addressing the linkages between climate change and vulnerability to food insecurity testing a...
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Addressing the linkages between climate change and vulnerability to
food insecurity
Testing a methodology in Nicaragua
Jeronim Capaldo – Agricultural Economics Division (ESA)Anna Ricoy - Climate, Energy and Tenure Division (NRC)
Purpose, rationale and approach
• PurposeTo contribute to a comprehensive research approach that bridges the gap between analysis of climate change (CC) impacts on food security (FS) and policy-making
• RationaleDownscale the broad and global CC agenda at the local level Engage policy makers to better address the impact of CC on FS at household level
• ApproachFocus on vulnerable groupsAddress the access component of FS
Background: Conceptual framework on CC and FS
Migration
Climate change variables
CO2 fertilization effects
Increase in global temp.
Changes in precipitation
Frequency of extreme events
Greater weather variability
Changes in consumption
patters
Changes in Food Systems Assets
Food production assets
Infrastructure
Agriculturally-based livelihoods
Non-farm livelihoods assets
Food preparation assets
Changes in Food Systems Assets
Food production assets
Infrastructure
Agriculturally-based livelihoods
Non-farm livelihoods assets
Food preparation assets
Changes in Food Systems Activities
Producing food
Storing and processing of food
Distributing food
Consuming food
Changes in Food Systems Activities
Producing food
Storing and processing of food
Distributing food
Consuming food
Changes in Components of Food Security
Food availability
Food accessibility
Food utilization
Food system stability
Changes in Components of Food Security
Food availability
Food accessibility
Food utilization
Food system stability
Adaptive responses
Source: Interdepartmental Group on Climate Change (IDWG) 2008
Background: Conceptual framework on CC and FS
Migration
Climate change variables
CO2 fertilization effects
Increase in global temp.
Changes in precipitation
Frequency of extreme events
Greater weather variability
Changes in consumption
patters
Changes in Food Systems Assets
Food production assets
Infrastructure
Agriculturally-based livelihoods
Non-farm livelihoods assets
Food preparation assets
Changes in Food Systems Assets
Food production assets
Infrastructure
Agriculturally-based livelihoods
Non-farm livelihoods assets
Food preparation assets
Changes in Food Systems Activities
Producing food
Storing and processing of food
Distributing food
Consuming food
Changes in Food Systems Activities
Producing food
Storing and processing of food
Distributing food
Consuming food
Changes in Components of Food Security
Food availability
Food accessibility
Food utilization
Food system stability
Changes in Components of Food Security
Food availability
Food accessibility
Food utilization
Food system stability
Source: Interdepartmental Group on Climate Change (IDWG) 2008
Adaptive responses
Key analytical questions
• How does CC affect access to food at household level?
• How does household vulnerability to food insecurity evolve as a result of CC?
• How will vulnerability be distributed as a result of CC?
• What policy instruments to increase the resilience of vulnerable groups to deal with the impact of CC on FS?
• How to improve the design and targeting of policy responses to address the impacts of CC on vulnerable groups?
Methodological framework
High-resolution CC projections at district level
Detailed profiling of vulnerable households
groups
Policy recommendations for the design
and implementation
of targeted policy interventions
Downscaling of GCM using RCM
Analysis of vulnerability to food insecurity
Analysis of implications at
policy level
Addressing the linkages between CC and vulnerability to food insecurity
Methodological framework
High-resolution CC projections at district level
Detailed profiling of vulnerable households
groups
Policy recommendations for the design
and implementation
of targeted policy interventions
Downscaling of GCM using RCM
Analysis of vulnerability to food insecurity
Analysis of implications at
policy level
Addressing the linkages between CC and vulnerability to food insecurity
1 - Downscaling of CC scenarios• Generation of high-resolution climate change projections using
RCMs (PRECIS, Hadley Center)
• Under ECHAM4, for A2 scenario
CC scenarios to a 50x50km scale for the whole Nicaragua, at “municipio” level
Time series of estimated temperature and precipitation projections to the 2030 horizon
coordinates of the PRECIS grid
Change Temperature (Annual mean) –2080s
Methodological framework
High-resolution CC projections at district level
Detailed profiling of vulnerable households
groups
Policy recommendations for the design
and implementation
of targeted policy interventions
Downscaling of GCM using RCM
Analysis of vulnerability to food insecurity
Analysis of implications at
policy level
Addressing the linkages between CC and vulnerability to food insecurity
2 - Analysis of vulnerability to food insecurity
• Quantitative analysis of the livelihood effect of CC:- building on the notion of vulnerability to food insecurity- using an analytical model developed by ESA based on
rural national household datasets • CC enters the model through the impacts that temperature
and precipitation changes have on income (value of land productivity) and food consumption (expenditure)
• Model allows characterizing vulnerability and identifying variables associated with highest levels of vulnerability Profiling of vulnerable household groups
Methodological framework
High-resolution CC projections at district level
Detailed profiling of vulnerable households
groups
Policy recommendations for the design
and implementation
of targeted policy interventions
Downscaling of GCM using RCM
Analysis of vulnerability to food insecurity
Analysis of implications at
policy level
Addressing the linkages between CC and vulnerability to food insecurity
3 - Analysis of policy implications
Purpose: to provide recommendations for improvements in the design and targeting of policy responses that address the impacts of CC on household FS
Next steps, in-country:What instruments should be promoted to increase households’ ability
to cope with the impacts of CC on FS and adapt to climate change?What are the policies, institutions and multi-level governance
arrangements needed to support vulnerable households?
• Links to specific practices: synergies adaptation, mitigation,, FS• Short + long-term policies addressing DRM/CCA measures tailored
to vulnerable groups• Integration of the linkages between CC and household FS within all
the phases of the policy cycle • Coherence between the local, national, regional level
Presentation of results of the analysis of vulnerability to food insecurity
High-resolution CC projections at district level
Detailed profiling of vulnerable
households groups
Policy recommendations for the design and implementation of
targeted policy interventions
Downscaling of GCM using RCM
Analysis of vulnerability to food insecurity
Analysis of implications at
policy level
Addressing the linkages between CC and vulnerability to food insecurity
Capaldo, P. Karfakis, M. Knowles, M. Smulders - ESACapaldo, P. Karfakis, M. Knowles, M. Smulders - ESA
Background on analysis of vulnerability to food insecurity
• Improve targeting and design of interventions
• Initial steps
• Conceptual and methodological developments
• Country application
Concepts
• Definitions of vulnerability:– Vulnerability to what?– Current or future?
• Our view:– A household’s probability to fall or stay below a food-
security threshold
Concepts
Analytical model
Households’ Demographic characteristics Climate DataHouseholds’ Assets
Distribution of Land Productivity
Distribution of Consumption
HH Food Security Threshold
Vulnerability
Categorization of Households Profiles
Vulnerability Threshold
Data
Model
output
Targeting
Data sources
• Households:– Rural Income-generating Activities dataset
(RIGA)– 1831 Households surveyed in 2001
• Climate:– Temperature and precipitation– PRECIS ECHAM4, A2 scenario– Downscaled data
Geographic distribution of vulnerability
Improved targeting
Proportion of vulnerable households and average vulnerability (2001)
Not Vulnerable Vulnerable Total
Proportion of
households
Average vulnerability
Proportion of
households
Average vulnerability
Proportion of
households
Average vulnerability
Food secure 70% 6% 5% 73% 75% 11%
Food insecure 7% 27% 18% 82% 25% 67%
Total 77% 8% 23% 80% 100% 25%
Improved targeting
Proportion of vulnerable households and average vulnerability (2001)
Not Vulnerable Vulnerable Total
Proportion of
households
Average vulnerability
Proportion of
households
Average vulnerability
Proportion of
households
Average vulnerability
Food secure 70% 6% 5% 73% 75% 11%
Food insecure 7% 27% 18% 82% 25% 67%
Total 77% 8% 23% 80% 100% 25%
Improved targeting
Proportion of vulnerable households and average vulnerability (2001)
Not Vulnerable Vulnerable Total
Proportion of
households
Average vulnerability
Proportion of
households
Average vulnerability
Proportion of
households
Average vulnerability
Food secure 70% 6% 5% 73% 75% 11%
Food insecure 7% 27% 18% 82% 25% 67%
Total 77% 8% 23% 80% 100% 25%
Profile of vulnerable households: gender
Not Vulnerable Vulnerable Total
Proportion of households
Average vulnerability
Proportion of households
Average vulnerability
Proportion of households
Average vulnerability
Female-headed households
9.87% 8% 3.01% 82% 12.88% 25%
Male-headed HH
67.20% 8% 19.92% 80% 87.12% 25%
Total 77.07% 8% 22.93% 80% 100% 25%
Proportion of vulnerable households and average vulnerability (2001), by gender of head of household
Profile of vulnerable households: assets and livelihoodsClass of
vulnerability unit 0-20% 20-50% 50-60% 60-70% 70-80% 80-90% 90-100% Total
Education (head)
Years 2.51 1.89 0.72 0.64 1.56 0.77 0.94 2.06
HH Size adul. eq. 5.34 6.79 6.74 7.73 7.63 8.72 8.36 6.15
Female head Bin. 0.13 0.13 0.08 0.10 0.17 0.13 0.15 0.13
Access to safe water
Bin. 0.59 0.48 0.51 0.37 0.36 0.57 0.31 0.53
Distance to major road
Km 54.45 60.41 23.54 57.55 37.88 54.93 56.90 54.04
# Bikes 0.39 0.19 0.23 0.20 0.09 0.05 0.06 0.30
Land operated
Acres 8.47 7.05 7.24 6.27 3.40 6.41 4.64 7.57
Land owned Acres 10.88 8.68 8.09 7.61 2.64 5.29 6.02 9.44
# draft anim. 1.27 0.64 0.47 0.70 0.55 0.87 0.73 1.05
HH received Loan
Bin. 0.09 0.12 0.02 0.05 0.00 0.05 0.01 0.08
Gov’t prog. Bin. 1.56 1.35 1.18 1.24 0.96 1.86 0.99 1.45
Fertil. Chem. Bin. 0.45 0.33 0.26 0.25 0.31 0.31 0.16 0.38
Fertil. Org. Bin. 0.08 0.03 0.04 0.02 0.00 0.09 0.02 0.06
Pesticide Bin. 0.53 0.44 0.45 0.42 0.40 0.47 0.30 0.48
Temperature % 0.04 0.05 0.07 0.06 0.07 0.06 0.05 0.05
Vulnerability and Crops
Profile of vulnerable households: assets and livelihoods
• education of head < 3 years
• highest education in the hh < 6 years
• household size > 5 members
• agriculture oriented > 50% share of income
• low use of fertilizers and pesticides in the area
• livestock in TLU < 4 units
• no irrigation
• no credit access
• distance to road > 60 km
• distance to health facility > 6 km
• distance to school > 1.5 km
Policy Simulations: Current Climate
Policy Simulations: Higher Temperatures
Policy Simulations: Higher Temp.+ Responses
Conclusions on the analysis of vulnerability to food insecurity
• Model contributes to improved program design and preparedness planning by:
– Making distinction between transitory and chronically food insecure households
– Estimating impact of shocks (e.g. climate) on household vulnerability and number of affected households
– Profiling the vulnerable
Lessons learned
• matching data to geographical locations with GIS
• biophysical impacts on crop production• Estimation of vulnerability with climate data
requires non-linear models• Estimation of probability
How can the assessment be improved?How can the assessment be improved?
Moving forward
• Nicaragua is a pilot. Lessons learned will serve to improve the methodology
• Replication envisaged in different institutional and policy contexts
• Ultimate goal is to develop a robust research framework on the impacts of CC on household FS and related policy-level implications
