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Coffee Climate Initiative Hamburg Meeting
 

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 ...

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 Coffee Climate Initiative Hamburg Meeting Presentation Transcript

  • Assessing climate change impact in coffee systems
    P Läderach, O Ovalle, A Eitzinger
    Presented by Christian Bunn
    2nd Coffee & Climate Steering Committee Meeting July 2011
    • Context
    • Methodologies + Results
    Climate data
    • Precis
    • Downscaling
    • Climate Change in Guatemala
    Crop suitability
    • Modeling Approaches
    • Brazilian Research
    • Guatemala Results
    • Outlook
    Outline
  • 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)
    • Mexico (GMCR)
    • El Salvador (GMCR)
    • Guatemala (GMCR)
    • Nicaragua (GMCR)
    Method partially implemented
    • Peru (AdapCC, GTZ)
    • Kenya (AdapCC, GTZ)
  • Context
    General livelihood impacts in Nicaragua
    Highly variable yields
    Dependency on coffee
    Postharvest management
    Pest and disease issues
    Migration
  • 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
    • Climatic changes only relevant at global scale
    • At regional scale relationships between variables are constant
    • Detailled and Quick and All GCMs
    Regional Climate Models
    • Full Climate Model with detailled information
    • 25km grid
    • Few GCMs and computing time intensive
  • Guatemala Climate Projection
    Methodology
    -
    +
    2050
    2020
    -
    +
    -
    current
    -
    +
    -
    -
    -
    -
    -
  • Crop Modeling
    Methodology
    Crop models
    Introduction to crop prediction models
    Differences between models
    First results for Guatemala
  • Crop Modeling
    Methodology
    Statistical Regression Models
    Agro-Ecological Zoning
    Mechanistic Environmental Niche Models
    Ecocrop
    Correlational Environmental Niche Models
    MaxEnt
    CaNaSTA
    Process Model
    Caf2007
  • 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.
  • Crop Prediction Models
    Methodology
    What is the suitability of a crop to the climate?
    Suitability to future climate(2050) – Current suitability = Change in suitability
    Current Suitability
    Future Suitability 2050
    Change in Suitability to Future Climate (2050)
    Ecocrop Database (FAO)
    (Food and Agriculture Organization of the UN)
    Ranges: Temperature and precipitation
    Precipitation
    Calibration with optimal points
    • Samples (GPS points)
    • Altitude range
    • Current Production Areas
    • Soil types
    Calibrated
    Temperature and
    Precipitación
    Ranges!
    WorldClim Climate Data
    http://worldclim.org
    More than 47,000 stations worldwide
    Temperature
  • Ecocrop Results Guatemala
    Methodology
  • Maxent - Points of Presence
    Methodology
    Maxent
    Machine Learning Algorithm
    Principle of Maximum Entropy
    Uses monthly data
    Very accurate
  • Maxent Results Guatemala - I
    Methodology
  • Maxent Results Guatemala - II
    Methodology
  • Results Guatemala - III
    Methodology
  • Future work
    Outlook
    Production is affected worldwide
    Can we link impact models with trade models?
  • Future work
    Outlook
    Processmodel- Caf2007
    • Daily time step data by MarkSim.
    Process Crop Yield Models can be used to simulate adaptation options
    • O. Ovalle is improving the implemention of CAF2007
    • Cost Benefit Analysis of adaptation is a key objective
  • Results need to be seen within the context of their methodology
    Crop prediction modeling yields results with good confidence
    Guatemala will see drastic changes in some of their most important coffee growing regions
    Possibly this is associated with increasing lack of precipitation
    Additional research is needed
    Conclusions
  • Assessing climate change impact in coffee systems
    P Läderach, O Ovalle, A Eitzinger
    Presented by Christian Bunn
    2nd Coffee & Climate Steering Committee Meeting July 2011
    Thank you!
    Peter Läderach (CIAT)
    p.laderach@cgiar.org
    Christian Bunn (CIAT)
    Christian.Bunn@gmail.com