Pic by Neil Palmer (CIAT)
Assessing climate change impact in coffee systems
P Läderach, O Ovalle, A EitzingerPresented by Christian Bunn2nd Coffee & Climate Steering Committee Meeting July 2011
• Context• Methodologies + Results
i. Climate data• Precis• Downscaling• Climate Change in
Guatemala
ii. Crop suitability• Modeling Approaches• Brazilian Research• Guatemala Results
• Outlook
Outline
“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 Perceptions
Context Overall Approach
Global Climate Model (GCM) Outputs
Production and Quality Data
Socio Economic Information
Statistical Downscaling of
Climate Information
Crop Suitability and Niche Modeling
Vulnerability Analyses
Future Climatesat Local scale
Yield and Quality Impacts
Alternative Livelihood Strategies
DIRECT IMPACT
INDIRECT SENSITIVITYADAPTIVE CAPACITY
Inputs Process Output
ObjectivePredict 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 Coffee Under Pressure (CUP) Project
The socio-economic impact of climate change on Mesoamerican coffee productionContext General livelihood impacts in Nicaragua
Physical
Natural
HumanSocial
Financial
0
2
4
SensitivityAdaptive capacity
Highly variable yieldsDependency on coffee
Postharvest managementPest and disease issues
Migration
The socio-economic impact of climate change on Mesoamerican coffee productionContext 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.
Climate Change models
– Differences between regional climate scenarios– Overview of climatic change in Guatemala
Methodology Future Climate
Methodology Future Climate
Regional ClimateMethodology
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 ProjectionMethodology
2050
0
50
100
150
200
250
300
350
400
450
500
0
5
10
15
20
25
30
Precipitation(mm)
Temperature (ºC)
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
- - -
-
- -
-
+
+
-+
-
current
2020
2050
Crop models
– Introduction to crop prediction models– Differences between models– First results for Guatemala
Crop ModelingMethodology
• Statistical Regression Models• Agro-Ecological Zoning• Mechanistic Environmental Niche Models
– Ecocrop• Correlational Environmental Niche Models
– MaxEnt– CaNaSTA
• Process Model– Caf2007
Crop ModelingMethodology
AEZ BrazilMethodology
(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.
What is the suitability of a crop to the climate?
Suitability to future climate(2050) – Current suitability = Change in suitability
Current SuitabilityFuture Suitability 2050Change in Suitability to Future Climate (2050)
Temperature
Prec
ipita
tion
Calibration with optimal points• Samples (GPS points)• Altitude range• Current Production Areas• Soil types
CalibratedTemperature and
PrecipitaciónRanges!
Ecocrop Database (FAO)(Food and Agriculture Organization of the UN)
Ranges: Temperature and precipitation
WorldClim Climate Data http://worldclim.orgMore than 47,000 stations worldwide
Crop Prediction ModelsMethodology
Ecocrop Results GuatemalaMethodology
Maxent - Points of PresenceMethodology
• Maxent– Machine
Learning Algorithm
– Principle of Maximum Entropy
– Uses monthly data
– Very accurate
Maxent Results Guatemala - IMethodology
Maxent Results Guatemala - IIMethodology
Results Guatemala - IIIMethodology
400 800 1200 1600 2000 2400 28000.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0
50000
100000
150000
200000
250000
300000
350000
400000 current + Stdv av-erage 2050 - Stdv
Altitude (msnm)
Su
ita
bili
ty
Are
a (h
a)
Variable AdjustedR2
R2 due to variable
% of totalvariability
Present mean
Change by 2050s
Locations with decreasing suitability (n=89.8 % of all observations)BIO 14 – Precipitación del mes más seco 0.0817 0.0817 24.8 24.49 mm -3.27 mm
BIO 04 – Estacionalidad de temperatura 0.1776 0.0959 29.1 0.83 0.166BIO 12 – Precipitación anual 0.2057 0.0281 8.5 2462.35 mm -24.31 mmBIO 11 - Temperatura media del cuarto más frío 0.2633 0.0576 17.5 20.11 ºC 1.86 ºC
BIO 19 - Precipitación del cuarto más frío 0.2993 0.0155 4.7 169.13 mm -7.08 mm
BIO 05 - Temperatura máxima del mes más cálido 0.3198 0.0102 3.1 28.45 ºC 2.30 ºC
BIO 13 - Precipitación del mes más húmedo 0.2838 0.0205 6.2 450.27 mm 10.72 mm
Otros - - 6.2
Future workOutlook
Production is affected worldwide
Can we link impact models with trade models?
Future workOutlook
Process model- 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
Pic by Neil Palmer (CIAT)
Assessing climate change impact in coffee systems
Peter Läderach (CIAT)[email protected] Bunn (CIAT)[email protected]
P Läderach, O Ovalle, A EitzingerPresented by Christian Bunn2nd Coffee & Climate Steering Committee Meeting July 2011
Thank you!
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