Galaz Et Al 2009

Frontiers in Ecology and the Environment

Can web crawlers revolutionize ecological monitoring? Victor Galaz, Beatrice Crona, Tim Daw, Örjan Bodin, Magnus Nyström, and Per Olsson Front Ecol Environ 2009; doi:10.1890/070204 This article is citable (as shown above) and is released from embargo once it is posted to the Frontiers e-View site (www.frontiersinecology.org).

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CONCEPTS AND QUESTIONS

Can web crawlers revolutionize ecological monitoring? Victor Galaz1*, Beatrice Crona1,5, Tim Daw3, Örjan Bodin1,4, Magnus Nyström1,2, and Per Olsson1 Despite recent advances, ecosystem service monitoring is limited by insufficient data, the complexity of social–ecological systems, and poor integration of information that tracks changes in ecosystems and economic activities. However, new information and communication technologies are revolutionizing the generation of, and access to, such data. Can researchers who are interested in ecological monitoring tap into these increased flows of information by “mining” the internet to detect “early-warning” signs that may signal abrupt ecological changes? Here, we explore the possibility of using web crawlers and internet-based information to complement conventional ecological monitoring, with a special emphasis on the prospects for avoiding “late warnings”, that is, when ecosystems have already shifted to less desirable states. Using examples from coral reef ecosystems, we explore the untapped potential, as well as the limitations, of relying on web-based information to monitor ecosystem services and forewarn us of negative ecological shifts. Front Ecol Environ 2009; doi:10.1890/070204

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he combined impacts of global environmental change and the complex behavior of ecological systems, create opportunities for major “ecological surprises” at various spatial scales (Schneider and Root 1995; Gunderson 2003; Gordon et al. 2008). Ecosystems provide many vital ecosystem services (ES), such as water purification and food production, but rapid changes due to, for instance, climate change and shifting global markets, present serious challenges to their future ability to deliver these life supporting services (MA 2005). Examples of such changes include collapsing fisheries at national and global scales (Berkes et al. 2006), irreversible degradation of freshwater ecosystems and coral reefs, and decreasing soil productivity (Scheffer et

In a nutshell: • Steering away from catastrophic shifts in ecosystems is of prime concern in an era of global environmental change • Existing monitoring of ecosystem services is poor and fragmented, especially in developing countries • Information and communications technology is revolutionizing the generation of, and access to, social, ecological, and economic information • Systematic “data mining” of such information through the internet can provide important early warnings about possible pending abrupt losses of ecosystem services

1

Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden *([email protected]); 2Department of Systems Ecology, Stockholm University, Stockholm, Sweden; 3 School of Development Studies, University of East Anglia, Norwich, UK; 4Department of Government, Uppsala University, Uppsala, Sweden; 5The Centre for the Study of Institutional Diversity, Arizona State University, Tempe, AZ © The Ecological Society of America

al. 2001; MA 2005).The situation is exacerbated by national and international responses to such changes that are either insufficient or non-existent. Restoration may be difficult, because feedbacks in the system can act to stabilize these new, undesirable ecosystem states (Scheffer et al. 2001; Gordon et al. 2008). It is therefore of primary importance to try and avoid crossing the thresholds that lead to these outcomes. Despite advances in monitoring technology (Clark et al. 2001), it is evident that existing information on changes in ES tends to be poor and contains serious gaps. Furthermore, existing monitoring systems are unable to capture the impacts of rapid demographic, economic, and sociopolitical changes that result from economic development and increasing global flows of information, trade, and technology (MA 2005; Berkes et al. 2006; Carpenter et al. 2006). The difficulties in quantifying social and ecological uncertainty, the lack of expert agreement on what indicators to monitor, poor-quality existing data, and the costs associated with setting up long-term monitoring programs (Walters 2007) all hamper our ability to steer away from, or to prepare for, abrupt changes to ecosystems and the loss of related ES. This is particularly true for countries that suffer from poor governance and weak environmental institutions (Danielsen et al. 2003; UNEP 2007).

! Information and communication technologies The role of information and communication technology (ICT) – for economic growth, education, and human development – has been discussed elsewhere (Leach and Scoones 2006). Meanwhile, the evolution of “web 2.0” permits more interactive use of the internet and allows users to post, edit, comment on, and provide information www.fr ontiersinecology.or g

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in blogs and wikis or via podcasting, videoblogs, and other networking tools. Globally, access to information technology is very unequally distributed (IER 2005; Leach and Scoones 2006), but access to, and use of, the internet is increasing rapidly in all regions of the world. For example, between 2000 and 2004, the number of internet users in the developing world tripled, from 96 million to almost 333 million; in Africa alone, the number of users increased more than five-fold, from 4.3 to 21.8 million, during that same period (IER 2005). The rapid development of ICT has not only led to increased flows of information at a global scale, but also sets the stage for innovative uses of internet-based information – ranging from e-mail lists and local newspaper articles to preprints of peer-reviewed journal articles – as an important complement to conventional ecological monitoring. The potential of ICT is currently being explored in a number of contexts for ecology. Examples here range from the Resilience Assessment wiki (http://wiki.resalliance.org), to online datasets such as those posted by the US National Center for Ecology and Analysis and Synthesis (www.nceas.ucsb.edu), to the use of the internet to coordinate citizen-science projects (Levitt 2002). In addition, Crowl et al. (2008) suggest the creation of a coordinated “cyber-infrastructure” to facilitate prompt warnings of invasive alien species and infectious diseases. Here, we explore the possibilities and limitations of more systematic “data mining” of the internet, and the potential for obtaining complementary information and early warnings – not only about discrete ecological events (eg a disease outbreak caused by invasive species), but also changes in ecological drivers, and the impacts of ecosystem change – to forewarn us of ES losses.

! Ecology on the internet One example of how informal ICT information can support ecological monitoring is the use of electronic mailing lists to disseminate and compile field observations tracking global-scale coral bleaching during the 1997–1998 El Niño event. The existence of an electronic mailing list for coral reef-associated news proved invaluable for prompt assessments of the mass-bleaching event (Hoegh-Guldberg 1999), with reports ranging from “detailed accounts with accurate measures of bleaching and mortality, to brief anecdotal reports obtained during a rapid site visit” (Wilkinson 1999; see WebPanel 1). Information of this kind can, in principle, be easily associated with participatory ecological monitoring projects or citizen-science initiatives, provided that they are posted on the internet (see Andrianandrasana et al. [2005] on wetland monitoring in www.fr ontiersinecology.org

Madagascar and Leach and Scoones [2006] on participatory geographic information system “citizen-maps” for hydrological monitoring). One primary difficulty, however, lies in designing monitoring systems that are able to scan the internet continuously for predefined ecological events and changes that might signal emerging ecological vulnerabilities, and subsequently integrating that information with existing, official monitoring data. Although the realization of such a system is far into the future, innovative uses of web crawlers (software programs or automated scripts that browse the World Wide Web in a methodical, automated manner) are likely to provide an important complement to conventional monitoring in the present. The case study we highlight of the live reef fish trade is a clear example of the problems inherent in relying on official data alone, and one where a creative application of internet-based information could provide a valuable resource (see Panel 1). The potential of web crawlers is illustrated by the success of the Global Public Health Intelligence Network (GPHIN), an early disease detection system developed by Health Canada for the World Health Organization (WHO). GPHIN gathers information about unusual disease events by monitoring internet-based global media sources, such as news wires, web sites, local online newspapers, and public health e-mail information services, in eight languages, with non-English articles filtered through a translation engine. The system retrieves approximately 2000–3000 news items per day; roughly 30% are rejected as duplicative or irrelevant, but the remainder are sorted by GPHIN analysts and posted on GPHIN’s secure website (Weir and Mykhalovskiy 2006). The ability to trawl extensively for various signals, the wide diversity of information sources, and the ability to identify alarming early-warning signs seem give the system the flexibility and speed needed to detect unexpected

Panel 1. We b c r a w l e r s a n d t h e l i v e f i s h t r a d e Globalized markets have become important drivers for fisheries systems, driving rapid development, overexploitation, and collapse of local fisheries, before effective management can be established (Berkes et al. 2006). The live reef fish trade (LRFT) supplying seafood to restaurants in Asia is a good example. This fishery has been characterized by a boom-and-bust pattern of sequential exploitation of reefs and nations, and serial depletion of the most valuable species (Scales et al. 2006). Although some Pacific Ocean nations have recognized the threat of LRFT and have started to take precautionary actions, coordinated by the Secretariat of the Pacific Community (Sadovy et al. 2003), many in other areas, such as the Caribbean and the Western Indian Ocean, have not, and lack of data on the status of many small-scale reef fisheries has also been a severe impediment to action. Socioeconomic and ecological signals, provided by web crawlers, could potentially improve early detection of nations and regions at risk of being hit by the next sequential wave of LRFT. Examples of the types of signals that could be used include trade advertisements, availability of products by area, prices, number of suppliers, observations by non-state entities, such as environmental organizations, and newsletters. © The Ecological Society of America

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Driver signals

Data type

Development aid investment

Subsidies for exploitation

Coastal development and construction

Government fisheries stats Disease outbreak

Trade volumes, trophic levels, size grades

Regional

Foreign investment

Coral cover, fish community composition

Local

Local

Coral reef

Regional

Courtesy of B Crona and R Kautsky/Azote

Impact signals

Global

Global

Drivers of system change

Data type

Online news media (eg newspapers, radio and television, and online newsletters)

Published (online) reports and documents from government agencies, UN agencies, OECD, and similar

Biogs (eg dialogues conducted through dive clubs, interest groups, NGOs, electronic mailing lists, purchase requests)

Online accessible databases (eg trade statistics, landing statistics)

Figur e 1. Examples of drivers and impact signals regarding a coral reef social–ecological system that, in principle, could be detected by a web crawler. “Driver signals” are key social, ecological, and economic factors that risk leading to loss of ecosystem services. “Impact signals” are changes that may indicate pending loss of ecosystem services. Note that the list of signals is not exhaustive. Based on Nyström et al. (2000); Berkes et al. (2006); Scales et al. (2006); and McCook et al. (2007). The analysis of these signals is not necessarily carried out by a single entity or individual, but rather may include, for example, academia, UN agencies, NGOs, government and citizen scientists, and military and diplomatic agencies.

disease outbreaks. For example, GPHIN currently captures the first hints of about 40% of the 200–250 outbreaks subsequently investigated and verified by WHO each year. GPHIN was also one of the first systems to obtain non-official reports of a suspected influenza outbreak in mainland China in 2002, which, 3 months later, was identified by WHO as severe acute respiratory syndrome (SARS; Fidler 2005; Weir and Mykhalovskiy 2006).

! Web crawlers and ecosystems Abrupt losses of ecosystem services are obviously difficult to forecast with certainty, mainly because they result from multiple changes at different scales (Clark et al. 2001). However, research on coupled social and ecological systems over the past decade has identified several changes that may provide early warnings of potential damage to ecosystem services. For example, an abrupt transition from a coral-dominated reef to an algae-dominated one may be © The Ecological Society of America

preceded by declining abundance of large herbivorous fish (Nyström et al. 2000); a rapid transition from a clear to a highly turbid and eutrophic state in a lake may be preceded by increased fertilizer use on nearby farms (Gordon et al. 2008); and heavy investment in specific fishing gear and technical equipment may precede the loss of certain key species in marine fisheries (Berkes et al. 2006). Figure 1 uses the example of coral reef ecosystems to illustrate diverse sources of internet-based information on both drivers and ecosystem responses, to monitor and forewarn of pending ecological shifts. Nonetheless, the collection and presentation of signals need to be supplemented by expert analysis, knowledge management approaches (see McDermott [1999] for more information), and an understanding of local ecological and social conditions. Only then will we be able to obtain robust estimates of possible impacts and to evaluate the possible countermeasures or adaptation strategies we might use in response (Crowl et al. 2008). www.fr ontiersinecology.or g

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(a)

responses before the ES are lost. Here, we suggest three potential ways to using web crawlers to forewarn of ecological shifts. First, web crawlers can collect information on the drivers of ecosystem change, and not just on the resulting impacts. For example, if emerging markets for high-value species are known to be socioeconomic drivers that lead to the overexploitation and collapse of a fishery (see Panel 1), web crawlers can be designed to collect information on rapid changes in prices, landings, or investments in particular regions (Figure 2). Meyerson and Reaser (2003), for instance, report on a web crawler developed by the US (b) Department of Agriculture’s Animal and Plant Health Inspection Service to search for, and report on, sales of prohibited organisms over the internet, in an attempt to address the threat of (c) invasive alien species. Second, future early-warning systems can make use of the recent insight that variance within ecosystems can increase in response to Figure 2. Ecological information is often accessible in several languages and stress. For example, the variability of fish popdiverse settings on the internet. (a) This screen shot from a Chinese food ulations has been shown to increase in market web page illustrates the type of information that can be retrieved. (b) response to exploitation (Hsieh et al. 2006). Information about marine species for sale in the market, together with Carpenter and Brock (2006) argue that variinformation about the highest, lowest, and average price. The last column ance within complex ecological systems genprovides price statistics for the chosen species. (c) A news section, which erally increases in advance of catastrophic includes changes in access to specific marine species. First news item reads: shifts. Although web crawlers harvest infor“According to an integrated investigation of the coastal zone, both Chinese mation on discrete events, rather than providprawn and little yellow croaker have returned in the Bohai Sea”, while the ing the time series needed to formally analyze sixth news item reads: “Big stocks of little yellow croaker have re-emerged variance patterns, increases in variance are after 30 years in the Yellow Sea”. very likely to result in an increased frequency of what is perceived as “unusual events”, Analysis and response are not necessarily organized which may make their way into local newspapers, around a single – ie national government – entity. On blogs, or electronic mailing lists (Figure 3a). the contrary, both might occur as a result of collabora- Nonetheless, the realization that increased variance tions between, for example, state agencies and other indicates a pending ecological shift is a recent one, expert analysts in the form of non-governmental organi- based on ecological modeling (compare with Oborny zations, private companies, universities, and the general et al. 2005; van Nes and Scheffer 2007). Thus, whether public. If the outputs are more widely available, analysis this approach is possible with web-crawler-based monand response could even be the result of autonomous itoring systems needs to be explored further. actions, assumed by independent organizations and Finally, a more clear-cut approach is one that builds individuals. on the fact that ecological shifts at small scales often precede similar shifts in other locations or, more seriously, larger-scale systemic changes. Examples include Warnings that come too late ! outbreaks of invasive alien species (Meyerson and There are important differences between monitoring for Reaser 2003), or the way in which resilience of ecosysloss of ES and disease outbreaks. Web-crawler-based tems, such as forest reserves and coral reefs, is thought early-warning systems for disease epidemics rely on the to be dependent on surrounding refuge areas, which can identification of discrete events (Weir and Mykhalovskiy aid the recovery from small-scale shifts through, for 2006), rather than on monitoring underlying social, eco- example, the movement of species and supply of larvae nomic, or ecological changes. However, discrete events (Nyström et al. 2000; Bengtsson et al. 2003; see Figure can, in principle, be used as early warnings of approach- 3b). Therefore, repeated small-scale shifts may not only ing abrupt shifts in ecological systems. Given the poten- lead to a cumulative loss of “spatial resilience”, but can tial for irreversible loss of ES, early warnings are impor- also provide early indications of large-scale systemic tant in allowing the introduction of management losses of ES (Figure 3b). www.fr ontiersinecology.org

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(a)

(b) Time series

Distributions

System 1

Probabilities for unusual events

System 2

System 3

Healthy local ecosystem Local ecosystem in degraded state Flows from refuge areas to assist recovery

Figure 3. (a) Increasing variance of a key system variable (eg fish abundance or nutrient concentration) (top). As variance increases, the probability distribution changes (bottom), which could imply more frequent observations of “unusual” events (beyond horizontal dotted lines). (b) Ecological shifts at smaller scales can provide warnings of impending changes to large-scale systems. System 1: recovery from disturbances is assisted by multiple sources of “ecological memory”. System 2: higher frequency of local shifts, which increases the risk of the system moving into a large-scale phase shift. System 3: majority of sites are degraded, making recovery of both local sites and the large-scale system unlikely. Adapted from Nyström et al. (2008).

! Data management and lack of societal response Despite the exciting possibility of using web crawlers for ecological monitoring and in early-warning systems, we recognize that crucial challenges need to be addressed before these systems can contribute to the detection (and possible avoidance) of abrupt ecosystem changes. There is still a need to integrate, verify, and manage ecological and socioeconomic data. Data integration, expert analysis, and knowledge management have proven to be the main obstacles to ecological monitoring (Carpenter et al. 2006), even among well-defined monitoring systems in developed countries. For example, communicable disease surveillance in the European Union (Amato-Gauci and Ammon 2008) and invasive species monitoring in the US (Meyerson and Reaser 2003; Crowl et al. 2008) illustrate the difficulties posed by fragmented or otherwise insufficient social and ecological data, and the continuing risk of creating “information junkyards” – ie increasingly large collections of data with little or no practical value (McDermott 1999) – instead of robust ecological monitoring systems. Any web-crawler-based monitoring system would therefore require the support of a coupled knowledge management and expert judgment system. Early warnings are never a guarantee of timely and appropriate remedial responses. The need for prompt responses to outbreaks of Ebola hemorrhagic fever and avian influenza (H5N1), for example, has gained increased social and political support over the past few years, spurring the development of new, international regulations and response operations. This is facilitated by a relatively strong international organization for human health, with an international mandate – the WHO (Fidler 2005). This development is in stark contrast with global environmental governance, which suffers from implementation deficits, serious coordination failures, and inadequate funding (Biermann 2002). Responses to infectious disease (eg isolation, vaccination, medical care) are also likely to be simpler and less politically © The Ecological Society of America

contentious than the responses to approaching ecological shifts (eg fishing restrictions, restrictions on agricultural activity, implementation of deforestation legislation). The challenges of data integration and the current lack of governmental response to ecological change should not be underestimated. They do not, however, preclude the need to explore innovative solutions to bridge the gap between poor monitoring, and the rapid rate of social–ecological change, with potentially serious repercussions for human well-being. The use of web crawlers should be explored further, in an attempt to prepare for the ecological challenges of an uncertain future.

! Call for comments The authors invite readers to discuss and comment on this article at http://resilienceinnovation.blogspot.com

! Acknowledgements This work was supported by the Stockholm Resilience Centre, and by grants from the Foundation for Strategic Environmental Research (Mistra). We thank F Westley of the University of Waterloo and several other colleagues for inspirational discussions on this subject. Assistance in translation and with the web search was provided by G Han, Stockholm Environment Institute.

! References

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V Galaz et al. – Supplemental information WebPanel 1. Selected excerpts from the Coral List from early 1998 Accessible at www.coral.noaa.gov/lists/archives.shtml. Senders e-mail addresses have been removed, and region added by article authors. Panama Wed, 1 Oct 1997 14:49:26 Significant coral bleaching was observed on 17 September 1997 at Uva Island in the Gulf of Chiriqui, Pacific Panama.All zooxanthellate scleractinian coral species were affected, at all depths (no corals present > 20 m). The most severely bleached (completely white) colonies still had extended polyps and no signs of algal overgrowth, suggesting the event occurred relatively recently. Most colonies of the hydrocoral Millepora intricata (the only common species of the genus remaining after the 1982–83 ENSO) were already dead and covered with a thin algal film, suggesting they may have bleached earlier than the scleractinians. Galapagos Thu, 5 Jan 1998 21:11:06 As of Dec 18–30, bleaching was observed first hand in Galapagos. Roughly 20% of polyps of roughly 80% of the coral I saw was bleached near the top (mostly a brown lumpy coral, I don’t know the name, anyone?) although I was only able to visit Santa Cruz, Bartolome, Santa Fe, and Espanola; NOT the islands typically known for large coral assemblages (Devil’s Crown, Isabella). Galapagos Sat, 21 Jan 1998 12:32:09 FYI, a NOAA Press Release: EL NINO CAUSING CORAL BLEACHING IN GALAPAGOS, NOAA ANNOUNCES El Niño’s extremely warm waters in the Pacific Ocean have caused coral bleaching in the waters around the Galapagos Islands, the Commerce Department’s National Oceanic and Atmospheric Administration announced today. Hawaii Tue, 3 Mar 1998 20:46:37 The coral reef here is a bloody disaster.What isn’t dead is bleached so white from loss of algae that I think much of it will starve before it comes good.The sea temp reached 33˚C at 15 meters depth at four mile reef last month.We are getting South easters, now bringing in cooler water but it is still very hot.This is unprecedented. No one can remember anything like this happening before. Western Samoa Thu, 5 Mar 1998 13:20:18 A survey at Palolo Deep (a National Marine Park near Apia,Western Samoa) on 28 February revealed severe coral bleaching. Between 60 to 70% of all staghorn Acropora on the reef top was bleached.This has occurred with amazing rapidity (over a period of 5–6 days). In deeper water, all seemed well.

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