Coffee Under Pressure (CUP)Sustainable Food Laboratory (SFL) Meeting

18 of March 2010, Monte de la Cruz, Costa Rica

Peter Laderach (CIAT)p.laderach@cgiar.org

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)p.laderach@cgiar.org