Mapping hotspots of climate change and food insecurity across the global tropics

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Mapping hotspots of climate change and food insecurity across the global tropics

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  • Possible regions: Southern Africa, West Asia-North Africa, Central Africa, Central America, upland South America, lowland South America, South Asia outside the IGP, South-East Asia, East Asia, Pacific, coastal zones, small island states, …
  • Meta analysis of food economy studies in Southern Africa reveals that although environmental stresses are important they are never the only reason for a food insecure situation. Other stresses are always involved.
  • Discuss each aspect; explain measurement and indicators.
  • Explain visa vi entitlements (trade, labour)
  • Explain high, low.
  • Large exposure – some in areas with not too much cropping BUT also large high sensitive areas throughout Africa and INDIA!
  • Much more restrictive exposure measure – only small areas in the HHL (bright red) category
  • Slightly larger area / most high exposure not in extensively cropped areas
  • Quite inclusive threshold but not so much in combination with high resilience and low capacity / HHL mainly India, Bangladesh
  • HHL in West-Africa, India – some high exposure and currently low sensitivity might change with crop expansion
  • Not so much exposure – some HHL in Nigeria and India
  • High exposure in a number of quite densely populated areas: west and southern africa / SA & SEA
  • Very inclusive
  • Read from report.
  • Mapping hotspots of climate change and food insecurity across the global tropics

    1. 1. Mapping hotspots of climate change and food insecurity across the global tropics Polly Ericksen, Philip Thornton, An Notenbaert, Laura Cramer, Mario Herrero 14 April 2011
    2. 2. <ul><li>Three initial target regions (East Africa, West Africa, Indo-Gangetic Plain) </li></ul><ul><li> five by 2012! </li></ul><ul><li>Vulnerability mapping work + selection criteria + list of potential target regions as inputs to a process of selection </li></ul><ul><li>Weighting exercise for each candidate region for different stakeholder groups: </li></ul><ul><li>Contact points and global partners </li></ul><ul><li>CRP7 management team </li></ul><ul><li>CRP7 steering committee </li></ul><ul><li>Final decision by November </li></ul>CCAFS transition to CRP 7
    3. 3. Vulnerability of food security to climate change <ul><li>Vulnerable people/systems ~ those that stand a high change to be negatively affected by a (series of) events </li></ul><ul><ul><li>“ Where are the areas that are most likely to experience more food insecurity due to climate change?” </li></ul></ul><ul><li>3 components to vulnerability assessment </li></ul><ul><ul><li>Exposure </li></ul></ul><ul><ul><li>Sensitivity </li></ul></ul><ul><ul><li>Coping capacity </li></ul></ul><ul><li> Construction of “vulnerability domains” </li></ul>
    4. 4. Food security .....exists when all people, at all times, have physical and economic access to sufficient, safe, and nutritious food to meet their dietary needs and food preferences for an active and healthy life. (World Food Summit 1996)
    5. 5. <ul><li>Food insecurity arises from overlapping and interacting stressors </li></ul>Misselhorn 2005 Global Environmental Change
    6. 6. Vulnerability to climate change GECAFS 2005 Climate Change Change in type, frequency & magnitude of climate events FOOD SYSTEM RESILIENCE / VULNERABILITY SOCIETAL CHANGE Change in institutions, resource accessibility, economic conditions, etc. Capacity to cope with &/or recover from CC Exposure to CC
    7. 7. Vulnerability analysis Exposure of populations to the impacts of climate change (hi, lo) Sensitivity of food systems to these impacts (hi, lo) Coping capacity of populations to address these impacts (hi, lo) x x Agricultural land areas from 35 ⁰S to 45 ⁰N (Ramankutty et al., 2008) plus LGP>60 days
    8. 8. GCM consistency in regional precipitation projections for 2090-2099 (SRES A1B). IPCC, 2007 Region Jun-Aug Dec-Jan Sahara Small decrease (5-20%) Inconsistent West Africa Inconsistent Inconsistent East Africa Small increase (5-20%) Inconsistent Southern Africa Inconsistent Large decrease (>20%)
    9. 9. Downscaling GCMs for impact / exposure analysis <ul><li>Use ensembles of “equally-likely” combinations of climate model + emissions scenario  mean response and s.e. of response </li></ul><ul><li>Downscale spatially, from 2 ° lat-long grids to a more useful resolution (e.g. 9-km grids) </li></ul><ul><li>Downscale temporally from long-term climatology to characteristic daily weather data </li></ul><ul><ul><li>Use MarkSim as a GCM downscaler: difference interpolation + stochastic downscaling + weather typing </li></ul></ul><ul><ul><li> Generate exposure indicators based on daily data </li></ul></ul>
    10. 10. Exposure thresholds 1 Length of growing period (LGP) declines by >5% 2 Flip from LGP > 120 days in the 2000s to LGP < 120 in the 2050s 3 Flip from Reliable Crop Growing Days per year > 90 days in the 2000s to RCGDs < 90 in the 2050s 4 Flip from an average annual temp < 8°C in the 2000s to Tav > 8°C in the 2050s 5 Flip from an average annual maximum daily temp < 30°C in the 2000s to Tmax > 30°C in the 2050s 6 As above, but for the 150 days from the start of the primary growing season 7 Rainfall per rainday decreases by >10% to the 2050s 8 Rainfall per rainday increases by >10% to the 2050s 9 Areas in which current annual rainfall CV is >21%
    11. 11. Areas that flip from > 90 Reliable Crop Growing Days (RCGD) per year in the 2000s to < 90 RCGD by the 2050s Cropping becomes very risky in areas with RCGD < 90 Reliable Crop Growth Days, calculated over n seasons per year as n RCGD = Σ season length j * (1 – failure rate j ) j=1 Exposure 3
    12. 12. Areas where maximum temperature during the primary growing season is currently < 30 ° C but will flip to > 30 ° C by the 2050s Yield of many crops is considerably reduced at higher temperatures Boote et al. (1998) Exposure 6
    13. 13. Using current rainfall variability as a proxy for climate variability Areas with current annual rainfall CV > 21% (the modal CV for cropped areas in the tropics, excluding irrigated areas) Rainfall CV (%, x-axis), cropping extent (y-axis) Exposure 9
    14. 14. Mapping the number of these 9 potential climate threats that apply in each pixel For the positive temperature flip (from < 8 ° C to > 8 ° C), we reduced the number of threats by one Expanded crop suitability? Andes, parts of Central and highland South Asia, Southern China Multiple Exposures
    15. 15. Regional maps for E Africa, W Africa, IGP Exposures 5, 6
    16. 16. FOOD UTILISATION Components of Food Security & Key Elements FOOD ACCESS <ul><li>Affordability </li></ul><ul><li>Allocation </li></ul><ul><li>Preference </li></ul><ul><li>Nutritional Value </li></ul><ul><li>Social Value </li></ul><ul><li>Food Safety </li></ul>FOOD AVAILABILITY <ul><li>Production </li></ul><ul><li>Distribution </li></ul><ul><li>Exchange </li></ul>
    17. 17. Availability: crop production Also mapped beans, rice, wheat, sorghum, millet and cassava. You, L., S.Crespo, Z. Guo, J. Koo, W. Ojo, K. Sebastian, M.T. Tenorio, S. Wood, U. Wood-Sichra. Spatial Production Allocation Model (SPAM) 2000 Version 3 Release 2. http://MapSPAM.info .
    18. 18. Availability: Food Production Index Average 2003-2007. FAO Statistics Division, FAOSTAT.
    19. 19. Access: population with less than $2 per day http://geonetwork.csi.cgiar.org/geonetwork/srv/en/main.home
    20. 20. Access: staple food prices http://www.fao.org/giews/pricetool/ )
    21. 21. Utilization: wasting prevalence World Development Indicators Database
    22. 22. Resource pressure: arable land per capita FAO STAT
    23. 23. Vulnerability of food security to climate change <ul><li>Vulnerable people/systems ~ those that stand a high change to be negatively affected by a (series of) events </li></ul><ul><li>“ Where are the areas that are most likely to experience more food insecurity due to climate change?” </li></ul><ul><li>3 components </li></ul><ul><li>Exposure </li></ul><ul><li>Sensitivity </li></ul><ul><li>Coping capacity </li></ul><ul><li> Construction of “vulnerability domains” </li></ul>
    24. 24. Exposure <ul><li>The thresholds </li></ul>
    25. 25. Sensitivity <ul><li>Areas with more dependence on crop agriculture are assumed to be more sensitive to a change in climate. 16% is mode for tropics. </li></ul>
    26. 26. Coping capacity <ul><li>We considered that chronic food insecurity could be a proxy for coping capacity, as inability to tackle chronic food insecurity indicates a number of institutional, economic and political problems. </li></ul>
    27. 27. Combination in “domains” <ul><li>3 components * 2 classes  8 domains </li></ul>Domain Exposure Sensitivity Coping capacity HHL High High Low HHH High HLL Low Low HLH High LHL Low High Low LHH High LLL Low Low LLH High
    28. 28. Combination in “domains” <ul><li>3 components * 2 classes  8 domains </li></ul>Domain Exposure Sensitivity Coping capacity HHL High High Low HHH High HLL Low Low HLH High LHL Low High Low LHH High LLL Low Low LLH High
    29. 29. LGP change > 5%
    30. 30. LGP flips to < 120 days
    31. 31. RCGD flip to < 90 days
    32. 32. Max. daily temp flip to > 30 deg C
    33. 33. Growing season Temp flip to >30 degC
    34. 34. Rain per rain day decrease > 10%
    35. 35. Rain per rain day increase > 10%
    36. 36. CV rainfall > 21%
    37. 37. Conclusions <ul><li>Climate hotspot indications: </li></ul><ul><ul><li>Cropping thresholds (growing period reduced) </li></ul></ul><ul><ul><li>Temperature extremes (max and min) increasing </li></ul></ul><ul><ul><li>Increased dryness, increased rain intensity? </li></ul></ul><ul><li>Food security hotspots: </li></ul><ul><ul><li>Stagnant PI </li></ul></ul><ul><ul><li>Poverty </li></ul></ul><ul><ul><li>Undernourished population </li></ul></ul>
    38. 38. Conclusions <ul><li>Domains </li></ul><ul><ul><li>High exposure, high sensitivity, low capacity </li></ul></ul><ul><ul><li>But also watch HHH because other capacity indicators </li></ul></ul><ul><ul><li>HLL: increase in cropping? </li></ul></ul><ul><ul><li>Variation in “low exposure” category </li></ul></ul><ul><ul><li>Populations included vary considerably </li></ul></ul><ul><ul><ul><li>Exposure 1 has most; exposure 3 and 6 least. </li></ul></ul></ul>
    39. 39. Next steps <ul><li>Try with other coping capacity indicators </li></ul><ul><ul><li>E.g. with better household level data </li></ul></ul><ul><li>Map drivers of food insecurity not outcomes </li></ul><ul><li>Model scenarios of food security to 2050 </li></ul>
    40. 40. International Livestock Research Institute Better lives through livestock Animal agriculture to reduce poverty, hunger and environmental degradation in developing countries ILRI  www.ilri.org

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