1. 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)

2. Purpose, rationale and approach Purpose To contribute to a comprehensive research approach that bridges the gap between analysis of climate change (CC) impacts on food security (FS) and policy-making Rationale Downscale 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 Approach Focus on vulnerable groups Address the access component of FS

3. 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

4. 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

5. 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?

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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 - ESA

14. Background on analysis of vulnerability to food insecurity Improve targeting and design of interventions Initial steps Conceptual and methodological developments Country application

15. 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

16. Concepts

17. 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

18. Data sources Households: –Rural Income-generating Activities dataset (RIGA) –1831 Households surveyed in 2001 Climate: –Temperature and precipitation –PRECIS ECHAM4, A2 scenario –Downscaled data

19. Geographic distribution of vulnerability

20. Improved targeting Proportion of vulnerable households and average vulnerability (2001) Not VulnerableVulnerableTotal 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%

21. Improved targeting Proportion of vulnerable households and average vulnerability (2001) Not VulnerableVulnerableTotal 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%

22. Improved targeting Proportion of vulnerable households and average vulnerability (2001) Not VulnerableVulnerableTotal 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%

23. Profile of vulnerable households: gender Not VulnerableVulnerableTotal Proportion of households Average vulnerability Proportion of households Average vulnerability Proportion of households Average vulnerability Female- headed household s 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

24. Profile of vulnerable households: assets and livelihoods Class of vulnerabilityunit0-20%20-50%50-60%60-70%70-80%80-90%90-100%Total Education (head) Years 2.511.890.720.641.560.770.942.06 HH Sizeadul. eq. 5.346.796.747.737.638.728.366.15 Female headBin. 0.13 0.080.100.170.130.150.13 Access to safe water Bin. 0.590.480.510.370.360.570.310.53 Distance to major road Km 54.4560.4123.5457.5537.8854.9356.9054.04 # Bikes 0.390.190.230.200.090.050.060.30 Land operated Acres 8.477.057.246.273.406.414.647.57 Land ownedAcres 10.888.688.097.612.645.296.029.44 # draft anim. 1.270.640.470.700.550.870.731.05 HH received Loan Bin. 0.090.120.020.050.000.050.010.08 Gov’t prog.Bin. 1.561.351.181.240.961.860.991.45 Fertil. Chem.Bin. 0.450.330.260.250.31 0.160.38 Fertil. Org.Bin. 0.080.030.040.020.000.090.020.06 PesticideBin. 0.530.440.450.420.400.470.300.48 Temperature% 0.040.050.070.060.070.060.05

25. Vulnerability and Crops

26. 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

27. Policy Simulations: Current Climate

28. Policy Simulations: Higher Temperatures

29. Policy Simulations: Higher Temp.+ Responses

30. 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

31. 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?

32. 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

33. Thank you! Anna Ricoy anna.ricoy@fao.org Jeronim Capaldo jeronim.capaldo@fao.org