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Symposium       15t   h
                                                                               ISTRC
                                                       TrIennIal of the SymposIum of the
                                      InternatIonal SocIety for TropIcal Root Crops
    2 – 6 N o v e m b e r, 2 0 0 9




Ex ante assessment of climate change adaptation
     strategies in resource-poor countries:
          study cases from East Africa
L. Claessens1,2, J.J. Stoorvogel2, J.M. Antle3, R.O. Valdivia3, P.K. Thornton4, M. Herrero4
1   International Potato Center, Nairobi, Kenya
2   Wageningen University, the Netherlands
3   Montana State University, Bozeman, USA
4   International Livestock Research Institute
Climate change and adaptation in SSA

IPCC Fourth Assessment Report (2007):

• CC predicted to have most negative impact on poorest people in SSA
• Impacts inevitable for next 30 years, regardless of global mitigation
  efforts
• Crop yields may fall by 10-20% by 2050, more severe in some areas
• CC will aggravate existing challenges to food security, economic
  development, health,…
• Adaptation strategies absolutely necessary to mitigate CC impacts
Number of growing seasons




                    Current conditions                      2050 (HadCM3, A1)

Source: Thornton et al., 2006
Percentage of failed seasons




                    Current conditions                         2050 (HadCM3, A1)

Source: Thornton et al., 2006
Climate change and adaptation in SSA

• Current research:
   • Downscaled GCM or RCM projections
      • Uncertain and highly variable (esp. rainfall, from 2050,…)
      • Different scenarios (~ world economy, emissions,…)
      • Feedback with land cover
   • Crop and livestock models: simulate effects on future productivity
      • Usually potential productivity (- management, diseases,…)
      • Often not parameterized for local varieties and conditions or no model
        at all (e.g. fruits, fodder crops,…)
      • No ‘mixed system’ models (intercropping, crop-livestock interactions)
   • Adaptation strategies:
      • Single crop, aggregated results, ‘representative farm’….
      • Hiding large variability and too general for locally specific adaptation
        strategies in semi-subsistence smallholder systems in SSA
      • Data intensive (high resolution bio-physical, socio-economic)
• Maize and beans yield by 2050 (Thornton et al., 2009)
    • DSSAT crop models
    • HadCM3 model, A1 scenario
• Changes in potato and sweet potato suitability by 2050 (Jarvis et al., 2009)
    • ECOCROP model
    • Average of 18 GCMs, scenario
Change in suitability 2020




                 Change in suitability 2050
Potatoes

High
       importance
Low
>20 % loss in LGP
5-20 % loss in LGP
Sweet
       Potatoes
High
       importance
Low
>20 % loss in LGP
5-20 % loss in LGP
Climate change and adaptation in SSA

In summary:
• Adaptation strategies in smallholder agriculture context:
    • Need to disaggregate to agricultural system / household level!
    • Bio-physical & socio-economic aspects
       • Complex, data demanding, time consuming,…
       • Problem of ‘quantification’ of adaptation strategies
   • Development of simple, reliable enough methods to ex ante assess
     adaptation strategies (technologies, policies)
       • Capture key components of system and variability (sensitivity analysis)
       • Realize but minimize uncertainties and assumptions
       • Data / model scarcity: analogue approaches, empirical
         equations,…pragmatic tools!
Research methodology:

Tradeoff Analysis (TOA) framework

• Assessing environmental and economic feasibility of alternative technologies and
policies

• Linking stakeholders with research teams (‘reality check’)

• Using (semi-)quantitative impact assessment tools and models

• Using site specific (often readily available) data to capture variation in farm
population (land and resource allocation, productivity, off farm income,….) at the
agricultural system level
↔ ‘representative farm’ approaches
Agricultural systems classification
(ILRI, Seré and Steinfield, 1996)
Tradeoff Analysis methodology for climate change impact assessment
farmers, extension workers, local community leaders
                                                      poverty rates
           • Public stakeholders                      soil productivity
           • Policy makers                            nutritional status
           • Scientists
                                               dual-purpose sweet potato, drought tolerant potato
                                               improved livestock management
      Identify indicators and scenarios
                                               investment in transportation infrastructure
                                               Payment for environmental services (C seq.)
     Coordinated Disciplinary Research
                 • Downscale GCM and RCM output
                 • Prepare crop and livestock models
                 • Prepare economic data and models
                 • Prepare environmental data and models
                 • Set up scenarios for simulation
                 • Implement analysis using TOA software


     Evaluate results with stakeholders
Application




              Two examples from Kenya:

              •Vihiga (MRT), western province

              •Machakos-Makueni (MRA),
               eastern province
Study area: Vihiga, western Kenya
Alt. (m)  Prec. (mm) Temp.(°
                           C)      Main crops
1300-1500 1800-2000 14-32          maize, beans, sweet potato, Napier
Mixed crop-livestock system, semi-subsistence
Depleted soils, small farms
One of the poorest districts in Kenya (60% on <$1/day)
Study area: Machakos, Eastern province
 Alt. (m)    Prec. (mm) Temp.(°
                              C)       Main crops
 400-2100    500-1300 15-25            maize, beans, veg., cassava
  Mixed crop-livestock system, semi-subsistence
  Depleted soils, small farms
  Terraces, small scale irrigation for vegetables
Tradeoff Analysis methodology for climate change impact assessment



1. Characterization of the current agricultural system
2. Simulation of effects of climate change on current system
3. Simulation of adaptation strategies
(e.g. Introduction improved varieties, payment for environmental services,...)



Towards reduced complexity modeling (‘Minimum Data’ approach):
  • Data on land use allocation (crop area, yield, livestock,…) and net returns
  • Experimental (on farm) yield data for DP SP
  • Livestock feed characteristics (DM, energy, crude protein, harvest index)
  • Empirical data on effect of feed quality on milk production
  • Climate change projections
  • Estimated effects of CC on crop yields (crop models, analogue approaches)
• CC: Production changes per agricultural system (Thornton et al., 2009)
    •   DSSAT crop models for maize and beans
    •   Mean of four combinations of HadCM3 and ECHam4 GCMs, A1 and B1
    •   Observed analogue productivity data for other crops (/sensitivity analysis)
    •   Assumed no direct effect of CC on livestock productivity




    • Adaptation strategies tested:
       • Machakos:      - drought tolerant maize variety
                        - introduction of sweet potato
       • Vihiga:        - introduction of dual-purpose sweet potato
Machakos:   - drought tolerant maize
            - introduction sweet potato
Vihiga: - dual-purpose sweet potato
Conclusions

• Serious implications from CC in SSA, but not negative everywhere…
• Lots of issues and uncertainties in CC projections and
  methodologies to assess site-specific adaptation
• Need for simple, reliable enough methods to ex ante assess
  adaptation strategies at agricultural system / household level
• Minimum Data TOA approach proposed for rapid integrative analysis
  of adaptation options (being aware of limitations!)
• Two contrasting examples for different agricultural systems Kenya:
• Adverse effects of CC only partially offset by proposed adaptation
  strategies
• Some regions are predicted to benefit from CC
• Ongoing work to cover other agricultural systems in the region
  (potato and sweet potato areas in Kenya, Uganda, Ethiopia)
Ex ante assessment of climate change adaptation strategies in resource-poor countries: Study cases from East Africa

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Ex ante assessment of climate change adaptation strategies in resource-poor countries: Study cases from East Africa

  • 1. Symposium 15t h ISTRC TrIennIal of the SymposIum of the InternatIonal SocIety for TropIcal Root Crops 2 – 6 N o v e m b e r, 2 0 0 9 Ex ante assessment of climate change adaptation strategies in resource-poor countries: study cases from East Africa L. Claessens1,2, J.J. Stoorvogel2, J.M. Antle3, R.O. Valdivia3, P.K. Thornton4, M. Herrero4 1 International Potato Center, Nairobi, Kenya 2 Wageningen University, the Netherlands 3 Montana State University, Bozeman, USA 4 International Livestock Research Institute
  • 2. Climate change and adaptation in SSA IPCC Fourth Assessment Report (2007): • CC predicted to have most negative impact on poorest people in SSA • Impacts inevitable for next 30 years, regardless of global mitigation efforts • Crop yields may fall by 10-20% by 2050, more severe in some areas • CC will aggravate existing challenges to food security, economic development, health,… • Adaptation strategies absolutely necessary to mitigate CC impacts
  • 3. Number of growing seasons Current conditions 2050 (HadCM3, A1) Source: Thornton et al., 2006
  • 4. Percentage of failed seasons Current conditions 2050 (HadCM3, A1) Source: Thornton et al., 2006
  • 5. Climate change and adaptation in SSA • Current research: • Downscaled GCM or RCM projections • Uncertain and highly variable (esp. rainfall, from 2050,…) • Different scenarios (~ world economy, emissions,…) • Feedback with land cover • Crop and livestock models: simulate effects on future productivity • Usually potential productivity (- management, diseases,…) • Often not parameterized for local varieties and conditions or no model at all (e.g. fruits, fodder crops,…) • No ‘mixed system’ models (intercropping, crop-livestock interactions) • Adaptation strategies: • Single crop, aggregated results, ‘representative farm’…. • Hiding large variability and too general for locally specific adaptation strategies in semi-subsistence smallholder systems in SSA • Data intensive (high resolution bio-physical, socio-economic)
  • 6. • Maize and beans yield by 2050 (Thornton et al., 2009) • DSSAT crop models • HadCM3 model, A1 scenario
  • 7. • Changes in potato and sweet potato suitability by 2050 (Jarvis et al., 2009) • ECOCROP model • Average of 18 GCMs, scenario
  • 8. Change in suitability 2020 Change in suitability 2050
  • 9. Potatoes High importance Low >20 % loss in LGP 5-20 % loss in LGP
  • 10. Sweet Potatoes High importance Low >20 % loss in LGP 5-20 % loss in LGP
  • 11. Climate change and adaptation in SSA In summary: • Adaptation strategies in smallholder agriculture context: • Need to disaggregate to agricultural system / household level! • Bio-physical & socio-economic aspects • Complex, data demanding, time consuming,… • Problem of ‘quantification’ of adaptation strategies • Development of simple, reliable enough methods to ex ante assess adaptation strategies (technologies, policies) • Capture key components of system and variability (sensitivity analysis) • Realize but minimize uncertainties and assumptions • Data / model scarcity: analogue approaches, empirical equations,…pragmatic tools!
  • 12. Research methodology: Tradeoff Analysis (TOA) framework • Assessing environmental and economic feasibility of alternative technologies and policies • Linking stakeholders with research teams (‘reality check’) • Using (semi-)quantitative impact assessment tools and models • Using site specific (often readily available) data to capture variation in farm population (land and resource allocation, productivity, off farm income,….) at the agricultural system level ↔ ‘representative farm’ approaches
  • 13. Agricultural systems classification (ILRI, Seré and Steinfield, 1996)
  • 14. Tradeoff Analysis methodology for climate change impact assessment farmers, extension workers, local community leaders poverty rates • Public stakeholders soil productivity • Policy makers nutritional status • Scientists dual-purpose sweet potato, drought tolerant potato improved livestock management Identify indicators and scenarios investment in transportation infrastructure Payment for environmental services (C seq.) Coordinated Disciplinary Research • Downscale GCM and RCM output • Prepare crop and livestock models • Prepare economic data and models • Prepare environmental data and models • Set up scenarios for simulation • Implement analysis using TOA software Evaluate results with stakeholders
  • 15. Application Two examples from Kenya: •Vihiga (MRT), western province •Machakos-Makueni (MRA), eastern province
  • 16. Study area: Vihiga, western Kenya Alt. (m) Prec. (mm) Temp.(° C) Main crops 1300-1500 1800-2000 14-32 maize, beans, sweet potato, Napier Mixed crop-livestock system, semi-subsistence Depleted soils, small farms One of the poorest districts in Kenya (60% on <$1/day)
  • 17. Study area: Machakos, Eastern province Alt. (m) Prec. (mm) Temp.(° C) Main crops 400-2100 500-1300 15-25 maize, beans, veg., cassava Mixed crop-livestock system, semi-subsistence Depleted soils, small farms Terraces, small scale irrigation for vegetables
  • 18. Tradeoff Analysis methodology for climate change impact assessment 1. Characterization of the current agricultural system 2. Simulation of effects of climate change on current system 3. Simulation of adaptation strategies (e.g. Introduction improved varieties, payment for environmental services,...) Towards reduced complexity modeling (‘Minimum Data’ approach): • Data on land use allocation (crop area, yield, livestock,…) and net returns • Experimental (on farm) yield data for DP SP • Livestock feed characteristics (DM, energy, crude protein, harvest index) • Empirical data on effect of feed quality on milk production • Climate change projections • Estimated effects of CC on crop yields (crop models, analogue approaches)
  • 19. • CC: Production changes per agricultural system (Thornton et al., 2009) • DSSAT crop models for maize and beans • Mean of four combinations of HadCM3 and ECHam4 GCMs, A1 and B1 • Observed analogue productivity data for other crops (/sensitivity analysis) • Assumed no direct effect of CC on livestock productivity • Adaptation strategies tested: • Machakos: - drought tolerant maize variety - introduction of sweet potato • Vihiga: - introduction of dual-purpose sweet potato
  • 20. Machakos: - drought tolerant maize - introduction sweet potato
  • 21. Vihiga: - dual-purpose sweet potato
  • 22. Conclusions • Serious implications from CC in SSA, but not negative everywhere… • Lots of issues and uncertainties in CC projections and methodologies to assess site-specific adaptation • Need for simple, reliable enough methods to ex ante assess adaptation strategies at agricultural system / household level • Minimum Data TOA approach proposed for rapid integrative analysis of adaptation options (being aware of limitations!) • Two contrasting examples for different agricultural systems Kenya: • Adverse effects of CC only partially offset by proposed adaptation strategies • Some regions are predicted to benefit from CC • Ongoing work to cover other agricultural systems in the region (potato and sweet potato areas in Kenya, Uganda, Ethiopia)