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 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 Literature Review

5. Factors Associated With Adaptive Capacity Literature Review

6. Adaptation Research Next Steps Consider multiple factors in the same analysis Multi-disciplinary Explicitly consider climate as a driving factor Literature Review

7. Current Research Limitations Quantify whether a changed behavior is actually adaptive

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

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

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

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

12. Agricultural Communities in Northwest India Case Study

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

14. Household-level Adaptation 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? Household-Scale Decision- making

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

17. Main Monsoon Crops CottonCash-Crop Short Duration CastorCash-Crop Long Duration SorghumHousehold-use Short Duration MilletHousehold-use Short Duration Water Intensive Household-Scale

18. Crop Planting Date by Rainfall

19. -3-3 -2-2 -1 1 2 3 Adjusted R 2 =.173 Previous Crop Failure Water Insecurity Precipitation Required to Sow Land Owned Asset Index Household-Scale

20. Adjusted R 2 =.127 Land Owned Soil Fertility Date Planted # of Irrigations Amt of Fertilizer Amt of Pesticides Predictors of Cotton Yield Parameter Value Household-Scale

21. Regional-level Adaptation How consistent are these patterns at the regional scale? Regional Scale Decision- making Local Scale

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

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

24. Water Single Double Triple

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

26. Water Low Medium High

27. 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

28. 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

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