addressing the linkages between climate change and vulnerability to food insecurity testing a...

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

Thank you!

Anna Ricoyanna.ricoy@fao.org

Jeronim Capaldojeronim.capaldo@fao.org