framework for assessing adaptive capacity in social-ecological systems

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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. - PowerPoint PPT Presentation

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Framework for Assessing Adaptive Capacity in Social-Ecological Systems

Meha Jain, Ph.D. CandidateDept of Ecology, Evolution, and Environmental Biology

Columbia University

Governance of Adaptation

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

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

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

Liter

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e Re

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Factors Associated With Adaptive Capacity

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Adaptation Research Next Steps

• Consider multiple factors in the same analysis

• Multi-disciplinary

• Explicitly consider climate as a driving factor

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Economic

Decision to Cope

Climate

Biophysical

Perceptional

Social

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Adaptive

Economic

Decision to Cope

Climate

Biophysical

Perceptional

Social

Current Research Limitations

• Quantify whether a changed behavior is actually adaptive

Current Research Limitations

• Understand the scale of interactions

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atur

e Re

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Current Research Limitations

• Understand the scale of interactions

Liter

atur

e Re

view

Current Research Limitations

• Understand the scale of interactions

Liter

atur

e Re

view

New FrameworkFr

amew

ork

Effects

Multiple Drivers

Natio

nal o

r Glo

bal S

cale

Regi

onal

Sca

le

Loca

l Sca

le

Decision-making

Agricultural Communities in Northwest India

Case

Stu

dy

Study Area• Hierarchical study

design• Household-level

Surveys• Regional remote

sensing analyses

Met

hods

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?

Hous

ehol

d-Sc

ale

Effects

Multiple Drivers

Decision-making

Adaptation Strategies• Switch crop type• Shift planting date• Alter cropping intensity

Water-intensive Drought-tolerant

Main Monsoon CropsCotton Cash-Crop

Short DurationCastor Cash-Crop

Long DurationSorghum Household-use

Short DurationMillet Household-use

Short Duration

Wat

er In

tens

ive

Hous

ehol

d-Sc

ale

Crop Planting Date by Rainfall

-3

-2

-1

1 2 3Adjusted R2= .173

Previous Crop Failure

Water Insecurity

Precipitation Required to Sow

Land Owned

Asset Index

Hous

ehol

d-Sc

ale

Adjusted R2= .127

Land Owned

Soil Fertility

Date Planted

# of Irrigations

Amt of Fertilizer

Amt of Pesticides

Predictors of Cotton Yield

Parameter Value

Hous

ehol

d-Sc

ale

Regional-level Adaptation

• How consistent are these patterns at the regional scale?

Effects

Multiple Drivers

Regi

onal

Sca

le

Decision-making

Loca

l Sca

le

Study Area• Hierarchical study

design• Household-level

Surveys• Regional remote

sensing analyses• Assess cropping

patterns and their association with climate

Met

hods

First Planting Date

Crop 1 Crop 2

May November April

Remote Sensing AnalysesRe

gion

al-S

cale

MODIS (250 m) Enhanced Vegetation Index (EVI)

WaterSingle Double Triple

Association with Climate

2000 2001 2002 2003 2004 2005 2006 2007 20080

0.5

1

1.5

2

2.5

3

3.5

4

2000 2001 2002 2003 2004 2005 2006 2007 20080

0.5

1

1.5

2

2.5

3

3.5

4

Rainfall (avg mm/day – TRMM)Cropping Intensity

Regi

onal

-Sca

le

WaterLowMedium High

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

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

AcknowledgementsAdvising CommitteeDr. Ruth DeFries, Dr. Shahid NaeemDr. Trevor Birkenholtz, Dr. Vijay Modi, Dr. Ben Orlove, Dr. Paige WestCollaboratorsDr. Chris Small, Dr. Gillian Galford, Dr. Pinki Mondal, Columbia Water Center (CWC), Amir Jina (and photo credits)

FundingNSF, NASA, CWC, AC4, National Geographic

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