Assessing climate change impact in coffee systems<br />P Läderach, O Ovalle, A Eitzinger<br />Presented by Christian Bunn<...
<ul><li>Context
Methodologies + Results</li></ul>Climate data		<br /><ul><li>Precis
Downscaling
Climate Change in Guatemala</li></ul>Crop suitability<br /><ul><li>Modeling Approaches
Brazilian Research
Guatemala Results
Outlook</li></ul>Outline<br />
Context<br />Perceptions<br />“The climate has become inpredictable it rains less and very irregularly, my yield has decre...
Context<br />Overall Approach<br />Output<br />Process<br />Inputs<br />Statistical Downscaling  of Climate Information<br...
Context<br />Coffee Under Pressure (CUP) Project<br />Objective<br />Predict the impact of climate change on coffee produc...
El Salvador (GMCR)
Guatemala (GMCR)
Nicaragua (GMCR)</li></ul>Method partially implemented<br /><ul><li>Peru (AdapCC, GTZ)
Kenya (AdapCC, GTZ)</li></li></ul><li>Context<br />General livelihood impacts in Nicaragua<br />Highly variable yields<br ...
Context<br />Specific vulnerability profiles of farmers in Nicaragua<br />Matagalpa is characterized by high exposure (cof...
Methodology<br />Future Climate<br />Climate Change models<br />Differences between regional climate scenarios<br />Overvi...
Methodology<br />Future Climate<br />
Regional Climate<br />Methodology<br />Downscaling<br /><ul><li>Climatic changes only relevant at global scale
At regional scale relationships between variables are constant
Detailled and Quick and All GCMs</li></ul>Regional Climate Models<br /><ul><li>Full Climate Model with detailled information
25km grid
Few GCMs and computing time intensive</li></li></ul><li>Guatemala Climate Projection<br />Methodology<br />-<br />+<br />2...
Crop Modeling<br />Methodology<br />Crop models<br />Introduction to crop prediction models<br />Differences between model...
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Coffee Climate Initiative Hamburg Meeting

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In this presentation we report progress on a climate change impact assessment in Guatemala and a comparison of our methodology with alternatives for coffee to the steering comittee of the Coffee and Climate Initiative. http://www.coffeeandclimate.org/

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  • Explanation is needed as to what we see here.This is the summary of the livelihoods analysis for the entire country.Change to same format at previous graphs and text.Has been done
  • See previous mapWhat does this map add? Local scale variability?See previous slide.
  • Coffee Climate Initiative Hamburg Meeting

    1. Assessing climate change impact in coffee systems<br />P Läderach, O Ovalle, A Eitzinger<br />Presented by Christian Bunn<br />2nd Coffee & Climate Steering Committee Meeting July 2011<br />
    2. <ul><li>Context
    3. Methodologies + Results</li></ul>Climate data <br /><ul><li>Precis
    4. Downscaling
    5. Climate Change in Guatemala</li></ul>Crop suitability<br /><ul><li>Modeling Approaches
    6. Brazilian Research
    7. Guatemala Results
    8. Outlook</li></ul>Outline<br />
    9. Context<br />Perceptions<br />“The climate has become inpredictable it rains less and very irregularly, my yield has decreased and I have more pest and disease problems.”<br />Don Pedro, Nicaragua, Madriz, January, 2010<br />
    10. Context<br />Overall Approach<br />Output<br />Process<br />Inputs<br />Statistical Downscaling of Climate Information<br />Future Climates<br />at Local scale<br />Global Climate Model (GCM) Outputs<br />Crop Suitability and Niche Modeling<br />Yield and Quality Impacts<br />Production and Quality Data<br />DIRECT IMPACT<br />Vulnerability Analyses<br />Socio Economic Information<br />ADAPTIVE CAPACITY<br />Alternative Livelihood Strategies<br />INDIRECT SENSITIVITY<br />
    11. Context<br />Coffee Under Pressure (CUP) Project<br />Objective<br />Predict the impact of climate change on coffee production and farmers livelihoods and develop chain inclusive adaptation strategies<br />Beneficiaries (7000 farmers) <br /><ul><li>Mexico (GMCR)
    12. El Salvador (GMCR)
    13. Guatemala (GMCR)
    14. Nicaragua (GMCR)</li></ul>Method partially implemented<br /><ul><li>Peru (AdapCC, GTZ)
    15. Kenya (AdapCC, GTZ)</li></li></ul><li>Context<br />General livelihood impacts in Nicaragua<br />Highly variable yields<br />Dependency on coffee<br />Postharvest management<br />Pest and disease issues<br />Migration<br />
    16. Context<br />Specific vulnerability profiles of farmers in Nicaragua<br />Matagalpa is characterized by high exposure (coffee suitability decreases drastically) high sensitivity (high variability in yields) and low adaptive capacity (poor access to credit, poor knowledge on pest and disease management and low diversification). <br />The adaptation strategy focuses on diversification, capacity building, strengthening of the organizations and on the enforcement of environmental laws and development policies for the coffee sector.<br />
    17. Methodology<br />Future Climate<br />Climate Change models<br />Differences between regional climate scenarios<br />Overview of climatic change in Guatemala<br />
    18. Methodology<br />Future Climate<br />
    19. Regional Climate<br />Methodology<br />Downscaling<br /><ul><li>Climatic changes only relevant at global scale
    20. At regional scale relationships between variables are constant
    21. Detailled and Quick and All GCMs</li></ul>Regional Climate Models<br /><ul><li>Full Climate Model with detailled information
    22. 25km grid
    23. Few GCMs and computing time intensive</li></li></ul><li>Guatemala Climate Projection<br />Methodology<br />-<br />+<br />2050<br />2020<br />-<br />+<br />-<br />current<br />-<br />+<br />-<br />-<br />-<br />-<br />-<br />
    24. Crop Modeling<br />Methodology<br />Crop models<br />Introduction to crop prediction models<br />Differences between models<br />First results for Guatemala<br />
    25. Crop Modeling<br />Methodology<br />Statistical Regression Models<br />Agro-Ecological Zoning<br />Mechanistic Environmental Niche Models<br />Ecocrop<br />Correlational Environmental Niche Models<br />MaxEnt<br />CaNaSTA<br />Process Model<br />Caf2007<br />
    26. AEZ Brazil<br />Methodology<br />(i) an annual water deficit of 0 to 100mm, (ii) average annual temperature between 18°C and 22°C, and a frost risk of less than 25%. Areas with annual temperature means between 22°C and 23°C and a water deficit up to 150mm are considered suboptimal.<br />
    27. Crop Prediction Models<br />Methodology<br />What is the suitability of a crop to the climate?<br />Suitability to future climate(2050) – Current suitability = Change in suitability <br />Current Suitability<br />Future Suitability 2050<br />Change in Suitability to Future Climate (2050)<br />Ecocrop Database (FAO)<br />(Food and Agriculture Organization of the UN)<br />Ranges: Temperature and precipitation<br />Precipitation<br /> Calibration with optimal points<br /><ul><li> Samples (GPS points)
    28. Altitude range
    29. Current Production Areas
    30. Soil types</li></ul>Calibrated<br />Temperature and<br />Precipitación<br />Ranges!<br />WorldClim Climate Data <br />http://worldclim.org<br />More than 47,000 stations worldwide<br />Temperature<br />
    31. Ecocrop Results Guatemala<br />Methodology<br />
    32. Maxent - Points of Presence<br />Methodology<br />Maxent<br />Machine Learning Algorithm<br />Principle of Maximum Entropy<br />Uses monthly data<br />Very accurate<br />
    33. Maxent Results Guatemala - I<br />Methodology<br />
    34. Maxent Results Guatemala - II<br />Methodology<br />
    35. Results Guatemala - III<br />Methodology<br />
    36. Future work<br />Outlook<br />Production is affected worldwide<br />Can we link impact models with trade models?<br />
    37. Future work<br />Outlook<br />Processmodel- Caf2007<br /><ul><li>Daily time step data by MarkSim. </li></ul>Process Crop Yield Models can be used to simulate adaptation options<br /><ul><li> O. Ovalle is improving the implemention of CAF2007
    38. Cost Benefit Analysis of adaptation is a key objective</li></li></ul><li>Results need to be seen within the context of their methodology<br />Crop prediction modeling yields results with good confidence<br />Guatemala will see drastic changes in some of their most important coffee growing regions<br />Possibly this is associated with increasing lack of precipitation<br />Additional research is needed <br />Conclusions <br />
    39. Assessing climate change impact in coffee systems<br />P Läderach, O Ovalle, A Eitzinger<br />Presented by Christian Bunn<br />2nd Coffee & Climate Steering Committee Meeting July 2011<br />Thank you!<br />Peter Läderach (CIAT)<br />p.laderach@cgiar.org<br />Christian Bunn (CIAT)<br />Christian.Bunn@gmail.com<br />

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