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Framework for Assessing Adaptive Capacity in Social-Ecological Systems

Framework for Assessing Adaptive Capacity in Social-Ecological Systems. Meha Jain, Ph.D. Candidate Dept of Ecology, Evolution, and Environmental Biology Columbia University. Governance of Adaptation.

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Framework for Assessing Adaptive Capacity in Social-Ecological Systems

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  1. Framework for Assessing Adaptive Capacity in Social-Ecological Systems Meha Jain, Ph.D. Candidate Dept of Ecology, Evolution, and Environmental Biology Columbia University

  2. Governance of Adaptation • Need to understand autonomous adaptation and drivers of adaptive capacity to design effective adaptation policies • Framework • Case Study

  3. Framework Goals • Identify which socio-economic, biophysical, and perceptional factors enhance adaptive capacity • Identify current gaps in research methodology and important next steps for adaptation research

  4. Methods Literature Review • Searched for studies that assess the socio-economic, biophysical, and perceptional factors that are associated with increased adaptive capacity • ISI Web of Knowledge • 200 studies that were most cited • Span the disciplines of anthropology, economics, geography, psychology, and social-ecology

  5. Factors Associated With Adaptive Capacity Literature Review

  6. Adaptation Research Next Steps Literature Review • Consider multiple factors in the same analysis • Multi-disciplinary • Explicitly consider climate as a driving factor Economic Climate Decision to Cope Social Biophysical Perceptional

  7. Current Research Limitations Literature Review • Quantify whether a changed behavior is actually adaptive Economic Climate Decision to Cope Adaptive Social Biophysical Perceptional

  8. Current Research Limitations Literature Review • Understand the scale of interactions

  9. Current Research Limitations Literature Review • Understand the scale of interactions

  10. Current Research Limitations Literature Review • Understand the scale of interactions

  11. New Framework Framework Local Scale Regional Scale National or Global Scale Multiple Drivers Effects Decision-making

  12. Agricultural Communities in Northwest India Case Study

  13. Study Area Methods • Hierarchical study design • Household-level Surveys • Regional remote sensing analyses

  14. Household-level Adaptation Household-Scale • Are farmers shifting behavior based on climate variability? • Which socio-economic, biophysical, and perceptional factors are associated with farmers who adapt? • Are these coping strategies adaptive? Multiple Drivers Effects Decision-making

  15. Adaptation Strategies • Switch crop type • Shift planting date • Alter cropping intensity Water-intensive Drought-tolerant

  16. Main Monsoon Crops Household-Scale Water Intensive

  17. Crop Planting Date by Rainfall

  18. Previous Crop Failure Household-Scale Water Insecurity Precipitation Required to Sow Land Owned Asset Index Adjusted R2= .173 3 -1 1 -3 2 -2

  19. Predictors of Cotton Yield Land Owned Household-Scale Soil Fertility Date Planted # of Irrigations Amt of Fertilizer Adjusted R2= .127 Amt of Pesticides Parameter Value

  20. Regional-level Adaptation • How consistent are these patterns at the regional scale? Local Scale Regional Scale Multiple Drivers Effects Decision-making

  21. Study Area Methods • Hierarchical study design • Household-level Surveys • Regional remote sensing analyses • Assess cropping patterns and their association with climate

  22. Remote Sensing Analyses Regional-Scale • MODIS (250 m) Enhanced Vegetation Index (EVI) Crop 2 Crop 1 First Planting Date May November April

  23. Water Single Double Triple

  24. Association with Climate Regional-Scale Rainfall (avg mm/day – TRMM) Cropping Intensity

  25. Water Low Medium High

  26. Conclusions • Farmers alter cropping strategies based on inter-annual rainfall variability at both local and regional scales • Farmers with irrigation access are less likely to alter cropping strategies • Yield is best explained by number of irrigations but is not affected by planting date

  27. Conclusions • Framework allows us to assess: • the relative importance of various inter-disciplinary drivers for decision-making • whether coping strategies are adaptive • whether our results are generalizeable across a broader region

  28. Acknowledgements Advising Committee Dr. Ruth DeFries, Dr. ShahidNaeem Dr. Trevor Birkenholtz, Dr. Vijay Modi, Dr. Ben Orlove, Dr. Paige West Collaborators Dr. Chris Small, Dr. Gillian Galford, Dr. PinkiMondal, Columbia Water Center (CWC), Amir Jina(and photo credits) Funding NSF, NASA, CWC, AC4, National Geographic

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