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Assessing climate change impact in coffee systems P LĂ€derach, O Ovalle, A Eitzinger Presented by Christian Bunn 2nd Coffee & Climate Steering Committee Meeting July 2011
[object Object]
Methodologies + ResultsClimate data		 ,[object Object]
Downscaling
Climate Change in GuatemalaCrop suitability ,[object Object]
Brazilian Research
Guatemala Results
OutlookOutline
Context Perceptions “The climate has become inpredictable it rains less and very irregularly, my yield has decreased and I have more pest and disease problems.” Don Pedro, Nicaragua, Madriz, January, 2010
Context Overall Approach Output Process Inputs Statistical Downscaling  of Climate Information Future Climates at Local scale Global Climate Model (GCM) Outputs Crop Suitability and Niche Modeling Yield and Quality Impacts Production and Quality Data DIRECT IMPACT Vulnerability Analyses Socio Economic Information ADAPTIVE CAPACITY Alternative Livelihood Strategies INDIRECT SENSITIVITY
Context Coffee Under Pressure (CUP) Project Objective Predict the impact of climate change on coffee production and farmers livelihoods and develop chain inclusive adaptation strategies Beneficiaries (7000 farmers)  ,[object Object]
El Salvador (GMCR)
Guatemala (GMCR)
Nicaragua (GMCR)Method partially implemented ,[object Object]
Kenya (AdapCC, GTZ),[object Object]
Context Specific vulnerability profiles of farmers in Nicaragua 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).  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.
Methodology Future Climate Climate Change models Differences between regional climate scenarios Overview of climatic change in Guatemala
Methodology Future Climate
Regional Climate Methodology Downscaling ,[object Object]
At regional scale relationships between variables are constant
Detailled and Quick and All GCMsRegional Climate Models ,[object Object]
25km grid
Few GCMs and computing time intensive,[object Object]
Crop Modeling Methodology Crop models Introduction to crop prediction models Differences between models First results for Guatemala

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Coffee Climate Initiative Hamburg Meeting

  • 1. Assessing climate change impact in coffee systems P LĂ€derach, O Ovalle, A Eitzinger Presented by Christian Bunn 2nd Coffee & Climate Steering Committee Meeting July 2011
  • 2.
  • 3.
  • 5.
  • 9. Context Perceptions “The climate has become inpredictable it rains less and very irregularly, my yield has decreased and I have more pest and disease problems.” Don Pedro, Nicaragua, Madriz, January, 2010
  • 10. Context Overall Approach Output Process Inputs Statistical Downscaling of Climate Information Future Climates at Local scale Global Climate Model (GCM) Outputs Crop Suitability and Niche Modeling Yield and Quality Impacts Production and Quality Data DIRECT IMPACT Vulnerability Analyses Socio Economic Information ADAPTIVE CAPACITY Alternative Livelihood Strategies INDIRECT SENSITIVITY
  • 11.
  • 14.
  • 15.
  • 16. Context Specific vulnerability profiles of farmers in Nicaragua 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). 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.
  • 17. Methodology Future Climate Climate Change models Differences between regional climate scenarios Overview of climatic change in Guatemala
  • 19.
  • 20. At regional scale relationships between variables are constant
  • 21.
  • 23.
  • 24. Crop Modeling Methodology Crop models Introduction to crop prediction models Differences between models First results for Guatemala
  • 25. Crop Modeling Methodology Statistical Regression Models Agro-Ecological Zoning Mechanistic Environmental Niche Models Ecocrop Correlational Environmental Niche Models MaxEnt CaNaSTA Process Model Caf2007
  • 26. AEZ Brazil Methodology (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.
  • 27.
  • 30. Soil typesCalibrated Temperature and PrecipitaciĂłn Ranges! WorldClim Climate Data http://worldclim.org More than 47,000 stations worldwide Temperature
  • 32. Maxent - Points of Presence Methodology Maxent Machine Learning Algorithm Principle of Maximum Entropy Uses monthly data Very accurate
  • 33. Maxent Results Guatemala - I Methodology
  • 34. Maxent Results Guatemala - II Methodology
  • 35. Results Guatemala - III Methodology
  • 36. Future work Outlook Production is affected worldwide Can we link impact models with trade models?
  • 37.
  • 38.
  • 39. Assessing climate change impact in coffee systems P LĂ€derach, O Ovalle, A Eitzinger Presented by Christian Bunn 2nd Coffee & Climate Steering Committee Meeting July 2011 Thank you! Peter LĂ€derach (CIAT) p.laderach@cgiar.org Christian Bunn (CIAT) Christian.Bunn@gmail.com

Hinweis der Redaktion

  1. 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
  2. See previous mapWhat does this map add? Local scale variability?See previous slide.