Climate change and cassava in Latin America

Andy Jarvis, Julian Ramirez, Emmanuel Zapata

Contents

• About climate change and predictive models

• Expected changes for Latin America

• Some implications for cassava

• Challenges ahead

Sources of Agricultural Greenhouse Gasesexcluding land use change Mt CO2-eq

Source: Cool farming: Climate impacts of agriculture and mitigation potential, Greenpeace, 07 January 2008

How can we be sure that it is changing?

Arctic Ice is Melting

In order to prepare, we need to know what to prepare for….

….but how?

Global Climate Models (GCMs)

• 21 global climate models in the world, based on atmospheric sciences, chemistry, biology, and a touch of astrology

• Run from the past to present to calibrate, then into the future

• Run using different emissions scenarios

So, what do they say?

Temperatures rise….

Changes in rainfall…

Trajectories and risks

0.0

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-600 -400 -200 0 200 400 600

Precipitation anomaly (mm)

Tem

pe

ratu

re a

no

ma

ly (

ºC)

Haiti Cuba MexicoCentral African Republic Venezuela Myanmar BurmaBurundi Japan VanuatuChina Colombia Costa RicaEcuador

1870Baseline

2099 Modelingtime-limit

2050 Modelingtime-limit

2020 Modelingtime-limit

CIAT’s Data

• 18 GCM models to 2050, 9 to 2020

• Different scenarios, A1b, B1, commit

• Downscaled using empirical methods

http://gisweb.ciat.cgiar.org/GCMPage/home.html

Britanicos

Canadienses

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23.5

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1870 1890 1910 1930 1950 1970 1990 2010 2030 2050 2070 2090Año

Tem

per

atu

ra m

edia

an

ual

(ºC

)

Temperatura media anual (ºC)

Tendencia temporal

Intervalo de confianza (95%)

2500

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2950

1870 1890 1910 1930 1950 1970 1990 2010 2030 2050 2070 2090

Año

Pre

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to

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mm

)

Precipitación total anual (mm)Tendencia temporalIntervalo de confianza (95%)

Colombia compared to the world

Colombia

650

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810

1870 1890 1910 1930 1950 1970 1990 2010 2030 2050 2070 2090

Año

Pre

cip

itac

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to

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mm

)

Precipitación total anual (mm)Tendencia temporalIntervalo de confianza (95%)

6.0

7.0

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12.0

1870 1890 1910 1930 1950 1970 1990 2010 2030 2050 2070 2090Año

Tem

per

atu

ra m

edia

an

ual

(ºC

)

Temperatura media anual (ºC)

Tendencia temporal

Intervalo de confianza (95%)

Mundo +4.5ºC+14%

+3.1ºC+8.1%

Region DepartamentoCambio en

Precipitacion

Cambio en Temperatura

media

Cambio en estacionalidad de

precipitacion

Cambio en meses

consecutivos secos

Incertidumbre entre modelos (StDev prec)

Amazonas Amazonas 12 2.9 1.4 0 135Amazonas Caqueta 138 2.7 -1.3 0 193Amazonas Guania 55 2.9 -3.2 0 271Amazonas Guaviare 72 2.8 -2.9 -1 209Amazonas Putumayo 117 2.6 0.6 0 170Andina Antioquia 18 2.1 1.3 0 129Andina Boyaca 50 2.7 -3.9 -1 144Andina Cundinamarca 152 2.6 -2.6 0 170Andina Huila 51 2.4 1.0 0 144Andina Norte de santander 73 2.8 -0.4 0 216Andina Santander 51 2.7 -2.4 0 158Andina Tolima 86 2.4 -3.1 0 148Caribe Atlantico -74 2.2 -2.9 2 135Caribe Bolivar 90 2.5 -1.8 0 242Caribe Cesar -119 2.6 -1.3 0 160Caribe Cordoba -11 2.3 -3.8 0 160Caribe Guajira -69 2.2 -1.8 0 86Caribe Magdalena -158 2.4 -1.8 0 153Caribe Sucre 10 2.4 -4.1 -1 207Eje Cafetero Caldas 252 2.4 -4.2 -1 174Eje Cafetero Quindio 153 2.3 -4.1 -1 145Eje Cafetero Risaralda 158 2.4 -3.5 -1 141Llanos Arauca -13 2.9 -6.4 -1 188Llanos Casanare 163 2.8 -5.7 -1 229Llanos Meta 10 2.7 -5.4 -1 180Llanos Vaupes 46 2.8 -1.4 0 192Llanos Vichada 59 2.6 -2.6 0 152Pacifico Choco -157 2.2 -1.2 0 148Sur Occidente Cauca 172 2.3 -1.6 0 168Sur Occidente Narino 155 2.2 -1.4 0 126Sur Occidente Valle del Cauca 275 2.3 -5.1 -1 166

Climate characteristic

Climate Seasonality

General climate change description

The maximum temperature of the year increases from 24.33 ºC to 25.09 ºC while the warmest quarter gets hotter by 0.77 ºC The minimum temperature of the year increases from 13.36 ºC to 14.14 ºC while the coldest quarter gets hotter by 0.74 ºC The wettest month gets wetter with 349.97 millimeters instead of 338.14 millimeters, while the wettest quarter gets wetter by 7.43 mm

The rainfall decreases from 2751.9 millimeters to 2741.06 millimetersTemperatures increase and the average increase is 0.77 ºC

Average Climate Change Trends of Risaralda

Temperature predictions were uniform between models and thus no outliers were detectedThe coefficient of variation of temperature predictions between models is 0.85%

The mean daily temperature range decreases from 9.98 ºC to 9.88 ºC

These results are based on the 2050 climate compared with the 1960-2000 climate. Future climate data is derived from 14 GCM models from the 3th (2001) and the 4th (2007) IPCC assessment, run under the A2a scenario (business as usual). Further information please check the website http://www.ipcc-data.org

The coefficient of variation of precipitation predictions between models is 5.67%

General climate

characteristics

Extreme conditions

Variability between models

Overall this climate becomes more seasonal in terms of variability through the year in temperature and more seasonal in precipitation

The driest month gets drier with 141.43 millimeters instead of 150.79 millimeters while the driest quarter gets drier by 15.73 mm

The maximum number of cumulative dry months increases from 0 months to 1 months

Precipitation predictions were uniform between models and thus no outliers were detected

0

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1 2 3 4 5 6 7 8 9 10 11 12Month

Pre

cip

itat

ion

(m

m)

0

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30

Tem

per

atu

re (

ºC)

Current precipitation

Future precipitation

Future mean temperature

Current mean temperature

Future maximum temperature

Current maximum temperature

Future minimum temperature

Current minimum temperature

Climate characteristic

Climate Seasonality

General climate change description

The maximum temperature of the year increases from 24.21 ºC to 27.37 ºC while the warmest quarter gets hotter by 2.45 ºC The minimum temperature of the year increases from 13.31 ºC to 15.06 ºC while the coldest quarter gets hotter by 2.05 ºC The wettest month gets wetter with 343.72 millimeters instead of 337.91 millimeters, while the wettest quarter gets wetter by 23.62 mm

The rainfall increases from 2753.76 millimeters to 2857.4 millimetersTemperatures increase and the average increase is 2.21 ºC

Precipitation predictions were uniform between models and thus no outliers were detected

Average Climate Change Trends of Risaralda

The coefficient of variation of temperature predictions between models is 4.27%

The maximum number of cumulative dry months keeps constant in 0 months

These results are based on the 2050 climate compared with the 1960-2000 climate. Future climate data is derived from 14 GCM models from the 3th (2001) and the 4th (2007) IPCC assessment, run under the A2a scenario (business as usual). Further information please check the website http://www.ipcc-data.org

The coefficient of variation of precipitation predictions between models is 5.09%

General climate

characteristics

Extreme conditions

Variability between models

Overall this climate becomes more seasonal in terms of variability through the year in temperature and less seasonal in precipitation

The driest month gets wetter with 154.32 millimeters instead of 150.3 millimeters while the driest quarter gets wetter by 33.43 mm

Temperature predictions were uniform between models and thus no outliers were detected

The mean daily temperature range increases from 9.91 ºC to 10.46 ºC

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1 2 3 4 5 6 7 8 9 10 11 12Month

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(m

m)

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ºC)

Current precipitation

Future precipitation

Future mean temperature

Current mean temperature

Future maximum temperature

Current maximum temperature

Future minimum temperature

Current minimum temperature

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(%

)

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%)

Precipitation Mean temperature Maximum temperature Minimum temperature

Site-specific monthly coefficient of variation using 18 GCM models (IPCC, 2007) for precipitation and temperature

Región PaísCambio en

Precipitación total (mm)

Cambio en Temperatura

media anual (°C)

Belize -144.951 2.190 2.866 0 7.560 3.204Bolivia -0.209 2.818 2.193 0 8.318 4.364Brazil 7.024 2.524 0.909 0 5.563 3.844Chile 34.353 2.335 6.955 1 46.694 5.600Colombia 59.364 2.364 -2.463 -1 5.780 3.484Costa Rica -66.537 2.082 -0.481 0 7.427 2.319Ecuador 114.114 2.094 -3.993 0 6.472 2.850El Salvador -60.796 2.302 -2.452 0 7.414 3.387French Guiana -126.417 2.508 4.306 0 14.194 4.469Guatemala -93.319 2.367 0.647 0 5.361 3.650Guyana -136.198 2.368 5.945 0 12.711 3.631Honduras -116.272 2.339 2.798 0 8.296 3.481Mexico -46.867 2.372 -0.803 0 4.856 3.780Nicaragua -118.649 2.298 0.059 0 9.259 2.833Panama 4.867 1.828 -2.061 -1 6.490 2.485Paraguay -7.375 2.585 5.823 0 7.717 4.692Peru 82.387 2.547 1.548 0 5.849 4.878Suriname -115.235 2.286 6.485 0 13.964 3.743Uruguay 68.274 1.948 6.405 0 6.727 5.152Venezuela -34.579 2.666 2.271 1 10.005 4.254

Norte América United States 3.997 2.780 18.928 1 16.839 4.838

América Latina

Changes in Cassava production areas in Latin America

Impacts on production of cassava

The Model: EcoCrop

It evaluates on monthly basis if there are adequate climatic conditions within a growing season for temperature and precipitation…

…and calculates the climatic suitability of the resulting interaction between rainfall and temperature…

• So, how does it work?

Worldwide cassava production climatic constraints

Grey areas are the crop’s main niche.

Blue areas constrained by precipitation

Yellow-orange constrained by temperature

Impact of climate change on cassava suitable environments

Global cassava suitability will increase 5.1% on average by 2050… but many areas of Latin America suffer negative impacts

What are the expected global benefits?

Increase of 5-10% in potential land area for cassava when implementing either drought or flood tolerance

21.9 million hectares (16.9% of global cassava fields) under cultivation would benefit

63.3 million hectares of new land would become suitable for cassava

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Ropmin ------------------------------- Ropmax

Ch

ang

e in

are

a (%

) Waterlogging tolerance

Drought tolerance

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Drought tolerance (Ropmin) Waterlogging tolerance (Ropmax) Not benefited

Ben

efit

ed a

reas

(m

illi

on

hec

tare

s)

Currently cropped lands

Not currently cropped lands

…….and for Latin America?Drought or flooding tolerance

30% of current cassava fields would benefit from enhanced drought or flooding tolerance

1.6m Ha still suffering climatic constraint

2.23m Ha of current production

2.1m Ha of new land would become suitable for cassava

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-2.5% -2% -1.5% -1% -0.5% None +0.5% +1% +1.5% +2% +2.5%

Mejora en la resiliencia de los cultivos

Cam

bio

en

áre

as a

dap

tab

les

[>80

%]

(%)

Áreas cultivadas

Áreas no-cultivadas

Total áreasadaptables

Toleracia a sequias

Toleracia a inundación

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-2.5% -2% -1.5% -1% -0.5% None +0.5% +1% +1.5% +2% +2.5%

Mejora en la resiliencia de los cultivos

Cam

bio

en

áre

as a

dap

tab

les

[>80

%]

(%)

Áreas cultivadas

Áreas no-cultivadas

Total áreasadaptables

Toleracia a sequias

Toleracia a inundación

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Ropmin Ropmax Not benefited

Áre

as b

enef

icia

das

(m

illi

ón

de

hec

táre

as)

Áreas cultivadas actualmente

Áreas no-cultivadasactualmente

…….and for Latin America?Heat or cold tolerance

27% of current cassava fields would benefit from enhanced cold or heat tolerance

2.23m Ha of current production

2.2m Ha of new land would become suitable for cassava

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-2.5ºC -2ºC -1.5ºC -1ºC -0.5ºC None +0.5ºC +1ºC +1.5ºC +2ºC +2.5ºC

Mejoramiento en la resiliencia del cultivo

Cam

bio

en

áre

as a

dap

tab

les

[>80

%]

(%)

Áreas cultivadas

Áreas no-cultivadas

Total áreas adaptables

Toleracia al calor

Toleracia al frío

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-2.5ºC -2ºC -1.5ºC -1ºC -0.5ºC None +0.5ºC +1ºC +1.5ºC +2ºC +2.5ºC

Mejoramiento en la resiliencia del cultivo

Cam

bio

en

áre

as a

dap

tab

les

[>80

%]

(%)

Áreas cultivadas

Áreas no-cultivadas

Total áreas adaptables

Toleracia al calor

Toleracia al frío

0

1

1

2

2

3

Topmin Topmax Not benefited

Áre

as b

enef

icia

das

(m

illó

n d

e h

ectá

reas

) Áreas cultivadas actualmente

Áreas no-cultivadasactualmente

Evaluating Technology Options: Crop Improvement for Cassava

Grey areas would get no benefit from drought or flood tolerance.

Blue areas benefit from drought tolerance improvement

Purple areas benefit from flood tolerance improvement

Pest and Disease Impacts

Impacts on green mite

to 2020

Impacts on whitefly to

2020

Challenges ahead

• Further analysis: improvement of the parameters, greater uncertainty in GCMs

• Inclusion of post-harvest impacts – drying for example

• Further work in pest and disease impacts• ….but too late to wait for 100% certainty• Crop improvement and targeted varietal

selection can support adaptation• CLAYUCA network is critical to enabling

adaptation

GRACIAS!!!!

a.jarvis@cgiar.org