Measuring Sustainability and Sustainable Livelihoods
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Birds Eye View Understanding Sustainable Development
Existing Indicators of Development
Measuring SD
Generationalisation & Problems 2
Development Goals Human Development – indicators related to health, education and income Equity - trends of economic inequality is increasing Human rights - exercise of civil liberty and human rights by all Empowerment - marginalized (SC / ST / women / minorities/ persons with disability) Sustainability- rights of future generations as against present generation, multi-dimensional concept
Sustainable Development (SD) Development that meets the needs of the present without compromising the ability of future generations to meet their own needs. - (The Brundtland Commission on Environment and Development: 1987)
Improving the quality of human life while living within the carrying capacity of the supporting mechanisms - (The IUCN / UNEP/ WWF definilion: 1991)
Sustainable Development (SD) SD debate - Brundtland - in terms of rights of present vs future generations.
However, it necessarily involves all three issues: Rights of future generations as against present generation Rights of the poor in the present generation as against those of the rich. Rights of non-humans as against humans
Goals of Sustainable Development What is to be sustained Nature Earth Biodiversity Ecosystems
Life support Ecosystem services Resources Environment Community Cultures Groups Places
What is to be developed People Child survival Life expectancy Education Equity Equal opportunity Economy Wealth Productive sectors Consumption Society Institutions Social capital States Regions 6
Sustainable Development (SD) SD is three dimensional concept: Ecological security Economic efficiency Social equity
Technology as fourth dimension
Existing Indicators of Sustainable Development
Economics GDP
NPP EF EStI LPI EPI EVI CCC MSY PSR
Ecology
EDP GSI
HDI SLSI ISEW CDI SNBI
RMS SMS WI
PQLI
Equity
GDP
Gross Domestic Product
PQLI
Physical Quality of Life Index
NPP EF EStI LPI EPI EVI MSY PSR CCC
Net Primary Productivity Ecological Footprint Environmental Sustainability Index Living Planet Index Environmental Performance Index Environmental Vulnerability Index Maximum Sustainable Yield Pressure-State-Response model Concept of carrying capacity
HDI
Human Development Index
RMS SMS WI
Relative Measure of Sustainability Safe Minimum Standard Well Being Index
GSI EDP
Genuine Savings Index Environmental Adjusted Domestic Product
CDI ISEW SNBI SLSI
City Development Index Index of Sustainable Economic Welfare Sustainable Net Benefit Index Sustainable Livelihood Security Index
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Component Variables Ecological security represented by variables – forest cover, land degradation status, soil and water quality parameters, air quality parameters, groundwater depletion, etc.
Economic efficiency represented by variables – land productivity, labour productivity, marketable surplus, input–output ratio, etc.
Social equity represented by variables –distribution of land, asset and income, people below poverty line, female literacy, MMR, IMR etc. 9
Variables for Measuring Ecological Security Land degradation status Gullied and ravinous land Land affected by Salinity/ alkalinity Shifting cultivation areas Mining / industrial wasteland
Soil quality parameters Pesticide residues in soils
Water quality parameters Nitrate Fluride TDS Toxic substances Heavy metals
Ground Water Depletion status Over-exploited (if net draft > 100% of utilizable recharge) Dark or critical (if net draft is 85% to 100% of utilizable recharge) Grey or semi-critical (if net draft is 65% to 85% of utilizable recharge) White or safe (if net draft < 65% of utilizable recharge) 10
Sustainable Livelihood Security (SLS) RLS - capability, equity, and sustainability - Chambers and Conway
SLS - livelihood options that are ecologically secure, economically efficient, and socially equitable- Swaminathan
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Preconditions for Measuring SLSI It should be simple, flexible, and information-efficient Given the dynamic nature of SD, it needs to be relative rather than absolute The index needs to be composite so as to take stock not only of the conflicts between the three aspects of sustainability but also of the intrinsic synergy among them It should be easy to construct and understand by policy makers, local-level administrators, and, more importantly, by rural families It should be a tool both for policy making as well as for public education 12
Measuring SLSI To measure is the first step to improve -Sir William Petty (1623 – 1687)
Steps involved: Identify component variables Get the data Make them comparable Use the formula to construct component indices Find the arithmetic or appropriately weighted mean of the three indices
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Formula for Developing SLSI The relative performance of jth geographical unit in the ith component of the index can be represented as: Xij - min Xij j SLSIij = ──────── max Xij - min Xij j j
(i = 1,2,..,I) (j = 1,2,.....n)
To put simply:
SLSI = (X-Min)/(Max-Min) 14
Measuring SLSI: When Standard is provided
SLSI = (X-min)/(standard-min) Minimum should be minimum of the entire data Example: forest cover
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SLSI at Agro-climatic Level in India Zon e Agro-Climatic Region No.
Forest Net Cover Sown (%) Area (%)
I II III IV V VI VII VIII IX X XI XII XIII XIV XV
45.30 42.80 11.00 8.70 4.50 3.20 35.20 14,20 11.80 17.10 18.70 29.00 10.90 1.20 88.10
Western Himalayas Eastern Himalayas Lower Gangetic Plain Middle Gangetic Plain Upper Gangetic Plain Trans-Gangetic Plain Eastern Plateau & Hill Plateau & Hill Western Plateau & Hill Southern Plateau & Hill East Coast Plain & Hill West Coast Plain & Ghat Gujarat Plain & Hill Western Dry Island
18.20 18.70 63.80 62.80 70.10 80.90 35.90 45.00 59.70 48.40 43.30 37.20 51.40 47.70 4.20
Land Productivity (Rs/ha)
3516 3411 4743 3043 5125 4672 2528 2089 2202 3388 5480 5453 3013 659 5892
Area Under People Above Female Cereals (%) the Poverty Literacy Line (%) (%)
91.75 91.37 83.07 74.02 77.36 71.74 83.51 65.61 61.40 61.57 74.21 80.39 45.93 65.68 35.80
79.60 69.90 61.00 51.00 58.60 82.20 50.20 54.50 58.70 61.80 61.90 75.60 72.10 67.20 71.80
23.10 27.20 31.80 12.20 15.10 32.10 15.60 14.20 27.40 32.60 30.30 56.20 32.70 9.60 39.10
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Indices of the Variables at Agro-climatic Regions of India Zon Agro-Climatic Region e No.
Ecological Indices Forest Cover
Economic Indices
Cereal Area Net Sown Land Area Productivity
Equity Indices Poverty Variable
Female Literacy
I II III IV V VI VII VIII IX X
Western Himalayas Eastern Himalayas Lower Gangetic Plain Middle Gangetic Plain Upper Gangetic Plain Trans-Gangetic Plain Eastern Plateau & Hill Plateau & Hill Western Plateau & Hill Southern Plateau & Hill
0.67 0.64 0.52 0.40 0.18 0.11 1.00 0.40 0.33 0.50
0.18 0.19 0.78 0.76 0.86 1.00 0.41 0.53 0.72 0.58
0.55 0.53 0.78 0.46 0.85 0.77 0.36 0.27 0.29 0.52
1.00 0.99 0.84 0.68 0.74 0.64 0.85 0.53 0.46 0.46
0.92 0.62 0.34 0.02 0.26 1.00 0.00 0.13 0.27 0.36
0.29 0.38 0.48 0.06 0.12 0.48 0.13 0.10 0.38 0.49
XI XII XIII XIV XV
East Coast Plain & Hill West Coast Plain & Ghat Gujarat Plain & Hill Western Dry Island
0.55 0.87 0.30 0.00 1.00
0.51 0.43 0.62 0.57 0.00
0.92 0.92 0.45 0.00 1.00
0.69 0.80 0.18 0.53 0.00
0.37 0.79 0.68 0.53 0.67
0.44 1.00 0.50 0.00 0.63
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Ranking the Agro-climatic Regions by SLSI Zone No.
I II III IV V VI VII VIII IX X XI XII XIII XIV XV
Agro-Climatic Region
Western Himalayas Eastern Himalayas Lower Gangetic Plain Middle Gangetic Plain Upper Gangetic Plain Trans-Gangetic Plain Eastern Plateau & Hill Plateau & Hill Western Plateau & Hill Southern Plateau & Hill East Coast Plain & Hill West Coast Plain & Ghat Gujarat Plain & Hill Western Dry Region Islands
Ecological Security Index 0.428 0.413 0.649 0.581 0.517 0.553 0.707 0.468 0.527 0.536 0.527 0.648 0.459 0.284 0.500
Ranks 13 14 2 4 9 5 1 11 8 6 7 3 12 15 10
Economic Efficiency Index 0.773 0.760 0.813 0.569 0.798 0.705 0.605 0.403 0.376 0.491 0.804 0.857 0.315 0.267 0.500
Ranks 5 6 2 9 4 7 8 12 13 11 3 1 14 15 10
Sustainable Livelihood Security Ranks Index Ranks 4 0.602 4 6 0.556 6 8 0.623 3 15 0.397 13 12 0.502 8 2 0.666 2 14 0.459 10 13 0.329 14 10 0.409 12 7 0.485 9 9 0.579 5 1 0.801 1 5 0.455 11 11 0.272 15 3 0.551 7
Social Equity Index 0.604 0.497 0.407 0.040 0.190 0.741 0.064 0.117 0.324 0.428 0.405 0.897 0.590 0.266 0.654
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Dealing with the Values of Opposite Quality Reversing the variable Or Using different Formula For example If SLSI = (X-Min)/(Max-Min) Then for opposite variables
SLSI = (Max-X)/(Max-Min)
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SLSI at District Level in Gujarat Based on ecological as well as socio-economic status, and the availability of district-wise data, we have selected the following indicators for the construction of SLSI: Ecological security indicators: forest cover, water quality unaffected habitations (i.e. habitations that are not affected by pollutants such as fluorides, nitrates, and brackishness), and groundwater recharge potential; Economic efficiency indicators: total food grain yield, milk yield, and net sown area;
Social equity indicators: percentage of population above poverty line, female literacy, maternal survival rate, per capita food grain production, and per capita milk production. 20
Data Used for the Calculation of SLSI in Gujarat Ecological Security Indicators District
Ahmedabad Amreli Anand Banaskantha Bharuch Bhavnagar Dahod Dangs Gandhinagar Jamnagar Junagadh Kaira Kutch Mahesana Narmada Navsari Panchmahals Patan Porbandar Rajkot Sabarkantha Surat Surendranagar Vadodara Valsad
Forest cover (%) 2 3.2 1.9 8.7 5.3 2.9 16 80.4 6.8 2.6 19.4 2.6 5 2.8 39 14.2 12.9 3 4.9 1.3 10.8 17.7 1.6 8.1 32.9
Water quality unaffecte d habitation s (%) 64 67 68 62 76 68 76 100 51 62 57 79 60 52 91 96 57 38 21 27 67 90 52 73 98
Economic Efficiency Indicators
Total food Recharge grain potential yield (%) (kg/ha) 94 150 184 86 179 159 165 493 55 173 142 112 152 67 318 215 171 75 118 143 121 276 157 148 233
1,769 1,665 1,911 1,093 852 1,665 950 1,341 2,190 1,480 2,939 1,961 717 1,592 1,072 2,002 860 989 1,916 1,991 1,256 1,499 1,322 1,075 1,530
Social Security Indicators
Milk yield (kg/day)
Net sown area (%)
APL population (%)
Female literacy rate
Maternal survival rate
2.3 2.8 2.8 3.1 2.5 2.6 1.3 0.4 2.9 2.7 2.8 2.4 2.3 4.1 1.7 3.3 1.9 3.4 3.4 3 2.8 3 2.5 2.1 2.7
62.6 73.3 60.7 68 50.1 55.8 18.9 15.9 73.7 42.7 59.7 71.1 9.9 79.3 40.3 66.9 52.3 66.6 50.2 66.4 59.7 55.4 65.7 67.5 53.1
99 93 94 95 92 97 79 88 94 94 96 95 95 98 86 94 87 96 97 97 89 95 95 95 79
42 42 40 33 42 40 40 34 41 41 41 40 38 41 38 44 36 37 42 43 38 40 38 41 41
919 941 801 914 803 926 802 905 908 925 954 835 933 915 898 947 999 884 897 955 964 992 950 866 999
Food grain production per capita of rural population (kg/yr) 370 105 266 170 101 83 197 303 181 102 228 320 124 126 115 130 125 117 148 119 165 126 137 130 106
Milk production per capita of rural population (kg/yr) 216 202 235 269 121 194 127 18 240 207 193 160 306 434 97 151 149 341 373 228 308 186 194 146 106
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Generalization of the SLSI Methodology Households in a village Villages in a taluka or district Districts in a state States in a country
Agro-climatic region in a planning context Project units in a project Resource/ecosystem level for intergenerational analysis Countries at global level
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SLSI at Household Level in a Village Ecological dimension may be fixed if ecological endowment of the village under evaluation forms the common basis for the livelihoods of all households Economic Dimension
Social Dimension
Income status, Asset ownership status, Food and nutritional status etc.
Educational status, Health status, Access to common property etc.
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Candidate Variables for Representing the Three components of the SLSI at the Global Level Environnent Dimension
Economic Dimension
Social/ Human Dimension
Net Deforestation (Deforestation minus Reforestation)
Per Capita GDP
Per Capita Calorie Available as a Percentage of Need
Favorable water budget of Energy Requirements usable water Per Unit of Output
Female Literacy
Per Capita Co2 Industrial Emission
Crop Land Per Capita
Yield Per Hectare of food crops
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Problems in the Construction of SLSI While the SLSI methodology is simple and conceptually sound, it faces the same problems often encountered in the construction of any composite index The choice of the component variables Identification of appropriate weights for its different components
Within the data constraints, the variable choice becomes more of an art than a science
Naturally, the SLSI constructed by two individuals with differential preferences will not be the same
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