Climate Change Adaptation and Mitigation in the Kenyan Coffee Sector
CIAT – International Center for Tropical Agriculture <ul><li>CIAT:  Part of Consultative Group on International Agricultur...
Content <ul><li>A: Introductions </li></ul><ul><li>B: Research questions </li></ul><ul><li>C: Methods and data generation ...
Introductions <ul><li>Study objectives: </li></ul><ul><li>Elaboration of future climate scenarios to indicate the impact o...
Research questions <ul><li>Where will coffee grow in the future? </li></ul><ul><li>Where will coffee not grow any more? </...
Methods and data generation <ul><li>Historical climate generation </li></ul><ul><li>Future climate </li></ul><ul><li>Suita...
Historical climate generation <ul><li>WorldClim ( www.worldclim.org ) database (Hijmans et al, 2005) </li></ul><ul><li>Bas...
Future climate <ul><li>Global circulation models (GCM) </li></ul><ul><li>Calibrated in the past (using time-series), and p...
Global circulation models (GCM) <ul><li>20 models (different institutions) </li></ul>C
bioclimatic variables <ul><li>Bio1 = Annual mean temperature </li></ul><ul><li>Bio2 = Mean diurnal range (Mean of monthly ...
Generation of future climate <ul><li>Current climate from worldclim (1km resolution) </li></ul><ul><ul><li>Prec, temp min/...
Suitability prediction <ul><li>finding the probability distribution of maximum entropy (MAXENT) </li></ul>C MAXENT is gene...
Methodology – the process <ul><li>Compilation of evidence data. </li></ul><ul><li>Generation of future climates. </li></ul...
Results of analysis: Regional changes <ul><li>Evidence data: </li></ul><ul><li>805  Arabica coffee farms in Kenya </li></u...
Results of analysis: Regional changes <ul><li>Annual precipitation 2020 </li></ul><ul><ul><li>rainfall increases from 1405...
Results of analysis: Regional changes <ul><li>Annual precipitation 2050 </li></ul><ul><ul><li>rainfall increases from 1405...
Results of analysis: Regional changes <ul><li>Annual temperature 2020 </li></ul><ul><ul><li>temperature increases by 1°C <...
Results of analysis: Regional changes <ul><li>Annual temperature 2050 </li></ul><ul><ul><li>temperature increases by 2.3°C...
Results of analysis: Regional changes <ul><li>The maximum temperature of the year increases from 28.6°C to 31.2°C in 2050 ...
Results of analysis: Regional changes <ul><li>Current suitability of coffee </li></ul><ul><ul><li>according to the MAXENT ...
Results of analysis: Regional changes <ul><li>Coffee suitability in 2020 </li></ul><ul><ul><li>in general decreases </li><...
Results of analysis: Regional changes <ul><li>Coffee suitability in 2050 </li></ul><ul><ul><li>in general decreases quite ...
Results of analysis: Regional changes <ul><li>Change of suitability in 2020 </li></ul>D
Results of analysis: Regional changes <ul><li>Change of suitability in 2050 </li></ul>D
Results of analysis: Relation of suitability & altitude <ul><li>Areas at higher altitudes become suitable for producing co...
Results of analysis: model agreement <ul><li>Measure of agreement of models predicting changes in the same direction as th...
Results of analysis: model agreement <ul><li>Mean coefficient of variance of bioclimatic variables </li></ul>D
Results of analysis: stepwise regression <ul><li>in general </li></ul><ul><ul><li>increasing temperature </li></ul></ul><u...
Results of analysis: site-specific changes <ul><li>Annual precipitation 2050 </li></ul>D
Results of analysis: site-specific changes <ul><li>Annual temperature 2050 </li></ul>D
Results of analysis: site-specific changes D Bungoma Embu Kericho Kiambu Kirinyaga Kisii  Machakos Meru Murang'a Nithi Nya...
Conclusions and recommendations <ul><li>Overall conclusions </li></ul><ul><ul><li>changes in suitability are site-specific...
Conclusions and recommendations <ul><li>Specific conclusions </li></ul><ul><ul><li>How will the climate in the project are...
Conclusions and recommendations <ul><li>Specific conclusions </li></ul><ul><ul><li>What impact will climate change have fo...
Conclusions and recommendations <ul><li>Specific conclusions </li></ul><ul><ul><li>What are the climatic factors that dete...
Conclusions and recommendations <ul><li>Recommendations </li></ul><ul><ul><li>It would be possible to make much more preci...
DAPA – Decision and Policy Analysis group of CIAT: A. Eitzinger, Dr. P.Laderach O. Ovalle, J. Ramírez and Dr. A. Jarvis Th...
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A Eitzinger - Climate Change Adaptation and Mitigation in the Kenyan Coffee Sector

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A Eitzinger - Climate Change Adaptation and Mitigation in the Kenyan Coffee Sector

  1. 1. Climate Change Adaptation and Mitigation in the Kenyan Coffee Sector
  2. 2. CIAT – International Center for Tropical Agriculture <ul><li>CIAT: Part of Consultative Group on International Agriculture Research </li></ul><ul><li>Mission: To reduce hunger and poverty, and improve human health in the tropics through research aimed at increasing the eco-efficiency of agriculture. </li></ul>DAPA: Decision and Policy Analysis What we do: Spatial Analysis, climate change, Impact analysis models. Project-Team: A. Eitzinger, Dr. Peter Laderach, O. Ovalle, J. Ramírez and Dr. A. Jarvis
  3. 3. Content <ul><li>A: Introductions </li></ul><ul><li>B: Research questions </li></ul><ul><li>C: Methods and data generation </li></ul><ul><li>D: Results of analysis in Kenya </li></ul><ul><ul><li>Regional changes </li></ul></ul><ul><ul><li>Site-specific changes </li></ul></ul><ul><li>E: Conclusions and recommendations </li></ul>
  4. 4. Introductions <ul><li>Study objectives: </li></ul><ul><li>Elaboration of future climate scenarios to indicate the impact of climate change on adaptability of coffee in Kenya which will be accessible and available for international and regional organizations such as the Coffee Research Foundation and the 4C Association. </li></ul>A Climate Change Adaptation and Mitigation in the Kenyan Coffee Sector
  5. 5. Research questions <ul><li>Where will coffee grow in the future? </li></ul><ul><li>Where will coffee not grow any more? </li></ul><ul><li>Where can coffee still grow with adapted mgt? </li></ul><ul><li>What are the decisive factors to manage? </li></ul>B Pics by Neil Palmer (CIAT)
  6. 6. Methods and data generation <ul><li>Historical climate generation </li></ul><ul><li>Future climate </li></ul><ul><li>Suitability prediction </li></ul>C
  7. 7. Historical climate generation <ul><li>WorldClim ( www.worldclim.org ) database (Hijmans et al, 2005) </li></ul><ul><li>Base line for climate change calculations </li></ul><ul><li>Meteorological Stations with data of: </li></ul><ul><li>Worldwide: </li></ul><ul><li>precipitation: 47,554 </li></ul><ul><li>Mean temp.: 24,542 </li></ul><ul><li>Min/max temp: 14,835 </li></ul><ul><li>For Kenya: </li></ul><ul><li>Precipitation: 736 </li></ul><ul><li>Mean temp.: 708 </li></ul><ul><li>Min/max temp: 61 </li></ul>C
  8. 8. Future climate <ul><li>Global circulation models (GCM) </li></ul><ul><li>Calibrated in the past (using time-series), and projected to the future </li></ul><ul><li>Intergovernmental Panel on Climate Change - IPCC ( http://www.ipcc.ch/ ) </li></ul><ul><li>Fourth Assessment Report, based on the results of 21 global climate models (GCMs) </li></ul>C <ul><li>Generation of future climate </li></ul><ul><li>Downscaling to provide higher-resolution surfaces if the likely impacts of climate change on agriculture are to be forecast </li></ul>
  9. 9. Global circulation models (GCM) <ul><li>20 models (different institutions) </li></ul>C
  10. 10. bioclimatic variables <ul><li>Bio1 = Annual mean temperature </li></ul><ul><li>Bio2 = Mean diurnal range (Mean of monthly (max temp - min temp)) </li></ul><ul><li>Bio3 = Isothermality (Bio2/Bio7) (* 100) </li></ul><ul><li>Bio4 = Temperature seasonality (standard deviation *100) </li></ul><ul><li>Bio5 = Maximum temperature of warmest month </li></ul><ul><li>Bio6 = Minimum temperature of coldest month </li></ul><ul><li>Bio7 = Temperature Annual Range (Bio5 – Bi06) </li></ul><ul><li>Bio8 = Mean Temperature of Wettest Quarter </li></ul><ul><li>Bio9 = Mean Temperature of Driest Quarter </li></ul><ul><li>Bio10 = Mean Temperature of Warmest Quarter </li></ul><ul><li>Bio11 = Mean Temperature of Coldest Quarter </li></ul><ul><li>Bio12 = Annual Precipitation </li></ul><ul><li>Bio13 = Precipitation of Wettest Month </li></ul><ul><li>Bio14 = Precipitation of Driest Month </li></ul><ul><li>Bio15 = Precipitation Seasonality (Coefficient of Variation) </li></ul><ul><li>Bio16 = Precipitation of Wettest Quarter </li></ul><ul><li>Bio17 = Precipitation of Driest Quarter </li></ul><ul><li>Bio18 = Precipitation of Warmest Quarter </li></ul><ul><li>Bio19 = Precipitation of Coldest Quarter </li></ul>C
  11. 11. Generation of future climate <ul><li>Current climate from worldclim (1km resolution) </li></ul><ul><ul><li>Prec, temp min/mean/max </li></ul></ul><ul><li>Future climate </li></ul><ul><ul><li>Calculate anomaly (future – current) </li></ul></ul><ul><ul><li>Downscale (spline interpolation) </li></ul></ul><ul><ul><li>Add to current climate (worldclim) </li></ul></ul><ul><ul><li>Calculate 19 bioclimatic variables </li></ul></ul>C Current climate + Climate-Change = Future climate
  12. 12. Suitability prediction <ul><li>finding the probability distribution of maximum entropy (MAXENT) </li></ul>C MAXENT is generally considered to be the most accurate model (Elith et al. 2006) and was selected for the analyses of the present study after an initial iteration of analysis in the study region using all four models. Current climate Future climate Relation Projection Evidence data of coffee crops today Prediction of Future evidence of Coffee crops 19 bioclim variables Key of investigation
  13. 13. Methodology – the process <ul><li>Compilation of evidence data. </li></ul><ul><li>Generation of future climates. </li></ul><ul><li>MaxEnt: Future suitability predictions for each model </li></ul><ul><ul><li>3 measurements of uncertainty to exclude outliers: </li></ul></ul><ul><ul><ul><li>agreement among models as percentage of models predicting changes in the same direction </li></ul></ul></ul><ul><ul><ul><li>mean suitability: upper and lower 95% confidence intervals (C.I.) </li></ul></ul></ul><ul><ul><ul><li>the coefficient of variation (CV) among models. </li></ul></ul></ul><ul><ul><li>Final run with confirming models </li></ul></ul><ul><li>Prediction of future coffee distribution. </li></ul><ul><li>Identification of decisive growth factors. </li></ul><ul><ul><li>Stepwise regression of suitability-shift per data point </li></ul></ul>C
  14. 14. Results of analysis: Regional changes <ul><li>Evidence data: </li></ul><ul><li>805 Arabica coffee farms in Kenya </li></ul><ul><li>collected using GPS </li></ul><ul><li>161 collected by desk studies </li></ul>D
  15. 15. Results of analysis: Regional changes <ul><li>Annual precipitation 2020 </li></ul><ul><ul><li>rainfall increases from 1405 millimeters to 1435 (+30) </li></ul></ul><ul><ul><li>The maximum number of cumulative dry months keeps constant in 4 months </li></ul></ul>D
  16. 16. Results of analysis: Regional changes <ul><li>Annual precipitation 2050 </li></ul><ul><ul><li>rainfall increases from 1405 millimeters to 1575 (+ 170) </li></ul></ul><ul><ul><li>The maximum number of cumulative dry months keeps constant in 4 months </li></ul></ul>D
  17. 17. Results of analysis: Regional changes <ul><li>Annual temperature 2020 </li></ul><ul><ul><li>temperature increases by 1°C </li></ul></ul>D
  18. 18. Results of analysis: Regional changes <ul><li>Annual temperature 2050 </li></ul><ul><ul><li>temperature increases by 2.3°C </li></ul></ul><ul><ul><li>temperature range increases from 15.6 °C to 15.9 °C </li></ul></ul>D
  19. 19. Results of analysis: Regional changes <ul><li>The maximum temperature of the year increases from 28.6°C to 31.2°C in 2050 </li></ul><ul><li>The minimum temperature of the year increases from 9.8°C to 12.0°C in 2050 </li></ul><ul><li>The wettest month gets wetter with 330 millimeters instead of 305 millimeters in 2050 </li></ul><ul><li>The driest month keeps constant with 30 millimeters in 2050 </li></ul>D
  20. 20. Results of analysis: Regional changes <ul><li>Current suitability of coffee </li></ul><ul><ul><li>according to the MAXENT model, the most suitable of them are concentrated in the higher areas of: Bungoma, Embu, Kericho, Kiambu, Kirinyaga, Kisii, Machakos, Meru, Muranga, Nithi, Nyamira, Nyeri and Trans-Nzoia. </li></ul></ul>D
  21. 21. Results of analysis: Regional changes <ul><li>Coffee suitability in 2020 </li></ul><ul><ul><li>in general decreases </li></ul></ul><ul><ul><li>go up higher </li></ul></ul>D
  22. 22. Results of analysis: Regional changes <ul><li>Coffee suitability in 2050 </li></ul><ul><ul><li>in general decreases quite seriously </li></ul></ul><ul><ul><li>decreases to between 30 and 50% today 60 - 80%! </li></ul></ul><ul><ul><li>go up higher </li></ul></ul><ul><ul><li>gaining suitability (20 – 30% by 2050) in: </li></ul></ul><ul><ul><li>Rift valley </li></ul></ul>D
  23. 23. Results of analysis: Regional changes <ul><li>Change of suitability in 2020 </li></ul>D
  24. 24. Results of analysis: Regional changes <ul><li>Change of suitability in 2050 </li></ul>D
  25. 25. Results of analysis: Relation of suitability & altitude <ul><li>Areas at higher altitudes become suitable for producing coffee: </li></ul><ul><li>Optimum coffee-producing zone: </li></ul><ul><ul><li>current between 1400 and 1600 masl </li></ul></ul><ul><ul><li>between 1600 and 1800 masl at 2050 </li></ul></ul><ul><ul><li>altitudes around 1200 masl will suffer the highest decrease </li></ul></ul><ul><ul><li>areas around 2000 masl the highest increase in suitability </li></ul></ul>D
  26. 26. Results of analysis: model agreement <ul><li>Measure of agreement of models predicting changes in the same direction as the average of all models at a given location </li></ul>D
  27. 27. Results of analysis: model agreement <ul><li>Mean coefficient of variance of bioclimatic variables </li></ul>D
  28. 28. Results of analysis: stepwise regression <ul><li>in general </li></ul><ul><ul><li>increasing temperature </li></ul></ul><ul><ul><li>increase of rainfall </li></ul></ul><ul><li>as drivers of the predicted negative suitability shifts </li></ul>D
  29. 29. Results of analysis: site-specific changes <ul><li>Annual precipitation 2050 </li></ul>D
  30. 30. Results of analysis: site-specific changes <ul><li>Annual temperature 2050 </li></ul>D
  31. 31. Results of analysis: site-specific changes D Bungoma Embu Kericho Kiambu Kirinyaga Kisii Machakos Meru Murang'a Nithi Nyamira Nyeri Trans-Nzoia
  32. 32. Conclusions and recommendations <ul><li>Overall conclusions </li></ul><ul><ul><li>changes in suitability are site-specific </li></ul></ul><ul><ul><li>solution is site-specific management </li></ul></ul><ul><ul><li>there will be differnt sites: </li></ul></ul><ul><ul><ul><li>become unsuitable to grow coffee  farmers will need to identify alternative crops </li></ul></ul></ul><ul><ul><ul><li>remain suitable, but  agronomic management need to adapt to changed conditions </li></ul></ul></ul><ul><ul><ul><li>in future will become suitable for coffee  need strategic investments to develop coffee production </li></ul></ul></ul><ul><ul><li>climate change will bring not only bad news but also a lot of new potential. </li></ul></ul><ul><ul><li>the winners will be those who are prepared for change and know how to adapt. </li></ul></ul>E
  33. 33. Conclusions and recommendations <ul><li>Specific conclusions </li></ul><ul><ul><li>How will the climate in the project area change by the year 2050? </li></ul></ul><ul><ul><ul><li>yearly/monthly rainfall will increase progressively by 2050 </li></ul></ul></ul><ul><ul><ul><li>yearly/monthly minimum and maximum temperatures will increase progressively by 2050 </li></ul></ul></ul><ul><ul><ul><li>overall climate will become less seasonal in temperature/precipitation </li></ul></ul></ul><ul><ul><ul><li>maximum number of cumulative dry month will stay constant at 4 months </li></ul></ul></ul><ul><ul><ul><li>precipitation for specific districts will increase by 135 to 205 mm by 2050 </li></ul></ul></ul><ul><ul><ul><li>temperatures for specific districts increase by 2050 between 2.2 and 2.4 °C </li></ul></ul></ul>E
  34. 34. Conclusions and recommendations <ul><li>Specific conclusions </li></ul><ul><ul><li>What impact will climate change have for suitability of coffee and how will coffee areas change? </li></ul></ul><ul><ul><ul><li>by 2050 suitability of 13 municipalities in general decreases quite seriously </li></ul></ul></ul><ul><ul><ul><li>areas that still are suitable decreases to between 30 and 60% (today 50-70%) </li></ul></ul></ul><ul><ul><ul><li>optimum coffee-producing zone in 2050 increases to 1700 masl (today 1600 - compensates for the increase in temperature) </li></ul></ul></ul><ul><ul><ul><li>areas around 1300 masl will suffer the highest decrease in 2050 </li></ul></ul></ul><ul><ul><ul><li>areas around 2200 masl the highest increase in suitability </li></ul></ul></ul>E
  35. 35. Conclusions and recommendations <ul><li>Specific conclusions </li></ul><ul><ul><li>What are the climatic factors that determine the suitability for coffee? </li></ul></ul><ul><ul><ul><li>by 2050, decrease of precipitation of driest month and increase of minimum temperature of the coldest month are main negative factors driving suitability together with increasing precipitation of the coldest quarter </li></ul></ul></ul><ul><ul><ul><li>the positive suitability shifts at the highest altitudes of the present growth range of coffee, on the other hand, were mostly driven by increasing temperatures </li></ul></ul></ul>E
  36. 36. Conclusions and recommendations <ul><li>Recommendations </li></ul><ul><ul><li>It would be possible to make much more precise predictions by using expert knowledge to refine the results presented here. </li></ul></ul><ul><ul><li>Local experts and community need to be made aware of the results of this study and the likely effects on livelihoods </li></ul></ul><ul><ul><li>Road maps for each specific areas should be defined, e.g.: </li></ul></ul><ul><ul><ul><li>Identification of alternative crops </li></ul></ul></ul><ul><ul><ul><li>Adaptation of agronomic management such as shade, varieties, irrigation, etc. </li></ul></ul></ul><ul><ul><ul><li>Strategic planning for areas with new potential for coffee production. </li></ul></ul></ul>E
  37. 37. DAPA – Decision and Policy Analysis group of CIAT: A. Eitzinger, Dr. P.Laderach O. Ovalle, J. Ramírez and Dr. A. Jarvis Thank you!
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