perspectives. Methods are demonstrated through a case study of historic ethnobotanical specimens collected by Richard Spruce in the northwest Amazon. Key words Indigenous biocultural knowledge (IBK), Traditional ecological knowledge (TEK), Ethnobiology, Ethnobotany, Brazil

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Biocultural Collections Biocultural collections are ethnobiological specimens, artifacts, and documents—plant, animal, and cultural—that represent the dynamic relationships between peoples, biota and environments [1]. They are repositories for plants and animals used by people, products made from them, and information about them, also including objects not made of vegetal or animal material, but used in the processing of these materials. Ethnobiology is a dynamic field that relates processes, transformations and associations, and biocultural collections are therefore more than a “collection of objects.” Documentation of provenance, language, images, use, local meanings, processing and ethnographic context, and of interconnections between different forms of specimens, is critically important [2].

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_15, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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Biocultural specimens can include: herbarium, xylarium and zoological specimens, with label information on use, preparation, common name or other cultural and linguistic information; seeds of plants, fruits, roots, leaves, flowers, bark, tubers, animals, horns, bones, skin, hair, etc.; vegetable and animal products and processes e.g. clothing (vegetable and animal fibers), commercial and medicinal food, religious artifacts, toys, vegetable and animal products (varnish, starch, latex, resins, waxes, oils, essential oils etc.); ethnographic materials and cultural artifacts; DNA collections of useful plants and animals and their wild relatives; living collections (in situ and ex situ collections of plants and animals); archaeological plant and animal remains; biocultural documentation (information from libraries and archives, cultural texts, narratives, field research notes, maps, audios, photo and video files) [1]. Biocultural collections became popular in the mid-nineteenth century, particularly as a means of recording information about plant and animal uses that might be valuable to industrial economies. They were often closely associated with colonial botany. The Museum of Economic Botany at Kew, founded in 1847, was the model for many such museums worldwide. From the 1950s the decline in empire, and rise of oil-based products, led to the closure of most such collections. However, in the last two decades it has become clear that such biocultural collections, whether old or newly formed, can play an important part in the modern work of the ethnobiologist [1].

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Collaborative Research Biocultural conservation addresses the loss of biological and cultural diversity. It is grounded in the theory of dynamic and interdependent socio-ecological systems, in the lessons of work on diversity and biocultural heritage, integrated conservation and development, co-management, and community-based conservation [3]. If well used, biocultural approaches to conservation can be a powerful tool to reduce the overall loss of biological and cultural diversity. Biocultural collections are applicable to many aspects of biocultural conservation (Fig. 1). In the scope of biocultural conservation and biocultural collections, there are important debates on the nature of collaborative processes with local communities [4]. Intercultural collaborative research is complex; it requires a constant dialogue as it articulates diverse epistemic and ontological concepts leading to “co-theorization”, facilitating the participation of all researchers in generating “new conceptual tools that make contemporary realities meaningful” [5]. Fortunately, there is substantial experience of community collaboration in conservation and in museum collections on which we can draw [3, 6]. Non-indigenous researchers should be attuned

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Fig. 1 Biocultural collections serve applied research, plant conservation, animals and traditional knowledge, natural resource management, economic and social development, education and community service. Adapted from [1]

to the necessity of working side-by-side with indigenous participants in all phases of research, beginning with the elaboration of projects, defining themes and objectives, fieldwork (which is not merely data collection), and “space of conceptualization” [5]. Likewise, the coauthoring of work and sharing the resultant benefits are imperative when working with traditional knowledge associated with biodiversity.

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Case Study: The Northwest Amazon The Northwest Amazon comprises a large region of equatorial forest on the border of Brazil, Colombia, and Venezuela, which has been inhabited by indigenous peoples since the pre-colonial period. Today they occupy 80% of its area. The region is known as a multiethnic social system comprising about thirty linguistic groups from three linguistic families. The Eastern Tukanoan and Arawak peoples are riparian and farmers, whereas the Maku are more mobile, exploring more dispersed resources in interfluvial areas. This area is characterized by serious ecological limitations: acid soils and waters, nutrient-poor and of low productivity, and extensive areas covered by Amazonian caatinga, which is very restrictive for agricultural practices. These two factors—antiquity of occupation and serious ecological limitations—have led the indigenous peoples to a long process of adaptation, finding effective and sophisticated forms of management of the land, forests and agriculture, fish and game. Some travellers, like Richard Spruce who visited the region in the nineteenth century, described the vitality and dynamics of these populations, demonstrated by the size of their longhouses, their extensive intercommunal ceremonies, and their rich material culture. This regional social system underlies the constitution of contemporary indigenous organization and of their federation ˜ es Indı´genas do Rio Negro—FOIRN). (Federac¸˜ao das Organizac¸o Major issues include environmental management, community wellbeing, territorial governance, education, and health care. The use of plant resources is a key priority, both for human livelihoods and the maintenance of ecosystem services. Important and potentially valuable information relevant to this challenge is contained in biocultural collections held both within and outside Brazil. Unlocking this potential requires an integrated, equitable approach to collections research, and the capacity to develop platforms for transmission of information to a wide range of end users. Beginning in 2015, a collaboration between indigenous peoples in the region and institutions in Brazil and the UK has been based on nineteenth century ethnobotanical specimens, collected by the botanist Richard Spruce, and housed at the Royal Botanic Gardens, Kew and the British Museum (Box 1; Fig. 2) [7, 8]. A diachronic approach to such research facilitates a better understanding of the shifting relationships between people and natural resources, with potentially important implications for the future.

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Fig. 2 (a) Detail of herbarium specimen of tururi (Brosimum utile (Kunth) Pittier), collected by Richard Spruce in Sa˜o Gabriel da Cachoeira in 1852 (No. 2144; barcode K000947729); (b) Demonstration of bark extraction today; (c) Tanga made of tururi from the Rio Uaupe´s, collected by Richard Spruce (EBC 42839); (d) Exchanging information about Richard Spruce collections during workshop; (e) Practising interviewing in the field. Courtesy of Royal Botanic Gardens, Kew (a, c); Luciana Martins (b, e) and Adeilson Lopes da Silva (d)

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Box 1 Example of a participatory study conducted by Jardim Botaˆnico do Rio de Janeiro (JBRJ), Instituto Socioambiental (ISA), Royal Botanic Gardens, Kew, Birkbeck (University of London), Federac¸˜ ao das Organizac¸o ˜ es Indı´genas do Rio Negro (FOIRN) and Museu Paraense Emı´lio Goeldi (MPEG), supported by Newton Fund (Institutional Skills) from the government of the UK. The activities reported took place in 2016–2017: Study area—Brazil, Northwest Amazonian, Upper Rio Negro, Sa˜o Gabriel da Cachoeira. Objectives l

To build capacity among Brazilian research institutes to research, catalogue, and mobilize data from biocultural collections, and to develop these important resources for improved understanding of the useful and cultural properties of plants.

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To build capacity among indigenous peoples to research and document traditional knowledge, combining techniques from standard scientific practice with indigenous perspectives.

Participatory research—The training program included four main elements. 1. Integrated collections research and knowledge transfer through hands-on research at Kew, working with Richard Spruce’s collections from the Brazilian Amazon. Staff from JBRJ were trained in current methods of curation and community use of biocultural collections. 2. At JBRJ, building capacity for enhancement of an existing platform (currently focused on plant specimens— REFLORA), extending its value as a key Brazilian biocultural resource and opening opportunities for integration of data from other collections. 3. Capacity building in integrated collections research and mobilization among a range of Brazilian organizations, while strengthening interinstitutional collaboration and knowledge-sharing within Brazil (1-week training course delivered in Rio de Janeiro, applying Brazil- and UK-based expertise while drawing on specialist knowledge and expertise among the trainees). 4. Development of skills in autonomous biocultural research and interpretation/education among indigenous communities in the Upper Rio Negro, building on the Instituto Socioambiental’s existing program in the region. The main activity was a training course for indigenous researchers held in Sa˜o Gabriel da Cachoeira. Richard Spruce’s collections, many of which originated from this region, were used as

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Box 1 (continued) source material for part of the training, alongside a focus on contemporary material culture and plant use. The workshop in Sa˜o Gabriel da Cachoeira was followed by a 5-month field research program, supported by ISA, assisting indigenous trainees to put their new learning into practice in the context of projects focused on sustainable resource use, and documenting/valuing traditional knowledge and practices.

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Plant Identification Identification of plants used in the production of biocultural collections requires a numbered voucher specimen (preferably housed permanently in a herbarium) relating to the occurrence of a plant in a given place, its respective indigenous names, and its uses [8]. Ideally the plant should be fertile (e.g., with flowers or fruits), as this can help taxonomists identify the species. It is useful to produce high resolution photography of the plant, not only to assist taxonomists but also because these may be used in displays, publications, and materials for local communities. Carefully photographing the plant collections in a systematic process (e.g., photographing the environment; the whole plant; part of the plant with leaves and flowers/fruits; leaves; flowers; fruits; seed; bark) is important. With access to a digital scanner, plants can be scanned and sent quickly to botanical experts. Avoid mixing up photos of plants: one suggestion is to take a first picture of just the collecting number, and then of the plant images relating to it. Also, it is best to note the photo numbers on the specimen data form. The unique specimen voucher number should be connected to all related data: notes, recordings, biocultural collections etc., assuring the quality of the botanical identification. Richard Spruce was a pioneer in collecting herbarium voucher specimens in connection with artifacts, and recent work at Kew has enabled ethnobotanical specimens to be reconnected with herbarium material and correctly named, despite the passage of 170 years.

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Raw Materials and Manufacture Biocultural collections have a strong emphasis on the type of raw material utilized (fibers, dyes, fruits, seeds, inner bark, exudates, etc.). It should be collected with data on selection criteria for the plant, when and how it was collected (e.g., perennially or seasonally); who collected the plant (men or women); what procedures were used after gathering (washed, ground, sun-dried or shade-

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dried, storage techniques, etc.); and how it is transported. In relation to the plants providing the raw materials, further data include: the name of the location where it was encountered, its characteristics (life form, height, odor, taste, color, and texture of its flowers, leaves, fruits, bark; presence of exudates, etc.), location (upland forest, va´rzea, etc.), if the plant is abundant or rare (its conservation status), and the part of the plant that is collected. If the raw material was obtained by another person, it should be noted whether it was given or purchased, and in the latter case, its price. It is also useful to record which other plants can be used for a given purpose, as well as those being immediately gathered. Recording the making of an object should be done through drawings, photographs and/or video recordings, embracing all phases of production. If possible, the object should be recorded at its various stages of completion, concentrating on the ‘points of transition’ [8]. Yet beyond these technical aspects of the fabrication process, it is equally important to inquire about the sociocultural aspects associated with the crafting of the artifact. Research should document who made the artifact (men, women, young, elderly, clans, age groups, etc.), including gender, generation, and social organization. In this respect, it is very important to document if the person elaborating the artifact are observing dietary and sexual taboos, among other acts. It is also important to inquire about where and when the artifact should be made, its appropriate space (domestic, ritual, natural environment) and timing (season, moon, ritual calendar, etc.). It is vital that the name and its meaning or significance is recorded in its local language, and if it is made with various parts, also note their respective names [2].

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Documenting the Use of Artifacts One of the first tasks is to identify the type of use designated for the object, addressing diverse categories (domestic, body ornamentation, musical instruments, toys, ritual uses, among others). Object use is also associated with gender (men, women), generation (young, elderly, others) and social organization (clan, age grade, etc.). It is also important to indicate who uses the artifact (men, women, clan or specific social group, age), and in the case of objects specifically used in rituals, restrictions or prohibitions in handling them. In the northwestern Amazon, there is an artisanal specialization among ethnic groups [9]. For example, the Tukano specialize in the manufacture of wooden benches, the Tuyuka and Bara´ in the fabrication of canoes, the Hupda in making the baskets used to carry cassava, and the Desana and Baniwa in basketry of various types and uses. Curare poison is made by the Maku peoples and the Makuna. Likewise, one should register: special uses and

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preparations; when to use; how they should be employed; and for what end. Another aspect that should be documented regarding ritual objects is whether they should be used alone, or in combination with other objects to give them cultural significance. Various types of objects and instruments can be used together in certain contexts. For example, in the northwestern Amazon, ornaments used in ceremonies are composed of several parts that are stored together in a box made with the sewn fibre. This fibre is derived from the leaves of a palm tree which has a very restricted distribution across the region. With this, we emphasize the importance of recording as much detail related to the object and especially its cultural meanings, such as ceremonial use objects. We need to be careful in the record, exemplified by a testimony (current) of a Tukano Indian, who reported that he was shocked when he saw a Tukano bench—an important object in their culture, where the elders sit down to tell stories—in the bathroom of an apartment in Sa˜o Paulo. We need to register, transmit and respect the local cultural significance of the objects.

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Documenting Biocultural Collections Biocultural artifacts exhibit two interrelated dimensions that need to be studied, analyzed, and documented in the research process, namely, the biological and cultural dimensions. The biological dimension is primarily linked to the raw materials, mostly from plant material (wood, leaves, fiber, resins, oils, etc.), and animals (feathers, bones, teeth, hides, and skins) comprising these objects. Occasionally, though currently infrequently in the northwest Amazon, artifacts can also consist of human material (hair, teeth, and bones). Documenting cultural artifacts aims to situate and contextualize objects in the world in which they were produced. In this sense, an ethnographic approach can document sociocultural aspects associated with these objects: “a classic analysis of ethnographic objects embraces four main aspects: raw materials, crafting techniques, their formal aspect, and functions” [10]. As such, as pointed out by van Velthem, “it is unfathomable to study artifact without considering their aesthetic and economic aspects as well as their epistemological significance” [10]. Likewise, Silva and Gordon [11] propose analyzing the “material, environmental, historical and significant” aspects of these objects. The cultural dimension is related to human intervention in the process of crafting the artifact; this involves a series of interactions and knowledge beginning with the selection of raw materials and their extraction from the environment, handling, the techniques

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involved in crafting and finishing, their social dimension in craftsmanship, utilization and meaning of the artifacts, considerations in the shelf life, the agency and potential of these objects. Objects occupy a special place in Amerindian cosmology, with qualities that go beyond materiality such as agency and power [12]. These attributes need to be documented, by interviewing people working on these objects and those familiar with myths and tales that detail the origins of these artifacts. Questions about narratives, chants and associated rituals, and their importance in the lives of indigenous people should also be addressed. In this way, it is possible to unearth the ontological dimensions of these objects, their aesthetic qualities, and features contributing to their beauty. In collaborative research on ethnographic objects with indigenous peoples of the Amazon at the Goeldi Museum (Bele´m), “conversations about objects” are generally initiated by documenting raw materials followed by production aspects of the objects, considering the person involved in crafting it and the descriptions about elaboration techniques. In turn, details are provided about the use of the object, who utilizes it, how it is used, why it is used, if it is still in use, and if there is a history or narrative associated with it [13].

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Digital Repatriation and Indigenous Knowledge Digital repatriation projects may promote the safeguarding of indigenous knowledge through the integration of scientific documentation, notes, images and vouchers (botanical material). This kind of dynamic, complementary, and integrated data may reinvigorate traditional practices and maintain the culture and the ways of life. This may have an impact on technological changes and cultural needs on individual communities, as well as regional and international networks (Box 2). Box 2 Example of repatriation and sharing of information previously stored in scientific collections: The REFLORA Project, in which Kew and JBRJ are major partners, has made great progress in repatriating important botanical collections and data held outside the country, contributing to the development of greatly enhanced understanding of Brazil’s plant diversity. The project initially focused on herbarium specimens collected in Brazil but now housed in museums around the world. However, its scope has now increased to include the 300 ethnobotanical artifacts collected by Richard Spruce and housed in Kew’s Economic Botany Collection. In

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Box 2 (continued) future it may expand to include manuscripts associated with Spruce and other past botanists. The data and images of artifacts and plant samples have been repatriated and are now accessible on a free platform—the Herbario Virtual Reflora (URL link to reflora.jbrj.gov.br), being made available digitally to the descendants of the peoples visited by Spruce for more than a century, as well as the public in general. The research on the Rio Negro reported here has also disseminated results to different audiences in other ways: l

A training manual on biocultural research, published initially in Portuguese, the Manual de Etnobotaˆnica: Plantas, Artefatos e Conhecimento Indı´gena [8] (also available online), is now being translated into Tukano and Baniwa languages. In addition to giving visibility to this pioneering research program, the manual responds to the requests of local indigenous schools and organizations for research tools to develop their botanical knowledge.

l

A video based on the footage shot at the Sa˜o Gabriel da Cachoeira workshop and in the Kew collections. Luciana Martins and the Derek Jarman Lab at Birkbeck, produced a video entitled The Many Lives of a Shield (available online at vimeo.com/194984574). Cross-referencing Kew sources including manuscripts, herbarium samples and publications, the video provides glimpses of the stories told by the peoples of the Rio Negro about the ceremonial shield and the raw materials used to produce it, including the cosmologies associated with them. They also produced a video documenting the main activities of the workshop (vimeo.com/ 201827169).

l

An exhibition at Kew’s Shirley Sherwood Gallery of Botanical Art entitled “Plantae Amazonicae” by Kew artist-in-residence Lindsay Sekulowicz. Supported by Arts Council England, the exhibition ran from October 2017 until March 2018 to record audiences (>75,000). The exhibition represented Sekulowicz’s own encounters with Spruce’s ethnobotanical artifacts, herbarium specimens, and notebooks. Her artworks were juxtaposed with indigenous objects (including the shield video) and Spruce’s field observations. The exhibition made tangible to a non-indigenous, international audience the link between Amazonian plants, artifacts, history, indigenous knowledge, and contemporary art.

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Notes on Fieldwork The majority of researchers who are interested in ethnosciences have either received a training in an ‘exact’ science, like botany, or a training in a social science such as anthropology. Few have received training in both spheres of science. A good ethnoscientist needs to be an autodidact, to fill up the gap in formal education. Seeking council from a specialist in the other sphere of sciences is advisable. This is especially the case for a researcher with a training in exact science. The basics of botanical science are pretty much the same the world over, but local cultures can vary greatly, even among neighboring groups. Practical tips can be acquired through conversations with people who have worked and/or lived with the people of the culture that are being studied. If the aspiring ethnoscientist wants to acquire an object, or indeed some fresh food, what should he pay for it with? Barter, money, or both. If barter can be used, what type of goods can be used? If money, what is the average value of a basket, a fish, or a pineapple? If offered a drink during a party, can you refuse, must you drink the whole cup, or can you just take a sip? This is valuable information and will not normally be found in the literature. Of course, permission must be obtained from the institutions representing the state, but also from the leaders of the local communities. It is a mistake to think that official permission is enough. Even when in contact with local ‘leaders’, it is possible that they do not have real authority (in the sense that they can command). The ‘spokesman’ of a culture, communicating with the outside world, are often people who speak the official language of the country (e.g., Spanish or Portuguese) and have received some non-traditional education (e.g., a schoolmaster). This does not necessarily mean that they are the leaders. Always try to explain, as often as possible, what you are intending to do, preferably in community meetings. Who owns the traditional knowledge from local communities, and how can it be used? This is a complex problem, which is now governed by interdisciplinary protocols (e.g., Convention on Biological Diversity, Nagoya Protocol), national research rules, and local peoples. This is a complicated area. The “maker” of a biocultural collection may own it, be happy to share his knowledge, and be happy to trade it. Others, from the same community, may see this information as a key part of their culture, requiring a wider decision regarding intellectual property rights. Prior Informed Consent is important for working with local peoples, but who should sign it is another question. And how should the data be used? Ideally a full, collaborative partnership between scientists and local peoples, with clear protocols and outputs, should be clear at

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the start. Where should biocultural collections be located (e.g., museums), and/or should they be kept in the community? How can the data help support education, health, nutrition, sustainability, and incomes? How can previous collections and data (e.g., those collected by Richard Spruce) be used to support the outcomes? How to present the data in a format that is useful, and comprehensible? Collecting plant specimens usually requires a permit, at least in scientific research. You can collect them, photograph them, scan them, make objects from them. . . but modern herbaria require authorisation. For local people involved in collaborative research, you therefore probably need to involve a trained botanist. Taking specimens away for identification is important, but ideally one should keep duplicate specimens within the community. This is difficult, particularly in humid areas without electricity. Producing high-resolution images of the specimens may be preferable. Collecting herbarium specimens as a ‘voucher’ for ethnobotanical recording should, ideally, be stored permanently in the Herbarium. In the future, another researcher (taxonomist, ethnobotanist, botanist) can check the identification in accordance with the new or updated taxonomies. However, in some cases the voucher may be sterile (without flowers of fruits). In most cases these sterile specimens can be identified to species, but many herbaria will not them in the collection. Storing them in boxes on the office may work (for a while), but eventually they will probably be thrown away. One answer is to scan the specimens (at high resolutions) and then store them on an institutional database or website. Ideally, a multi-institutional database for ethnobotanical vouchers could be set up, allowing us to compare the collections and uses between other researchers. Aspiring ethnoscientists, working with local people, must not fall in the trap of seeing the people of the culture as mere ‘informants’. Seeing “traditional” people as coworkers is more efficient, more revealing, and more respectful. Seeking informal conversations while eating, resting, or preparing to sleep can reveal insights and information that will not appear in formal interviews. Explaining the scientific perspective of the things, alongside “traditional” explications, can be useful to establish a more informal relationship with local coworkers. Paying locals for gathering data may be problematic, as others in the community may feel they are left out. However, by trying to engage more people in the research (albeit not as coworkers) may help to resolve this. Indigenous people are often very interested in “western” knowledge, and eager to learn more about this, though this does not mean that the scientific explanation will be accepted without questioning. In the present day of scientific research, field periods are rather short. Gone are the days of the naturalist (e.g., Spruce and Bates) where researchers stayed many months or even years in the field. It

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takes time to establish a more relaxed working relationship with local people, to dismantle initial distrust, to work out the right methodology of research, and to find out the nuances of a certain culture. Perhaps the best method to overcome this problem is to try to join one project proposal with another, creating a string of projects with the same people working on the same or similar objects/subjects. If possible, the first project should be more educational-orientated than science-orientated. References 1. Salick J, Konchar K, Nesbitt M (eds) (2014) Curating biocultural collections: a handbook. Royal Botanic Gardens, Kew 2. Bahuchet S (2014) Curating ethnographic information for biocultural collections. In: Salick J, Konchar K, Nesbitt M (eds) Curating biocultural collections: a handbook. Royal Botanic Gardens, Kew 3. Gavin MC, McCarter J, Mead A et al (2015) Defining biocultural approaches to conservation. Trends Ecol Evol 30:140–145 4. Bishop LS (2014) Native American perspectives on biocultural collections and cultural restoration. In: Salick J, Konchar K, Nesbitt M (eds) Curating biocultural collections: a handbook. Royal Botanic Gardens, Kew 5. Rappaport J (2007) Ma´s alla´ de la escritura: la epistemologı´a de la etnografı´a en colaboracio´n. Rev Colomb Antropol 43:197–229 6. Bell JA (2017) A bundle of relations: collections, collecting, and communities. Annu Rev Anthropol 46:241–259 7. Kruel V, Martins L, Nesbitt M, Milliken W ˜ es de (2018) Nova pesquisa sobre as colec¸o Richard Spruce na Amazoˆnia: uma colaborac¸˜ao Brasil-Reino Unido. Ethnoscientia. https:// doi.org/10.22276/ethnoscientia.v3i2.127 8. Cabalzar A, Kruel V, Martins L, Milliken W, Nesbitt M (2017) Manual de etnobotaˆnica:

plantas, artefatos e conhecimentos indı´genas. Instituto Socioambiental e Federac¸˜ao das ˜ es Indı´genas do Rio Negro, Sa˜o Organizac¸o Paulo. issuu.com/instituto-socioambiental/ docs/manual_de_etnobotanica_baixa 9. Ribeiro BG (1995) Os ´ındios das a´guas pretas. Companhia das Letras, Sa˜o Paulo 10. van Velthem LH (2012) Objeto etnogra´fico e´ irredutı´vel? Pistas sobre novos sentidos e ana´lises. Bol Mus Para Emı´lio Goeldi Cieˆnc Hum Bele´m 7:51–66. https://doi.org/10.1590/ S1981-81222012000100005 11. Silva FA, Gordon C (2011) Objetos vivos: a curadoria da colec¸˜ao etnogra´fica Xikrin. In: Silva FA, Gordon C (eds) Xikrin: uma colec¸˜ao etnogra´fica. Universidade de Sa˜o Paulo, Sa˜o Paulo 12. Santos-Granero F (2012) Introduccio´n. In: Santos-Granero F (ed) La vida oculta de las cosas: teorı´as indı´genas de la materialidad y la personeidad. Abya-Yala, Quito 13. Lo´pez G, Claudia L, Franc¸ozo M, Van Broekhoven L, Ka’apor V (2017) Conversa˜es desassossegadas: dia´logos sobre colec¸o ˜ es c¸o etnogra´ficas com o povo indı´gena Ka’apor. Bol Mus Para Emı´lio Goeldi Cieˆnc Hum 12 (3):713–734. https://doi.org/10.1590/ 1981.81222017000300003

Chapter 16 Protocols and Ethical Considerations in Ethnobiological Research Sofia Zank, Rafaela Helena Ludwinsky, Graziela Dias Blanco, and Natalia Hanazaki Abstract In this chapter, we present and clarify the main protocols and ethical considerations for the development of ethnobiological research. We present the context in which such guidelines emerged, the operational aspects that should be observed, and the future challenges related to this issue. Key words Legal aspects, Code of ethics, Law 13123, Traditional knowledge, Indigenous peoples and local communities

1

Introduction After years of discussions on human rights, ethics in science, and access to knowledge and rights of indigenous and traditional peoples, we need to analyze the tools we have and how we use them to ensure an ethical commitment in research [1–3]. The development of ethnobiological and ethnoecological research must respect international and national laws and ethical precepts aimed at respecting human beings, the environment, and the rights of indigenous peoples and local communities (IPLC) and family farmers in relation to their traditional knowledge associated with biodiversity and to the genetic resources they manage and innovate. Before approaching the legal and ethical issues, we give an overview about the context that gave rise to the legislation related to environmental protection and genetic heritage, to the rights of IPLC, and to human rights in general. Thus, we first address a brief history of the regulation of the ethical and legal aspects of ethnobiological research through international and national frameworks (Fig. 1). Subsequently, we present the procedures that must be followed by researchers according to the ethical guidelines of the

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_16, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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Sofia Zank et al. United Nations Declaration on the Rights of Indigenous Peoples (2006)

CBD (1992)

ISE - Code of Ethics (2006)

International Milestones Nurenberg code (1947)

Declaration of Helsinki (1964)

C169 - Indigenous and Tribal Peoples Convention (1989) ISE (1988)

American Declaration on the Rights of Indigenous Peoples (2016)

IT (2001)

ICMSO Guidelines (1993)

Nagoya Protocol (2010)

Brazilian Milestones Brazilian Federal Constitution (1988)

SNUC LAW 9.985 (2000)

Decree 6040 (2007)

Biodiversity Decree Law 8.772 13.123 (2016) (2015)

Provisional Measure No. 2.186-16 (2001)

Fig. 1 Timeline with the main international and national legal marks about ethical and legal procedures in ethnobiological research

International Society for Ethnobiology (ISE), of other related documents, and of the Brazilian legislation. It is common for researchers who have never worked with human beings to feel confused and even discouraged because of the amount of information, procedures, and legal devices taken into account in the research. In this chapter, we present practical guidelines on these procedures for ethnobiological research, and we provide step-by-step procedures with some remarks at the end. 1.1 International Milestones

The tripod formed by the Nuremberg Code (1947), the Declaration of Helsinki (1964), and the Guidelines for Research on Human Beings of the International Council of Medical Sciences Organizations (ICMSO) [4] directs the discussions about freedom and people’s consent in research. The ethical attention and concerns for the consent of participation in research came first in the health studies. The trial of crimes committed by Nazi physicians in World War II aroused discussions about the position and voice of the patient, once the oath of Hippocrates had been broken for the benefit of a state. These discussions resulted in the Nurenberg Code in 1947, in which the first topic manifests free will in participating in research [5, 6]. To ensure this essential consent, the declaration of Helsinki (1964) implements the following items into the medical routine: a clear explanation of the objectives of the

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treatments applied, the risks and benefits, and the free will to participate and withdraw from the research at any time. In 1993, the International Council for International Organizations of Medical Sciences, in collaboration with the World Health Organization, created ethics committees to review projects and research protocols [4]. With a convergence in relation to ethical precepts, the advancement of discussions on access to traditional knowledge and benefit sharing came later with the Convention on Biological Diversity (CBD), the Food and Agriculture Organization (FAO) International Treaty, and the Nagoya Protocol. The rights of indigenous peoples are specifically addressed in International Labour Organization (ILO) Convention 169, the American Declaration of Indigenous Peoples, and the United Nations Declaration on the Rights of Indigenous Peoples. From these international milestones, each signatory country has been developing its specific legislation and procedures to address these issues. The CBD is an instrument of international law that was agreed upon at the United Nations meeting in 1992. The CBD addresses all issues that directly or indirectly relate to biodiversity, serving as a legal and policy framework for other specific environmental conventions and agreements. Within the CBD, for the first time, the importance of IPLC in the conservation of biodiversity and their rights in relation to the knowledge they have produced about biodiversity and the genetic heritage they have conserved and innovated were recognized. In addition to instituting the notion that genetic resources should sovereign to the countries in which they are located, this milestone also mentions the fair and equitable distribution of the benefits derived from the utilization of genetic resources and associated knowledge [1]. The International Treaty on Plant Genetic Resources for Food and Agriculture (IT PGRFA, or simply IT) of the Food and Agriculture Organization of the United Nations (FAO) was signed in Rome in 2001. Today, it is intrinsically linked to the CBD. While the CBD deals with native biodiversity, the IT deals with agricultural biodiversity [7]. The objective of the IT is conservation and sustainable use of plant genetic resources for food and agriculture and the fair and equitable sharing of the benefits derived from their use for sustainable agriculture and food security [7]. The 2010 Nagoya Protocol, which has been in force since 2014, is a supplementary agreement to the CBD and seeks to achieve the objectives of the CBD and IT. Prior informed consent and agreements on the fair and equitable sharing of benefits are fundamental elements, in addition to the recognition of customary laws and procedures and the traditional use and exchange of genetic resources [8]. The Nagoya Protocol was signed by Brazil, but it has not been ratified, and in this way, it still has no force of law in our country.

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Convention 169 of the International Labor Organization (ILO), signed in 1989, is the most important international policy document dealing specifically with the rights of indigenous and tribal peoples. Convention 169 affirms rights concerning the identity, traditionally occupied territories, and the rights of participation of indigenous peoples in the use, management, and conservation of their territories, including free, prior, and informed consultation. Brazil ratified the convention in 2002 through Decree 5051 of 2004. The United Nations declaration of December 20, 2006, was another important milestone for the rights of indigenous peoples in Latin America. Since then, the individual rights of each indigenous person have been recognized as equal to that of all other citizens of each nation. In addition, it highlighted the importance of safeguarding and recognizing the cultural distinctions of indigenous communities as unique. Among the duties that states have with their indigenous peoples are the provision of access to quality public schooling and health and the protection and encouragement of cultural practices. Also concerning indigenous peoples, the American Declaration on the Rights of Indigenous Peoples (ADRIP) by the Organization of American States (OAS) promotes and protects the rights of indigenous peoples in the Americas. Approved in 2016, this statement took 17 years to be written and approved. ADRIP addresses four new themes: (1) recognition and respect for the multicultural and multilingual nature of indigenous people; (2) recognition of the different forms of community organization; (3) the recognition and right of indigenous peoples to maintain and promote their own family systems; and (4) freedom of choice for indigenous children, which ensures that each child must have the right to enjoy her/his own culture, religion, or language [9]. Another important point is related to indigenous communities that are isolated or in a state of initial contact and that have the right to remain in this condition and to live freely and according to their cultures. Within the scope of ethnobiological studies, the Declaration of Bele´m (1988) is recognized as the main international milestone that guides the ethics code of the International Society for Ethnobiology (ISE). This declaration also influenced other documents, such as the Code of Ethics of the Sociedad Latino Americana de Etnobiologı´a (SOLAE) [10] and the Tkarihwaie´:ri Code of Ethics Conduct [1]. 1.2 National Milestones: The Brazilian Context

Supported by the discussions on the international scenario, the National Health Council (linked to the Brazilian Ministry of Health) has standardized the research guidelines in the field of health and established ethics committees in human research since 1988. More recently, the guidelines for research with human beings in the health area were extended to research with human beings in other areas, especially through the Resolutions of the National

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Health Council 466/2012 and 510/2016. The latter resolution, for example, defined rules that are applicable to research in the social sciences and humanities in which the methodological procedures involve the use of data directly obtained from participants. Nevertheless, it is common to find scientific articles in which the consent to participate in the research is not mentioned [11]. Regarding the environment, the legal mark of the Federal Constitution of 1988 ensures a specific chapter (article 225) that imposes the duty to defend and preserve the environment on the public authority and the community. The responsibilities of public authorities include the preservation of the diversity and integrity of the genetic heritage of the country, the supervision of entities dedicated to the research and manipulation of genetic material, and the definition of territorial spaces and their components to be especially protected. Part of these responsibilities were regulated through Law 13123/2015 and Decree 8772/2016, which pertain to access to genetic heritage, protection, and access to the traditional knowledge associated with biodiversity, and benefit sharing for the conservation and sustainable use of biodiversity. These two regulations require the completion of legal procedures by researchers, which will be further detailed. These responsibilities of the public authority also resulted in Law 9985/2000, which established the National System of Conservation Units (or Sistema Nacional de Unidades de Conservac¸˜ao, SNUC). The establishment of the SNUC defined criteria and standards for the creation, implementation, and management of protected areas, or conservation units, also including areas for sustainable use. Among the issues addressed by this law, the scientific community is encouraged to articulate the value of the knowledge of traditional people in the development of research on the biodiversity of protected areas and on sustainable use. Scientific research within protected areas depends on prior approval and is subject to the supervision of the institution responsible for its administration. At the federal level, the Normative Instruction of the Chico Mendes Institute for Biodiversity Conservation (ICMBio) number 03/2014 established and regulated the Biodiversity Authorization and Information System (SISBIO). Through SISBIO, researchers must request the ICMBio authorizations and licenses for scientific or didactic activities that involve the use of biodiversity or access to federal protected areas. Another important advance of the Federal Constitution of 1988 was the inclusion of articles focused on indigenous rights. Articles 231 and 232, together, are important tools that recognize and protect the cultural rights and knowledge of the indigenous peoples of Brazil. These articles assure the recognition of the cultural and linguistic practices of indigenous peoples; the recognition and legitimacy of the multicultural presence of indigenous peoples in Brazil; the protection and rights to land, water, and natural

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resources; and the legitimization of indigenous peoples as independent organizations, being able to act in defense of their own rights and interests. In Brazil, we consider indigenous people as those of Amerindian origin (or descendants of pre-Columbian inhabitants). In Brazil, the public agency responsible for research permission with indigenous people is called the National Indian Foundation (FUNAI). FUNAI was created in 1967 during the period of the military dictatorship of Brazil (1964–1985). This initial period of operation of FUNAI was marked by two situations; on the one hand, strategies were created to attract indigenous people to areas of interest, such as defense battalions, and, on the other hand, they were removed from other strategic areas (e.g., less freedom in selfmanagement of their lands) [12, 13]. This situation was achieved because of a monopoly on tutelary relationships, in which activities such as access to education and health were centralized in FUNAI. This situation left indigenous people with little or no freedom of action, becoming extremely dependent on FUNAI for any type of action. Structurally, FUNAI was divided (and still continues today) into three spatial levels: national, regional, and local. From the 1970s and 1980s, social and indigenous movements began to emerge more strongly in Brazil and in the world. These movements fostered the emergence of institutions and legislation in favor of indigenous communities, which influenced some changes in FUNAI [13, 14]. FUNAI, as of Presidential Decree No. 7056, underwent a major administrative restructuring in 2009. From this moment, qualified technicians began to develop activities and plans, with the participation and performance of indigenous people. However, the great challenge of FUNAI today is, with little recourse and lack of professionals, to be able to deal with a great diversity of indigenous people with diverse demands. Additionally, the National Policy for the Sustainable Development of Traditional Peoples and Communities (PNDSPCT), established by Decree 6040/2007, formally recognized the traditional Brazilian communities and extended to these people the rights that were previously reserved to indigenous and quilombolas, according to the Federal Constitution of 1988. The IPLC are defined in this decree as follows: Culturally differentiated groups recognized as such, having their own forms of social organization, which occupy and use territories and natural resources as a condition for their cultural, social, religious, ancestral and economic reproduction, using knowledge, innovations and practices generated and transmitted by tradition.

IPLC include quilombolas, gypsies, people from the African matrix, artisanal fishers, rubber tappers, coco-de-babassu harvesters, grassland communities, faxinalenses, riverine people, caic¸aras, sertanejos, azoreans, and pantaneiros, among others (see also

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Decree 8750/2016, which establishes the National Council of Traditional Peoples and Communities). PNDSPCT aims to recognize, strengthen, and guarantee the territorial, social, environmental, economic, and cultural rights of IPLC, with respect and appreciation for their identity, their forms of organization, and their institutions. Among these rights are those related to the recognition and protection of traditional knowledge, practices, and uses, which are the focus of ethnobiological and ethnoecological research. 1.2.1 Law 13123 and Decree 8772

Law 13123 and Decree 8772 (which have been in force since 2015 and 2016, respectively) set the current legal mark related to CBD, determining the access to genetic heritage, providing protection and access to the traditional knowledge associated with biodiversity, and establishing benefit sharing for conservation and sustainable use of biodiversity [15, 16]. Brazil ratified the CBD in 1994, which became a law, but it did not become operative without regulation. The first regulation to operationalize it was Provisional Measure (PM) 2186–16, approved in 2001. This PM created the Genetic Heritage Management Council (Conselho de Gesta˜o do Patrimoˆnio Gene´tico, CGEN) and determined that access to and remittance of genetic heritage and access to associated traditional knowledge in the country depended on the authorization of this council. This PM was controversial [11] and criticized due to its excessive bureaucracy [17]; however, over time, the resolutions and deliberations of the CGEN created conditions for the system to function in a slightly more agile way, aiming to adapt the regulations to the reality of scientific research and technological development [18]. The PM had been in force for almost 15 years when it was replaced by the Law of Biodiversity. This law has brought both advances and setbacks in relation to the rights of IPLC and traditional farmers. According to the Law 13123, in relation to scientific research, the access to genetic heritage or associated traditional knowledge, carried out solely for this purpose, does not require prior authorization. However, researchers need to electronically register in the National Genetic Heritage and Associated Traditional Knowledge Management System (Sistema Nacional de Gesta˜o do Patrimoˆnio Gene´tico e do Conhecimento Tradicional Associado, SisGen), which has been in operation since 2017. The law deals with the traditional knowledge associated with the genetic heritage of indigenous peoples, traditional communities, and traditional farmers, with the adaptation of the term IPLC used in the CBD to maintain consistency with other Brazilian regulations. It is worth to highlight that the segments affected by the law criticized these denominations, since they recognize themselves as indigenous peoples, traditional peoples and communities, and family farmers. Since the approval of the Law 13123, registration or authorization for

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access to traditional knowledge, even that obtained from secondary sources (e.g., fairs, publications, inventories, films, scientific articles, registers, and other forms of systematization and registration of this knowledge), has been required. In addition, the research that does not access the traditional knowledge, but access the genetic heritage, or “information of genetic origin of plant species, animal, microbial species or otherwise, including substances derived from the metabolism of these living beings,” also needs to be registered on SisGen. The law divides the traditional knowledge associated with genetic heritage into two categories: (1) identifiable origin and (2) non-identifiable origin. With identifiable origin, it is possible to identify at least one person or community that holds it. Non-identifiable origin is when it is not possible to define a people or community that holds such knowledge. According to Decree 8772, “Any indigenous people, traditional community or traditional farmer who creates, develops, holds or retains certain associated traditional knowledge is considered to be an identifiable source of that knowledge.” This concept corroborates the consensus among IPLC about the fact that all traditional knowledge is of “identifiable origin” [19] (Box 1). Box 1 What Is the Consequence of Considering Knowledge as Being of Non-identifiable Origin?: According to Law 13123, for this type of knowledge, prior informed consent is not mandatory. In other words, a company or researcher can access it without prior informed consent. In addition, the sharing of benefits arising from access to this type of knowledge would be destined to the National Fund for Benefit Sharing. In what other cases is there exemption from prior consent? This occurs in cases that access the genetic heritage of traditional local or Creole variety or locally adapted breed or Creole for agricultural activities. ...but the absence of prior consent of the IPLC or traditional farmer who creates, develops, holds or preserves variety or race is considered a violation of human rights!

One of the innovations of the law was the creation of the National Benefit Sharing Fund (Fundo Nacional de Repartic¸˜ao de Benefı´cios, FNRB), which aims to value genetic heritage and associated traditional knowledge and promote its use in a sustainable way. However, one of the controversial points of benefit sharing is the existence of several exemptions that have led to distortions of the foundations of the CBD and in the international legal framework. According to the Law 13123, benefit sharing only occurs when there is economic exploitation of a finished product or

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reproductive material arising from accessing genetic heritage or associated traditional knowledge. The law exempts the manufacturers of intermediary products, micro enterprises, small businesses, and individual micro entrepreneurs from sharing benefits. The law seeks to guarantee the rights of indigenous peoples, traditional communities, and traditional farmers to (1) have recognized their contribution to the development and conservation of genetic heritage, in any form of publication, use, exploitation, and dissemination; (2) have indicated the origin of access to associated traditional knowledge in all publications, uses, holdings, and disclosures; receive benefits for the economic exploitation by third parties, directly or indirectly, of associated traditional knowledge; (3) participate in the decision-making process on issues related to access to traditional associated knowledge and benefit sharing resulting from such access; (4) freely use or sell products that contain genetic heritage or associated traditional knowledge; (5) conserve, manage, store, produce, exchange, develop, or improve reproductive material that contains genetic heritage or associated traditional knowledge.

2

Ethical and Legal Procedures in Ethnobiological Research

2.1 Ethical Procedures

Prior to concerns about legal procedures, it is essential that researchers be enlightened and oriented about ethical procedures in ethnobiological research. We use here as a reference the ISE code of ethics, developed over more than a decade and the product of a series of consensus-based discussion forums involving ISE members [2]. We chose this document due to its historical importance, but we emphasize the convergences with the Code of Ethics of the SOLAE and the Tkarihwaie´:ri Code of Ethics Conduct. An important value here is the concept of mindfulness, calling our obligation to be “fully aware of one’s knowing and unknowing, doing and undoing, action and inaction” [2] (see also translations in several languages, including Brazilian Portuguese). The 17 principles, aligned with the compliance with national and international legislation and customary practices (Box 2), describe the conduct of research or the organization of collections, publications, databases, and audio or video recordings, among other research products and related activities. Despite a well-marked political direction, we know that the absorption of such principles by ethnobiological researchers is still timid.

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Box 2 Principles for the Ethnobiological Research with Indigenous Peoples, Traditional Societies, and Local Communities (IPLC) (Adapted from ISE [2]): 1. Principle of prior rights and responsibilities IPLC have prior proprietary rights over interests in and cultural responsibilities for all air, land, and waterways and the natural resources within them that these peoples have traditionally inhabited or used, together with all knowledge, intellectual property, and traditional resource rights associated with such resources and their use. 2. Principle of self-determination IPLC have a right to self-determination (or local determination for traditional and local communities), and researchers and associated organizations will acknowledge and respect such rights in their dealings with these peoples and their communities. 3. Principle of inalienability The rights of IPLC are inalienable in relation to their traditional territories and the natural resources within them and their associated traditional knowledge. These rights are collective by nature but can include individual rights; and the nature, scope, and alienability of their respective resource rights regimes must be determined by themselves. 4. Principle of traditional guardianship Humanity has a holistic interconnectedness with the ecosystems of our Sacred Earth and the obligation and responsibility of IPLC to preserve and maintain their role as traditional guardians of these ecosystems through the maintenance of their cultures, identities, languages, mythologies, spiritual beliefs, and customary laws and practices. 5. Principle of active participation It is crucial that IPLC actively participate in all phases of research and related activities from inception to completion, as well as in the application of research results. Active participation includes collaboration on research design to address local needs and priorities and the prior review of results before publication or dissemination. 6. Principle of full disclosure IPLC are entitled to be fully informed about the nature, scope, and ultimate purpose of the proposed research (including objective, methodology, data collection, and

(continued)

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Box 2 (continued)

the dissemination and application of results). This information is to be given in forms that are understood and useful at a local level, considering cultural preferences and modes of transmission of these peoples and communities. 7. Principle of educated prior informed consent Educated prior informed consent is mandatory before any research is undertaken at individual and collective levels, as determined by community governance structures. Prior informed consent is an ongoing process that is based on a relationship and maintained throughout all phases of research. IPLC have a right to say no. 8. Principle of confidentiality IPLC, at their sole discretion, have the right to exclude from publication and/or to have kept confidential any information concerning their culture, identity, language, traditions, mythologies, spiritual beliefs, or genomics. 9. Principle of respect This principle recognizes the necessity for researchers to respect the integrity, morality, and spirituality of the culture, traditions, and relationships of IPLC with their worlds. 10. Principle of active protection Researchers must take active measures to protect and enhance the relationships of IPLC with their environment and thereby promote the maintenance of cultural and biological diversity. 11. Principle of precaution Proactive and anticipatory actions are needed to identify and to prevent biological or cultural harms resulting from research activities or outcomes, including a responsibility to avoid imposing external or foreign conceptions and standards. 12. Principle of reciprocity, mutual benefit, and equitable sharing IPLC are entitled to share in and benefit from tangible and intangible processes, results, and outcomes, direct or indirect, and over the shorter and longer term, from ethnobiological research and related activities that involve their knowledge and resources. 13. Principle of supporting indigenous research This principle recognizes and supports the efforts of IPLC in undertaking their own research based on their

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own epistemologies and methodologies. For that, capacity building, training exchanges, and technology transfer for IPLC should be included in research whenever possible. 14. Principle of the dynamic interactive cycle Research and related activities should not be initiated unless all stages can be completed: (a) preparation and evaluation; (b) full implementation; (c) evaluation, dissemination, and return of results; and (d) training and education as an integral part of the project. All projects must be seen as cycles of continuous and ongoing communication and interaction. 15. Principle of remedial action Every effort will be made to avoid any adverse consequences to IPLC from research and related activities and outcomes. Any such remedial action may include restitution, when agreed to and appropriate. 16. Principle of acknowledgement and due credit IPLC must be acknowledged in accordance with their preference and given due credit in all agreed-upon publications and other forms of dissemination for their tangible and intangible contributions to research activities. Coauthorship should be considered when appropriate. This extends to secondary or downstream uses and applications. 17. Principle of diligence Researchers are expected to have a working understanding of the local context prior to entering into research relationships with a community and to conduct research in the local language to the degree possible.

2.2

Legal Procedures

2.2.1 National System of Research Ethics Involving Human Subjects

Currently, international organizations and research funding agencies around the world have developed their own project submission protocols [20]. We recommend studying the current legislation and protocols specific to the country in which data collection will take place. We recall that protocols may change, but prior information and consent for research participation remain as a solid foundation. In Brazil, according to the legal frameworks of the health area for research with human beings, which also apply to research even

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outside the health area, research projects must be previously approved by a research ethics committee of a university or research ´ tica em Pesquisa, CEP, or Comiteˆ de E´tica institution (Comiteˆ de E em Pesquisa com Seres Humanos, CEPSH) and be consented to by the research collaborators. A CEP is an institutional body that has the role of reviewing scientific research projects, besides the assignment of an advisory and educational role [21, 22]. A crucial point in this approval by a CEP is the preparation of a document of free informed consent (Termo de Consentimento Livre e Esclarecido, TCLE). The TCLE, also known as prior consent, has the role of clarifying and protecting the research collaborator, as well as the researcher [23]. These procedures converge with some of the requirements of the Law 13123, which are dealt with in the following item of this text. Then, in Box 3, we summarize a checklist with guidelines for the steps prior to conducting the research and for the elaboration of a TCLE so that it ensures the ethical precepts that guide the studies with human beings. In the case of access to knowledge of IPCL and traditional farmers, which should follow the Law 13123, it is required to include the impacts resulting from the execution of the research, the rights and responsibilities of each party, the right to deny access, and in the case of research with an economic bias, information on the distribution of benefits (Articles 16 of Decree 8772/2016).

Box 3 Guidelines and Checklist of the Mandatory Steps in the Preparation of a Prior Informed Consent Term (Termo de Consentimento Livre e Esclarecido, TCLE) in Brazil: 1. Invitation to participate in the research Participation in a research project is not mandatory. In this moment, the researcher should try to establish a relationship of trust between the researcher and the research collaborator. Thus, the invitation to participate is essential. 2. Identification of the research Research title, objectives, justification, and procedures should be identified, always written clearly and objectively. 3. Research methods How will the data be collected? Who will do interviews? What will be included in the interview? How will this data be recorded or registered?

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Box 3 (continued) 4. Right to not participate The document should statemake clearly the right of refusal of the research participation at any time or stage of the research. 5. Research follow-up Besides the researcher, who else will be doing the research? The researcher must provide the name of your supervisor and of the people who will help with data collection and their respective links to their institutions. 6. Secrecy The researcher needs to explain how the data will be stored and assure the interviewee’s anonymity. 7. Publications and use of information Provide a brief explanation of how the data will be used (publications of articles, development of drugs, cosmetics, etc.). We encourage a mention about benefit sharing and returning the data to the research collaborators and how it is intended to happen. 8. Risks and benefits Risks of the research are commonly overlooked in the formulation of the TCLE. Even if your data collection involves an interview, you need to consider tiredness and boredom during participation in the survey, as well as embarrassment, discomfort, and even breach of confidentiality. The latter, even if involuntary, should be included in the TCLE. Reimbursement and indemnification must also be guaranteed in the case of any damage resulting from the research. Regarding the benefits, all scientific research is expected to bring some benefit to society. We can then explain what we expect to achieve from tangible and intangible benefits in the short and long term. In addition, depending on the type of benefit, such as those resulting in monetary outcomes of the research, you will need to describe in detail how it will be assured to the collaborator. 9. Consent/agreement The TCLE must contain a field for registration of the acceptance to collaborate with the research. When the subject is underage, illiterate, or has some intellectual disability, the document then should request the consent of the parents or legal guardian. The TCLE does not necessarily have to be obtained in writing: other media are allowed (see CNS 510/16).

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Box 3 (continued) 10. Researcher’s signature The researcher’s signature as the researcher is a way of legally showing the commitment to comply with the terms of the ethnobiological code of ethics and the current resolution related to research with human beings used in the country (e.g., CNS 466/12 in Brazil; always remember to cite these documents). 11. How to contact the researcher or the ethics committee Include information about how to contact the researcher, research group or laboratory, and the ethics committee that approved the project (address, telephone of the researcher and supervisor, and email addresses).

In Brazil, the submission of a research project is done through an online portal called Plataforma Brasil (http://plataformabrasil. saude.gov.br). Through this portal, all documents related to research should be sent, and the evaluations can then be monitored (Box 4). When the project is approved, annual or final reports (depending on the duration of the project) should be sent to the platform as a form of follow-up of the research. In the case of non-approval of the project by the indication of pending issues, it is necessary to carefully read the evaluation to make a new submission. The project must be approved before data collection starts. Box 4 Checklist for Insertion of Documents in the Plataforma Brazil: 1. Research project. 2. Model of the prior informed consent term (TCLE); see guidelines in Box 3. 3. Authorizations of competent bodies in the case of floristic and faunistic collections. 4. Authorization of community leaders (if applicable). 5. Authorization statement of the participating institution(s): statement of the institution(s) involved authorizing the research signed by the person in charge of the institution(s). 6. Filling in the form with details of the research in Plataforma Brasil. 7. Cover sheet generated within Plataforma Brasil: at the end of the completion of the form, a cover page will be made available, which must be signed by the coordinator of the research and the person responsible for the proposing institution.

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2.2.2 Access to Traditional Associated Knowledge and Genetic Resources and Equitable Sharing of Benefits

To comply with the Law 13123 and Decree 8772, we present the steps for the development of a research study that does not aim at the economic exploitation of a product by the user (researcher, company, government, etc.), which is the reality of most ethnobiological research. However, in the case of research with economic exploitation, it is necessary for the reader to seek detailed information on the process of authorization of the research and on equitable benefit sharing [15, 16]. The first step in the development of the research is to obtain prior and informed consent by the community to be investigated, which as mentioned before, is convergent with the objectives of obtaining the free informed consent or TCLE (Box 3). According to the law, prior informed consent may occur by signing a prior consent term, obtaining an audiovisual record of consent, ascertaining an opinion of the competent official body, or being recognized by the community protocol. Community protocols are internal rules created by the communities themselves that say how the government, companies, researchers, and others interested in accessing their associated traditional knowledge should proceed in a way that respects customs, uses, and traditions. The evidence of consent instrument must be prepared in an accessible language, containing the description of the consent process, the organization and representation of the community studied, and information about the research (objective, duration, budget, financing, etc.), uses that are intended to provide the knowledge, the area of coverage of the project and the communities studied, and whether the community received technical and legal advice in the process (Articles 17 of Decree 8772/2016). Although it is possible in Brazilian legislation to prove prior and informed consent through the opinion of a competent official body, it is imperative that prior and informed consultation with the people or community to be studied occurs, not violating ethical precepts and internationally recognized human rights [2, 24]. We believe that all ethnobiological and ethnoecological research should follow the ethical precepts of the ISE Code of Ethics (see Sect. 2.1) and the legal instruments internationally recognized about the rights of IPLC (see Sect. 1.1), even in the cases in which the Law 13123 suggests that access to knowledge of unidentified origin does not require prior informed consent. In other words, all research must request prior and informed consent of the community and respect the collective organization (e.g., even if the research works with local experts, it is important to attain a collective authorization for the research through its community-based organization). It is also important that the community should agree with the deadline for the registration of SisGen during the consent. The researcher must be aware that the community has the right to deny access to their associated traditional knowledge, and this decision must be respected.

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After obtaining the prior informed consent of the community to be studied, the researcher can register on SisGen (see checklist in Box 5). It should be noted that research on secondary data must also be registered on SisGen. Although the Brazilian legislation only requires the register of research with indigenous peoples, traditional peoples and communities, and traditional farmers, we suggest that research with local communities be also registered as a way of safeguarding the knowledge of these groups that in the future may have economic exploitation. According to the law, the registration must be made before the following: the dissemination of results (final or partial) in scientific circles; the shipment of samples to third parties; the application for an intellectual property right on a process, product, or cultivar developed from access; the notification to CGEN of the finished product or reproductive material developed as a result of access; and the commercialization of the intermediate product. Any research that does not access the traditional knowledge of thepeoples and communities mentioned in the law, but access genetic heritage also need to be registered on SisGen.

Box 5 Checklist for Registration in the National Genetic Heritage and Associated Traditional Knowledge Management System (Sistema Nacional de Gesta˜o do Patrimoˆnio Gene´tico e do Conhecimento Tradicional Associado, SisGen): 1. Basic information about the research or technological development activity, including: – Summary of the activity and its objectives. – Application sector, development.

in

the

case

of

technological

– Expected or obtained results, depending on the time of registration. – Research staff, including information on students or fellows. – Other national institutions participating in the execution of the activity, when applicable, including international institutions. – When the activity happened or will happen? – What was the genetic heritage accessed (identification at the strictest possible taxonomic level)?

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Box 5 (continued) – Declaration whether the genetic heritage is a traditional local or Creole variety or locally adapted or Creole breed, or if the species is on the official list of species threatened with extinction. – Who provided the traditional knowledge associated and a description of the sources of this knowledge (including secondary sources)? – Where the study was done (geo-referenced coordinates), except for knowledge of non-identifiable origin? – Previous registration or authorization number in the case of research or technological development carried out after June 30, 2000. 2. Testimony for obtaining prior informed consent of the provider of associated traditional knowledge of identifiable origin. 3. If needed, request the confidentiality of information by presenting the relevant legal foundation and a non-confidential summary. 4. When it applies, declare if it is a case of legal exemption or non-allocation of benefit sharing.

If information provided on SisGen changes, the researcher must update the relevant data at least once a year. Researchers should indicate the source of the associated traditional knowledge in disclosures and publications. This is a way to recognize the traditional knowledge and, most importantly, is an IPLC right that should be respected. The system still needs to be much improved, since some points currently make it difficult for researchers to legalize their research, such as entering the CPF or CNPJ of research informants conducted since 2000 or the need to manually enter the traditional knowledge information for each accessed genetic resource. Thus, the researcher must be aware that many adjustments in the system are still expected, but they depend on the managers of the SisGen. The legislation determines fines for infractions, such as (a) accessing traditional knowledge of identifiable origin without obtaining prior informed consent, or in disagreement with it; (b) disclosing results, final or partial, in scientific or communication media without previous registration; (c) failing to indicate the

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origin of associated traditional knowledge of identifiable origin in publications, uses, holdings, and disclosures resulting from the access; and (d) presenting totally or partially false or misleading information, whether in the official systems or in any other administrative procedure related to the genetic heritage or associated traditional knowledge. 2.2.3 Research with Indigenous Peoples

In Brazil the institutions responsible for authorizing research with indigenous peoples were those already mentioned in this text (CEP, CGEN, SisGen, SISBIO, and FUNAI). To obtain authorization, the researcher may start the procedures with a CEP and FUNAI, at the same time. The projects with indigenous people submitted to local ethics committees (CEP) through Plataforma Brasil will be directed to the National Ethics Committee (Comissa˜o Nacional de E´tica em Pesquisa, CONEP). To begin the authorization process by FUNAI, the researcher must submit a series of documents by conventional mail, and the checklist of the documents to be forwarded is provided in Box 6 [25]. After the processing of the project in the Plataforma Brasil and the acceptance of the documents provided, the researcher may send the technical advice from CONEP to FUNAI. Then, FUNAI is responsible for collecting the signatures of the indigenous community and presenting them the project. However, it is important to note that this structure of acquisition of authorizations to work with indigenous peoples often becomes impractical within the reality of the researcher, who has limited time to conduct his research. However, FUNAI is divided structurally at national, regional, and local levels, and due to the large number of villages in Brazil, the practice of collecting signatures involves a lot of complexity and makes the formal authorization difficult. For this reason, the collection of permits is often carried out by the researcher herself/himself, even if in theory, it is not allowed to enter the village until the authorization is obtained. Moreover, the lack of communication between institutions such as FUNAI and the local ethics committees makes the process even slower and more difficult. In addition to these authorizations, in the case of collection of botanical, animal, microbiological, or fungal material, as well as when the village is located within a protected area, the researcher must register on SISBIO, and in the case of seeking access to associated traditional knowledge or genetic resources, the researcher must also register the research on SisGen (see Sect. 2.2.4).

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Box 6 Checklist of the Documents Needed to Be Sent to FUNAI: 1. Letter from the researcher requesting permission to enter any indigenous territory, addressed to the FUNAI Presidency, specifying the indigenous land and village, indigenous people, entry period, contact information of the researcher, and a list of team members, if any. 2. Letter of the research advisor, presenting the researcher. 3. Statement of formal link with the research institution. 4. Research project. 5. Researcher’s curriculum. 6. Copy of the personal identification documents of the researcher and the team. In the case of a foreign researcher, a copy of the passport with identification and entry visas in the country. 7. Authorization published by the Ministry of Science, Technology, and Innovation (MCTI) when it is a foreign researcher.

2.2.4 Collection of Biological Material and Research in Protected Areas

Many ethnobiological researchers must also comply with regulations related to the collection of biological material (animals or plants) in areas that are protected as conservation units. Authorization for the collection of biological material and research in federal protected areas and caves is carried out through SISBIO (http:// ibama.gov.br/sisbio/sistema/). Researchers must register and continually update their personal data, the identification of the relevant scientific institution, and their curriculum in the Lattes Platform of the National Council of Scientific and Technological Development (Conselho Nacional de Desenvolvimento Cientı´fico e Tecnolo´gico, CNPq). For registration in SISBIO, besides the project, the researcher must provide other details, such as the taxa that will be collected, captured, marked or transported; the intended destination for the collected material; when the collection will happen; and whether there will be access to the genetic heritage or associated traditional knowledge. In the case of the collection of botanical, fungic, or microbiological materials that are not in protected areas (conservation units) and species that are not threatened with extinction, it is not necessary to request authorization via SISBIO.

3 Conclusion: Step-by-Step Protocol to the Ethnobiological Research Complying with Ethical and Legal Issues To help the reader with the understanding of the complexity of legal issues, we present a summary of the steps that researchers in

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Fig. 2 Summary of steps to comply with legal procedures in ethnobiological research

the field of ethnobiology and ethnoecology must carry out to conduct their research in accordance with Brazilian legislation (Fig. 2). Prior to using this flowchart, we assume that the research does access knowledge. We also assume that all institutions and systems implicated are fully operational.

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3.1 Understanding the Local Reality

Before beginning any research activity, there should be a good understanding of the local context, the representative institutions of the community, and their interest in the research, as well as knowledge of community cultural protocols.

3.2 Prior Informed Consent

Prior informed consent must be established before conducting any research activity. This consent needs to be developed with the persons or deliberative bodies identified as the most representative authorities of each potentially affected community. In addition, in the case of projects involving more than one community, this process should be carried out with each community being studied. It is essential to emphasize that before any legal obligation, there is an ethical duty to request prior informed consent.

3.3 Legal Authorization Processes

The researcher may request authorization from CEP or CONEP (through the Brazil Platform). After approval, the process of prior informed consent can start. If the community authorizes the project, the next steps can be followed: (a) If the research accesses genetic patrimony or associated traditional knowledge without economic interest, it must be registered on SisGen. We recommend that all ethnobiological research be registered, as a way to safeguard the knowledge of local communities, even though there is no such requirement in Brazilian law. In the case of research with economic interest, this should be notified in SisGen, and the benefit-sharing procedure must be carried out. (b) If botanical, fungal, zoological, and microbiological material that is threatened with extinction or within a protected area will be collected, the researcher will need the authorization of SISBIO. After the project is authorized by CEP or CONEP and SISBIO and registered in SisGen, the researchers must be attentive to the deadlines for reports and to update the information when needed. In the case of research with indigenous peoples, authorizations must be sent to FUNAI and CONEP concomitantly.

3.4 Conducting Research Using Good Faith

Research should be conducted using good faith, respecting and acting in accordance with the cultural norms and dignity of all the potentially affected communities, and respecting the communities’ relevant norms and belief systems following a holistic context.

3.5 Dissemination and Publication of Results

At this stage, it is important to specify attribution, credit, authorship, coauthorship, and due recognition to all contributors to the research processes and their results, recognizing and valuing local specialists as well as academic experts. In addition, all educational uses of the research materials should be consistent with good faith and respect for cultural integrity and developed in collaboration with such communities for mutual use. Researchers must pay attention to other agreements needed before publications and dissemination of the results, such as for the use of photos and parts of interviews or even data about species and uses based on traditional knowledge.

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Sharing Results

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The ways to share the results, even when not framed in the legal stipulations for benefit sharing, should be agreed upon with the communities. This process should define the format, information, and results that will be shared with each affected community. It is important to support community information management systems, such as local registries and local databases. Sometimes, producing materials that can be used in local schools can be a way to put traditional knowledge in the foreground, or producing printed materials using accessible language, short films, or other ways to disseminate the results among the research subjects can be useful. Researchers should be creative and be concerned with the local reality. At the time of closing of this chapter, it is important to emphasize that the legal system still presents operational problems that can undermine the very initial purpose behind this discussions, which is the rights of IPLC. Solving these problems is a challenge to the governmental institutions involved, and it also requires the positioning and informed opinions of ethnobiology researchers. Finally, we emphasize the importance of ethnobiologists and ethnoecologists, whether or not they are members of scientific societies, to ensure that project proposals, planning, and budgeting are appropriate to interdisciplinary and multicultural research collaboration and that they are in accordance with the ethical principles guiding the ethnobiological research. In this way, we should also sensitize funding agencies and academic institutions on the increased time and costs that may be involved in adhering to these ethical principles. Ethnobiological research should involve not only the conventional steps of theoretical rationale/data collection/discussion of results/publication but also need to adequately incorporate both prior essential elements, such as prior informed consent and legal authorizations, and subsequent elements, such as the dissemination of results and benefit sharing. It is not just about following legal norms; it is mainly about respecting the fundamental human rights of indigenous peoples and traditional communities.

Acknowledgements We are grateful for the whole team at the Laboratory of Human Ecology and Ethnobotany of UFSC for their insightful discussions on the topics of this chapter. This study was financed in part by the Coordenac¸˜ao de Aperfeic¸oamento de Pessoal de Nı´vel Superior Brasil (CAPES) - Finance Code 001 for R.H.L. and G.D.B. doctoral scholarships. N.H. thanks CNPq for a research scholarship (309613/2015-9).

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References 1. Convention on biological diversity – CBD (1992) https://www.cbd.int/doc/legal/cbden.pdf. Accessed 30 Apr 2018 2. International Society of Ethnobiology – ISE (2006) International Society of Ethnobiology code of ethics (with 2008 additions). http:// ethnobiology.net/code-of-ethics. Accessed 30 Apr 2018 3. Albuquerque UP, Hanazaki N, Santilli J (2013) Acess and benefit-sharing in Brazil: towards the appropriation of the commons. In: Boef WS, Subedi A, Peroni N, Thijssen M, O’Keeffe MTE (eds) Community biodiversity management: promoting resilience and the conservation of plant genetic resources. Routledge, New York, pp 328–333 4. International Council of Medical Sciences Organizations – ICMSO (1993) International ethical guidelines for biomedical research involving humans subjects. WHO, Geneva 5. Shuster E (1997) Fifty years later: the significance of the Nuremberg code. NEJM 337:1436–1440 6. Sardenberg T, Mu¨ller SS, Pereira HR, Oliveira De RA, Hossne WS (1999) Ana´lise dos aspectos e´ticos da pesquisa em seres humanos con˜ es aos autores de 139 revistas tidos nas instruc¸o cientı´ficas brasileiras. RAMB Brasil 45 (4):295–302 7. Food and Agriculture Organization of the United Nations – FAO (2001) International treaty on plant genetic resources for food and agriculture. http://www.fao.org/3/a-i0510e. pdf. Accessed 16 May 2018 8. Gross AR (2013) Dia´logo sobre o Protocolo de Nagoia entre Brasil e Unia˜o Europeia. MMA, Brası´lia, p 29 9. Instituto Socioambiental – ISA (2018) http:// www.funai.gov.br/index.php/comunicacao/ noticias/3815-oea. Accessed 16 May 2018 10. Contreras EJC, Medinaceli A, Diago OLS, Villamar AA (2015) Co´digo de E´tica para la investigacio´n, la investigacio´n-accio´n y la colaboracio´n etnocientı´fica en Ame´rica Latina Versio´n Dos. SOLAE 13(1):3–30 11. Liporacci HSN, Miaranda TM, Hanazaki N, Peroni N (2015) How are legal matters related to the access of traditional knowledge being considered in the scope of ethnobotany publications in Brazil? Acta Bot Bras 29 (2):251–261. https://doi.org/10.1590/ 0102-33062014abb0007 12. Cunha MC (1987) Os Direitos do I´ndio: Ensaios e Documentos. Editora: rasiliensi, p 320

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Part IV Methods and Techniques of Related Areas

Chapter 17 Methods in the Extraction and Chemical Analysis of Medicinal Plants Akram M. Salam, James T. Lyles, and Cassandra L. Quave Abstract This chapter aims to give an overview of advanced techniques for the extraction, isolation, and analysis of natural products from medicinal plants. It is of great pharmacological interest to isolate and study bioactive natural products. Although sometimes the plants selected for study are chosen based on their traditional medicinal uses, this need not be the case as other attributes may justify study, such as chemical diversity and lack of previous study. Extraction techniques represent one of the earliest steps in natural products isolation, and as such can greatly impact results. Once a crude extract is obtained, compound isolation is achieved through the framework of bioassay-guided fractionation. Under this framework, chromatographic separations are used to iteratively generate fractions, each enriched with a compound or set of compounds of a certain attribute, until finally single compounds are isolated. Analysis of extracts, fractions, and single compounds is performed via spectroscopy, through which the chemical character of fractions and structural attributes of compounds of interest can be elucidated. Key words Extract, Flash chromatography, Mass spectrometry, High-performance liquid chromatography, Nuclear magnetic resonance

1

Introduction Extraction is the process of releasing natural products from a biomass [1]. The biomass is often a pulverized plant or plant part, but may also be a preparation of a fungus or other microorganism. It is important to begin with good quality starting material that meets the standards of the World Health Organization’s guidelines on Good Agricultural and Collection Practices (GACP) for medicinal plants [2]. For example, collection of certain plants specimens should be avoided, such as those subjected to agrochemical runoff, those that are in close proximity to roadsides, and those that belong to threatened or endangered species. Furthermore, international collections need to incorporate consideration of appropriate collection and import/export permits and adhere to the principles of the Nagoya protocol [3]. After plant collection, a chief consideration is

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_17, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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whether to dry the plant material. Dried material lasts longer at ambient temperature and can easily be shipped without decay, though drying may result in loss of some volatile compounds. If fresh material is to be extracted, freezing may be necessary for shipping. For all collected plants, a herbarium voucher specimen must be made. Extraction of a biomass is usually undertaken with a liquid solvent, the polarity of which being one of the key determinants of the types of natural products that migrate and dissolve into the liquid [4]. Another key determinant is the length of time the biomass and solvent are in contact and the degree and type of agitation exerted. The initial extraction of a given biomass yields a crude extract, referred to as such because it is yet unrefined by chromatographic techniques. A crude extract may contain anywhere from a few to hundreds or even thousands of unique compounds and isomers. To isolate compounds from this composition, chromatographic methods are employed, such as partitioning, column chromatography, and high performance liquid chromatography (HPLC). The goal of chromatography is the separation of compounds in a sample based on attributes such as polarity, size, and chemical functionalization [5]. Fractions of a crude extract may be referred to as enriched extracts since they are enriched for chemicals with a certain set of attributes, or they may simply be referred to as “fractions.” Extracts and isolated compounds are analyzed via spectroscopic techniques such as ultraviolet-visible spectroscopy (UV-Vis), mass spectrometry (MS) and nuclear magnetic resonance (NMR). While only mass spectrometry is capable of providing the masses of analytes, both MS and NMR can be used to elucidate the structure and connectivity of functional groups, with NMR being more capable in this respect [6]. Compounds do not necessarily have to be isolated before analysis. With hyphenated techniques, separation and analysis of compounds can be coupled into one procedure [7]. This has made the quick identification of natural products possible and has opened many doors to the analysis of complex chemical samples. Nevertheless, the vast majority of natural products isolation and structural elucidation is performed without the aid of these hyphenated techniques, often due to the expense of the instrumentation. Figure 1 provides an example of a general workflow for identifying single compounds from plant material.

2

Extraction Techniques

2.1 Maceration and Decoction

Maceration is a simple and widely used extraction technique in which pulverized biomass is left to soak in a solvent in a closed container at ambient temperature [5]. Stirring may be incorporated to speed up the extraction process. Macerations are typically run for

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Fig. 1 Example of a general workflow for the identification of natural products from plants. (a) Workflow for isolating single compounds from plant material. In the bioassay-guided fractionation box, the vertical arrows indicate examples of chromatographic methods employed to obtain further fractions of a sample. For example, F1–F8 are example names of fractions obtained from the flash chromatography of the ethyl acetate partition of the crude extract. (b) Workflow for the identification of a previously undiscovered compound. (c) Workflow for the identification of a previously discovered compound

at least three days [8]. Eventually, the concentration of compounds in the solvent reaches equilibrium with the concentration of compounds in the biomass and the extraction effectively stops [5]. Maceration is usually followed by filtration, where the solvent containing the extracted compounds is completely separated from the extracted biomass (marc). In cases where the pulverized biomass is very fine and easily clogs up filter paper, centrifugation is performed beforehand to force the biomass to the bottom of the container prior to decanting for filtration. Often, a maceration is followed by a second or more macerations, where all residual biomass is returned to its container and fresh solvent is added. Macerations are often used in traditional medicinal practices for chemical extraction, as are decoctions, where the biomass of interest is immersed in boiling water throughout the boiling process [9]. Decoctions are usually performed for 15–20 min, although different types of decoctions can run for much longer [9, 10]. An infusion is different from a decoction, where boiling solvent, also

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usually water, is poured onto the biomass. For the purposes of analyzing plants used in traditional medicine, the traditional extraction technique is often replicated so as to most accurately assess the traditional preparations under study. 2.2 Reflux, Soxhlet Extraction, and Percolation

Reflux extraction is a continuous solvent extraction usually performed in a round bottomed flask or boiling flask containing both the extracting solvent and the material undergoing extraction [11]. It utilizes elevated, controlled temperatures at ambient pressure to increase extraction efficiency. As such, reflux is a heated extraction technique, and thermolabile components are at risk of degradation. The elevated temperatures result in reflux and gradual evaporation of the extracting solvent; as such, the round bottomed flask neck is connected to a condenser that preserves the volume of extracting solvent in the system. Common solvents for natural products reflux extractions include: ethanol, methanol, and ethyl acetate; 8 h is a common extraction time. Soxhlet extraction is also a continuous solvent extraction, but the extracting solvent and material are placed in separate compartments [1]. The extracting solvent is present in a round flask at the base and is heated to a boil. The Soxhlet apparatus is placed into the mouth of the flask and allows the vapors of the solvent to be condensed by a condenser above and the now cold solvent to drip into the thimble, where the material is stored. Drops of solvent gradually fill the thimble until it automatically siphons back down to the round flask, carrying extracted compounds with it. This way, as with reflux extraction, the total volume of extracting solvent is preserved. Unlike reflux extraction, Soxhlet is a cold extraction technique because it is the condensed solvent that contacts the material. After siphoning, however, the extract is transferred into the solvent being heated, which may lead to degradation of thermolabile components. For more reading on Soxhlet, evolutions thereof, and applications, a review has been written on the topic [12]. Commonly, extraction time is determined by the number of cycles (fill/siphon) completed per hour, and 4–6 cycles per hour are often observed. A total of 72 cycles is often used as a benchmark, though this can be shortened, especially if it is a fraction of a crude extract that is being extracted. A similar technique to the reflux and Soxhlet extractions is percolation, which is performed using a percolator, an apparatus similar to a separatory funnel [13]. The material to be extracted sits above the drain valve, sometimes packed in between filters or sometimes isolated from the valve by a cotton plug. The material is first soaked with extraction solvent, and then additional solvent is poured so as to allow the extract to percolate dropwise through the drain valve [1]. Successive percolations can be performed for exhaustive extraction. The main drawback of a percolation extraction is high consumption of solvent and time due to lack of agitation and

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dependence on gravity for flow. In order to reduce the overall solvent consumption, the extract can be reused in subsequent percolations, rather than fresh solvent. In order to have a successful percolation, the particle size of the ground material must be coarser than material used in other extraction techniques. 2.3 UltrasoundAssisted Extraction

Ultrasound-assisted extraction (UAE) is an extraction technique where, typically in a maceration-type setup, ultrasound waves are used to assist in the extraction process [14]. The employment of ultrasound reduces the extraction time to minutes, reduces the volume of solvent needed, and consumes less energy as compared to other extraction techniques. Commonly used UAE systems include: Erlenmeyer flask in an ultrasound bath, an ultrasound reactor with stirring, and use of an ultrasound probe. For the extraction of chemicals from plant material, the ultrasound bath is preferred, though high power ultrasonic probes are preferred for most other applications. In both systems, transducers serve as the source of ultrasound waves. A number of mechanisms have been identified as aiding in the effectiveness of ultrasound to increase extraction efficiency: fragmentation, erosion, sonocapillary effect, sonoporation, local shear stress, and destruction–detexturation of plant structures. These mechanisms, as well as parameters that affect the extraction process, have been thoroughly discussed in a recent review of the field [14].

2.4 Essential Oil Extraction

An essential oil is a concentrated hydrophobic liquid obtained from a plant that contains the volatile aroma compounds (e.g., terpenoids) that yield its characteristic fragrance. The most common method of essential oil extraction is steam distillation, where steam from boiling water passes through the plant material of interest, releases its essential oil, carries it through a condenser, after which the water and oil deposit and form two layers that can be separated [15]. Hydro-distillation is also common and follows the same principle, except that the plant material is placed in the boiling water. Other methods of essential oil extraction are discussed in a number of review articles [15, 16]. Of note, enfleurage, specifically the hot enfleurage, is considered the oldest known procedure for extracting essential oils. In this technique, solid odorless fats are heated and stirred with plant material, with spent plant material removed and fresh material added repeatedly until the fat is satisfactorily saturated with fragrance. In the cold enfleurage, plant material is placed on solid, odorless fat in a chassis, and diffusion of essential oils into the fat is allowed to take place over the course of 1–3 days. Fresh plant material is repetitively replenished until saturation is achieved.

2.5 Supercritical Fluid Extraction

Supercritical fluid extraction (SFE) is a chemical extraction process in which the extracting solvent is a supercritical fluid (SCF)

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[17]. An SCF is any substance at a temperature and pressure above its critical point. As a result, an SCF has no distinct liquid or gas phase but is rather in a state between these two extremes, able to both effuse through solids (like a gas) and dissolve compounds (like a liquid). CO2 is the most widely used SCF for extraction, usually employed for large-scale decaffeination of coffee beans [18]. A dedicated instrument is required to perform SFE. The instrument first withdraws liquid CO2 from a CO2 tank, heats and pressurizes it beyond the critical temperature (31
C) and pressure (74 bar), and then either flows the supercritical CO2 through the biomass to be extracted or fills a vessel containing the biomass for a static extraction. After a predetermined contact period, the instrument separates the extract from the now gaseous CO2, condenses the gas back to its liquid form, and returns it to the storage tank. Alternatively, the used CO2 can be vented, leaving the extract behind in a collection vessel. There are some limitations to SFE. CO2 is a poor solvent for polar molecules due to its hydrophobicity. This can be somewhat circumvented by pumping cosolvents such as methanol through the biomass along with the supercritical CO2, thus increasing the range of compounds extracted. On the other hand, this limitation gives SFE a niche in the extraction and analysis of hydrophobic compounds such as essential oils, with several reviews written on the topic [19, 20]. Another limitation is cost, which primarily arises from the need to pressurize the CO2. SFE is often used when extraction selectivity and speed are very important. Because different cosolvents can be used and the properties of an SCF can be adjusted by changing the temperature and pressure, selective extractions can be performed. For instance, it was found that by varying temperature, pressure, and cosolvents in an extraction of Plantago major, selective enrichment of triterpenic acids, α-LNA, and oleanolic and ursolic acids could be achieved [21]. Additionally, an SFE can be completed in relatively short time due to the enhanced diffusion properties of SCFs as compared to liquids. Another advantage of utilizing SCFs is that they largely circumvent oxidizing and thermally degrading extracted compounds. They are also less costly to dispose of (e.g., CO2 can be released into the air) and are generally nontoxic, contaminant-free, and inexpensive. A commonly cited advantage of SFE is its environmental friendliness. However, in applications that require the full range of polar compounds to be extracted, substantial amount of modifier such as 30% methanol must be used, negating this benefit [13]. 2.6 Accelerated Solvent Extraction

Accelerated solvent extraction (ASE) is a fully automated rapid extraction technique that enjoys widespread use due to rapid extraction times requiring little solvent. The technique was developed by Dionex Corporation and introduced in 1995, and they remain the sole manufacturer of ASE equipment [22]. It employs

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common solvents at elevated temperature and pressure, which increases extraction efficiency. Because the temperatures used are usually above the boiling point of the solvent, the increased pressure (1000–2000 psi) functions to maintain the liquid state. Commonly used organic solvents include n-hexane, dichloromethane, acetone, and methanol. ASE is capable of extraction for sample sizes of 100 g or less in minutes while consuming very small volumes of solvent. As a result, the cost per sample tends to be lower than that of other extraction techniques. A main advantage of ASE is that it aims to maximize the extraction of compounds present at low concentrations in the matrix, and it generally is an exhaustive extraction technique. A disadvantage is the increased likelihood of thermal degradation of susceptible compounds. While most ASE extractions utilize a temperature between 75 and 125
C, 100
C is the most commonly setting chosen. Temperature is the dominant factor in ASE’s exhaustive extraction, with selectivity tunable by lowering extracting temperature and choosing an appropriate solvent. ASE is increasingly used in the extraction of contaminants in foods for analysis, with a review having been written on the topic, giving a deeper overview of the technique [23]. 2.7 MicrowaveAssisted Extraction

Microwave-Assisted Extraction (MAE) is a rapid extraction technique in which solvent extraction is supported by heating with microwaves [24]. As in ASE, the heating yields the benefit of increased extraction efficiency. This brings the advantage of lowering volume of solvent and cost, but also the limitation of thermal degradation of susceptible compounds. MAE can be performed in ways as simple as inserting a maceration flask into a microwave oven to ways as complex as utilizing a dedicated instrument with a variety of controls and vessel options. Many different types of MAE instruments have been developed. For high-throughput sample preparation, for example, an instrument may enclose numerous maceration capsules in a microwave box for heating. MAE can also be used to assist reflux and Soxhlet extractions by physically placing the biomass-containing piece of glassware in a specially made microwave unit [25, 26]. There are several examples of the literature of natural products having been extracted more efficiently from a biomass of interest via MAE, such as luteolin and apigenin from tree peony pod and fucoidan from marine algae [27, 28].

2.8 Extraction Efficiencies

In order to provide insight into the relative extraction efficiencies of some of the most popular extraction methods, a few examples from the literature are given where extraction techniques have been optimized. Interestingly, most studies of comparative extraction efficiencies study the extraction of pollutants rather than natural products, though conclusions may be drawn from these studies. Here, Soxhlet extraction has been considered as the reference. ASE and Soxhlet extraction have been found to extract volatile and

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phenolic compounds with higher efficiency than SFE from mint (Lamiaceae) species [29]. Soxhlet was also found to achieve the higher extraction yield of terpenoids and sterols from tobacco than ASE, though the latter was faster and used less solvent [30]. However, for the extraction of polycyclic aromatic hydrocarbons and organochlorine pesticides from soils, Soxhlet and MAE were found to have similar efficiencies, though ASE proved more efficient than the two, and both MAE and ASE consumed less solvent and time [31]. In a study on the extraction of twelve polychlorinated biphenyls (PCBs) from algae samples, Soxhlet and SFE were found to have same extraction efficiencies for most PCBs, though SFE had the advantage of leading to the detection all PCBs at lower concentrations and reducing extraction time and solvent consumption [32]. In a study on the extraction of N-nitrosamines and aromatic amines from various soil matrices, MAE was found to be superior to Soxhlet while also requiring just 3 min for extraction [33]. It is the opinion of the authors based on the literature and experience that Soxhlet is often capable of extraction efficiencies similar to ASE and MAE. However, other extraction methodologies are often chosen for increased throughput, reduced solvent usage, or available processing time. A comparison of other attributes of extractions techniques is summarized in Table 1. The following section will discuss chromatographic techniques, and a comparison of their attributes is summarized in Table 2.

3

Chromatographic Techniques

3.1 Flash Chromatography

Flash chromatography is a type of preparative (as opposed to analytical) liquid chromatography used for the separation of organic compounds, which is widely used for natural product extract separation. While flash chromatography began as a low-pressure technique, now vacuum pressure or, more often, pumps are employed to achieve medium pressures for faster flow rates and quicker separation [34]. Numerous types of columns (and hence separation methods) exist. Although columns can be packed in the laboratory, one of the key advantages to flash chromatography is that columns can be purchased as prepacked, one-time use columns. One of the most commonly used columns is packed with a silica adsorbent with a particle size usually between 40 and 60 μm [35]. Particle shapes are often irregular, and the particle size distribution in any particular column tends to be relatively wide. The smaller the silica particle size, the more tightly packed a column is, the more backpressure builds in response to a given flow rate of a mobile phase. As compared to high-performance liquid chromatography (HPLC), flash chromatography uses larger particle sizes and thus generates lower backpressures than HPLC. Flash chromatography is often performed on a flash instrument, which

Requires instrumentation

Exhaustive in most cases

Cold extraction

Limited risk of compound degradation

✓

✓

✓

✓

✓

Requires little solvent

✓

✓

✓

Hot extraction

Reflux

✓

Infusion

✓

Decoction

Often takes <1 h

Maceration

Table 1 Comparison of attributes of different extraction methods

✓

✓

✓

Soxhlet

✓

Percolation

✓

✓

✓

✓

UAE

✓

✓

✓

✓

SFE

✓

✓

✓

✓

✓

ASE

✓

✓

✓

✓

✓

MAE

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Table 2 Comparison of attributes of different chromatographic methods Flash Can be analytical or preparative

HPLC

GC

SFC

✓

✓

✓

✓

✓

More amenable to larger sample sizes

✓

✓

More amenable to compound isolation

✓

✓

Variable separation chemistries

✓

✓

✓

Fig. 2 Examples of column employed for flash chromatography and HPLC. (a) Commercially available Teledyne Isco flash columns arranged from high to low (1–7) loading capacities ranging from 33 g to 5.5 mg. Most of the columns are silica columns; column 6 is a diol column. (b) HPLC columns arranged from large to small (1–9) sizes ranging from 30  250 mm to 6.4  30 mm. Columns 1 and 2 are preparative columns, 3 and 4 are semipreparative, and the rest are analytical. Columns 4 and 5 are fitted with compatible guard columns. Most of the columns are C-18 columns, and particle sizes range from 2.6 to 5 μm. Columns 3 is a C-5 column, while columns 7 and 9 phenyl columns

not only pumps the mobile phase but also detects column eluate, usually via a UV-Vis absorbance detector and sometimes with an evaporative light scattering detector (ELSD) and produces a chromatogram of the run. In addition to normal and reverse phase columns, amine, cyano, diol, ion exchange, and many more types

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of columns are available. Figure 2a shows examples of different flash columns. Flash chromatography has been used extensively as a step in bioassay-guided fractionation and to isolate single compounds [36–40]. Given the importance of flash chromatography as a separation technique, efforts have been made to construct flash apparatuses with inexpensive setup costs [41]. 3.2 HighPerformance Liquid Chromatography (HPLC)

HPLC is a type of liquid chromatography that can be used for both analytical and preparative purposes. Analytical HPLC and larger scale preparative HPLC each require separate, dedicated instruments, although hybrid systems are available, most commonly for analytical and semi-preparative HPLC. As compared to flash chromatography, HPLC columns contain silica with smaller particle sizes ranging from 2 to 50 μm [35]. Additionally, particles are spherical in shape, and in any given column the particle size distribution is narrow. Particle size plays a role in resolution. Consider the fundamental resolution equation pffiffiffiffiffi N α1 K0 R¼   1þK 4 α where N ¼ efficiency, α ¼ selectivity, and K ¼ retention capacity. Since separation efficiency increases with decreased particle size, HPLC has the advantage of higher efficiency as compared to flash chromatography, allowing for higher resolutions to be reached. This concept is modeled by the theoretical plate model of chromatography, which supposes that a chromatographic column consists of a large number of imaginary separate layers called theoretical plates (N). As such, decreased particle size results in decreased height equivalent to a theoretical plate; thus, more theoretical plates are present in a given column length, increasing separation efficiency. Modern HPLC instruments nearly always include a UV/Vis or a photodiode array (PDA) detector as a spectroscopic component for the characterization of column eluate. For natural product extracts, analytical HPLC is used specifically for chemical characterization, where chromatograms are compared for different runs, be they same-extract batches, different extracts, chemical standards, etc. This function utilizes small amounts of extract or standards; therefore, column eluate is usually not collected because it amounts to very little material. In preparative HPLC, on the other hand, column eluate is collected because the purpose of the separation is the production of large amounts of extract fractions. Therefore, column length and especially diameter for preparative HPLC are larger than those for analytical HPLC (typically 2.1–4.6 mm diameter, 30–250 mm length), as these attributes yield higher column throughput and capacity. Column particle sizes are often slightly larger than those of analytical HPLC columns, where resolution is

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more highly emphasized. Beyond these factors, several differences between analytical and preparative HPLC result in the need for separate instrumentation for each. Chief among these differences is the capacity to accommodate higher flow rates in preparative HPLC while maintaining an acceptable backpressure that will not damage the instrument of the chromatographic column. It is possible to use an analytical HPLC instrument for fraction production; this is often called semi-preparative HPLC. This usually calls for a larger analytical column—still much smaller than preparative columns—and many more runs are required as compared to preparative HPLC to produce a given amount of a fraction. Additionally, an even higher resolution form of analytical HPLC is UPLC (ultra-performance liquid chromatography). UPLC is chiefly characterized by even smaller particles sizes (sub 2 μm), resulting in a higher theoretical plate count and thus increased separation efficiency. Because of this, UPLC columns sizes are often shorter to reduce run times, and UPLC instruments require the capacity to accommodate even higher backpressures. Numerous types of columns exist for all HPLC instruments. In addition to normal phase and reverse phase columns, there are sizeexclusion, ion-exchange, chiral, and bioaffinity columns, among many others. Figure 2b shows examples of different HPLC columns. Columns may be fitted with a guard column on the inlet end to protect them from particulate matter in a sample by trapping it in the sacrificial guard column. Besides the column, the schematic of a HPLC instrument usually consists of a degasser, sampler, pumps, and a detector, usually a UV/Vis or a photodiode array (PDA) detector. There are established methods for the separation of compounds for botanicals and herbs of commerce. Refer to pharmacopoeia of the United States [42], Europe [43], and China [44] for methods on specific materials. 3.3 Gas Chromatography (GC)

GC is a group of analytical separation techniques used to separate volatile compounds in the gas phase [45]. While the success of GC has largely been associated with analytical purposes, GC can be successfully used for preparative purposes as well [46]. Unlike liquid chromatography where the sample, dissolved in liquid, is pushed by a liquid mobile phase through a packed column, in GC the sample, also dissolved in liquid, is vaporized and pushed by an inert gas mobile phase through a heated column, usually hollow. Separation occurs only due to the interaction of the sample components with the coating inside the hollow column (the stationary phase). Because the mobile phase is inert, separation is not due to differential chemical interactions with the mobile phase (none occur). The stationary phase can be either a liquid on an inert support (gas–liquid chromatography) or, more commonly, a solid adsorbent (gas–solid chromatography). A very typical GC column is a fused-silica capillary of varying length from 5 to 100 m, in

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which the inner surface of a silica capillary is coated with one of several polymer stationary phases and the outside of the capillary is coated with a polyamide polymer to add strength. A review of many of the types of GC columns describes them in detail [47]. Usually, nonpolar samples are analyzed by GC, interacting with a similar stationary phase to achieve sufficient separation. As such, in the realm of natural products, GC is most adept to separation of components of nonpolar, volatile samples such as essential oils. The schematic of a GC instrument begins with a source of carrier gas connected to a flow controller [45]. The most common carrier gases are helium, nitrogen, argon, and hydrogen, but the exact gas to use is usually determined by the detector being employed. Carrier gas then flows to the column inlet (or injector), which provides the means to introduce a sample into a continuous flow of carrier gas. The inlet is a piece of hardware attached to the column head. The most common inlet type is an S/SL (split/splitless) injector, where a small, heated chamber facilitates volatilization of the sample solution. Once the sample is swept by the carrier gas, it flows through a column heated by an oven, after which the sample finally hits a detector. The flame ionization detector (FID) and the thermal conductivity detector (TCD) are the most typically employed detectors. Both can accommodate a wide range of sample concentrations and are sensitive to a wide range of components. Other detectors have a shorter range of usability but are used when dealing with specific types of substances. 3.4 Supercritical Fluid Chromatography

Supercritical fluid chromatography (SFC) is very similar to LC, where the defining feature is that the mobile phase is a supercritical fluid, usually CO2. The instrumentation is nearly identical to that of LC, and there are both analytical and preparative instruments. The pumping system consists of two pumps: one delivers supercritical CO2, and the other delivers a cosolvent, such as a simple alcohol, acetonitrile, chloroform, or ethyl acetate. The cosolvent and CO2 are homogenized by a static mixer, and the mobile phase is delivered to the autosampler, equipped with an injection value for delivery to the front of the chromatographic column. The columns are present in an oven to maintain a temperature of above 40
C for supercritical conditions to be achieved with CO2. Column eluate then reaches the detector. Until this point, the instrumentation is almost identical to that of liquid chromatography. An additional component is the automated backpressure regulator, which provides a control parameter not found in LC—pressure. In terms of operation, SFC is as simple and robust as LC, and fraction collecting is even easier due to the evaporation of the CO2 component of the mobile phase. For natural products, supercritical fluid chromatography is mainly utilized for the separation of nonpolar compounds such as carotenoids, fatty acids, and terpenes, though it is has also been successfully used with more polar natural products [48–51].

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Prefractionation

3.6 Solid-Phase Extraction

Of great importance, flash chromatography and HPLC are often employed in the prefractionation of crude extracts so as to remove chemicals unlikely to be pharmacologically active prior to screening [52–63]. Prefractionation prior to high-throughput screening (HTS) results in higher hit rates, such as in screening campaigns that revealed pharmacological activity of fractions where the crude extracts were previously identified as inactive [56, 57]. A review has been written with an expanded discussion on this topic and the place of natural products in drug discovery [64]. Prefractionation is also used to “clean up” a fraction or extract so as to remove compounds that may bind to a stationary phase to be used for subsequent chromatographic separation [65]. In addition to chromatographic methods of prefractionation, a manual method of liquid–liquid partitioning is commonly employed prior to flash chromatography or HPLC. The extract is suspended in a solvent (e.g., water) and successively partitioned against solvents of differing polarity (e.g., hexanes, ethyl acetate, n-butanol) using a separatory funnel apparatus to create two distinct layers of solvent and extract constituents at each step. The advantage of this method is avoidance of loss of compounds to the column matrix, but a disadvantage is the manual and time-consuming nature of the technique. Solid-phase extraction (SPE) is a sample preparation technique where compounds in a liquid mixture are separated from each other based on chemical and physical characteristics. The most common SPE format consists of a syringe cartridge that contains 50 mg to 20 g of stationary phase [66]. After pouring the sample solution into the cartridge, a plunger or vacuum can be used to push it through the stationary phase. Any type of stationary phase can be used, except those used for exclusion chromatography. As such, SPE allows for rapid, simple, and reproducible analyte purification. While liquid–liquid partitioning can be used for similar purposes, it is more time consuming and emulsions may form between different liquid phases. SPE is also often employed for analyte concentration. Very commonly, a stationary phase is selected such that it retains the analytes of interest; subsequently, the cartridge is rinsed with a small volume of a strong solvent to elute the analytes [67]. Opposite to this retentive mode, SPE can be utilized in non-retentive mode, where it is the desired solutes that pass through the stationary phase [66]. When SPE is used to prepare a sample prior to HPLC, the need for a guard column may be negated [65]. SPE can also serve as a concentration step for compounds which are retained; a relatively large volume containing a small amount of the analytes of interest can be loaded onto the column. Then the analytes are eluted with a small volume of very strong solvent, thus increasing their concentration for analysis without the time required to dry down the initial extraction solvents.

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Spectroscopic Techniques

4.1 Mass Spectrometry

Mass spectrometry (MS) is an analytical technique for determining the mass of individual compounds that comprise a given sample. This is achieved through the ionization of chemical species and their sorting based on their mass-to-charge ratio (m/z). Solids, liquids, or gasses may be analyzed by mass spectrometery. There are three main components of a mass spectrometer: ion source, mass analyzer, and detector. The ion source ionizes the chemical species present in the sample. For gaseous samples, the most common ionization techniques are electron ionization and chemical ionization, whereas for liquid samples, the most common are electrospray ionization (ESI) and atmospheric-pressure chemical ionization (APCI). For solid samples and some proteins, matrixassisted laser desorption/ionization (MALDI) is employed. In ESI, a high voltage is applied to a liquid being sprayed in order to create an aerosol of ions, whereas in APCI the nebulized effluent passes over a coronal discharge needle and as the liquid evaporates due to elevated temperature the remaining compounds acquire a charge. On the other hand, there is an array of ambient ionization techniques, where ions are produced outside of the mass spectrometer in ambient conditions from samples that require little to no pretreatment [68]. Since the development of the first reported technique, desorption electrospray ionization (DESI), dozens more have been developed [69]. After ionization, ions are transported by magnetic or electric fields to the mass analyzer, which separates ions based on their m/z. The time-of-flight (TOF) analyzer is a mass analyzer that uses an electric field to accelerate ions toward a detector, measuring the time they take to reach it. Velocities of the ions depend solely on their masses due to identical charge, which tends to make all kinetic energies constant. As such, ions with lower masses will travel faster and reach the detector sooner. Quadrupole mass analyzers utilize a quadrupole field created between four parallel rods. Oscillating electrical fields produced by the rods stabilize or perturb the paths of ions passing such that, at any time, only the ions in a certain range of m/z are passed through. The quadrupole ion trap is very similar, except that the ions are trapped and sequentially ejected toward the detector. The state-of-the-art of mass analyzers is the Orbitrap, where ions are electrostatically trapped in an orbit around a central, spindle-shaped electrode such that they also oscillate along the electrode’s long axis. Through detector plates, the instrument records image currents generated by the oscillations, the frequencies of which depend on the m/z values of the ions. Fourier transformation is used to translate the image currents to mass spectra.

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Imaging mass spectrometry (IMS) is a powerful method for the analysis of chemicals in a biological sample of interest. IMS was first popularized by the MALDI ionization method [70] and it can be used on a tissue section, bacterial colony, or even a whole organism. The sample is mounted on a conductive support, a thin layer of matrix is applied, and the sample is positioned on a stage in a vacuum [71]. The surface of the sample is scanned by a laser, ionizing compounds, and then a 2D image of the sample is constructed with mass data. 3D images can also be constructed using cross-sections of samples. MALDI is the most commonly used ionization method for imaging, and it has the advantage of allowing for the detection of molecules in a wide m/z range. What may be the key shortcomings of using MALDI in natural product research is interference by low mass-to-charge molecules present in the MALDI matrix as well as reproducibility, contingent on the quality of the sample [72]. Ambient ionization methods such as DESI circumvent these shortcomings due to the ability to ionize samples under ambient conditions and the lack of sample preparation [71]. Tandem mass spectrometry (MS/MS) is an important analytical tool in the field of natural products research. After a first stage of MS where, as described above, ions are formed and separated by their m/z ratio, a second stage of MS is performed. In this second stage, ions of a certain m/z are fragmented. Each molecule of an individual compound always fragments into a characteristic pattern that depends on the fragmentation technique employed, allowing mass spectra to be used as “fingerprints” for identifying compounds. Indeed, functional groups such as alkyl chains may be structurally elucidated based on fragmentation of the group specific to its chemical characteristics and the fragmentation technique. Throughout the 1960s–1980s hundreds of proposed structures were determined for natural products, many identified due in part to fragmentation studies [73]. MS/MS is also the backbone of molecular networking, an informatics approach used for both dereplication and identification of structural analogs [74–76]. Through this approach, all MS/MS data in an experiment is mapped according to mass spectral structural space, resulting in the clustering of molecular families with related MS/MS spectra. 4.2 Nuclear Magnetic Resonance Spectroscopy

Nuclear Magnetic Resonance (NMR) spectroscopy, or simply NMR, is a spectroscopic technique for observing local magnetic fields around atomic nuclei. Because these fields are highly unique to individual atoms in any given compound, NMR is primarily employed for the elucidation of chemical structures in natural products research. Over the past several decades, improvements to NMR hardware and methodology have reduced the amount of sample required for analysis from tens of milligrams to often under 1 mg. A NMR experiment operates by first applying a constant magnetic field (B0) to the sample such that the magnetic nuclear

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spins align with B0 either with the field (low-energy state) or 180
against the field (high-energy state). Because resolution depends directly on magnetic field strength, modern NMR spectrometers are fitted with a very powerful and large liquid helium-cooled superconducting magnet. Second, radio frequency (RF) pulses are used to perturb the alignment in order to obtain a nuclear magnetic resonance response, also called a free induction decay (FID). Following the pulse, the population nuclei in the sample are excited and flip orientations. This flipping of energy states produces a very weak voltage, which is detectable in sensitive radio receivers surrounding the sample tube. This signal is then digitized and Fourier transformed to yield a frequency spectrum of the NMR signal, or the NMR spectrum. This nuclear magnetic resonance phenomenon is commonly used to study 1H and 13C atoms in a compound in order to determine each of their environments and subsequently elucidate the compound’s structure. These isotopes, respectively present in 99.98% and 1.1% abundance, are studied because they exhibit nuclear spin and are thus detectable by NMR. The general workflow for determining the structure of a natural product often begins by obtaining a proton (1H) spectrum and carbon-13 (13C) spectrum. For organic compounds, the 1H NMR spectrum is characterized by peaks representing at least one proton each, each having a unique chemical shift in the range +14 to 4 ppm, indicating local electronegativity. Peaks containing multiple peaks represent the spin-spin coupling between protons, and the integration curve for each peak relative to the others reflects the number of protons represented by that peak. The 13C spectrum is analogous to 1H spectrum in that it allows the identification of carbon atoms, though 13C chemical shifts fall along a much larger range than for 1 H. This 1D data is then combined with additional data from 2D experiments, obtained from spectra such as the 1H-1H correlation (COSY) spectrum and the one-bond 13C-1H correlation (e.g., HMQC) spectrum, to determine the structures of fragments of a compound. These fragments are then tied together using information from the long-range 13C-1H correlation (HMBC) spectrum. Many different pulse sequences for 2D NMR have been developed to obtain various correlations. It is necessary to combine a variety of NMR methods with calculations of the energies of different conformations, and techniques for doing so have been thoroughly reviewed [77]. Here, we give an overview of the most commonly employed 2D NMR techniques. COSY (Correlation Spectroscopy) provides correlation data for all coupled protons (1H-1H correlation). This data gives unequivocal proof of proton assignments. DEPT (Distortionless Enhancement of Polarization Transfer) determines the number of hydrogen atoms bonded to each carbon in the molecule, and thus differentiates between primary, secondary, and tertiary carbon atoms.

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HETCOR (Heteronuclear Correlation spectroscopy) reveals all coupling of protons and attached carbons (1H-13C correlation), complementing DEPT, but is less frequently used. HMQC (Heteronuclear Multiple Quantum Coherence) gives the same results as HETCOR, but is much more efficient in terms of sensitivity and speed and has almost completely replaced the technique. HMBC (Heteronuclear Multiple Bond Correlation) allows long-range correlation of protons and attached carbons (1H-13C correlation) over 2–3 bonds. It is important to note that all the aforementioned 2D techniques examine through-bond correlations. NOESY (Nuclear Overhauser Effect Spectroscopy) is unique in that, instead of determining through-bond relationships, the technique determines through-space NOE relationships. The NOE is the transfer of energy from one nucleus to another (usually protons) when the first nucleus relaxes from an excited nuclear spin state to its ground nuclear spin state. The NOESY spectrum reveals which protons are close enough to each other to transfer energy this way. NOE is not ˚. observed beyond roughly 5 A˚, and is usually observed within 3 A In addition to NMR’s utility in the determination of chemical structures, it can also be employed for spectral fingerprinting of complex mixtures, such as a natural product extract or fraction. Due to the NMR’s inherent reproducibility the instrument can provide rapid analysis of an extract. This data can be compared to a previously prepared data set to determine if the material is the same as other batches or lots of the same material. It can also be employed to determine if a sample is indeed authentic or adulterated. The limitation of these analyses is based on the diversity and depth of the samples used for the training set to create the model of what is an “authentic sample.” Nevertheless, given a robust enough set of authentic samples NMR fingerprinting is an extremely powerful tool for determining batch-to-batch consistency or adulteration of raw materials. Several reviews have discussed the details of these techniques [78, 79]. 4.3 Hyphenated Techniques

When two or more different analytical techniques are coupled via a proper interface, a hyphenated technique has been set [7]. Most commonly, chromatographic techniques are coupled to spectroscopic techniques, with the benefit of rapid identification of natural products directly from plant and marine extracts or fractions without the necessity of isolation. For example, HPLC is often coupled to MS to make HPLC-MS. In this case, the compounds that comprise a given sample are separated over time by HPLC and then introduced into an MS, yielding mass data of the HPLC eluate over time. This way, separation and detection are performed via one technique. The most common separation techniques that see hyphenated use are HPLC and GC, whereas the most common spectroscopy techniques are MS and NMR. UV detection is built into most automated chromatographic techniques and is not

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considered a standalone spectroscopic technique here. The ability to rapidly identify compounds allows for dereplication of natural products, metabolomics studies, chemotaxonomic studies, chemical fingerprinting, quality control of extracts, and many other studies. We will discuss dereplication here and metabolomics in the next section. Dereplication is the process of identifying compounds for which the structure is already known [80]. It is an integral part of natural products discovery, as it ensures that time and resources are not wasted toward elucidating structures of compounds that are already known. Most commonly, LC-MS is utilized to analyze crude extracts and fractions thereof to identify the masses of all constituents. These mass values are then screened against databases in order to identify putative chemical formulae and structures for the compounds. In bioassay-guided fraction studies, bioactive fractions are analyzed as such to determine whether active fractions contain previously identified compounds with the known therapeutic activity of interest. Some of the most commonly consulted databases include SciFinder [81], Dictionary of Natural Products [82], NAPRALERT [83], Global Natural Products Social Molecular Network [84], and MarinLit [85]. In microbial dereplication specifically, it is highly desirable to identify microbial strains capable of producing novel chemistries. To this extent, LC-MS data is often analyzed by principle component analysis or other multivariate methods to identify strains that synthesize molecules most different from where the rest of the strains cluster. There has also been interest in the field of natural product peptides to develop informatics tools to predict fragmentation data of known structures. This knowledge would help find matches with experimental fragmentation data, further aiding in dereplication [86–89]. While LC-MS enjoys an important role in natural products discovery, LC-NMR has proved less useful [77]. Whereas MS is capable of detecting the masses of LC eluates almost instantaneously during the course of continuous flow, NMR is capable of no more than obtaining 1H spectra, which takes several seconds. Additionally, LC-NMR requires either the use of costly deuterated solvents or the use of solvent peak suppression, which could result in loss of sample signals. To circumvent the first limitation, either (1) a stopped flow mode is employed where a valve stops elution when analyte reaches the flow cell volume of the rf coil, or (2) without interrupting the chromatographic run, a loop-storage mode is employed, where fractions are stored in individual capillary loops for later NMR analysis [90]. In both cases, analyte can be subjected to NMR longer to achieve adequate data acquisition times for less abundant material and for more time consuming sequences such as 13 C NMR. To further improve NMR detection after LC, fractions can be prepared for NMR by solid-phase extraction (SPE), concentrating them into an appropriate deuterated solvent prior to

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analysis. Indeed, numerous laboratories have had success with automated LC-SPE-NMR for the identification of natural products [91, 92]. MS can be coupled to this hyphenated technique via a splitter that performs a typically 95:5 split of the flow to NMR versus MS [93]. 4.4

Metabolomics

Recent advances in computing power and analytical instrumentation has allowed previously unthinkable analyses to be performed. These advances, combined with techniques developed from genomics, have allowed the use of larger data sets to produce proteomics and metabolomics analyses. The term proteomics, as well as proteome, was coined in 1995 [94] and can be narrowly defined as analyzing the expressed levels of proteins in a cell, thus providing insight into the current physiological state. From proteomics it was a short transition to the transcriptome, proteome, and finally analyzing the metabolome, the small molecules and metabolic products produced by an organism. Metabolomics in its most general definition involves completely analyzing all the known and/or unknown metabolites in a given biological sample [95]. Metabolomic analysis involves three major parts: sample preparation, data acquisition, and data analysis or chemometrics. The data acquisition can make use of several analytical instruments; NMR, GC-MS, or LC-MS to perform a targeted or non-targeted analysis. The preferred instrument in MS-based metabolomics is a high accuracy MS such as TOF, FT, or Orbitrap. Metabolomics analyses can be grouped based on approach: targeted and untargeted. In a targeted metabolomics study, the levels of a known set of compounds are quantified. The study can be quantitative or semiquantitative by using appropriate chemical standards in the study design [96]. One of the advantages of a targeted study is that since the compounds of interest are defined initially, the sample preparation and analytical methodologies can be optimized for those compounds, thus potentially reducing signal interference from other compounds. An untargeted metabolomics study is the analysis of all the measurable compounds in a sample, both the chemical knowns and unknowns [96]. Due to the nature of the study, careful sample preparations must be followed with a focus on minimizing any compound loss, degradation, or unintentionally enriching one group of compounds. The analytical method used to generate the metabolomics data must be broad spectrum and may require using multiple separations in tandem, such as HILIC and RP-C18 LC-MS methods. An untargeted study may generate a large amount of data and therefore is best analyzed with one of several chemometric data platforms such as MetaboAnalyst [97], XCMS [98], or others [99]. For many ethnobotanically related questions, an untargeted metabolomic analysis is the preferred study design. Again, sample

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preparation must be carefully designed and all samples processed using the same methods. The method of sample preparation needs to consider both the location and time the plant material is harvested, as well as if the plant tissue will be processed fresh, frozen or dried. The tissue is usually ground or homogenized to increase the extraction efficiency, and care must be taken to avoid sample cross contamination such as from the grinding equipment itself. The extraction of the plant material can be accomplished using various methods and solvents, many of which are discussed previously in this chapter. For metabolomics studies, a mid-polar solvent such as aqueous methanol or aqueous ethanol is commonly used. Depending on the extraction method, the crude extract can be directly analyzed, or it may need to be concentrated and prepared at a set concentration prior to the analysis. A 2009 review examined the aspects of plant sample preparation in detail [100]. The data acquisition portion of the analysis will depend on what instrumentation is available. A high accuracy LC-MS system is recommended; however, direct MS infusion of the sample is also possible [101]. The combination of HPLC and MS will provide an advantage of two dimensions of separation for the sample: the LC chromatographic separation as well as resolution in the mass domain. This allows for shorter chromatographic methods using smaller columns such as a 2.1  50 mm. Efforts should be made to develop a chromatographic system that resolves a wide range of compounds and is rapid. A 2017 review addresses the use of LC mobile phases and mobile phase additives to maximize ionization for plant metabolomics [102]. Since the chemicals of interest are not known in an untargeted metabolomics method, maximizing the number of chemicals that ionize for MS analysis is very important. Once the data has been collected, it must be analyzed to identify individual features [103]. For LC-MS data, a feature is an ion with a unique m/z and retention time. Every detected metabolite will have at least one and often several features. As part of the data analysis, a preprocessing step should be incorporated in order to determine the method’s noise floor and filter out “known unknowns” and identified contaminants. The remaining features may need to be filtered further, normalized, and scaled in order to yield the most information from the analytical analysis [104, 105]. Once the features are processed, they can be visualized and interpreted using a variety of algorithms and data visualization techniques, depending on the type of study being undertaken. One common method of analyzing the data is to use principle component analysis (PCA) [106]. Additionally, high-resolution mass spectral data can be used to dereplicate known compounds. One approach that has yielded success is searching chemical databases that can be filtered by botanical genus or species for compounds with exact masses corresponding to

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the experimental ions and comparing empirical formulas and fragmentation patterns [36]. The Dictionary of Natural Products and Scifinder are both useful for this type of screening.

5

Final Considerations In this chapter we summarize the chemistry workflow for an ethnobotanical approach to natural product isolation and drug discovery. This workflow begins with the plant collection itself, and is followed by plant material processing, extraction, chromatography, and spectroscopic analysis. The processing of plant material and their extraction essentially determines the portion of the chemical library contained in the plant that will be examined by all future studies. The chromatography of these extracts, especially when done in a bioassay-guided fraction framework, is perhaps the most time-consuming part of the workflow. Indeed, all fractions generated must be handled and stored with care. Although often only one fraction out of a set is proceeded with for further chromatographic separation, particularly in drug discovery, sister fractions should be preserved for potential future studies, including for studies of the originally pursued bioactivity. For example, it may very well be that a less active fraction, upon further fractionation, proves to be a source of highly bioactive compounds. To the extent that numerous fractions are generated through such studies, it is of the utmost importance to practice good note keeping and to maintain an updated database. This way, the origin and method of production of every fraction is known. If the same fractions are made on separate occasions or by different scientists, their identity can be compared to those of previous batches via spectroscopic methods such as analytical HPLC, ensuring reproducibility. With advances in spectroscopic technology in the past decade, now only very small quantities of fractions and single compounds are required for chemical analyses. The nature of ethnobotanical drug discovery is highly interdisciplinary, and collaborations are highly favored for combining areas of expertise of different laboratories, including botany, phytochemistry, in vitro and in vivo biological assays, and drug screening.

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root characterised using LC-SPE-NMR and LC-MS techniques. Phytochemistry 98:197–203 93. Gu WY, Li N, Leung EL, Zhou H, Yao XJ et al (2015) Rapid identification of new minor chemical constituents from Smilacis Glabrae Rhizoma by combined use of UHPLC-QTOF-MS, preparative HPLC and UHPLCSPE-NMR-MS techniques. Phytochem Anal 26:428–435 94. Wasinger Valerie C, Cordwell Stuart J, CerpaPoljak A, Yan JX, Gooley AA et al (1995) Progress with gene-product mapping of the Mollicutes: Mycoplasma genitalium. Electrophoresis 16:1090–1094 95. Griffiths WJ, Karu K, Hornshaw M, Woffendin G, Wang Y (2007) Metabolomics and metabolite profiling: past heroes and future developments. Eur J Mass Spectrom (Chichester) 13:45–50 96. Roberts LD, Souza AL, Gerszten RE, Clish CB (2012) Targeted metabolomics. Curr Protoc Mol Biol 30:2 97. Chong J, Soufan O, Li C, Caraus I, Li S et al (2018) MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis. Nucleic Acids Res:310, 486–494 98. SRI (2018) The Scripps Research Institute: XCMS. https://xcmsonline.scripps.edu 99. Roessner U, Dias DA (eds) (2013) Metabolomics tools for natural product discovery, vol 1055. Humana Press, Totowa, NJ 100. Kim Hye K, Verpoorte R (2009) Sample preparation for plant metabolomics. Phytochem Anal 21:4–13 101. Garcia-Flores M, Juarez-Colunga S, GarciaCasarrubias A, Trachsel S, Winkler R, Tiessen A (2015) Metabolic profiling of plant extracts using direct-injection electrospray ionization mass spectrometry allows for highthroughput phenotypic characterization according to genetic and environmental effects. J Agric Food Chem 63:1042–1052 102. Creydt M, Fischer M (2017) Plant metabolomics: maximizing metabolome coverage by optimizing mobile phase additives for nontargeted mass spectrometry in positive and negative electrospray ionization mode. Anal Chem 89:10474–10486 103. Gorrochategui E, Jaumot J, Lacorte S, Tauler R (2016) Data analysis strategies for targeted and untargeted LC-MS metabolomic studies: overview and workflow. Trends Analyt Chem 82:425–442 104. van den Berg RA, Hoefsloot HC, Westerhuis JA, Smilde AK, van der Werf MJ (2006)

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Chapter 18 Evaluation of the Antibacterial and Modulatory Activities of Zootherapeutics Dio´genes de Queiroz Dias, De´bora Lima Sales, Felipe Silva Ferreira, Izabel Cristina Santiago Lemos, Gyllyandeson de Arau´jo Delmondes, Renata Evaristo Rodrigues da Silva, Jose´ Galberto Martins da Costa, Marta Regina Kerntopf, Henrique Douglas Melo Coutinho, Roˆmulo Romeu No´brega Alves, and Walte´cio de Oliveira Almeida Abstract Bioprospecting of biotherapeutics focusing on the search for new drugs is still underdeveloped. Consequently, methodological bioprospecting aspects are also scarce. In this chapter, the reader will be exposed to a brief explanation of antibacterial and modulatory activity evaluation of zootherapeutics body fat. Key words Zootherapeutics, Fatty acids, Antibacterial activity, Modulatory effect

1

Introduction Human communities have developed substantial knowledge regarding zootherapeutic medicinal and therapeutic properties, where the use of these natural resources as medicine is indicated as an alternative for medicines the pharmaceutical industry makes available to the population at prices according to their socioeconomic or cultural reality [1]. Populations from developing countries primarily use traditional medicinal resources in their health systems [2]. Consequently, the biodiverse knowledge from traditional communities regarding pharmacological properties is essential for the discovery of new drugs [3]. The study by Mahawar and Jaroli [4] states that there is an increasing number of studies investigating which species are used and marketed in traditional medicine, showing that the use of medicines prepared from animal products is a common practice in deprived regions. In Brazil, studies report a wide variety of animals

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_18, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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being used for medicinal and magical-religious purposes, where the use and commercialization of the species occurs commonly in public markets, fairs, and fishing communities [5–7]. The use of zootherapeutics in traditional medicine raises discussions surrounding the conservation of the species used since many of them are present in endangered species lists [8]. However, understanding the relationships regarding traditional animal use is important even with the concern surrounding the conservation of endangered species. The association between traditional knowledge and scientific knowledge is fundamental for the development of strategies for conservation and management of natural resources [9]. Studies with the objective of evaluating the clinical and pharmacological potential of natural products originating from animals from the Northeast of Brazil have presented interesting results: secretions from the parotid glands of the Rhinella jimi frog can be a source of natural products with antibiotic modifying activity which can be used against multiresistant bacteria [10]; Nasutitermes corniger (“termite”) decoctions have been shown to have antibiotic modifying activity against multiresistant bacteria [11]; Leptodactylus vastus frog nests have shown antimicrobial, larvicidal, hemagglutinating, hemolytic, and surfactant activities [12]. Different biotherapeutic preparation and administration methods are reported. Snakes have their bones and rattles set to dry, followed by milling to obtain a powder, which will then be ingested as a tea or mixed in with meals [13]. Pacas (Agouti paca) have their heads used as amulets to facilitate childbirth [14], whereas secretions, fats, and oils are usually given orally or topically to treat diseases [15]. It is worth mentioning that the use of adipose tissue (fat) is one of the most widely used zootherapeutic resources for the treatment of diseases that occur in man and domestic animals (in ethnoveterinary practice) [16–18]. Moreover, a record of fat from the electric fish Electrophorus electricus, which is indicated for strokes, twists, and insect bites, exists. Hoplias malabaricus, “traı´ra,” is recommended for ophthalmic problems (cataracts). Fat from rattlesnakes (Caudisona durissa) and “Jibo´ia” (Boa constrictor) are used to treat rheumatism. Bird and mammal use for disease treatment is also known. Rhea americana fat is used for general pain, while chicken fat (Gallus gallus domesticus) is indicated for catarrh treatment. In mammals, the medical use of castrated sheep fat (Ovis aries) is reported for the treatment of twists and strokes. However, studies with the objective of validating the potential pharmacological activities originating from zootherapeutics are still scarce. Consequently, few studies describing the methodological processes surrounding zootherapeutic collection to prospection exist. Due to their importance in zootherapeuctics, fats have been

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analyzed for their possible pharmacological properties. From these properties, a growth in the number of studies evaluating their antimicrobial and modulatory activity were found [19, 20]. This study aims to describe the methodological aspects used in antimicrobial and modulatory activity evaluation of biotherapeutic fats developed at the Regional University of Cariri (URCA).

2

Zoological Material Collection Before starting the collection, a request for the permission to collect the desired species should be submitted to the specialized agencies (ethics committees). Another important aspect is that a preliminary investigation should be performed to identify possible collection methods for the species. In the collection area, it is necessary to note the collection date and geographical coordinates where individuals from the species were collected [21]. The transportation and the biological material extraction site must also be scheduled in anticipation. The collection period choice is also of great importance since certain species may not be found during certain periods of the year or may even have changes in body fat composition throughout the year [22, 23]. At the time of fat extraction, it is advisable to have prior knowledge regarding the anatomical aspects of the species analyzed since the material used in the extraction may vary according to the anatomy. Following biological material extraction, this is sent for fixed oil extraction and for specimen deposition at a zoological collection site.

3

Obtaining the Fixed Oil and Fatty Acid Determination Compound separation from natural products can be accomplished by transferring them from one phase to another (solid–liquid, liquid–liquid) [24]. Solvent extraction uses the differences in intermolecular interactions in the liquid phase to separate compounds. In this method, two phases are in intimate contact and the solute (s) can propagate from the solid phase to the liquid phase, causing the separation of the components originally contained in the solid [25]. The organic material used in the extraction should be initially ground and laminated to facilitate solvent penetration. Thus, the organic material, in addition to being contained within the cells (causing their removal through diffusion), is also being removed by simple dissolution. This process consists of two steps: first is dissolution, considered to be quick and easy to perform; second is diffusion, considered to be of a slower rate and it is therefore classified as the limiting phase of the process. At the end of the process, a high-velocity extraction at the beginning followed by a

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slower extraction not reaching complete removal in practice is performed [26]. According to Bockisch [27], an ideal solvent for oil extraction has the following characteristics: (a) A high oil solubility at low temperatures; (b) A high selectivity for the substance to be extracted; (c) To be chemically inert, preventing parallel reactions and protecting the equipment; (d) A low viscosity and surface tension, ensuring good percolation and surface wetting; (e) To be easily and completely removed from the oil, with a low energy demand; (f) To be immiscible in water which must be easily removed; (g) A low boiling point and low heat evaporation; (h) To be a low pollutant. An alkane hydrocarbon known as hexane is the most widely used organic solvent in the extraction process. This is because it is the most selective for apolar compounds due to its narrow boiling range and because it is not miscible with water, preventing the occurrence of azeotropic mixtures [26]. The extractor represents the main element of any extraction process. The Soxhlet extraction method was created for the extraction of lipids from a solid material. The extraction of lipids occurs through continuous passage of a solvent through the sample [28]. Fixed oils from zootherapeutics analyzed at the Regional University of Cariri (URCA) were acquired through the addition of adipose tissue to a Soxhlet device using hexane as solvent. After the mixture is filtered and decanted, the oil is dried in a water bath at 70  C for 2 h, and it is then stored in a freezer until needed. Fatty acids are indirectly determined using their corresponding methyl esters. The fixed oil is saponified for 30 min under reflux with potassium hydroxide solution in methanol, following the method described by Hertman and Lago [29]. After suitable treatment and pH adjustment, the free fatty acids from the fixed oil are methylated with methanol by acid catalysis to obtain the respective methyl esters. Constituent analysis is determined by gas chromatography coupled to mass spectrometry (CG/MS).

4

Microbiological Tests Studies have been developed and directed towards the discovery of new antimicrobials derived from natural products to use them in the pharmaceutical and cosmetic industries. Several methods used to evaluate the antibacterial and antifungal activity of these natural

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products exist, where the most commonly known ones are agar diffusion, macrodilution, and microdilution methods [30]. Antimicrobial activity is evaluated by determining the amount of a natural product capable of inhibiting the growth of the tested microorganism; this value is known as the minimum inhibitory concentration (MIC). A relevant characteristic for natural product MIC determination concerns the legal, toxicological, and microbiological aspects pertinent to these compounds or their combinations [31]. The search for new antimicrobial drugs is necessary following the emergence of antibiotic-resistant microorganisms and fatal opportunistic infections associated with AIDS, transplants and antineoplastic chemotherapy [32]. Thus, these studies may contribute to healthcare development by finding more effective and less toxic substances in the fight against resistance and the emergence of pathogenic microorganisms [33–35]. Several chemical compounds with a synthetic origin, as well as natural products, may exhibit direct antibacterial activity and/or increase the activity of specific antibiotics, reversing the resistance of bacterial types to certain antibiotics, promoting the elimination of plasmids that carry resistance determinants and inhibiting plasma membrane transportation of some classes of antibiotics. Increasing antibiotic activity or reversing resistance using natural or synthetic unconventional antibiotics are classified as antibiotic action modifying agents [36, 37]. Therefore, promoting studies aimed at discovering natural products with active principles that have direct antibacterial activity or modulating activity in combination with antibiotics may represent a new way of dealing with multiresistant microorganisms, as well as preventing bacterial contact with antibiotics, reducing the risk of selecting new or better bacterial resistance mechanisms [38]. 4.1 Preparation of the Initial Solution

The fixed oil from the species in the initial solution preparation will be solubilized in dimethyl sulfoxide (DMSO; Merk, Darmstadt, Germany), at a ratio of 10 mg of the fixed oil to 1 mL of dimethyl sulfoxide, obtaining an initial concentration of 10 mg/mL. This solution will then be microdiluted in sterile distilled water to reach a concentration of 1024 μg/mL.

4.2 Microorganisms for the Test

The experiments are performed with clinical isolates and standard lineages.

4.3 Preparation and Standardization of Bacterial Inocula

Before carrying out the tests, the selected strains should be transferred to HIA media and incubated at 37  C for 24 h. Afterwards, the strains should be inoculated in BHI at the concentration recommended by the manufacturer and incubated in the previously mentioned conditions. Suspensions with bacterial growth will be diluted in 10% BHI to reach 106 cells/mL [39].

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4.4 Minimum Inhibitory Concentration (MIC) Determination

MIC determination of the fixed oil occurs through the broth microdilution method with concentrations varying from 512 to 8 μg/mL. This method uses small volumes of the medium and the sample, distributed in sterile microplate wells. At 1024 μg/mL, 100 μL volumes will be serially diluted (1:1) in 10% BHI broth. The last cavity should be used as a control. The filled plates should be incubated at 37  C for 24 h [40]. The MIC of the samples is determined by the addition of the resazurin sodium (Sigma) indicator solution at 0.01% (w/v). After incubation, 20 μL of the indicator solution are added into the plate’s wells, where after 1 h at room temperature, the plate readings are taken. A change from blue to pink staining due to the reduction of resazurin pH indicates the presence of bacterial growth. The MIC is determined as the lowest concentration in which no growth is observed, as evidenced by an unaltered blue color [41].

4.5 Drug Action Modulation

To evaluate the fixed oil as a modulator of antibiotic action, MICs of the antibiotics should be evaluated in the presence of the oil in sterile 96-well plates. The oil should be mixed in 10% BHI broth at a sub-inhibitory concentration. Preparation of the antibiotic solution should be performed with the addition of sterile distilled water at a concentration double the initially defined concentration and 100 μL volumes serially diluted in 10% BHI broth. Each well with 100 μL of the culture medium contains the diluted bactericidal suspension (1:10). The filled plates will be incubated at 37  C for 24 h followed by resazurin addition for bacterial growth analysis [42].

4.6 Statistical Analysis

Data are expressed as Geometric Mean (G.M.) and Standard Error of the Mean (S.E.M.). Statistical significance was assessed using a two-way ANOVA (Analysis of Variance) followed by Bonferroni’s post hoc test (where p < 0.05 and p < 0.0001 were considered significant and p > 0.05 not significant), using the GraphPad Prism 6.0 software.

References 1. Alves RRN, Rosa IL (2005) Why study the use of animals products in traditional medicine? J Ethnobiol Ethnomed 1:1–5 2. Raskin I, Ribnicky DM, Komarnytsky S, Ilnic N, Poulev A, Borisjuk N, Brinker A, Moreno DA, Ripoll C, Yakoby N, O’neal JM, Cornwell T, Pastor I, Fridlender B (2002) Plants and human health in the Twenty-First century. Trends Biotechnol 20:522–531 3. Ragavan S (2008) New paradigms for protection of biodiversity. J Intellect Prop Rig 13:514–522

4. Mahawar MM, Jaroli DP (2008) Traditional zootherapeutic studies in India: a review. J Ethnobiol Ethnomed 4:1–12 5. Andrade JN, Costa-Neto EM (2005) Primeiro registro da utilizac¸˜ao medicinal de recursos pesqueiros na cidade de Sa˜o Fe´lix, Estado da Bahia, Brasil. Acta Sci Biol Sci 27:177–183 6. Alves RRN, Rosa IL (2007) Zootherapeutic practices among fishing communites in North and Northeast Brazil: a comparison. J Ethnopharmacol 111:82–103 7. Ferreira FS, Albuquerque UP, Coutinho HDM, Almeida WO, Alves RRN (2012) The

Antibacterial and Modulatory Activities trade in medicinal animals in northeastern Brazil. Evid Based Complement Alternat Med 2012:1–20 8. Alves RRN (2009) Fauna used in popular medicine in Northeast Brazil. J Ethnobiol Ethnomed 5:1–7 9. Rist S, Dahdouh-Gabas F (2006) Ethnosciences – a step towards the integration of scientific and indigenous forms of knowledge in the management of natural resources for the future. Environ Dev Sustain 8:467–493 10. Sales DL, Morais-Braga MFB, Santos TL, Machado AJT, Araujo-Filho JA, Dias DQ, Cunha FAB, Saraiva RA, Menezes IRA, Coutinho HDM, Costa JGM, Ferreira FS, Alves RRN, Almeida WO (2017) Antibacterial, modulatory activity of antibiotics and toxicity from Rhinella jimi (Stevaux, 2002) (Anura: Bufonidae) glandular secretions. Biomed Pharmacother 92:544–561 11. Coutinho HDM, Vasconcellos A, Lima MA, Almeida-Filho GG, Alves RRN (2009) Termite usage associated with antibiotic therapy: enhancement of aminoglycosides antibiotic activity by natural products of Nasutitermes corniger (Motschulsky, 1855). BMC Complement Altern Med 9:35 12. Hissa DC, Vasconcelos IM, Carvalho AFU, Nogueira VLR, Cascon P, Antunes ASL, Macedo GR, Melo VMM (2008) Novel surfactant proteins are involved in the structure and stability of foam nests from the frog Leptodactylus vastus. J Exp Biol 211:2707–2711 13. Alves RRN, Alves HN (2011) The faunal drugstore: animal-based remedies used in traditional medicines in Latin America. J Ethnobiol Ethnomed 7:9 14. Silva MLV, Alves AGC, Almeida AV (2004) A zooterapia no recife (Pernambuco): uma articulac¸˜ao entre as pra´ticas e a histo´ria. Biotemas 17:95–116 15. Alves RRN, Rosa IL (2006) From cnidarians to mammals: the use of animals as remedies in fishing communities in NE Brazil. J Ethnopharmacol 107:259–276 16. Confessor MVA, Mendonc¸a LET, Moura˜o JS, Alves RRN (2009) Animals to heal animal: ethnoveterinary practices in the semi-arid region, Northeastern Brazil. J Ethnobiol Ethnomed 5:37 17. Souto WMS, Moura˜o JS, Barbosa RRD, Alves RRN (2011) Parallels between zooterapeutic practices in ethnoveterinary and human complementary medicine in northeastern Brazil. J Ethnopharmacol 134:753–767 18. Costa-Neto EM, Alves RRN (2010) Estado da arte da zooterapia popular no Brasil. In: Costa-

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28. Correia IMS (2009) Extrac¸˜ao e piro´lise do o´leo de girassol (Helianthus annusl.) visando a produc¸˜ao de biocombustı´veis. Dissertac¸˜ao (Mestrado em Engenharia Quı´mica). Departamento de Engenharia Quı´mica, Universidade Federal do Rio Grande do Norte, Brasil 29. Hartman L, Lago RCA (1973) Rapid preparation of fatty acid methyl esters from lipids. Lab Pract 22:475–477 30. Ostrosky EA, Mizumoto MK, Lima MEL, Kaneco TM, Nishikawa SO, Freitas BR (2008) Me´todos para a avaliac¸˜ao da atividade antimicrobiana e determinac¸˜ao da concentrac¸˜ao inibito´ria minima (CIM) de plantas medicinais. Rev Bras Farmacogn 18(2):301–307 31. Pinto TJA, Kaneko TM, Ohara MT (2003) Controle biolo´gico de qualidade de produtos farmaceˆuticos, correlatos e cosme´ticos, 2nd edn. Atheneu, Sa˜o Paulo, p 323 ˜ es MC, 32. Penna C, Marino S, Vivot E, Cruan ˜ oz JD, Cruan ˜ es J, Ferraro G, Martino V Mun (2001) Antimicrobial activity of argentine plants used in the treatment of infections diseases. Isolation of active compounds from Sebastiana brasiliensis. J Ethnopharmacol 77:37–40 33. Michelin DC, Moreschi PE, Lima AC, Nascimento GGF, Paganelli MO, Chaud MV (2005) Avaliac¸˜ao da atividade antimicrobiana de extratos vegetais. Rev Bras Farmacogn 15:316–320 34. Leita˜o SG, Castro O, Fonseca EM, Julia˜o LS, Tavares ES, Leo RRT, Vieira RC, Oliveira DR, Leita˜o GG, Martino V, Sulsen V, Barbosa YAG, Pinheiro DPG, Silva PEA, Teixeira DF, Lourenc¸o MCS (2006) Screening of Central and South American plant extracts for antimycobacterial activity by the Alamar Blue test. Rev Bras Farmacogn 16:6–11 35. Lima IO, Oliveira RAG, Lima EO, Farias NMP, Souza EL (2006) Atividade antifu´ngica de o´leos essenciais sobre especies de Candida. Rev Bras Farmacogn 16:197–201

36. Molnar J, Molnar A, Spengler G, Mandi Y (2004) Infectious plasmid resistance and efflux pump mediated resistance. Acta Microbiol Immunol Hung 51:333–349 37. Wolfart K, Spengler G, Kawase M, Motohashi N, Molnar J, Viveiros M, Amaral L (2006) Interaction between 3,5-diacetyl1,4-dihydropyridines and ampicillin, and erythromycin on diferrent E. coli srains. In Vivo 20:367–372 38. NCCLS (Nattinal Committee For Clinical Laboratory Standards) (2003) Methods for dilution antimicrobial for susceptibility test for bacteria that grow aerobically, 6. Wayne, PA: NCCLS Approved Standard M7-A6, 50–62 39. Coutinho HDM (2010) Validation of biological activities and isolation of natural products Coutinho HDM (2010) Validation of biological activities and isolation of natural products of animal origin. In: Costa-Neto EM, RRN A (eds) Zoo Therapy: Animals in Brazilian Popular Medicine, NUPPEA, Recife, pp. 189–198 40. Javadpour MM, Juban MM, LO WC, Bishop SM, Alberty JB, Cowell SM, Becker CL, Mclaughlin ML (1996) De novo antimicrobial peptides with low mammalian cell toxicity. J Med Chem 39:3107–3113 41. Palomino JC, Martin A, Camacho M, Guerra H, Swings J, Portaels F (2002) Resazurin microtiter assay plate: simple and unexpensive method for detection of drug resistance in Mycobacterium tuberculosis. Antimicrob Agents Chemother 46:2720–2722 42. Coutinho HDM, Costa JGM, Lima EO, Falca˜o-Silva VS, Siqueira-Junior JP (2008) Enhancement of the antibiotic activity against a multiresistant Escherichia coli by Mentha arvensis L. and chlorpromazine. Chemotherapy 54:328–330

Chapter 19 Population Ecology of Plant Species Subjected to Extractivism: Collection and Data Analysis Methods Juliana Loureiro Almeida Campos, Ivanilda Soares Feitosa, and Ulysses Paulino Albuquerque Abstract Extractivism of forest products is an old practice that significantly contributes to the generation of income and subsistence of several traditional peoples and communities around the world. When practiced in an unsustainable manner, this action can compromise the population viability of the extracted species, leading to a decrease in plant populations and, in some cases, cause local extinction. In this chapter, we discuss the main methods and techniques used in research that seek to evaluate the ecological consequences of the extraction of forest products. We present the advantages and limitations of each method and the approaches for analyzing the data collected. Ultimately, it is the researcher’s decision to choose the most appropriate method for their research questions. Key words Harvesting effects, Population models, Sustainability

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Introduction Several plant species have been used by human populations to meet their subsistence demands, such as food, medicine and handicraft manufacturing (for commercial purposes, for example). Among the uses given to the most exploited plants, non-timber forest products (NTFPs) are the most remarkable. They are classified as general resources, with the exception of wood, extracted from natural forests for human use [1]. Examples of NTFPs are nuts, almonds, fruits, leaves, roots, bark, flowers, latex, resins, and fibers. The collection of NTFPs can help to promote the conservation of plant resources, while contributing to the income generation of extractivist families, contributing to their autonomy [2–4]. However, some studies have demonstrated that plant populations can be affected in different ways by these extractive activities [5, 6], and that the consequences of this practice are relatively intense depending on the part of the plant extracted and of the regeneration

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_19, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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capacity of the species. For example, intense leaf extraction for commercial purposes may lead to a decrease in the number of reproductive structures due to changes on resource allocation in the plant [7], while commercial extraction of fruits may lead to reduced recruitment, resulting in changes in the population structure of the exploited species [8]. Thus, in sites of intense leaf and fruit extraction, the populations of the exploited species may present a low amount of regenerating individuals when compared to populations whose species are not exploited. Wood exploitation is also frequent and is among the oldest forest uses [9]. Timber forest products cover all woody material with potential for use as stakes, firewood, and fences, and for use in constructions, power generation, and cellulose production [10, 11]. The consequences of logging are usually more damaging when compared to NTFP extraction, since this practice can lead to the immediate death of the individual. For example, the populations of the palm species Euterpe edulis Mart. (Juc¸ara) decreased dramatically due to intense palm heart extraction in the Brazilian Atlantic Forest [12]. In the case of species that occur in clumps, such as ac¸aı´ (Euterpe oleracea Mart.), a sustainable management is expected to present a greater chance of success [13]. In some African countries it is common to extract sap from the stipe of some palm species to produce an alcoholic beverage widely used by local populations [14]. However, depending on the intensity and purpose of the extraction, such action may lead to the death of the individuals extracted [15]. Extractivism may also present more severe consequences for species that have multiple uses when compared to species extracted for a single purpose [16]. In this chapter, we present the main methods used in researches that intend to evaluate the ecological consequences of the extraction of plant species by local populations. It is important to emphasize that there is no one method better than the other, but methods that are most appropriate for each research objective, considering factors such as time of accomplishment and resource availability.

2

Selection of Plant Species and Populations The first step to implement a study on extractivism assessment is to select the species and plant populations to be evaluated. In general, the local community can indicate the species and populations that are most extracted and the priority sites for the study. Based on this, it the level of exploitation is evaluated, as well as if they are threatened of local extinction. Whenever possible, it is important to select populations that undergo different exploitation intensities, besides including populations that do not experience exploitation (control areas). This is fundamental for directing conclusions related to the sustainability of the extractive practice. In addition,

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it is important to record the environmental characteristics of each selected population (e.g., temperature and mean air humidity, soil characteristics, types of anthropogenic disturbances, land use patterns, presence of cattle). These factors may influence the ecological responses of plants and should be considered for the research design.

3

Population Structure Studies The analysis of the population structure is one of the most applied methods in studies that aim to evaluate the ecological consequences of the extractive practice. The use of such methodologies in ethnobiological studies is important, for example, to identify the relationship between cultural importance, knowledge and use of one or more species, and the possible sustainability of the practices (Box 1). Individuals in a population differ in many ways, and some of these differences reflect the chances of their survival and reproduction. These differences can be measured by the diameter, height, or ontogenetic stage of individuals. These variables are used to verify the structure of the population. Generally, this analysis is associated with methods that assess the levels of resource extraction, in order to identify if this exploitation is causing negative effects on plant populations. This method is widely used due to its practicality in relation to other methods, because it depicts a punctual scenario about the distribution of the individuals in a place, without the need to follow them for some time. However, it also presents a limitation, since the static design decreases the researcher’s power to make inferences that are more robust. Regarding some points when assembling the sampling design of the study may reduce the problems that the limitation of the method presents. One example is to have a significant and distributed sample effort in different collection areas. The more the areas sampled, the more the researcher will have evidence that extractivism is actually responsible or presents a greater contribution to the observed population structure. Box 1 Example of the Use of the Population Structure Method in Ethnobiological Studies: Feitosa et al. [17] aimed to understand the sustainability of bark extraction from Stryphnodendron rotundifolium Mart., a species widely exploited by residents of the Araripe National Forest, Northeast Brazil, for medicinal purposes. For this, the authors analyzed the population structure and the exploitation rates of bark from this species, selecting two areas of vegetation (Cerrado) that seemed to undergo intense exploitation of this

(continued)

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Box 1 (continued) resource. In each area, a plot of one hectare was allocated, totaling two hectares. In each plot, all plants that were within the criterion of inclusion, which was presenting a diameter of 3 cm at ground level, were measured and georeferenced. Individuals that presented signs of exploitation were also measured in relation to their scars (strips of bark removed). At the end of the study, all plants were classified according to their diameter and percentages of bark removed. It was observed that the population structure of the species in question was compromised, since several diametric classes showed absence of individuals and many others were dead, probably due to bark extraction.

After selecting the areas, it is time to choose the sampling method to be applied. The most common methods are the use of plots or the point-quarter, the first being the most common. For the location of a plot, it is first necessary to demarcate the boundaries of the plot according to its size, using a tape measure and a string. The size and number of plots to be established depends greatly on the type of vegetation in which the study area is located, the size of the area to be sampled and the ecology of the species studied. For example, in the case of species that occur in spots, the ideal is that the plots are always located within the range of occurrence of the species. When subdivided, its limits can be signaled with pickets (pieces of wood stuck to the ground). This is usually arranged for the researcher to locate himself effectively within the perimeter (Fig. 1). Within each plot, all individuals of the species selected will be counted and measured for height (with the assistance of a graduated rod) and circumference at ground level (CGL) or circumference at breast height (CBH), both using the tape measure (Fig. 2). It is recommended that, after measurements, individuals are tagged (using the material of the researcher’s preference) to avoid double measurements of the same individual (see [17]). In general, in this type of study, inclusion criteria are defined for the measurement of individuals, which varies according to the vegetation type studied (see [17–20]). In a population structure study, it is important that individuals are classified into ontogenetic stages, which are the set of morphological, physiological, anatomical, and biochemical characteristics that represent the function of individuals within a population [21]. The determination of the ontogenetic stage may be more important than the chronological age, since plants at different stages exert different functions in a population [22]. Based on

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Fig. 1 Schematic representation of a sampling; (a) plot, (b) point-quarter

Fig. 2 Examples of sampling methods of plant species individuals. (a) Circumference measured at breast height; (b) circumference measurement at ground level; (c) total height measure of a seedling. Photos: Andre´ dos Santos Souza and Temo´teo Luiz Lima da Silva

this distribution, it is possible to compare the proportion of individuals at each ontogenetic stage among the studied populations, as well as to verify if there are relations between the intensity of extractivism, the environmental variables and the different ontogenetic stages within the same population. For example, Escalante

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et al. [23] found that in sites with greater light availability and moderate rates of environmental disturbance, leaf collection rates of Desmoncus orthacanthos Mart. may be higher, since these environments appear to be ideal for the development of this species. For the bromeliad of sub-forest Aechmea magdalenae (Andre´) Andre´ ex Baker, population growth rates were higher in secondary forest environments when compared to older forests, indicating that the former environments may provide greater economic incentives for the populations that collect the leaves of this species [24]. In the point-quarter method, the researcher draws a straight line (size defined according to the research objective) and perpendicular to it equidistant lines are drawn (quantity and distance defined according to the research objectives). In each of the lines wooden crosses are employed (point-quarter), located 10 m apart in a way that there is no overlap between the samples (Fig. 1), selecting at each point the individual closest to the point [25]. The same measurement and identification procedures described above are performed for the individuals selected at the point-quarter. The difference between the two methods is that, in the plots, the researcher identifies all the individuals that are the focus of the study (one or several species) within a delimited area, whose area depends on the aim of the research. By applying the point-quarter, the researcher only samples individuals that are close to the points marked within the transect (Fig. 3).

Fig. 3 Sampling of individuals using the point-quarter method. Photo: Andre´ dos Santos Souza

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After collecting the data on species growth (height, circumference at ground level, or circumference at breast height), they should be transferred to a spreadsheet editor and organized according to Table 1. The values of circumference measured at ground level (CGL) or circumference at breast height (CBH), if chosen for analysis, can be transformed into diameter at ground level (DGL) or diameter at breast height (DBH), by applying the following formulas: DGL ¼ CGL/π, in which π ¼ 3,14 or DBH ¼ CBH/π, in which π ¼ 3,14. The DGL (or DBH) and total height values of individuals should be included in classes that group a set of individuals together. We suggest that the diametric classes should follow the 2 cm interval between them, with the first class starting from the inclusion criterion. For example, if the inclusion criterion is DGL  3 cm, the following classes would be: class 1 (3–5 cm), class 2 (5.1–7 cm), class 3 (7.1–9 cm), class 4 (9.1–11 cm) and so on. Regarding the height, we suggest a 50 cm interval between the classes, with the first class starting from the lowest individual measured in the plot. For example, if the smallest individual presents a height of 2 m, the following classes are suggested: 1 (200–250 cm), class 2 (250,1–300 cm), class 3 (300,1–350 cm), class 4 (350.1–400 cm), class 5 (400.1–450 cm), and so on. After inclusion of the individuals in diametric classes and height classes, graphs with the results of the structure of each population studied should be plotted and interpreted. A population whose distribution is shaped as a “J-inverted1,” presents a large number of individuals in the classes of smaller size and this number

Table 1 Example of spreadsheet organization for collecting population structure data of plant species that experienced leaf and/or fruit extraction Area

Plot

Individual

Height (m)

CGL (cm)

CBH (cm)

1

1

1

5,5

16,1

15,5

1

1

2

3,2

12,2

10,4

1

1

3

1,7

6,0

5,0

1

1

4

...

...

CGL circumference at ground level, CBH circumference at breast height

1

The analysis of the “J-inverted” based on visual models exhibits limitations in the elaboration of conclusions related to the sustainability of the extraction, since other population parameters such as growth rate and mortality rate are not included in these analyses.

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Fig. 4 Examples of graphs that can be built based on the population structure data collected. (a) Example of graph with results of height classes. (b) Example of graph with diametric class results

decreases gradually towards the classes of larger sizes, suggesting population stability and a good capacity of regeneration. Figure 4 shows examples of graphs that can be built with the results of height classes and diametric classes of two fictitious populations. Notice in Fig. 4b the diametric distribution of the “J-inverted” shape. The adjustment of the height (or diametric) distributions of each of the populations to the “J-inverted” model can be calculated from a negative exponential model, with the equation y ¼ ae  bx: Where y represents the percentage of individuals in each class, x is the midpoint of the classes, a is the intercept, and b is the slope of the line, which biologically represents the population mortality rate [26]. Simple regression analyses should be performed with each of the populations studied. In these analyses, the number of individuals in each class will be considered the response variable and the value of the average points will be considered the explanatory variable. The slope values of line (b) are analyzed to verify the trend of self-perpetuation of populations, which can be verified when the slope of the line is negatively accentuated [27]. This regression can define specific collection or management rates in the different diametric classes [18]. An example of the use of the “J-inverted” model for the analysis of the viability of the population structure can be found in Giroldo and Scariot [28], who evaluated the influence of anthropogenic and ecological factors on the demography of Caryocar brasiliense, a species that has its fruits collected by local populations of the Brazilian Cerrado. The density of ontogenetic stages and the

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distribution of diametric classes of 34 populations of the species were associated with different forms of land use and different intensities of fruit extractivism. The majority of the populations presented a “J-inverted” diametric distribution, indicating good recruitment. The authors concluded that the levels of fruit extraction are not affecting the recruitment of populations. However, pasture was negatively associated with seedling and infant densities, while vegetation thinning was negatively associated with the densities of seedling, young and adult individuals [28].

4

Population Dynamics Studies The number of individuals in a population varies over time in terms of spatial, genetic, and population structures. The study of population dynamics aims at evaluating the size of populations due to different processes such as seed dispersal, seed survival in the soil, recruitment of seedlings, survival and growth of individuals, reproduction and mortality. As can be noticed, this method is more labor intensive and requires more time than the previous one, since populations are evaluated more than once, following the changes in the parameters evaluated. Next, we will present the main mathematical models used in population dynamics studies.

4.1 Life Tables (LTRE—Life Table Response Experiments)

The life table (LTRE) is ideal for the study of annual species, since the researcher must follow a cohort of individuals throughout their life cycle [29]. This method has been used to verify how the observed differences in survival, growth, and reproduction rates between exploited and non-exploited populations (control) contribute to the observed differences in population growth (λ) [30]. Thus, rates with high contributions in the life table are those that exert the greatest contributions on the differences observed in λ between the extracted and non-extracted populations [31]. Plots are the most common sampling method in this type of study, and its application follows the same steps described previously. Within the plots, a census of all individuals is performed in relation to the number of births and deaths. Censuses are executed at short intervals (e.g., monthly), with the same type of data being recorded for each census. Through such data it is possible to calculate population parameters such as survival, mortality rate, life expectancy, and fecundity. This method is advantageous when it is desired to verify which vital rate or which size class contributed most to the different rates of λ observed during the studied period, as well as the different conditions studied. However, the need for control areas often makes the execution of LTRE unfeasible. An example of the use of life tables can be verified in the study conducted by Gaoue and

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Ticktin [32]. When investigating the effects of bark and leaf collection on the population dynamics of Khaya senegalensis (Desv.) A. Juss, the authors observed that the differences observed in λ between populations subjected to different collection intensities and located in regions with different ecological characteristics, are mainly due to differences in individual stasis2 (54.4%) and growth (38.2%) of individuals. 4.2 Matrix Projection Models (MPM)

Matrix projection models (MPM) are suitable for the study of species with a long life cycle, since in this model it is not necessary to follow a cohort throughout its life cycle. MPMs are measures of vital rates (survival, growth, and reproduction) of individuals over time. Individuals are divided into size classes or ontogenetic stages (seedlings, infants, juveniles, adults, etc.). Based on it, population growth rates (λ) are calculated for each size class during a demographic interval3 to estimate the life expectancy of the species in question against the situation studied [30], verifying if the population is growing, is stable or tends to decline. After a certain time a new sampling should be performed, observing, for each previously identified individual, whether or not occurred a transition to another class or the death of the individual. Seedlings entering the population shall be recorded at each new sampling. The proportion of individuals moving from one size class to another, or remaining in the same size class, are recorded, determining transition values between matrices [33]. Thus, the dynamics of a population calculated by matrix models is described by the probabilities of individuals moving from one size class to another [34], applying the equation nðt þ 1Þ ¼ Anðt Þ Where n is a vector of size m that contains the number of individuals in each of the categories i of 1 to m, and A is the square matrix of dimension m  m that contains the transitions of the categories j (from 1 to m) at time t to categories i (from 1 to m) at time t + 1 [34]. Changes in vital rates (growth, survival, and reproduction) may promote changes in population growth rates (λ), and the importance of each of these parameters for λ can be calculated through sensitivity and elasticity analyses4 [31]. These analyses have been used to design changes in λ in response to small variations in the vital rates of the populations studied [30, 35], triggered by anthropic processes or environmental factors. Sensitivity analysis

2

Defined as the persistence of the individual at the same stage during its life history [32]. It is the time interval defined between two demographic samplings. 4 These are perturbation analyses that quantify the contribution of each element of the transition matrix to the composition of the population growth rate (λ). Sensitivity measures the absolute contribution, while elasticity is a relative measure of that contribution. 3

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allows us to verify the influence of different vital rates on λ, informing how changes in the vital rates of each age group affect population growth rates [30]. Conversely, the elasticity analysis allows us to verify how λ is modified in relation to small changes in the matrix transition elements (survival, growth, and reproduction) [36]. Thus, a change in vital rates that have high elasticity will result in a large impact on λ, just as changes in vital rates that have low elasticity will result in low λ changes [30]. Through the building of matrix models, Svenning and Macia [37] verified that the collection of leaves of the palm tree Geonoma macrostachys Mart. by the Huaorani indigenous people in the Ecuadorian Amazon presented greater long-term sustainability in open forests of more recent formation. Though, as a condition for this sustainability, it is necessary that the targets of the collection are adult individuals and not in sub-adults, which is common in the region. However, Lopez-Toledo et al. [38] observed that the cumulative effects of leaf extractions of the palm Chamaedorea elegans Willd reduced leaf characteristics (leaf size, leaf area, leaf persistence, and leaf production rate), survival, growth, and reproduction of the populations studied. This effect is stronger in female palms than in male palms, regardless of plant size, although the recovery of leaf extraction was faster in male palms. The survival rate recovered first, followed by growth, while reproductive characteristics showed a much slower recovery rate [37]. 4.3 Integral Projection Models (IPM—Integral Projection Model)

Although LTRE analyses and matrix projection models presented previously are extremely used in the modeling studies of populations subject to extractivism, they exhibit certain limitations. One is the need for individuals to be grouped into size classes for the construction of these models. In these groupings, very similar individuals are treated as if they were identical, especially if the population is divided into a few classes, often masking the transition dynamics of the population [39]. When dealing with species that present a long life cycle, such as trees and palm trees, the problem of the use of matrix models becomes even more significant, since the annual changes in the size of individuals are very small in comparison to the maximum size that they can reach, and the transitions between the different categories of matrices are practically impossible to observe from one year to the subsequent year [33]. For example, Enright et al. [40] found that in matrix models built for perennial species, the decrease in the number of size classes increased the importance of survival rates related to population growth rates. Increasing the number of size classes to minimize this problem can also generate errors in the analyses, since few individuals would be present at each stage [41]. Besides that, the separation into size classes may also affect the interpretation of the elasticity and sensitivity analyses [40].

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In this sense, Easterling et al. [39] proposed the integral projection model (IPM), an approach that avoids the need to group individuals in size classes and provides more precise analyses regarding the demographic behavior of the population at the individual level through the use of continuous variables that determine the size of individuals in a discrete time interval, such as height measurement, circumference at ground level, or circumference at breast height. Thus, vital rates do not depend on size classes, such as in matrix models, but on individual sizes. The IPM presents greater precision in the estimates than the matrix models, since it considers the variations between individuals. The integral projection model for the number of individuals of size y at time t + 1 is described by the equation: Z nðy; t þ 1Þ ¼ ½pðx; y Þ þ f ðx; y Þnðx; t Þdx K

Where p(x, y) ¼ probability of survival and growth of an individual from size x to size y, f(x, y) ¼ number of individuals of size y produced by parental individuals of size x. We can replace the two functions above by the equation: K ðy; x Þ ¼ pðy; x Þ þ F ðy; x Þ Where K is the projection core (kernel), which represents all possible transitions from size x to size y, and it is analogous to the projection matrix that contains nonzero entries for survival, growth, and fecundity [39]. The projection matrix is replaced by the projection core (kernel), represented by the equation: Z nðy; t þ 1Þ ¼ kðy; x Þnðx; t Þdx K

Where: [K] indicates the possible minimum and maximum sizes x at time t; n(x, t)dx is a distribution function that replaces the population size vector (nt), which is a continuous variable (x) that describes the size of the individual at the time t. Similarly to the matrix models, the IPM predicts the population growth rate (λ) and the elasticity and sensitivity functions are also calculated. However, while matrix models represent size distributions, reproductive value and constant sensitivities within a size class, the IPM allows the creation of curves according to individual sizes [39]. It allows the elaboration of more precise and robust conclusions regarding the demographic behavior of the population, allowing to verify the interaction of multiple factors on each individual and on the population as a whole [39, 41]. In addition, it is important to note that in IPM, sensitivity and elasticity analyses are most commonly performed on the kernel (e.g., to verify how the

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population growth rate (λ) changes when kernel disturbances occur) [42]. Martı´nez-Balleste´ and Martorell [43] investigated if the different forms of leaf management and extraction of the palms Sabal yapa Wright ex Becc. and Sabal mexicana Mart. by people of Maya origin affected the vital rates of species in backyards in Mexico. Through the construction of integral projection models, the authors verified that the traditional extraction presented no effect on the vital rates of S. yapa, but altered the individual growth rate of S. mexicana in one of the management systems, concluding that in a few decades this population could be locally extinct if the management procedures are not changed.

5

Final Considerations The present chapter illustrates different methods to evaluate the ecological consequences of extractive practices on exploited plant populations. It is important to mention that the choice of the most appropriate analysis by the researcher will depend on the time available for the research and the objectives to be achieved, given the particularities of each method presented here. In addition, we recommend that the results of researches in this field of study should be shared with the people who execute extractivism, since such results may be useful for the elaboration of management plans that aim at the conservation of the species studied. Finally, we suggest that the demographic analyses cited here should be performed in statistical programs and open source software, such as R [44], available for download at https://www.rproject.org/. We recommend the use of the following packages: popbio [33], demogR [45], popdemo [46], and IPMpack [47].

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Chapter 20 Noninvasive Sampling Techniques for Vertebrate Fauna Leonardo da Silva Chaves, Christini Barbosa Caselli, Rafael de Albuquerque Carvalho, and Roˆmulo Romeu No´brega Alves Abstract Understanding the current threats to biodiversity and how human actions have contributed to it is fundamental. In order to improve our knowledge on this subject, technical expertise is demanded from researchers involved in animal’s diversity studies. Because faunal surveys and monitoring may require a great logistical effort and investments of time and resources, it is important to know all available sampling techniques and how to use them to ensure and optimize the collection of reliable data. In this chapter, we present a brief summary on the main available noninvasive techniques for vertebrate sampling and list other important sources of information for each approach. Besides decreasing the interference in animals’ populations, the noninvasive sampling techniques make it possible to obtain reliable data with reduced investments of time and resources. Key words Trap, Survey, Animal, Ethnozoology, Vestiges

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Introduction In ethnozoological studies, obtaining reliable data on target taxa is a fundamental step to ensure robust results. Due to the great diversity of species biology, habits, and behaviors, when the study focus includes numerous species, the employment of several sampling techniques is usually necessary [1, 2]. This employment of multiple approaches represents an enormous limitation for ecological studies [2, 3] and, similarly, for ethnobiological studies, due to the required investments of time and resources. The accelerated process of defaunation, and the urgency to understand the contribution of human activities to such process require fast and well-targeted information collection [4]. The mission of acquiring such information will demand from ethnozoologists a good knowledge on available sampling techniques and their range of application. Traditional techniques employed on faunal data sampling usually involve animals’ capture and handling. This

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_20, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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approach, besides demanding a greater amount of time, also require a great logistic effort, and might expose both the researcher and animal to unnecessary risks [5, 6]. Another relevant drawback of invasive methods is the legal and ethical aspects involved, which demand project evaluation by local and national environmental and ethics committees. This chapter presents a synthesis of several methods commonly applied to obtain ecological data on terrestrial vertebrates without the need of capture or handling of animals, which are known as noninvasive [7]. In addition to their ethical and methodological advantage of reducing the researcher interference on the animal behavior and populations, such methods are particularly suitable for sampling cryptic species or species that often avoid the usual traps [8], such as carnivorous mammals. The increased use of non-invasive techniques has shown that such approaches are feasible and useful to generate reliable data within a short time period with a reasonable financial investment and logistical effort [1, 9], expanding the range of possibilities to outline effective sampling designs.

2

Using Bioacoustics in Biodiversity Survey Sounds produced by animals for communication and orientation can encode a signature for species identification [10, 11]. Acoustic signals can reach great distances, even within dense vegetation, and propagate in the darkness [11], allowing for species detection without the need to visualize it. Consequently, animal sounds have been increasingly used in surveys of many vertebrates, such as fishes, anurans, birds, and mammals [12–18]. For acoustically conspicuous species, acoustical sampling can be a simple and noninvasive alternative comparatively to other commonly employed techniques, such as catching or trapping [19]. Acoustical surveys can be conducted through point-counts during fixed intervals or along transects within defined areas [12, 19, 20]. In the simplest approach, trained listeners write down all species that are detected [21]. However, audio recordings are recommended to support acoustic detection and identification through further visual inspection of spectrograms, which can reveal signaling events not perceived in the field or signals that are out of the human hearing range, such as bat ultrasounds [19]. The use of recordings can avoid the potential observer effect, especially when more observers collect the data, reducing interobserver variance [12, 22]. The use of recordings to obtain the data will restrict the need of a trained expert only to interpret the recordings. Besides that, sound recordings can be stored and serve as an evidence of species detections [10, 15].

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Overall, acoustic survey usually involves the following steps: recording, visualizing, and analyzing sound recordings. These steps require appropriate equipment and software. In order to record animal sounds manually, a microphone and a digital recorder are needed, although self-contained systems like digital voice recorders can be used [23]. Considering the habitat of the species and the characteristics of their sounds, some important aspects of the equipment must be taken into account before choosing it. For instance, the omnidirectional microphone is preferred for obtaining acoustic recordings in acoustical surveys, given that the sounds of different species from any direction are usually the target. For both microphone and recorder, the researcher needs to check the equipment’s frequency response (related to the range of frequencies that can be registered), the gain (related to the equipment sensitivity) and evaluate the need of acquiring a waterproof equipment (or a hydrophone in case of underwater recordings). Today several options and suppliers are available. The Macaulay Library at the Cornell University provides valuable overviews of basic equipment (https://www.macaulaylibrary.org/contribute/audio-recordinggear/). For automated recordings, digital systems that are capable of recording on a programmable schedule are also becoming progressively affordable. The Song Meter (Wildlife Acoustics Inc., Concord, MA), is a popular and widely used dual-channel weatherproof acoustic recorder. Models for audible and ultrasonic sounds or to record both simultaneously are available. Other affordable options are the automated portable acoustic recorder of the Automated Remote Biodiversity Monitoring Network—ARBIMON (Sieve Analytics Inc., San Juan, Puerto Rico) and the terrestrial autonomous recording unit (Swift) supplied by the Cornell Lab’s Bioacoustics Research Program (Ithaca, NY). The sounds recorded can be identified by listening to the recordings [24] or by creating algorithms to automate species identification [25–28]. The use of automated recorders, for instance, will allow the collection of a huge number of recordings and, consequently, demand a greater effort for processing and analyzing it. Fortunately, new computer tools and algorithms that standardize and automate the process of signals detection, classification and identification are quickly becoming available for many vertebrates, such as bats [25, 29], marine mammals [30, 31], birds [10, 28], amphibians [15], and primates [32]. Moreover, estimates of wildlife diversity can focus on the soundscape produced by a local community rather than in identifying an individual species [17]. Software for sound visualization, editing and analysis include commercial products, such as Avisoft-SASLab Pro (Avisoft Bioacoustics, Glienicke, Germany), nonprofit software, such as Raven Pro (Cornell Lab’s Bioacoustics Research Program), which also offer discounts that depends on the country and for students. The

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“Selection Review” tool of Raven Pro is very helpful for reviewing and annotating detections along the recordings. Free and open source are also available, such as the Seewave [33] and warbleR [34] extension of the R software [35]. With the Seewave package, it is also possible to compute acoustic indices for inferring animal’s diversity from recordings of soundscapes [33]. The warbleR package provides a function to perform automatic signal detection. The commercial Kaleidoscope Pro software (Wildlife Acoustics Inc.) allows the user to build classifiers for automatic recognition and classification of species. For bats, the software license includes classifiers for automatic species identification of bats from North America, the Neotropics, the UK and Europe, and South Africa. Tools combining hardware and software for automating data acquisition, management, and species identification are also available, such as Automated Remote Biodiversity Monitoring Network— ARBIMON (Sieve Analytics, Inc.). The choice of the equipment and software will depend on the survey purpose, project budget, habitat type (transmission characteristics), focal taxa (signal proprieties and abundance), and the extent of the area to be covered. The last two factors combined with the characteristics of the receivers (microphone and recorders) also influence the active space of recording (distance over which the receivers can detect sounds). It should be considered to define the number of recordings to be deployed, as well as its arrangement in the field and protocol Schemes [23, 36, 37]. Another important auxiliary tool for acoustically surveying species is the use of playbacks. Such method, in combination with transects distributed throughout the entire study area does not only improve detection of vocally responsive species [20, 38, 39], but also allows to generate density estimates of individuals or groups [20, 40]. Thus, acoustic surveys have also been used to estimate animal abundance, density and others related metrics. For instance, the use of point-counts or automated recorders (scheduled to record at specific time intervals) spaced far enough apart to avoid recording the same individuals can be used to generate these estimates [20, 41]. In this approach, occupancy modeling can be useful to adjust the counts for incomplete detection and the sampled area [41, 42]. A final important thing to consider when planning an acoustic survey, especially when using autonomous acoustical processing, is to have basic knowledge about species-characteristic acoustic signals. In this sense, description of acoustic repertoire and sound libraries are fundamental sources for species’ sounds identification and training or adjusting software for automated detection. Links to animal sound collections and libraries are listed at the International Bioacoustics Council Website: http://www.ibac.info/links. html#libs.

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Sampling Fauna by Vestiges Animal sampling based on vestiges is generally used to obtain three basic parameters: distribution, relative abundance, and absolute abundance [43]. This can be a satisfactory alternative for sampling species [44] that are elusive, possess a large home range, or are capable of actively avoiding catch traps [43], like some carnivores. The fundamental assumption of a method based on vestiges is that many animals leave unquestionable signs of their presence in the area they use. In some cases, these signs are left intentionally. This is the case of species that use their excreta for territory demarcation, leaving them in sites relatively predictable for the researcher [45]. Other kind of vestiges, like footprints, are unwittingly left and, in addition to being easily detectable, its pattern of track records often can provide the researcher a clear information about the animal spatial occupation [45].

3.1

Feces Counting

Counting the fecal material of a species can be used to estimate its relative abundance between distinct areas or in a single area, in different moments. This can be done through two main approaches: (1) by comparing (proportion) the fecal material present in parcels or transects with standardized dimensions, randomly demarcated, or (2) by calculating the rate of accumulated fecal material in fixed parcels, which is monitored so that only fresh scats are counted. Estimating absolute abundance is also possible if there is information on the daily fecal production of the target species and the time of decomposition of the feces. Therefore, the absolute abundance is calculated by dividing the defecation rate (number of droppings/daily fecal production) for the time of decomposition (number of days the dropping takes to decompose [45]). The biggest problem of using feces as an estimator of abundance concerns its correct identification and the difficulty in correlating the recorded fecal material with the target species [44], especially when there are very closely related species in the sampled area. However, as demonstrated by Harrington and colleagues [46], local expertise can help to identify the scats with a high accuracy. Guides for scats, presented in the literature, concerning the country or region that contains the study area might be available and be crucial for the correct identification of the fecal material [46, 47] (but see [48]). Although this is not an essential step for most surveys, if it is necessary and there is the possibility of a slightly larger investment, the fecal material can be identified, in exceptional cases, by means of molecular analyses [49]. Feces counting may also be biased by behavioral factors. Carnivores, for instance, present a seasonal variation in their territorial demarcation behavior, which may influence the rate of feces drop.

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The presence of predators is another factor that may also modify the behavior of the target species in a similar way [46]. It is also noteworthy that environmental conditions may influence the process of fecal deterioration [50], leading to a loss of information if the monitoring of the parcel is performed between long intervals. Some cautions should be taken while designing the study to minimize some bias in the method of feces counting. The standardization of sampling sites and interval in long-term monitoring or the sampling more similar habitats when comparing areas, are strongly recommended. With the necessary logistic investment and the correct application of the method, the fecal collection and monitoring can provide very useful data [43]. 3.2

4

Trace Surveying

By traces, it is meant the various types of signs left in the environment by animal activity. Footprint are perhaps the most obvious and reliable traces, once animals in general present own morphological traits in their hands and feet that are particular to their species (i.e., autapomorphies), which allow to distinguish the imprints left by most of them [51]. Thus, searching for traces can be a relatively cheap and quite useful alternative for surveying information about wildlife. The simplest approach of a trace surveying method consists in establish standardized parcels and transects in areas with terrain that promote the impression of footprints, such as roadsides [52], rivers banks [43], or trails [53]. The estimates are performed by counting the number of footprints recorded, which provides an abundance index based on the number of occurrences by unity of sampling effort (see below). The estimate of absolute abundance can also be calculated whenever individual identifications are possible. Stander and colleagues [51] have shown that local experts and field assistants, besides being able to distinguish individuals’ footprints, are able to give information on gender and range, as well as details about the behavior of an animal by tracking them (apparently not so reliable with small-sized animals [54]). More objective methods are also useful for the individual differentiation, which involve taking detailed measures of footprints [51] and taking photography for further comparisons [55]. In addition, to allow the outfield identification of footprints, negative replicas can be made with plaster mold (following the manufacturer’s instructions) with the assistance of any object that works as mold (e.g., cross section of a PVC tube) [56].

Noninvasive Traps Beyond searching and recording animal traces or signs of the presence of some species, hair, feathers and feces can be actively collected by using specific noninvasive traps. Even though they

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spend a little more effort than simple trace surveying, they require a much lower logistical effort than the use of catch traps, allowing the elaboration of a standardized and systematized sampling design. Since the plots can be arranged at random, independently of the type of sediment, this approach allows ecological parameters (e.g., richness, abundance, density) to be estimated more accurately [45, 57]. 4.1

Track Stations

Track stations are simple and low-cost devices, elaborated with the purpose to record animal footprints with a higher precision. The two most common types of track stations are the sand parcels and track plates, which are particularly more efficient in detecting medium and large-sized mammals. Sand parcels are built with a four-square measuring at least 50
50 cm, 3 cm deep, containing thin sand, which must be installed in areas free of plant-litter [58]. It is usually made with a shallow wood box, used as a mold and filled with sifted sand, removed from the present site [58]. Each sand parcel must be daily moistened. In desert and semiarid regions, it must be done twice a day. Track plates, in turn, consists of aluminum plates, dimensioned as the sand parcels, covered by soot, which is usually obtained from the burning of kerosene [59], or by a solution of carpenter chalk and ethanol [60, 61]. An ink track tunnel might be a more suitable alternative for recording footprints of small-sized animals [62]. It consists of a cylindrical tube (e.g., a PVC pipe), with dimensions appropriate to the species to be registered. A sheet of paper with same length of the tube and about half the circumference is fixed inside the tube to cover its floor. At the edge of the tube, near one-third of the sheet is covered by an atoxic ink in a manner that by crossing the tube the animal may agitate its feet and leave prints on the white paper [63]. Track stations must be monitored daily for as long as the fieldwork lasts. If footprints are found, they must be recorded and erased (which must be done by hand, for sand parcels, or by applying more soot) or replaced. The main disadvantage of the track stations is that, except for the ink track tunnel, its efficiency is highly affected by environmental conditions, such as rain and wind. Still, such method has an inestimable value for surveying several animal groups, such as carnivores [61].

4.2

Hair-Traps

Hair-trap, also usually called hair-snare, is a general name given to any device capable of collecting animal hair. The simplest hair-trap consists in a carpet surface (10
10 cm), pierced by near ten nails with the tips facing outwards (roughly 1.5 cm length), which are able to catch the hair of medium and large-sized animals [64]. In order to record short-haired animals, an alternative is the use of two Velcro straps, with the hook-face turned outwards to contact the animal [65]. Other materials can be used, such as strong double sized adhesive tape or cat and dog brushes.

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The hair-traps can be fixed on tree trunks or even rocks, as well as adapted to convergence traps or tubes (e.g., PVC tubes) in order to induce the animal to contact the trap [66, 67]. In order to attract some type of animals, the use of essences is common, such as cat nip oil, some type of commercial fragrances and others lures (see [68] for carnivores). A huge variety of hair-traps designs has been described, with its applicability and efficiency in catching hair varying among different mammalian groups (e.g., [61, 69, 70]). Thus, the researcher must decide for a specific type or a set of hair-traps that may yield a better result according to the objectives of the study [65]. It is important, however, to keep in mind that there is a limitation of using hairtraps. Animals that possess very little hair, such as the armadillo species, or very reduced hair, such as kinkajou (Potos flavus), hardly will be recorded by any type of hair-traps [65]. Although hair-traps demand low financial and logistic investments in the field, it should be noted that such method invariably require a high post-collect effort. For an appropriate hair-based identification of the species, the use of macroscopy techniques [71, 72] or molecular analyses are [73, 74] necessary.

5

Camera Traps Camera trap consists in a method of photography and recording of short videos. Most commonly it uses a device that is triggered automatically by sensors that are capable of detecting an animal a few meters away. Such devices are quite versatile, once they can record animals of several taxa, including more elusive animals, like the felids [75]. In fact, some studies showed that almost the totality of the known species of medium and large-sized mammals of a specific area can be surveyed by using camera traps, depending only on how great the sampling effort is [76]. Some authors have also adapted the method in order to record arboreal small mammals [77, 78]. Camera traps installation must consider the habits of the target species of the study [57]. For aquatic or semiaquatic animals, the cameras should be placed near seas, lakes, rivers, or other bodies of water where they inhabit. For terrestrial animals, it is recommended to install the cameras along trails, which can be used by several species, with an angle set between 60 and 45 in relation to the trail direction (increasing the time of animal exposure) or perpendicular to it, in cases where pictures of the sides of the animals are necessary. Baits can be placed in front of the camera to attract the animals. Before placing and setting the cameras, searching for traces of the passage of animals, as well as the presence of natural attractive (e.g., body of waters, burrows, and fruit trees) can maximize the

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potential of capture. Furthermore, one should avoid placing the camera in sites that are under direct sunlight during the day, which may cause convection waves that are capable of repetitively triggering the camera, filling its memory and requiring an enormous effort to filter photos and videos [76]. When the installation sites are chosen, the camera can be fastened on tree trunks or artificial stakes, at roughly 50 cm from the ground. It is important to clean the area in front of the camera to prevent the animal from being partial or totally overgrown behind the herbaceous or shrub vegetation. It is also important to test the camera to make sure it is working adequately (following the manufacturer instructions), as well as to check the field of vision. One of the great advantages in using camera traps is the small logistic effort required. Such kind of equipment can be left running for weeks at the sampling site without any maintenance, while registering the exact day and time of each captured image. Not only these images may be used for estimating the data of abundance and species richness [9], but they also have been used for other purposes, such as ethological studies [78] and studies of habitat preference and use [79]. References 1. Lyra-Jorge MC, Ciocheti G, Pivello VR, Meirelles ST (2008) Comparing methods for sampling large- and medium-sized mammals: camera traps and track plots. Eur J Wildl Res 54(4):739–744. https://doi.org/10.1007/ s10344-008-0205-8 2. Garden JG, McAlpine CA, Possingham HP, Jones DN (2007) Using multiple survey methods to detect terrestrial reptiles and mammals: what are the most successful and cost-efficient combinations? Wildl Res 34(3):218–227. https://doi.org/10.1071/WR06111 3. Tobler MW, Carrillo-Percastegui SE, Leite Pitman R, Mares R, Powell G (2008) An evaluation of camera traps for inventorying largeand medium-sized terrestrial rainforest mammals. Anim Conserv 11(3):169–178. https:// doi.org/10.1111/j.1469-1795.2008.00169.x 4. Boivin NL, Zeder MA, Fuller DQ et al (2016) Ecological consequences of human niche construction: examining long-term anthropogenic shaping of global species distributions. Proc Natl Acad Sci U S A 113(23):6388–6396. https://doi.org/10.1073/pnas.1525200113 5. Kelt DA, Van Vuren DH, Hafner MS, Danielson BJ, Kelly MJ (2007) Threat of hantavirus pulmonary syndrome to field biologists working with small mammals. Emerg Infect Dis 13 (9):1285–1287. https://doi.org/10.3201/ eid1309.070445

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Chapter 21 Techniques to Evaluate Hunting Sustainability Leonardo da Silva Chaves, Christini Barbosa Caselli, Andre´ Luiz Borba Nascimento, and Roˆmulo Romeu No´brega Alves Abstract Hunting is an activity historically practiced by human populations in all regions of the planet. Currently, its impact on wild species populations has led to growing concerns about the consequences of the loss of wildlife biodiversity, especially in tropical forests, raising questions about the limits of its sustainability. In this chapter, we indicate the main protocols used in research to evaluate the impact of hunting on the populations of target animals, emphasizing their principles, describing their application and, finally, discussing how to make inferences about the sustainability of hunting activities. Key words Hunt, Conservation, Model, Bushmeat, Ethnozoology

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Introduction Subsistence hunting is an activity historically practiced by human populations in virtually every region of the planet [1, 2]. However, due to population growth, easy access to hunting areas and more efficient technologies for catching animals, this activity has intensified [3]. As a consequence, its impact on populations of wild species has led to a growing concern about the consequences for the loss of wildlife biodiversity, especially in tropical forests [1, 4]. Studies on the effects of hunting have demonstrated several scenarios in which this exploitation has promoted an intense depletion of the abundance of the target populations [5]. However, the effects of hunting are extremely variable and both hunting strategies and the target species population characteristics are factors that strongly influence potential impacts on biodiversity. For example, species with higher reproductive rates, such as rodents and wild pigs, seem to be quite resilient to hunting levels that are generally not supported by animals such as primates and tapirs [6]. In assessing the sustainability of game hunting, it is essential to define the concept of sustainability to be adopted. This is important

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5_21, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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because, in general, the studies evaluate the consequence of hunting, that is, how much hunting activity compromises the associated fauna, and infer about the sustainability of the activity. Thus, definitions of what is sustainable or not will vary depending on the particular characteristics of each species (e.g., reproductive and migratory capacity) and the spatial and temporal scale evaluated (e.g., single isolated fragment or multiple interconnected fragments; horizontal or longitudinal study). It is common to consider that there is sustainability of hunting when target populations remain “healthy” or “stable,” for example, if the removal of animals is lower than the recruitment capacity of new individuals of the populations investigated. However, these assessments are subjective and make it difficult to establish a single clear quantitative limit between sustainable and unsustainable hunting regimes [7], since this will depend on the research question. Thus, it is necessary to establish in advance the outline of the study to be performed, defining which species will be evaluated, what data will be collected, and what is the spatial and temporal scale to be considered. The most common work plans are based on comparing population data on a small set of hunted species between areas with higher levels of hunting pressure and areas with lower levels or no pressure. Less numerous, but also common and generally more reliable, are the monitoring approaches, which collect data over time and evaluate how populations of target species react to hunting pressures. In this chapter, we indicate the main protocols used in research to evaluate the impact of hunting on populations of target animals, highlighting their principles, describing their application and, finally, discussing how to make inferences about the sustainability of hunting activities. In order to better systematize this information, the protocols are categorized here into two groups: closed population models and open population models. The difference between these models is the analysis of the consequences of hunting in animal populations, where open population models consider ecological patterns in a broader spatial framework including the effect of events such as migration, while in closed population models these factors are disregarded.

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Closed Population Models

2.1 Density, Abundance, or Biomass Variation

The simplest approach to infer sustainability consists in comparing ecological parameters estimates such as density, abundance, or biomass of target species between hunting and non-hunting areas or control areas. This model assumes that differences found in these values between the two areas can be attributed to hunting pressure (see [8–10]).

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In order to conduct this type of research the researcher should: Define hunting areas and control areas—The choice of areas to be investigated is the crucial point in this technique, since it is based on the comparison of the areas. The means to make this choice are diverse, from individual interviews with hunters to participatory methods. Here we emphasize the use of community mapping [11], in which community members recognized as hunters gather and are invited to draw a map of the community and associated landscape, indicating the areas they access for hunting; Define the species to be evaluated—The choice of the evaluated species should be made based on records of their hunting in the investigated area (either directly, through interviews, or indirectly using local lists of hunting activity, or through scientific articles on the subject in the area under investigation). The researcher should ensure that hunting pressure is the differential factor among the populations of the species evaluated in the investigated areas, isolating, as much as possible, the effect of other variables (e.g., microhabitats, fragment size, availability of resources); Define the population parameter to be used—After defining areas and species, the researcher should consider what parameter will be the most appropriate for the scenario to be investigated. Abundance (total and relative) density (total and relative), and biomass (total and average) are the most common examples. The choice of the parameter and the species evaluated will guide the selection of the most appropriate fauna sampling method [12]. However, some knowledge about how these ecological parameters vary between the areas sampled in the absence of hunting and how the capture capacity of preys varies in relation to changes in density are desirable. The lower density of animals in a hunting area does not necessarily mean that hunting is not sustainable [7]. The observed difference between the areas may simply be the result of geographical variation, for example. Besides, even when the density of animals is below a supposed load capacity expected for the studied area, it is not possible to affirm that the hunting is at an unsustainable level. Since hunting pressure always causes a reduction in fauna density, it is necessary to know the effect of the reduced abundance on the local birth and mortality rate [13]. Density data of the game fauna from the monitoring of the population in the same area over time can also be used to make inferences about the sustainability of hunting. In this case, the rate of decline in ecological parameters estimates represents the impact of hunting and the fundamental idea is that a steady declines of populations subjected to a fixed rate of game pressure indicates its inability to recover. Therefore, hunting is unsustainable [13].

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The main limitation of this type of protocol is that it alone does not accurately evaluate the sustainability of hunting, since the population estimates obtained are very limited measures to consider all possible consequences of hunting activity [14]. In addition, there is great difficulty in finding comparable areas of hunted and non-hunted populations. 2.2 Variation in Hunting Yield

Another useful model for making inferences about sustainability is the use of the hunting rate (number of individuals caught or biomass hunted per unit of hunting effort) (see [15, 16]). This model is based on an indirect measure of the density of target species (individuals caught or biomass hunted) and its fundamental assumption is that similar areas subject to the same hunting pressure should present similar catch rates. Thus, areas with catch rates below the expected may be experiencing unsustainable hunting pressure. The Hunting Yield (R) is an estimate of hunting rate and can be measured by the number of individuals hunted annually in an area that can be obtained from the hunter’s personal records of how many animals were hunted by them at each collection event, during a year [17]. Alternatively, it can be measured by the carcasses of the animals counted by the researcher in each event of collection by hunter interviewed [17]. This data can be calculated as follows: 1. R ¼ n(a)/At where: “n(a)” is the total number of individuals collected in the assessed area per year, and “At” is the total area of the assessed fragment (km2). 2. R ¼ b(a)/At where: “b(a)” is the total biomass hunted (kg) collected in the assessed area evaluated per year, and “At” is the total area of the assessed fragment (km2). This model can also be used in a longitudinal study, based on the recording of the hunting yield over time. The prolonged decline in hunting yields may indicate the progressive depletion of hunting populations and consequently an unsustainable hunting scenario. However, it is important to evaluate the time that the area sampled has been subjected to hunting, since in areas where hunting activity is recent, a reduction in hunting yield is expected until there is a break-even point [13]. Studies that assess the hunting performance should also beware to changes in the composition of species caught by hunters. For instance, in tropical areas larger species are preferred and prioritized when hunting is practiced for subsistence purposes [18]. In an overcrowded scenario, as populations of larger biomass species are reduced, hunting efforts can be redirected to smaller species. Since in general smaller species occur in greater abundance, if hunting

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yield is being measured by the number of prey per unit of hunting effort, the data may indicate an increase in hunting yield, masking an unsustainable hunting scenario. Additionally, the results can be highly affected by the area evaluated (larger areas make it difficult to track the different hunters who forage in the area) and on the sample effort (number of hunters for whom the data were collected on each collection event), which can generate ambiguity about the information obtained from hunting [14]. 2.3 Assessment of Age Structure

3

A survey of the age structure of a population subject to hunting can also be used to assess the sustainability of hunting activity (e.g., [19]). In this case, the age structure of the target species is compared between hunting and control areas. In case there are significant differences between the areas, hunting is considered unsustainable [17]. The classification in age classes is generally performed according to the size of the animals captured (see [17, 20]). In situations where hunting is practiced selectively, effort is commonly directed to larger (older) individuals [18]. If hunting is occurring at a tolerable intensity, it is expected that there will be no change in the age structure of the population. Conversely, recording a high proportion of young individuals in the population may reflect excessive and unsustainable hunting activity [7, 13]. Changes in game population pyramid are therefore a possible evidence of high hunting intensity. However, alone they are not sufficient to access the sustainability of hunting activities [14].

Open Population Models

3.1 Population Analysis Model, and Combined Stock Recruitment and Population Analysis Models

Hunt sustainability can be directly evaluated by comparing the hunting pressure (HP; individual/km2) with game population’s production (P; individual/km2) [19]. The models using this approach are known as population analysis models [13]. It is based on some detailed information about species demography, such as population density, average number of young individuals per female, and average number of gestations per year. In order to calculate the annual population productivity ( p)—the average number of young individuals per female per year—the populations’ reproductive capacity (R) is multiplied by the female density. Female density can be derived from population density estimates (D) resulting from census, multiplied by ½, considering a population sex ratio of 1:1. The reproductive capacity is estimated by multiplying the mean number of offspring produced per females (row reproductive capacity, RR) for the mean number of gestation per year (G). The production (P; individual/km2) is then calculated as follows: P ¼ (0.5D)(RR * G). The hunting pressure (HP) is

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usually more difficult to obtain. However, it could be ideally estimated from data on the number of hunted animals for a defined catchment area (n/km2). After obtaining the final proportion of the population production hunted per year (HP/P), a final conclusion on how sustainable the local harvest is must consider the number of adult individuals in the population that will die even in the absence of hunt. The lifetime of a species is then used to derive some thresholds for sustainable harvest. Robinson and Redford [21] suggests that the proportion of production hunted can be set at 0.6 (or 60%) for very short-lived species (for which the last reproduction happens before 5 years), 0.4 for short-lived species, and 0.2 for long-lived species (for which the last reproduction happens from 10 years on). Thus, in order to be sustainable, the proportion of annual production harvest (HP/P) should not be greater than these thresholds, considering species’ lifetime (Sustainable Yield; SY). Let us consider the study case of hunting sustainability evaluation for Amazonian ungulates in the Tahuayo, Peru [19]. Based on the local productivity of female tapirs (0.25) and their mean number of gestation per year (0.5), the author of the study calculated a total productivity of 0.125. In order to obtain the local production we can multiply this value for half of tapir density (0.4), resulting in 0.05 individual/km2. Considering a hunting pressure of 0.08 individual/km2, the proportion of annual production harvest (HP/P) is 1.6 (or 160%), which is eight times greater than the 0.2 (or 20%) threshold considered for long-lived species. Thus, the current hunting pressure on tapir is not sustainable. The error involved in the calculation of all inputs in the model can also be included (e.g., for the density and hunting pressure estimates), when applicable, to evaluate whether the hunt is sustainable even when superior margins of error are included. An important drawback of the population analysis model is the fact that it evaluates hunting sustainability for a discrete period. The combination of this model with the stock recruitment model can circumvent this limitation, given that the stock recruitment model allows the evaluation of the harvest activity in the long term [22]. Similarly to the population analysis model, the evaluation of harvest sustainability in a discrete time is based on the comparison between the current proportion of the production hunted (HP/P) and the fixed sustainable thresholds based on species life span (20%, 40%, or 60% of the production). By combining this model with the Stock-recruitment Model, the sustainability of hunting activities can be evaluated for a range of population densities, varying from the extirpation point (when the population is zero) to the populations’ carrying capacity (K). In order to evaluate if the current explored production is sustainable in the long term, we can determine how close the current population is from its carrying capacity and from the maximum sustained yield (MSY), a fixed threshold for

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Fig. 1 Diagram representing the combined stock recruitment and population analysis models. Similarly to the stock recruitment model, the combined model allows the evaluation of hunting sustainability for a range of population densities ranging from its extirpation (0) to its carrying capacity (K). The line representing the sustained Yield (SY) set the limits for a sustainable hunting activity for a given production in time. Sustainable hunting activity can occur at any population density provided that the proportion of production hunted (HP/P) is below the sustainable yield thresholds (like in N2). When the proportion of production hunted surpass the line representing the sustained yield thresholds, overhunting is happening (such as in N1). The maximum sustained yield (MSY) set the limits for a sustainable hunting activity in the long term. A sustainable long-term hunting regime can only be established when the relative game population is located between its carrying capacity and the maximum sustained yield (MSY), like in N2

the relative population size (50%, 60%, or 80% of the population when on its carrying capacity) that is also based on individuals’ life span. Thus, for a hunting regime to be sustainable in the long term, the relative density of the population at a giving time must be greater than the fixed MSY considering its life span (80%: for long-lived species; 60%: for short-lived species; or 50% for very short-lived species; Fig. 1). 3.2 Population Growth Model

The “population growth model” [21] or “production model” [7] provide estimates to evaluate the sustainability of harvests in the absence of specific information on local density and reproductive yields. Thus, it is a commonly used model for evaluating sustainability of hunting in the Neotropics [23–25]. It evaluates the sustainability of the current harvest under the maximum game production condition. Estimates of the maximum game production available for harvesting is then calculated and compared with actual harvests. In order to estimate the maximum production (Pmax) this model requires information on the species carrying capacity (K) and maximum population growth rate (λmax), which is the rate of population increase when the population is not limited by resources constraints or by predation pressures (under optimal conditions). The latter is calculated based on life history data of the species under consideration, such as age at the first reproduction, age at the last reproduction, and the annual rate of births, that can be

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extracted from the literature. The maximum production is then calculated by multiplying the population density at its maximum productivity by its maximum growth rate (λmax). This model assumes that population density at its maximum productivity is at 60% of the carrying capacity (0.6K). Similarly to the Population Analysis Model, the thresholds for sustainable hunting is fixed in 60%, 40%, or 20% of the productivity, based on the species life span, from very-short lived to long-lived species [13]. The maximum population growth rate (λmax) is then weighted by these thresholds to obtain an effective population growth rate that is then used to determine the maximum productivity actually available for hunting, or the maximum potential yield (for details on how to calculate the maximum possible production of a population see [3]). Alvard et al. [23] produced estimates of maximum potential yield based on population growth model to evaluate the faunal harvests of two native subsistence Neotropical communities (Yomiwato and Diamante) in Peru. The authors also used indicators of game species abundance (encounters with prey per hour during hunts) to test for the depletion of species harvested in numbers greater than the predicted to be sustainable. The hunters at one or both communities harvested tapir, spider monkeys, and capuchin monkeys at rates higher than the predicted as the maximum sustainable. In the case of tapir, for example, the annual harvest (10.6–14.1 kg/km2) was more than twice the annual potential sustainable harvests estimated by the Population Growth Model (4.47 kg/km2). However, not all prey that the model predicted to be overhunted showed evidences of being locally depleted. This was the case for spider monkeys at Yomiwato. This find can reflect the limitations of this model, given that estimates are produced for a defined catchment area, assuming prey do not migrate. Another drawback of population growth model is that it estimates the maximum population production under optimal conditions [13]. Therefore, the model is suitable for evaluating when current harvesting activity is excessive or not sustainable, however, it cannot inform if it is sustainable when below the maximum potential yield. The advantage of this model is that it can provide a first assessment of game sustainability in the absence of detailed information on species. However, we must be aware that the estimates produced are rough. 3.3 Source–Sink Model

A fragility of models that assess the sustainability of hunting activities is that most of them ignore a fundamental aspect of ecosystems, the migration and dispersal dynamics of species between hunting and non-hunting areas [7]. Although some of the models presented previously assume that hunted populations are open, such models implicitly assume that the majority of species captured by hunters are exclusively the result of the reproduction of individuals within the hunting area [26].

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A great portion of the areas that are subject to strong hunting pressure in Neotropical regions, for example, are located near conservation units [26]. In such scenarios, once areas with higher hunting pressures experience a reduction of density of target species to a level below the carrying capacity of the environment, the recovery of hunted populations is not only linked to the birth rates in the hunting area but also to the dispersion of individuals from more preserved areas to more hunted areas [26]. The source–sink model adopts the assumption of the metapopulation structure and can be applied to both continuous and fragmented areas [7]. For this model, information on the status of target populations is required not only from the area with strong hunting pressure (sink), but also from source areas (with low or no hunting pressure). Besides that, whenever possible, information on movement of animals between areas is also required [7]. These animal subpopulations from uninhabited areas can migrate and supply the subpopulations of affected areas with new individuals. Thus, information from all areas can be incorporated, for example, into a unified model of exploitation (e.g., [27]), in which it is possible to calculate the percentage of hunted production and the risk of exploitation for each sampled area, independently. Thus, these parameters can be estimated throughout the “source–sink” region [7]. In this case, even though the level of exploitation is slightly above the safe limit in the area of higher hunting pressure, throughout the source-sink extension, it is possible that hunting is sustainable. However, it is important to emphasize that using source areas to justify the exploitation of excessive hunting in sink areas is a dangerous strategy. The most correct strategy would be to promote the management of source areas located near sink areas that are subject to sustainable levels of hunting as an approach to ensure the equilibrium of populations during possible excessive hunting periods [7]. In addition, data on the movement of animals between areas are difficult to collect, which does not ensure the real potential for migration of individuals between areas.

4

Final Considerations Throughout the chapter it is possible to observe different approaches to evaluate the sustainability of hunting. However, all the protocols presented here are subjected to certain limitation. Their application is often contingent on specific scenarios because of the incorporation of scant information on the biology of the target species and their population dynamics. Closed population models are simpler and easier to reproduce. However, they do not consider events that are fundamental for the demography of the evaluated species, such as migration. Conversely, open population

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models are less restrictive, although they lack a more accurate method to evaluate the effect of hunting on metapopulations. Thus, it is advisable to have a critical judgement in applying the abovementioned protocols, both for the improvement of the techniques listed here, and to have a certain parsimony regarding possible inferences for sustainability based on the results found. The use of more than one protocol can assist in the evaluation of hunting activities, providing better evidence on the sustainability of these activities in the evaluated areas. References 1. Alves RRN, Souto WMS, Fernandes-FerreiraH, Bezerra DMM, Barboza RRD, Vieira WLS (2018) The importance of hunting in human societies. In: Ethnozoology. Elsevier, Amsterdam, pp 95–118. https://doi.org/10.1016/ B978-0-12-809913-1.00007-7 2. Bahn PG, Vertut J (1997) Journey through the ice age, 1st edn. University of Clalifornia Press, Clalifornia 3. Robinson JG (1999) Calculating maximum sustainable harvests and percentage offtakes. In: Robinson JG, Bennett EL (eds) Hunting for sustainability in tropical forests. Columbia University Press, New York, pp 521–524 4. Robinson JG, Bennett EL (2002) Will alleviating poverty solve the bushmeat crisis? Oryx 36 (04):2014. https://doi.org/10.1017/ S0030605302000662 5. Benı´tez-Lo´pez A, Alkemade R, Schipper AM et al (2017) The impact of hunting on tropical mammal and bird populations. Science 356 (6334):180–183. https://doi.org/10.1126/ science.aaj1891 6. Bodmer RE, Eisenberg JF, Redford KH (1997) Hunting and the likelihood of extinction of Amazonian mammals. Conserv Biol 11 (2):460–466. https://doi.org/10.1046/j. 1523-1739.1997.96022.x 7. Bodmer RE, Robinson JG (2004) Ana´lise da sustentabilidade de cac¸a em florestas tropicais no Peru – Estudo de caso. In: Cullen L, Rudran R, Valadares-Pa´dua C (eds) Me´todos de Estudos Em Biologia Da Conservac¸˜ao e Manejo Da Vida Silvestre, vol 2004, 1st edn. Editora da UFPR, Curitiba, pp 593–629 8. Hill K, McMillan G, Farina R (2003) Huntingrelated changes in game encounter rates from 1994 to 2001 in the Mbaracayu Reserve, Paraguay. Conserv Biol 17(5):1312–1323. https:// doi.org/10.1046/j.1523-1739.2003.01135.x 9. Peres CA (2000) Effects of subsistence hunting on vertebrate community structure in Amazonian forests. Conserv Biol 14(1):240–253.

https://doi.org/10.1046/j.1523-1739.2000. 98485.x 10. Mena PV, Stallings JR, Regalado JB, Cueva RI (2000) The sustainability of current hunting practices by the Huaorani. In: Robinson JG, Bennett EL (eds) Hunting for sustainability in tropical forests, vol 2000, 1st edn. Columbia University Press, New York, pp 57–78 11. Sieber SS, da Silva TC, de Campos LZ O, Zank S, Albuquerque UP (2014) Participatory methods in ethnobiological and ethnoecological research. In: Albuquerque UP, Cruz da Cunha LVF, de Lucena RFP, Alves RRDN (eds) Methods and techniques in ethnobiology and ethnoecology, 1st edn. Humana Press, New York, NY, pp 39–58. https://doi.org/ 10.1007/978-1-4614-8636-7_3 12. Vieira KS, Vieira WLS, Alves RRN (2014). An introduction to zoological taxonomy and the collection and preparation of zoological specimens. In: Albuquerque UP, Cruz da Cunha LVF, Lucena RFP de, Alves RRDN, eds. Methods and techniques in ethnobiology and ethnoecology. 1st ed. New York, NY, Humana Press; 175–196. https://doi.org/10.1007/ 978-1-4614-8636-7_12 13. Robinson JG, Redford KH (1994) Measuring the sustainability of hunting in tropical forests. Oryx 28(4):249–256. https://doi.org/10. 1017/S0030605300028647 14. Weinbaum KZ, Brashares JS, Golden CD, Getz WM (2013) Searching for sustainability: are assessments of wildlife harvests behind the times? Worm B, ed. Ecol Lett 16(1):99–111. https://doi.org/10.1111/ele.12008 15. Fa JE, Ryan SF, Bell DJ (2005) Hunting vulnerability, ecological characteristics and harvest rates of bushmeat species in afrotropical forests. Biol Conserv 121(2):167–176. https://doi. org/10.1016/j.biocon.2004.04.016 16. Baker GB, Cunningham RB, Murray W (2004) Are red-footed boobies Sula sula at risk from harvesting by humans on Cocos (Keeling)

Techniques to Evaluate Hunting Sustainability Islands, Indian Ocean? Biol Conserv 119 (2):271–278. https://doi.org/10.1016/j. biocon.2003.11.018 17. Hurtado-Gonzales JL, Bodmer RE (2004) Assessing the sustainability of brocket deer hunting in the Tamshiyacu-Tahuayo Communal Reserve, northeastern Peru. Biol Conserv 116(1):1–7. https://doi.org/10.1016/ S0006-3207(03)00167-8 18. Peres CA, Emilio T, Schietti J, Desmouliere SJM, Levi T (2016) Dispersal limitation induces long-term biomass collapse in overhunted Amazonian forests. Proc Natl Acad Sci U S A 113(4):892–897. https://doi.org/10. 1073/pnas.1516525113 19. Bodmer RE (1994) Managing wildilife with local communities in the pervian amazon: the case of the reserva comunal TamshiyacuTahuayo. In: Western D, Wright M (eds) Natural Connections: perspectives in communitybased conservation, 1st edn. Island Press, Washington, DC, pp 113–134 20. Velasco A, Colomine G, Sola R De, Villarroel G (2003). Effects of sustained harvests on wild populations of Caiman Crocodilus Crocodilus in Venezuela. 28(9):544–548 21. Robinson JG, Redford KH (1991) Sustainable harvest of neotropical forest animals. In: Robinson JG, Redford KH (eds) Neotropical wildlife use and conservation. Columbia University Press, New York, pp 415–429

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22. Bodmer RE, Robinson J (2004) Evaluating the sustainability of hunting in the Neotropics. In: People in nature: wildlife conservation in South and Central America. Columbia University Press, New York, pp 299–323. https://doi. org/10.7312/silv12782-019 23. Alvard MS, Robinson JG, Redford KH, Kaplan H (1997) The sustainability of subsistence hunting in the Neotropics. L CJ, Rudran R, Valladares-Pa´dua C, eds. Conserv Biol 11 (4):977–982. https://doi.org/10.1046/j. 1523-1739.1997.96047.x 24. Wilkie DS, Curran B, Tshombe R, Morelli GA (2008) Modeling the sustainability of subsistence farming and hunting in the Ituri Forest of Zaire. Conserv Biol 12(1):137–147. https:// doi.org/10.1111/j.1523-1739.1998.96156.x 25. Naranjo EJ, Guerra MM, Bodmer RE, Bolanos J (2004) Subsistence hunting by three ethnic groups of the Lacandon forest, Mexico. J Ethnobiol 24(2):233–253 http://kar.kent.ac.uk/ 10675/ 26. Novaro AJ, Redford KH, Bodmer RE (2000) Effect of hunting in source-sink systems in the neotropics. Conserv Biol 14(3):713–721. https://doi.org/10.1046/j.1523-1739.2000. 98452.x 27. Naranjo EJ, Bodmer RE (2007) Source–sink systems and conservation of hunted ungulates in the Lacandon Forest, Mexico. Biol Conserv 138(3–4):412–420. https://doi.org/10. 1016/j.biocon.2007.05.010

INDEX A Accelerated solvent extraction (ASE).................. 262, 263 American Declaration on the Rights of Indigenous Peoples (ADRIP)......................................... 232 Analysis of Variance (ANOVA) .................................... 290 Anchorages (AC)............................................................. 57 Araucaria forest .................................................. 196, 200 Archaeological site human–plant interactions .............................. 190–191 Monte Castelo shell mound ................................... 188 Argentina urban agglomerations ............................................. 173 Aromatic amines............................................................ 264 Atmospheric-pressure chemical ionization (APCI).......................................................... 271 Audio recording technique.......................................35, 44 Automated Remote Biodiversity Monitoring Network (ARBIMON) ............................... 311 Autonomous acoustical processing .............................. 312 Avisoft-SASLab Pro ...................................................... 311

documentation ............................................... 223, 224 ethnobiology ........................................................... 215 fieldwork ......................................................... 226–228 herbarium, xylarium, and zoological specimens ..................................................... 216 indigenous knowledge ............................................ 224 industrial economies ............................................... 216 plant identification .................................................. 221 raw materials and manufacture...................... 221, 222 Biocultural diversity ........................................................ 81 Biocultural ecology nature and culture .......................................... 167, 168 people and environment ......................................... 165 Biodiversity Authorization and Information System (SISBIO) ......................................... 233 Biodiversity Law ............................................................ 236 Bonferroni’s post hoc test ............................................ 290 Bray-Curtis coefficient .................................................... 89 Brazilian legislation .............................................. 230, 249 Broth microdilution method........................................ 290 Buenos Aires-La Plata Metropolitan Area ................... 175

B

C

Bacterial inocula ............................................................ 289 Bayesian techniques ........................................................ 76 Bertholletia excelsa ......................................................... 193 Bioacoustics acoustic signals ........................................................ 310 acoustic survey......................................................... 311 audio recordings...................................................... 310 automated recorders ............................................... 311 auxiliary tool............................................................ 312 catching/trapping ................................................... 310 digital systems.......................................................... 311 nonprofit software................................................... 311 occupancy modeling ............................................... 312 sound visualization.................................................. 311 terrestrial autonomous recording unit................... 311 vertebrates ............................................................... 310 waterproof equipment ............................................ 311 Biocultural collections artefacts........................................................... 222, 223 artifacts..................................................................... 222 collaborative research ..................................... 216, 217 digital repatriation................................................... 224

Camera traps......................................................... 316, 317 Canonic correspondence analysis (CCA) .................... 119 ‘Case-by-case comparison’ technique ............................ 50 Cerrado protected areas.................................................. 97 Chico Mendes Institute for Biodiversity Conservation (ICMBio) ..................................................... 233 Chromatographic techniques flash chromatography..................................... 264, 267 GC................................................................... 268, 269 HPLC ............................................................. 266, 268 prefractionation ....................................................... 270 SFC .......................................................................... 269 SPE........................................................................... 270 Chromatography ........................................................... 258 Circumference at breast height (CBH) ....................... 296 Circumference at ground level (CGL)......................... 296 Closed population models age structure ............................................................ 327 density, abundance/biomass variation .............................................. 324, 325 hunting yield .................................................. 325, 327

Ulysses Paulino Albuquerque et al. (eds.), Methods and Techniques in Ethnobiology and Ethnoecology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-4939-8919-5, © Springer Science+Business Media, LLC, part of Springer Nature 2019

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Cognitive interview description ................................................................. 19 use of....................................................................19, 20 Collective subject discourse (CSD) advantages.................................................................. 66 central ideas of question X........................................ 59 characteristics............................................................. 66 construction ........................................................ 60–61 content analysis ......................................................... 56 discourse analysis....................................................... 56 ethnobiological approaches ................................ 61–65 ethnographic studies ................................................. 56 ideology ..................................................................... 56 method ................................................................ 57–60 natural sciences.......................................................... 55 nineteenth century .................................................... 55 qualitative aspects...................................................... 66 qualitative research .................................................... 56 systematic operationalization.................................... 66 verbal expressions ...................................................... 65 Collective Subject Discourse Research Institute (CSDRI)......................................................... 60 Comissa˜o Nacional de E´tica em Pesquisa (CONEP)..................................................... 245 ´ tica em Pesquisa (CEP) ........................... 241 Comiteˆ de E ´ tica em Pesquisa com Seres Humanos Comiteˆ de E (CEPSH)...................................................... 241 Communicational system ............................................. 173 Community-weighted mean (CWM) ............................ 98 Complexity disciplinary...................................................... 169, 170 ethnoscience ............................................................ 168 observer ................................................................... 170 resource.................................................................... 173 self-eco-organization............................................... 165 Computer Assisted Qualitative Data Analysis Software (CAQDAS)..................................... 50 Conselho de Gesta˜o do Patrimoˆnio Gene´tico (CGEN) ....................................................... 233 Content analysis (CA)..................................................... 56 Content validity............................................................... 18 Convention on Biological Diversity (CBD) ................ 231 Correlation spectroscopy (COSY) ............................... 273 Co-theorization............................................................. 216 Criterion-related validity................................................. 18 CSDsoft .............................................................. 60–61, 65 Cultural socioeconomic context .................................. 210

D Data analysis body size .................................................................... 96 EEC .................................................................. 90, 107 HDM ....................................................................... 107

ETHNOECOLOGY IndVal ...................................................................... 107 multidimensional hypotheses ................................... 94 nMDS plots ............................................................... 98 PCoA ....................................................................... 100 RDA ................................................................ 103–105 and visualization abundance data.................................................... 89 association measurement, Q mode ..............88, 89 PCA................................................................ 90–92 PCoA .............................................................91, 93 Data collection environmental risk perception research .............................. 150–152, 154–157 Data visualization ............................................................ 76 Decoctions..................................................................... 259 Defaunation................................................................... 309 Dereplication ................................................................. 275 Descriptive case study ....................................................... 9 Desorption electrospray ionization (DESI).......................................................... 271 Detrented correspondence analysis (DCA) .......................................................... 120 Diameter at breast height (DBH) ....................... 202, 299 Diameter at ground level (DGL) ................................. 299 Digital repatriation........................................................ 224 Digital voice recorders .................................................. 311 Direct observation ....................................................26, 29 Discourse analysis (DA) .................................................. 56 Distortionless enhancement of polarization transfer (DEPT)........................................... 273 Domesticated landscapes ..................................... 187, 201 Double Principal Coordinate Analysis ........................... 93 Drug action modulation............................................... 290 DSCsoft ........................................................................... 61

E Eigenanalysis..............................................................90, 91 Elaeis oleifera ................................................................. 193 Electrospray ionization (ESI) ....................................... 271 Encoding process ............................................................ 49 Environmental changes.............. 164, 176–178, 180–182 Environmental risk perception collection and analysis of ........................................ 150 drawing stimulus method .............................. 151, 152 harmful circumstances ............................................ 149 human ...................................................................... 149 incidence and severity ........................... 152, 154, 155 interviews........................................................ 150, 151 richness and sharing ...............................153, 156–158 Ephemeroptera species ........................................ 106, 107 Essential oil.................................................................... 261 Ethical considerations ...............................................43, 44 Ethics ................................................................................. 5

METHODS

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Ethnobiological particles .............................................. 135 Ethnobiological research audio and video recorders ........................................ 35 communication ......................................................... 36 community perspectives............................................ 35 conducted using good faith.................................... 250 data collection ........................................................... 15 dissemination and publication................................ 250 ethical issues .............................................................. 44 ethical principles ...................................................... 251 ethical procedures ................................................... 236 legal authorization processes .................................. 250 legal procedures biological material and research in protected areas ........................................ 248 indigenous peoples............................................ 245 national system of research ethics ...........................................240, 241, 243 prior informed consent term ............................ 241 traditional associated knowledge and genetic resources and equitable sharing..........244–247 local reality............................................................... 250 pilot studies .........................................................16, 17 pre-tests ..................................................................... 17 principles acknowledgement and due credit .................... 240 active participation ............................................ 238 active protection................................................ 239 confidentiality .................................................... 239 diligence............................................................. 240 dynamic interactive cycle .................................. 240 educated prior informed consent ..................... 239 full disclosure..................................................... 238 inalienability ...................................................... 238 precaution.......................................................... 239 prior rights and responsibilities ........................ 238 reciprocity, mutual benefit and equitable sharing.......................................................... 239 remedial action .................................................. 240 respect ................................................................ 239 self-determination ............................................. 238 supporting indigenous research ....................... 239 traditional guardianship .................................... 238 prior informed consent ........................................... 250 quality control of protocols ................................ 18–19 research protocol....................................................... 16 researcher ................................................................. 209 review of protocols.............................................. 19–22 sharing results.......................................................... 251 validity and reliability ................................................ 22 Ethnobiology .................................... 6, 9, 33, 35, 36, 44, 56, 62 Ethnobiology, ecology and conservation (EEC) ......... 72, 79, 83, 87–89, 91, 93, 94, 97, 98

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Ethnobotany data collection ......................................................... 190 Ethnoecology case of horticulturists .............................................. 178 disciplinary complexity .................................. 169, 170 and ethnobiology .................................................... 189 FCNM ..................................................................... 163 LEBA ....................................................................... 163 resource.................................................................... 172 science and ethnoscience ............................... 168, 169 UNLP ...................................................................... 163 Ethnography.............................................. 6, 7, 25, 29, 30 Ethnoichthyological work ................................... 212, 213 Ethnozoology....................................................... 209–212 Euterpe oleracea ............................................................. 199 Evaporative light scattering detector (ELSD) ............. 266 Evolutionary ethnobiology (EE) ................................. 129 Exploratory case study ................................................9, 12 Extraction ASE ................................................................. 262, 263 attributes.................................................................. 265 biomass .................................................................... 258 decoctions................................................................ 259 description ............................................................... 257 efficiencies....................................................... 263, 264 essential oil .............................................................. 261 hyphenated techniques ........................................... 258 maceration ............................................................... 258 MAE......................................................................... 263 percolation............................................................... 259 reflux ........................................................................ 259 SFE.................................................................. 261, 262 soxhlet...................................................................... 259 UAE ......................................................................... 261 Extractivism NTFPs...................................................................... 293 palm species ............................................................. 294 plant species and populations ........................ 294, 295 population dynamics (see Population dynamics) population structure (see Population structure) sustainable management ......................................... 294

F Facultad de Ciencias Naturales y Museo (FCNM) ....................................................... 163 Feces counting ..................................................... 313, 314 Federal legislation ......................................................... 210 Field journal analysis phase ............................................................. 30 anthropologist’s intimate material ........................... 29 audio recordings........................................................ 31 biodiversity ................................................................ 29 categories ................................................................... 31 content analysis ...................................................32, 33

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Field journal (cont.) earlier interpretations ................................................ 30 ethnographic process ................................................ 30 ethnographic study ................................................... 29 field notes .................................................................. 29 hermeneutic-dialectic method.................................. 32 inexhaustible source .................................................. 28 Malinowski’s personal journal .................................. 29 natural sciences.......................................................... 29 recording observations ............................................. 28 scientific instruments ................................................ 29 socioeconomic characteristics ................................... 30 types of....................................................................... 28 Flame ionization detector (FID).................................. 269 Flash chromatography ................................ 264, 266, 267 Food and Agriculture Organization (FAO) ................ 231 Free induction decay (FID).......................................... 273 Fundo Nacional de Repartic¸˜ao de Benefı´cios (FNRB) ........................................................ 236

G Gas chromatography (GC) .................................. 268, 269 Gaussian distribution .................................................... 156 Generalized Linear Models (GLM) ............................. 156 Genetic Heritage Management Council...................... 233 Genomic ethnobotany .................................................. 112 Geoglyphs...................................................................... 193 Geometric Mean (G.M.) .............................................. 290 Good Agricultural and Collection Practices (GACP) ........................................................ 257 Grounded theory (GT)................................................. 8, 9

H Hair-snare ...................................................................... 315 Hair-traps.............................................................. 315, 316 Hellinger transformation ................................................ 89 Hermeneutic-dialectic method ...................................... 32 Heteronuclear correlation spectroscopy (HETCOR) ................................................. 274 Heteronuclear multiple bond correlation (HMBC) ...................................................... 274 Heteronuclear multiple quantum coherence (HMQC)...................................................... 274 Hexane........................................................................... 288 High-performance liquid chromatography (HPLC)............................................... 266, 268 High-throughput screening (HTS) ............................. 270 Historical ecology Amazonian Dark Earth ........................................... 192 archaeological sites .................................................. 188 (see also Archaeological site) archaeology and ethnobiology ...................... 203–204 Bertholletia excelsa ................................................... 194

ETHNOECOLOGY Brazil nut ................................................................. 194 collaborators ................................................... 191–192 current riverside community .................................. 191 ethnobotanical and ethnoecological methods ....................................................... 189 floristic inventories ......................................... 201–203 guided tours ............................................................ 200 human activities....................................................... 187 human populations and landscapes........................ 188 landscape categories and plants ..................... 192–194 local oral history............................................. 197–198 long-term interaction.............................................. 189 paleoecological records ........................................... 189 paleoethnobotany.................................................... 189 participatory mapping.................................... 198, 199 people–plant interactions........................................ 189 plants........................................................................ 189 uses and management, plants ........................ 194–197 Homegardens ......................................190, 191, 195, 202 Homogenized matrix.................................................... 116 Human communities .................................................... 285 Human macro-ecology ........................................ 128, 134 Hunting biodiversity .............................................................. 323 closed and open population models ...................... 324 population growth .................................................. 323 spatial and temporal scale ....................................... 324 tropical forests ......................................................... 323 work plans................................................................ 324 Hunting pressure (HP)................................................. 327 Hydro-distillation.......................................................... 261 Hyphenated technique ............................... 273, 275, 276 Hypothesis testing ................... 91, 93, 95–100, 104–107 Hypothetico-deductive method (HDM) in EEC ....................................................................... 83 ethnobiology, ecology and conservation ........... 79–82 experimental design and statistical analysis........ 73–79 flowcharts .................................................................. 72 hypothesis testing.................................. 72, 73, 75, 76 predictions ................................................................. 78 qualitative/quantitative research.............................. 71 statistical thinking ..................................................... 74

I Imaging mass spectrometry (IMS) .............................. 272 Indicator value index (IndVal) ............................ 106–108 Indigenous peoples and local communities (IPLC).......................................................... 229 Informants ..................................................................... 227 Informed consent form (ICF).......................................... 5 Instituto Socioambiental (ISA) .................................... 220 Integral projection model (IPM) ........................ 303–305 Interculturality .............................................................. 176 Interdisciplinarity .......................................................... 170

METHODS

AND

Internal immigrants ...................................................... 176 International Council for International Organizations of Medical Sciences ..................................... 231 International Council of Medical Sciences Organizations (ICMSO) ............................. 230 International Labor Organization (ILO) ........... 231, 232 International milestones ............................................... 230 International Society for Ethnobiology (ISE).................................................... 229, 232 International Treaty on Plant Genetic Resources for Food and Agriculture (IT PGRFA) ........... 231 International Union for the Conservation of Nature (IUCN) ........................................................ 181

J Jardim Botaˆnico do Rio de Janeiro (JBRJ) ................. 220 J-inverted model ........................................................... 300 Junqueros ..................................................... 178, 181, 183

K Kaleidoscope Pro software............................................ 312 Knowledge Sharing Index (KSI) ................ 153, 156, 158 Knowledge Wealth Index (KWI) ............... 153, 156, 158

L Laboratorio de Etnobota´nica y Bota´nica Aplicada (LEBA).......................................... 163 Landscape transformations ......................... 188, 199, 203 Law................................................................................. 241 Legislation use and commercial trade of wild animals ................................................ 210, 211 Leisure activities .............................................................. 49 Len ˜ ateros ............................................................... 180, 182 Life table response experiments (LTRE) ............ 300, 302 Line-by-line coding......................................................... 50 Local knowledge systems............................ 170, 174, 178

M Macerations ................................................................... 258 Macro-ecological patterns ............................................ 139 Macro-ecology ..................................................... 136, 142 Macro-ethnobiology ..................................................... 129 anthropogenic activities .......................................... 136 application ............................................................... 137 biocultural diversity................................................. 137 biotic and abiotic conditions .................................. 136 data accumulation and informatics resources ........ 135 ecological systems ................................................... 135 geography and demography ................................... 142 hypothesis exploration ............................................ 138 meta-analytical approach ........................................ 144 multispecific methods ............................................. 135

TECHNIQUES

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ETHNOECOLOGY Index 339

natural and social sciences ...................................... 134 social-ecological relationships................................. 138 social-ecological systems ......................................... 138 spatiotemporal scales...................................... 134, 135 Macroscopic level study approach................................ 129 Mantel test............................................................ 123, 124 Mass spectrometry (MS)............................. 258, 271, 272 Matrix projection models (MPM) ...................... 302, 303 Matrix-assisted laser desorption/ionization (MALDI) ..................................................... 271 Mauritia flexuosa .......................................................... 199 Maximum sustained yield (MSY) ................................. 328 Meta-analysis ........................................................ 129–134 Metabolomics .............................................. 275, 277, 278 Microbiological tests antibacterial and antifungal activity........................ 288 antimicrobial activity ............................................... 289 bacterial inocula ...................................................... 289 drug action modulation.......................................... 290 healthcare development .......................................... 289 initial solution preparation ..................................... 289 MIC ................................................................ 289, 290 microorganisms ....................................................... 289 multiresistant microorganisms ............................... 289 statistical analysis ..................................................... 290 Microwave-assisted extraction (MAE) ......................... 263 Mindfulness ................................................................... 236 Minimal video techniques ...........................37, 38, 40–42 Minimum inhibitory concentration (MIC)........ 289, 290 Monte Carlo test ........................................................... 107 Multiculturality ............................................................. 176 Multivariate analyses classification analyses............................................... 118 cognitive structures ................................................. 112 cohesion................................................................... 118 dependence.............................................................. 118 descriptor types binary data ......................................................... 114 data transformation........................................... 115 multistate nonordered data .............................. 115 multistate ordered data ..................................... 115 quantitative data ................................................ 115 ethnobiology ........................................................... 112 ethnoecology .................................................. 112, 113 interdependence ...................................................... 118 isolation ................................................................... 118 matrices.................................................................... 113 ordination analyses .................................................. 118 pay attention................................................... 119–121 principal modes ....................................................... 114 qualitative data ............................................... 115, 116 samples..................................................................... 113 social/ethnic groups ............................................... 114 variables/descriptors ...................................... 113, 114

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Multivariate analysis of variance (MANOVA) ............... 97 Museum of Economic Botany at Kew ......................... 216

N Nagoya protocol .................................................. 231, 257 National Benefit Sharing Fund .................................... 236 National Indian Foundation (FUNAI)........................ 234 National milestones, Brazilian context FUNAI..................................................................... 234 indigenous people ................................................... 234 indigenous rights..................................................... 233 IPLC ........................................................................ 234 Law 13123 and Decree 8772............... 233, 236, 237 public authorities..................................................... 233 SISBIO .................................................................... 233 SNUC ...................................................................... 233 social sciences and humanities ................................ 233 National Policy for the Sustainable Development of Traditional Peoples and Communities (PNDSPCT) ................................................ 234 National System of Conservation Units ...................... 233 Natural products ........................................................... 259 Neo-Darwinian evolution............................................. 166 Niche construction theory (NCT)............................... 129 N-nitrosamines .............................................................. 264 Non-invasive traps camera trap ..................................................... 316, 317 hair-traps......................................................... 315, 316 track stations............................................................ 315 Nonmetric multidimensional analysis (NMDS)..........................................98, 99, 119 Non-timber forest products (NTFPs) ......................... 293 Non-trivial machine ...................................................... 172 Northwest Amazon....................................................... 218 Nuclear magnetic resonance (NMR) spectroscopy................................258, 272–274 Nuclear overhauser effect spectroscopy (NOESY) ..... 274

O Omnidirectional microphone ....................................... 311 Open population models population analysis model and combined stock recruitment ......................................... 327–329 population growth model.............................. 328, 330 source sink model .......................................... 330, 331 Ordination and clustering ............................................................ 87 constrained .............................................................. 100 data points (species) .................................................. 92 Euclidean property.................................................... 89 species matrix .......................................................... 100 unconstrained ordination ....................................... 107 Organization of American States (OAS) ..................... 232

ETHNOECOLOGY P P value........................................................................75, 76 Paleoethnobotany ......................................................... 189 Partial canonic correspondence analysis (pcca)................................................... 122, 123 Participant observation data collection .....................................................27, 28 definition ................................................................... 26 field journal and notes .............................................. 33 fieldwork .................................................................... 26 non-participant.......................................................... 26 objectivity .................................................................. 27 qualitative research.................................................... 25 record actions ............................................................ 26 Participatory risk mapping (PRM)..............................152, 153, 155 Participatory video ....................................................42, 43 Percolation..................................................................... 259 Permutational multivariate analysis of variance (PERMANOVA) .....................................97–99 Phenomenology ............................................................ 6, 8 Photodiode array (PDA) .............................................. 266 Plataforma Brazil ........................................................... 243 Pluricultural contexts environmental changes ......................... 176, 177, 184 human activity ......................................................... 164 immigration flows and pluriculturality ......... 175, 176 junqueros ......................................................... 181, 183 len ˜ ateros .......................................................... 180–182 local actors ...................................................... 177, 178 quinteros.......................................................... 178, 180 system complexity of the study area....................... 173 theoretical-methodological framework biocultural ecology....................................165–168 ecology...................................................... 164, 166 ethnoecology .................................................... 163, 168–170 observer .................................................... 170, 172 researcher .................................................. 173, 174 researcher’s presence ......................................... 172 Pluriculturality............................................................... 176 Point-quarter method................................................... 298 Polychlorinated biphenyls (PCBs) ............................... 264 Population dynamics IPM ................................................................. 303–305 LTRE .............................................................. 300, 302 MPM............................................................... 302, 303 Population growth model ................................... 328, 330 Population structure anthropogenic and ecological factors .................... 300 ethnobiological studies ........................................... 295 extractivism.............................................................. 295 inclusion criterion ................................................... 299

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J-inverted ........................................................ 299, 300 measurements .......................................................... 296 ontogenetic stages................................................... 296 point-quarter method ............................................. 298 resource extraction .................................................. 295 sampling method............................................ 296, 297 spreadsheet organization ........................................ 299 Prediction ..............................................73, 75, 78, 82, 84 Prefractionation............................................................. 270 Presuppositions ........................................... 164, 172, 183 Principal component analysis (PCA)...................... 88, 90, 91, 94, 95, 100, 121, 122 Principal component regression (PCR) ...................94–96 Principal coordinate analyses (PCoA/PCO) ................. 88, 91, 93, 100, 119 Protected areas (PAs) ...................................................... 80 Proteomics..................................................................... 275 Provisional Measure (PM) ............................................ 233

Q Qualiquantisoft .................................................. 60, 61, 65 Qualitative data analysis coding .................................................................. 48–51 data transcription ................................................ 47–48 population sampling ........................................... 46–47 sampling..................................................................... 45 triangulation ........................................................ 51–53 Qualitative research action-research method .......................................... 5, 6 bibliographic review and research question........... 4, 5 case study ...............................................................9, 12 data collection and analysis....................................... 25 ethnography ............................................................ 6, 7 fields of Psychology and Social Sciences .................... 3 grounded theory ..................................................... 8, 9 non-participant and participant observation ........... 26 novice researcher ......................................................... 4 phenomenology ...................................................... 6, 8 preparation and execution .......................................... 4 research location and ethical issues ............................ 5 social contexts ........................................................... 25 theoretical methods and perspectives ........................ 4 Quintas .......................................................................... 179 Quinteros............................................................... 178, 180

R R software ...................................................................... 312 Radio frequency (RF) ................................................... 273 Raven Pro ...................................................................... 311 Redundancy analysis (RDA).................88, 100, 104, 105 REFLORA Project ........................................................ 224 Reflux ............................................................................. 259 Regional University of Cariri (URCA) ............... 287, 288

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Reliability and validity (see Validity) research protocols ..................................................... 18 Research ethics committee (REC) ................................... 5 Rı´o de la Plata region.................................................... 177 Rı´o de la Plata riverside ................................................ 173 Risk Incident (I)............................................................ 154

S Science, Technology, Engineering, and Mathematics (STEM) .......................................................... 72 Scientific flowchart experimental design and statistical analysis........ 73–79 Scientific research workflow ......................................... 107 Selection Review tool.................................................... 312 Self-administered questionnaire (SAQ) ......................... 21 Severity Index (S)................................................. 153, 154 Shot composition techniques ......................................... 40 Sistema Nacional de Gesta˜o do Patrimoˆnio Gene´tico e do Conhecimento Tradicional Associado (SISGEN)............................................ 233, 245 Sistema Nacional de Unidades de Conservac¸˜ao (SNUC)........................................................ 233 Smartphone filming........................................................................ 38 Social-ecological patterns .................................... 128, 129 Social-ecological systems ................................... 47, 81, 82 Sociedad Latino Americana de Etnobiologı´a (SOLAE) ...................................................... 232 Solid-phase extraction (SPE)........................................ 270 Solvent extraction ......................................................... 287 Source-sink model................................................ 330, 331 Soxhlet ........................................................................... 259 Spatiotemporal scales .................................................... 129 Specimens, large vertebrates......................................... 212 Spectroscopic techniques hyphenated technique........................... 273, 275, 276 metabolomics ........................................ 275, 277, 278 MS................................................................... 271, 272 NMR............................................................... 272–274 Spondias mombin........................................................... 197 Standard Error of the Mean (S.E.M.) ......................... 290 Stock-recruitment model..................................... 328, 329 Supercritical fluid (SCF) ............................................... 261 Supercritical fluid chromatography (SFC)................... 269 Supercritical fluid extraction (SFE)..................... 261, 262 Sustainability................................................ 294, 295, 303 Systematized reviews..................................................... 130 Systemic arterial hypertension (SAH)............................ 63

T Talking books .................................................................. 36 Tandem mass spectrometry (MS/MS) ........................ 272

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Termo de Consentimento Livre e Esclarecido (TCLE) ........................................................ 241 Terra Preta de I´ndio............................................. 190, 192 Testimonial material............................................. 211–213 Test–retest technique ...................................................... 18 Theoretical saturation ..................................................... 46 Thermal conductivity detector (TCD) ........................ 269 Time-of-flight (TOF).................................................... 271 Trace surveying method ............................................... 314 Track stations ................................................................ 315 Traditional knowledge ...................... 111, 229, 231, 233, 235–237, 244, 246, 247, 250, 251 Transdisciplinarity ......................................................... 170 Triangulation .............................................................51–53 Trivial machine .............................................................. 172 Tururi (Brosimum utile) ............................................... 219

Vestiges carnivores ................................................................. 313 feces counting................................................. 313, 314 trace surveying......................................................... 314 Video awareness raising and advocacy ................................ 37 capacity building and learning.................................. 37 data collection and reporting ................................... 37 edition phase ............................................................. 42 guidelines................................................................... 41 preparation phase ...................................................... 41 recording phase ......................................................... 41 stakeholder engagement and discovery ................... 37 Video recording technique ............................................. 44 Vocalizations.................................................................. 213 Voucher specimens........................................................ 211

U

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Ultra-performance liquid chromatography (UPLC) ........................................................ 268 Ultrasound-assisted extraction (UAE)......................... 261 Ultraviolet–visible spectroscopy (UV-Vis) .................. 258 Universidad Nacional de La Plata (UNLP)................. 163 Useful plants forest patches........................................................... 196 landscape categories ....................................... 192–194 local knowledge and perceptions ........................... 200 participatory mapping.................................... 198, 199

Walk-in-the-woods technique ...................................... 200 Wood exploitation......................................................... 294 WorldClim database ........................................................ 95

V Validity content....................................................................... 18 criterion-related......................................................... 18 and reliability ................................................ 16, 18, 22 and replicability ...................................................15, 17 Verbal validation.............................................................. 52

Z Zoological material collection ...................................... 287 Zootherapeutics adipose tissue (fat)................................................... 286 antimicrobial and modulatory activity ................... 287 fixed oil and fatty acid determination ........... 287, 288 medicinal and magical-religious purposes ............. 286 microbiological (see Microbiological tests) multiresistant bacteria ............................................. 286 natural resources conservational and management ................................................ 286 socio-economic/cultural reality ............................. 285 zoological material collection................................. 287