P. Laderach. Coffee Under Pressure Cup Ciat Sfl Meeting
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Transcript of P. Laderach. Coffee Under Pressure Cup Ciat Sfl Meeting
Coffee Under Pressure (CUP)Sustainable Food Laboratory (SFL) Meeting
18 of March 2010, Monte de la Cruz, Costa Rica
Peter Laderach (CIAT)[email protected]
OUTLINE
- Objectives
- CIAT
- Partners
- Methodologies
- Results
- Work Plan
Coffee Under Pressure CUP
A: To predict the future suitability and distribution of coffee sourcing areas
E: To accompany farmer organizations and engage supply chain actors to design adequate scenarios
B: To evaluate potential impacts of cc on coffee quality and quantity
C: To identify alternative crops suitable under predicted climate change scenarios for key regions
D: To evaluate the implications of changes in coffee quality and quantity studies on social parameters (income, poverty and equity)
CIAT - International Centre for Tropical Agriculture
CIAT - International Centre for Tropical AgricultureCIAT: part of the Consultative Group on International
Agricultural Research CGIAR
Mission: Reduce hunger and poverty in the tropic through scientific research leading to new technology and knowledge
DAPA: Decision and Policy Analysis
What we do: Spatial analysis, climate change modelling impact analysis …etc.
The Partners - Catholic Relief Services CRSCRS is the official relief and development agency of the
Catholic community in the United States
Beneficiaries: More than 7000 farmers in Mexico, El Salvador, Guatemala and Nicaragua.
CAFE Livelihoods: Improve livelihoods of farmers in Mexico, El Salvador, Guatemala and Nicaragua through improved coffee productivity, quality and marketing
The Partners - Cropster.org
Cropster is a web-based traceability, quality management and marketing platform
Cropster will make sure that the production, quality and farm data will be available for the entire supply chain and for research
Cropster will feed back information back to the supply chain to assure improved decision making and support adaptation strategies
Why do we know that the climate is changing?
Why do we know that the climate is changing?
The Facts
METHODOLOGY - Objective A
A: Predict the future suitability and distribution of coffee sourcing areas
METHODOLOGY - Objective A
WorldClim (Hijmans et al, 2005)
Climate (Current)
METHODOLOGY - Objective A
WorldClim (Hijmans et al, 2005)
Climate (Current)
METHODOLOGY - Objective AClimate (Future)
• “Global climate models” (GCMs) based on atmospheric science, chemistry, physics and biology
• Runs from the past (to calibrate) and into the future
• Uses different gas emissions scenarios
METHODOLOGY - Objective AClimate (Future)
Originating Group(s) Country MODEL ID OUR ID GRID Year Bjerknes Centre for Climate Research Norway BCCR-BCM2.0 BCCR_BCM2 128x64 2050
CGCM2.0 CCCMA_CGCM2 96x48 2020 +
2050 CGCM3.1(T47) CCCMA_CGCM3_1 96x48 2050
Canadian Centre for Climate Modelling & Analysis
Canada CGCM3.1(T63) CCCMA_CGCM3_1_T63 128x64
2050 Météo-France Centre National de Recherches Météorologiques
France CNRM-CM3 CNRM_CM3 128x64 2050
Australia CSIRO-MK2.0 CSIRO_MK2 64x32 2020 CSIRO Atmospheric Research Australia CSIRO-Mk3.0 CSIRO_MK3 192x96 2050
Max Planck Institute for Meteorology Germany
ECHAM5/MPI-OM
MPI_ECHAM5 N/A 2050
Meteorological Institute of the University of Bonn Meteorological Research Institute of KMA
Germany Korea
ECHO-G MIUB_ECHO_G 96x48 2050
LASG / Institute of Atmospheric Physics China FGOALS-g1.0 IAP_FGOALS_1_0_G 128x60 2050 US Dept. of Commerce, NOAA Geophysical Fluid Dynamics Laboratory
USA GFDL-CM2.0 GFDL_CM2_0 144x90 2050
US Dept. of Commerce NOAA Geophysical Fluid Dynamics Laboratory
USA GFDL-CM2.0 GFDL_CM2_1 144x90 2050
NASA / Goddard Institute for Space Studies USA GISS-AOM GISS_AOM 90x60 2050 Institut Pierre Simon Laplace France IPSL-CM4 IPSL_CM4 96x72 2050
MIROC3.2(hires) MIROC3_2_HIRES 320x160 2050 Center for Climate System Research National Institute for Environmental Studies Frontier Research Center for Global Change (JAMSTEC)
Japan Japan
MIROC3.2(medres)
MIROC3_2_MEDRES
128x64
2050
Meteorological Research Institute Japan MRI-CGCM2.3.2 MRI_CGCM2_3_2a N/A 2050 National Center for Atmospheric Research USA PCM NCAR_PCM1 128x64 2050 Hadley Centre for Climate Prediction and Research Met Office
UK UKMO-HadCM3 HCCPR_HADCM3 96x73
2020 + 2050
Center for Climate System Research (CCSR) National Institute for Environmental Studies (NIES)
Japan NIES-99 NIES-99 64x32
2020
METHODOLOGY - Objective AVariables
Bio1 = Annual mean temperature Bio2 = Mean diurnal range (Mean of monthly (max temp - min temp)) Bio3 = Isothermality (Bio2/Bio7) (* 100) Bio4 = Temperature seasonality (standard deviation *100) Bio5 = Maximum temperature of warmest month Bio6 = Minimum temperature of coldest month Bio7 = Temperature Annual Range (Bio5 – Bi06) Bio8 = Mean Temperature of Wettest Quarter Bio9 = Mean Temperature of Driest Quarter Bio10 = Mean Temperature of Warmest Quarter Bio11 = Mean Temperature of Coldest Quarter Bio12 = Annual Precipitation Bio13 = Precipitation of Wettest Month Bio14 = Precipitation of Driest Month Bio15 = Precipitation Seasonality (Coefficient of Var iation) Bio16 = Precipitation of Wettest Quarter Bio17 = Precipitation of Driest Quarter Bio18 = Precipitation of Warmest Quarter Bio19 = Precipitation of Coldest Quarter
METHODOLOGY - Objective A
Current Climate
19 bioclimatic variables (WorldClim)
Climate Change
Downscaling: Spline interpolation (same as used in WorldClim)
Generation of 19 bioclimatic variables
Future Climate
Current Climate + Change = Future Climate
RESULTS - Objective A
A: Predict the future suitability and distribution of GMCR coffee sourcing areas
RESULTS - Objective A
RESULTS - Objective A
RESULTS - Objective AAverage climate change in Nicaragua
2020 2050
Average temperature change + 1,1 °C + 2,4 °C
Change in precipitation - 90 mm - 120 mm
RESULTS - Objective ASuitability change by 2050
RESULTS - Objective ASuitability versus altitude
METHODOLOGY - Objective B
A: Predict the future suitability and distribution of scoffee sourcing areas
B: Evaluate potential impacts of cc on coffee quality and quantity
METHODOLOGY - Objective BCropster.org
METHODOLOGY - Objective BCropster.org
RESULTS - Objective BCrop prediction models
METHODOLOGY - Objective C
A: Predict the future suitability and distribution of coffee sourcing areas
B: Evaluate potential impacts of cc on coffee quality and quantity
C: Identify alternative crops suitable under predicted climate change scenarios for key regions
METHODOLOGY- Objective C30 most important crop
Área sembrada
(Ha)
219584Mangifera indica L.Mango15
9175222Zea mays L. s. maysMaíz14
16756Lactuca sativa var. capitata L.Lechuga13
---Andropogon gayanus KunthGamba12
2119650Phaseolus vulgaris L.Frijol11
23001Brassica oleraceae var. BotrytisColiflor10
59574Allium cepa L. v cepaCebollas9
1287388Saccharum officinarum L.Caña de Azúcar8
82592Theobroma cacao L. Cacao7
---Brachiaria mutica Stapf.Brachiaria6
207175Musa acuminata Colla.Banano5
321764Oriza sativa L. s. japonicaArroz4
113414Gossypium hirsutum L.Algodón3
19065Agave sisalana \ americanaAgaves Otras2
189804Elaeis guineensis Jacq.Palma1
Nombre científicoCultivoNÁrea
sembrada (Ha)
Nombre CientíficoCultivosN
83054Arachis hypogaea L.Maní16
422754citrus Sinensis (L.) OsbeckNaranjas17
199595Cocos nucifera L. Coco18
90850Solanum tuberosum L.Batata19
26528Carica papaya L.Papaya20
66614Ananas comosusPiña21
57872Musa balbisiana CollaPlatano22
---Brassica oleraceae L.v capi.Repollo23
104700Sesamum indicum L.Sesamo24
78726Glycine max Soja25
2026824Sorghum bicolor L. MoenchSorgo26
24713Nicotiana tabacum L. Tabaco27
130812Lycopersicon esculentum M. Tomates28
38322Manihot sculenta Crantz.Yuca29
17073Daucus carota L.Zanahoria 30
RESULTS - Objective CSuitability change in crops
RESULTS - Objective CNumber of crops that loose out
RESULTS - Objective CNumber of crops that win
RESULTS - Objective CCombination of crops and coffee
METHODOLOGY - Objetive D
A: Predict the future suitability and distribution of coffee sourcing areas
B: Evaluate potential impacts of cc on coffee quality and quantity
C: Identify alternative crops suitable under predicted climate change scenarios for key regions
D: Evaluate the implications of changes in coffee quality and quantity case studies on social parameters (income, poverty and equity)
METHODOLOGY - Objetive D
METHODOLOGY - Objetive D
Nº Productores Municipio
Actual Futuro Cambio
AMATENANGO DE LA FRA. 3696 3950 254
MOTOZINTLA 5317 7417 2100
SILTEPEC 6035 478 -5557
TOTALES 21226 11845 -3203
Jornales
Municipio Actual Futuro Cambio
AMATENANGO DE LA FRA. 562763.9 601506 38742.1
MOTOZINTLA 1315439 1834974 519535.2
SILTEPEC 966061.1 76512.21 -889549
TOTALES 3848082 2512992 -331272
Producción QQ Municipio
Actual Futuro Cambio
AMATENANGO DE LA FRA. 38315.84 40953.6 2637.76
MOTOZINTLA 89561.8 124934.4 35372.6
SILTEPEC 65774.37 5209.342 -60565
TOTALES 261997.1 171097.3 -22554.7
METHODOLOGY - Objective E
A: Predict the future suitability and distribution of coffee sourcing areas
E: Accompany farmer organizations and engage supply chain actors to design adequate scenarios
B: Evaluate potential impacts of cc on coffee quality and quantity
C: Identify alternative crops suitable under predicted climate change scenarios for key regions
D: Evaluate the implications of changes in coffee quality and quantity in case studies on social parameters (income, poverty and equity)
Los colores muestran:Precipitación promedio anual
Cruz Alejandro GomezLa Maravilla | ID: NIC_024Matagalpa, Nicaragua
Factores ambientales:Precipitación promedio anual: 1.900mm
Los colores muestran:Cambio de la Adaptabilidad (%) para el año 2050
Cruz Alejandro GomezLa Maravilla | ID: NIC_024Matagalpa, Nicaragua
Factores ambientales:Cambio Adaptabilidad año 2050:-37%
Los colores muestran:Cambio de la Adaptabilidad (%) para el año 2050
Cruz Alejandro GomezLa Maravilla | ID: NIC_024Matagalpa, NicaraguaFactores ambientales:Cambio Adaptabilidad año 2050:-37%Cultivos alternativos (Adaptabilidad):1.Cacao 70%2.Frijol 56%3.Papa 34%
Coffee Under Pressure CUP
A: To predict the future suitability and distribution of coffee sourcing areas - 2009 -2011
E: To accompany farmer organizations and engage supply chain actors to design adequate scenarios - 2012 - 2014
B: To evaluate potential impacts of cc on coffee quality and quantity - 2010 - 2011
C: To identify alternative crops suitable under predicted climate change scenarios for key regions - 2010 - 2012
D: To evaluate the implications of changes in coffee quality and quantity in studies on social parameters (income, poverty and equity) - 2010 - 2013
¡Muchas gracias!
Peter Laderach (CIAT)[email protected]