Andy Jarvis - Climate Change Scenarios For Colombia And Rice Fedearroz Bogota Nov 2009

Escenarios de Cambio climático en Colombia y la agricultura: con una mirada hacia el arroz

Andy Jarvis, Julian Ramirez, Emmanuel Zapata, Peter Laderach, Edward Guevara

Program Leader, Decision and Policy Analysis, CIAT

Contenido

• Acerca de cambio climatico y los modelos GCM• El futuro de Colombia• Analisis de adaptabilidad global, y la realidad

Colombiana• El caso de arroz en Colombia• Lo que se debe hacer

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

Porque tan seguros que el clima esta cambiando?

Arctic Ice is Melting

Los modelos de pronostico de clima

Usando el pasado para aprender del futuro

Modelos GCM : “Global Climate Models”

• 21 “global climate models” (GCMs) basados en ciencias atmosféricas, química, física, biología

• Se corre desde el pasado hasta el futuro• Hay diferentes escenarios de emisiones de gases

INCERTIDUMBRE POLITICO (EMISIONES), Y INCERTIDUMBRE CIENTIFICO (MODELOS)

http://en.wikipedia.org/wiki/Image:Global_Atmospheric_Model.jpg

Entonces, ¿qué es lo que dicen?Variaciones en la temperatura de la superficie de la tierra: de 1000 a 2100

Bases de Datos

• Bases de datos de CIAT para 2050 y 2020• Para elaboración de senderos de adaptacion

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

23.0

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

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Colombia y el mundo en cambio climático

Colombia

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

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Mundo +4.5ºC+14%

+3.1ºC+8.1%

Region DepartamentoCambio en

Precipitacion

Cambio en Temperatura

media

Cambio en estacionalidad de

precipitacion

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

Distribución del arroz en Colombia por

sistemas de producción

Climate characteristic

Climate Seasonality

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

Average Climate Change Trends of

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 5.16%

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 41 millimeters instead of 39 millimeters while the driest quarter gets wetter by 20.75 mm

The maximum number of cumulative dry months keeps constant in 4 monthsThe mean daily temperature range decreases from 11.3 ºC to 11.28 ºC

Temperature predictions were uniform between models and thus no outliers were detectedThe coefficient of variation of temperature predictions between models is 0.3%

General climate change description

The maximum temperature of the year increases from 32.7 ºC to 33.48 ºC while the warmest quarter gets hotter by 0.85 ºC The minimum temperature of the year increases from 19.9 ºC to 20.9 ºC while the coldest quarter gets hotter by 0.8 ºC The wettest month gets wetter with 253.5 millimeters instead of 252 millimeters, while the wettest quarter gets drier by 6.75 mm

The rainfall decreases from 1444 millimeters to 1411.75 millimetersTemperatures increase and the average increase is 0.8 ºC

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Current maximum temperature

Future minimum temperature

Current minimum temperature

Campoalegre a 2020


Climate Seasonality

The coefficient of variation of temperature predictions between models is 3%

The maximum number of cumulative dry months keeps constant in 4 months

These results are based on the 2050 climate compared with the 1960-2000 climate. Future climate data is derived from 18 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


General climate

characteristics

Extreme conditions



The driest month gets drier with 37.45 millimeters instead of 39 millimeters while the driest quarter gets wetter by 15.55 mm in 2050

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

The mean daily temperature range increases from 11.3 ºC to 11.82 ºC in 2050


Average Climate Change Trends of Campoalegre


The maximum temperature of the year increases from 32.7 ºC to 35.61 ºC while the warmest quarter gets hotter by 2.56 ºC in 2050The minimum temperature of the year increases from 19.9 ºC to 21.88 ºC while the coldest quarter gets hotter by 2.14 ºC in 2050The wettest month gets wetter with 252.2 millimeters instead of 252 millimeters, while the wettest quarter gets wetter by 14.6 mm in 2050

The rainfall increases from 1444 millimeters to 1512.85 millimeters in 2050 passing through 1411.75 in 2020Temperatures increase and the average increase is 2.27 ºC passing through an increment of 0.8 ºC in 2020

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Precipitation 2020

Mean temperature 2020



Maximum temperature 2020



Minimum temperature 2020



Campoalegre a 2020 y 2050


Climate Seasonality


The driest month gets wetter with 45.9 millimeters instead of 41 millimeters while the driest quarter gets wetter by 9.85 mm in 2050



Average Climate Change Trends of Espinal


data.org


General climate

characteristics

Extreme conditions



The maximum temperature of the year increases from 34.8 ºC to 37.77 ºC while the warmest quarter gets hotter by 2.5 ºC in 2050The minimum temperature of the year increases from 21.8 ºC to 23.78 ºC while the coldest quarter gets hotter by 2.17 ºC in 2050The wettest month gets wetter with 213.45 millimeters instead of 212 millimeters, while the wettest quarter gets wetter by 10.05 mm in


The maximum number of cumulative dry months keeps constant in 3 monthsThe mean daily temperature range increases from 10.9 ºC to 11.38 ºC in 2050

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Temperature (ºC)

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Precipitation 2050

Precipitation 2020










Espinal2020 y 2050


Climate Seasonality



Average Climate Change Trends of Jamundi


The maximum temperature of the year increases from 30.3 ºC to 32.88 ºC while the warmest quarter gets hotter by 2.1 ºC in 2050The minimum temperature of the year increases from 17.8 ºC to 19.72 ºC while the coldest quarter gets hotter by 2.04 ºC in 2050The wettest month gets wetter with 226.05 millimeters instead of 221 millimeters, while the wettest quarter gets wetter by 15.2 mm in 2050


The maximum number of cumulative dry months keeps constant in 2 months


data.org


General climate

characteristics

Extreme conditions



The driest month gets wetter with 69.8 millimeters instead of 61 millimeters while the driest quarter gets wetter by 17.45 mm in 2050


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Precipitation 2050

Precipitation 2020










Jamundi2020 y 2050

Climate characteristi

cGeneral climate change description

Average Climate Change Trends of Sikasso

General climate

characteristics

The rainfall increases from 1061.65 millimeters to 1185.42 millimeters in 2050 passing through 1100.64 in 2020

Temperatures increase and the average increase is 2.65 ºC passing through an increment of 1.05 ºC in 2020


The maximum number of cumulative dry months decreases from 8 months to 7 months

Extreme conditions

The maximum temperature of the year increases from 37.41 ºC to 40.9 ºC while the warmest quarter gets hotter by 2.98 ºC in 2050

The minimum temperature of the year increases from 14.74 ºC to 17.02 ºC while the coldest quarter gets hotter by 2.54 ºC in 2050

The wettest month gets wetter with 300.47 millimeters instead of 282.08 millimeters, while the wettest quarter gets wetter by 14.07 mm in 2050

The driest month gets wetter with 2.86 millimeters instead of 0.81 millimeters while the driest quarter gets wetter by 30.71 mm in 2050

Climate Seasonality



The coefficient of variation of temperature predictions between models is 4.37%

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



These results are based on the 2050 climate compared with the 1960-2000 climate. Future climate data is derived from 18 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


Climate Seasonality



Average Climate Change Trends of Sikasso


The maximum temperature of the year increases from 37.41 ºC to 40.9 ºC while the warmest quarter gets hotter by 2.98 ºC in 2050The minimum temperature of the year increases from 14.74 ºC to 17.02 ºC while the coldest quarter gets hotter by 2.54 ºC in 2050The wettest month gets wetter with 300.47 millimeters instead of 282.08 millimeters, while the wettest quarter gets wetter by 14.07 mm in 2050

The rainfall increases from 1061.65 millimeters to 1185.42 millimeters in 2050 passing through 1100.64 in 2020Temperatures increase and the average increase is 2.65 ºC passing through an increment of 1.05 ºC in 2020

The maximum number of cumulative dry months decreases from 8 months to 7 months

These results are based on the 2050 climate compared with the 1960-2000 climate. Future climate data is derived from 18 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


General climate characteristics

Extreme conditions



The driest month gets wetter with 2.86 millimeters instead of 0.81 millimeters while the driest quarter gets wetter by 30.71 mm in 2050


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Current precipitationPrecipitation 2050Precipitation 2020Mean temperature 2020Mean temperature 2050Current mean temperatureMaximum temperature 2020Maximum temperature 2050Current maximum temperatureMinimum temperature 2020Minimum temperature 2050Current minimum temperature

Sikasso,Mali

The Impacts on Crop Suitability

Agricultural systems analysis• 50 target crops selected based on area harvested in

FAOSTATN FAO name Scientific name

Area harvested

(kha)26 African oil palm Elaeis guineensis Jacq. 1327727 Olive, Europaen Olea europaea L. 889428 Onion Allium cepa L. v cepa 334129 Sweet orange Citrus sinensis (L.) Osbeck 361830 Pea Pisum sativum L. 673031 Pigeon pea Cajanus cajan (L.) Mill ssp 468332 Plantain bananas Musa balbisiana Colla 543933 Potato Solanum tuberosum L. 1883034 Swede rap Brassica napus L. 2779635 Rice paddy (Japonica) Oryza sativa L. s. japonica 15432436 Rye Secale cereale L. 599437 Perennial reygrass Lolium perenne L. 551638 Sesame seed Sesamum indicum L. 753939 Sorghum (low altitude) Sorghum bicolor (L.) Moench 4150040 Perennial soybean Glycine wightii Arn. 9298941 Sugar beet Beta vulgaris L. v vulgaris 544742 Sugarcane Saccharum robustum Brandes 2039943 Sunflower Helianthus annuus L v macro 2370044 Sweet potato Ipomoea batatas (L.) Lam. 899645 Tea Camellia sinensis (L) O.K. 271746 Tobacco Nicotiana tabacum L. 389747 Tomato Lycopersicon esculentum M. 459748 Watermelon Citrullus lanatus (T) Mansf 378549 Wheat, common Triticum aestivum L. 21610050 White yam Dioscorea rotundata Poir. 4591

N FAO name Scientific nameArea

harvested (kha)

1 Alfalfa Medicago sativa L. 152142 Apple Malus sylvestris Mill. 47863 Banana Musa acuminata Colla 41804 Barley Hordeum vulgare L. 555175 Bean, Common Phaseolus vulgaris L. 265406 Common buckwheat* Fagopyrum esculentum Moench 27437 Cabbage Brassica oleracea L.v capi. 31388 Cashew Anacardium occidentale L. 33879 Cassava Manihot esculenta Crantz. 18608

10 Chick pea Cicer arietinum L. 1067211 White clover Trifolium repens L. 262912 Cacao Theobroma cacao L. 756713 Coconut Cocos nucifera L. 1061614 Coffee arabica Coffea arabica L. 1020315 Cotton, American upland Gossypium hirsutum L. 3473316 Cowpea Vigna unguiculata unguic. L 1017617 European wine grape Vitis vinifera L. 740018 Groundnut Arachis hypogaea L. 2223219 Lentil Lens culinaris Medikus 384820 Linseed Linum usitatissimum L. 301721 Maize Zea mays L. s. mays 14437622 mango Mangifera indica L. 415523 Millet, common Panicum miliaceum L. 3284624 Rubber * Hevea brasiliensis (Willd.) 825925 Oats Avena sativa L. 11284

Average change in suitability for all crops in 2050s

Winners and losers

Number of crops with more than 5% loss

Number of crops with more than 5% gain

Message 1

Adaptabilidad global para la agricultura reduce un poco a 2050, y habra problemas

de distribucion de alimentos: Opportunidades para arroz en America

Latina

Un Ejemplo mas local

El susto de café en Cauca

Climas mueven hacia arriba

Rango Altitudinal

Tmedia anual actual

Tmedia anual futuro

Tmedia anual

cambio (ºC)

Ppt total anual actual

190-500 25.54 27.70 2.16 5891 6002 1.88501-1000 23.47 25.66 2.19 3490 3597 3.041000-1500 21.29 23.50 2.21 2537 2641 4.101500-2000 18.36 20.58 2.22 2519 2622 4.082000-2500 15.60 17.82 2.22 2555 2657 4.002500-3000 13.33 15.54 2.21 2471 2575 4.20

Temperatura media reduce por 0.51oC por cada 100m en la zona cafetero. Un cambio de 2.2oC equivale a una diferencia de 440m.

Suitability in Cauca

• Significant changes to 2020, drastic changes to 2050

• The Cauca case: reduced coffeee growing area and changes in geographic distribution. Some new opportunities.

MECETA

Mensaje 2

Localmente va a ver cambios drasticos en los paisajes hacia 2050,

con la geografia de los cultivos cambiando

Un análisis sectorial para Colombia

Actual Temperatura (%) Precipitación (%) Cultivo Núm.

Deptos Área (ha) Pdn (Ton) 2-2.5ºC 2.5-3ºC -3-0% 0-3% 3-5%

Arroz total 26 460,767 2,496,118 64.6 35.4 15.7 23.6 60.7 Cebada 4 2,305 3,939 47.2 52.8 0.0 28.5 71.5 Maíz 31 626,616 1,370,456 80.5 19.5 27.7 37.1 35.2 Sorgo 14 44,528 137,362 97.0 3.0 33.8 3.8 62.4 Trigo 6 18,539 44,374 69.0 31.0 0.2 68.4 31.5 Ajonjolí 6 3,216 2,771 100.0 0.0 69.0 28.5 2.5 Fríjol 25 124,189 146,344 84.6 15.4 10.7 40.4 48.9 Soya 6 23,608 42,937 0.3 99.7 0.0 0.0 100.0 Maní 4 2,278 2,586 91.0 9.0 0.0 47.2 52.8 Algodón 15 55,914 126,555 98.0 2.0 14.6 55.7 29.7 Papa 13 163,505 2,883,354 71.5 28.5 2.6 27.1 70.4 Tabaco rubio 12 9,082 15,509 31.7 68.3 16.9 47.3 35.8 Hortalizas 14 20,265 270,230 84.9 15.1 16.1 28.7 55.2 Banano exportación 2 44,245 1,567,443 100.0 0.0 26.9 73.1 0.0 Cacao 27 113,921 60,218 40.2 59.8 17.3 53.2 29.5 Caña de azúcar 6 235,118 3,259,779 99.6 0.4 1.1 0.0 98.9 Tabaco negro 5 5,376 9,648 33.6 66.4 17.9 75.2 6.9 Flores 2 8,700 218,122 100.0 0.0 0.0 16.1 83.9 Palma africana 14 154,787 598,078 54.8 45.2 54.2 36.3 9.5 Caña panela 24 219,441 1,189,335 77.8 22.2 6.1 33.8 60.2 Plátano exportación 1 19,187 209,647 100.0 0.0 0.0 100.0 0.0 Coco 10 16,482 127,554 100.0 0.0 10.7 69.3 19.9 Fique 8 19,651 21,687 78.1 21.9 0.3 55.1 44.6 Ñame 9 25,105 261,188 100.0 0.0 46.7 53.3 0.0 Yuca 31 194,572 2,107,939 70.9 29.1 39.8 41.4 18.9 Plátano no exportable 31 375,232 3,080,718 79.8 20.2 7.2 36.1 56.6 Frutales 18 148,574 1,417,919 72.5 27.5 7.7 22.5 69.8 Café 17 613,373 708,214 84.7 15.3 8.2 28.8 63.1

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Cambio en temperatura mayor a 2.5ºC

Cambio en ppt mayor 3%

•50-60% de los productores de al menos el 70% de las actividades del pais son pequeños

•Cultivos permanentes (66.4% del PIB de 2007) seriamente afectados

Fuente: MADR, 2005 Fuente: CIAT, 2009

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Palma Banano Café Caña Arroz Cacao

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Vulnerabilidades del Sector

Minimising impacts: Breeding for beans (Phaseolus vulgaris L.) towards 2020

How are beans standing up currently?

Growing season (days) 90

13.6

17.5

23.1

25.6

Minimum absolute rainfall (mm)

200

Minimum optimum rainfall (mm)

363

Maximum optimum rainfall (mm)

450

Maximum absolute rainfall (mm)

710

Killing temperature (°C) 0

Minimum absolute temperature (°C)

13.6

Minimum optimum temperature (°C)

17.5

Maximum optimum temperature (°C)

23.1

Maximum absolute temperature (°C)

25.6

Parameters determined based on statistical analysis of current bean growing environments from the Africa and LAC Bean Atlases.

What will likely happen?

2020 – A2

2020 – A2 - changes

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-25% -20% -15% -10% -5% None +5% +10% +15% +20% +25%

Crop resilience improvement

Ch

ang

e in

su

itab

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reas

[>

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Cropped lands

Non-cropped lands

Global suitable areas

Technology options: breeding for drought and waterlogging tolerance

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Ropmin Ropmax Not benefited

Ben

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reas

(m

illi

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hec

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s) Currently cropped lands

Not currently cropped landsSome 22.8% (3.8 million ha) would benefit from drought tolerance improvement to 2020s

Drought tolerance

Waterlogging tolerance

Technology options: breeding for heat and cold tolerance

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

Crop resilience improvement

Ch

ang

e in

su

itab

le a

reas

[>

80%

] (%

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Cropped lands

Non-cropped lands

Global suitable areas

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Topmin Topmax Not benefited

Ben

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reas

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illi

on

hec

tare

s)

Currently cropped lands

Not currently cropped lands

Cold tolerance

Heat tolerance

Some 42.7% (7.2 million ha) would benefit from heat tolerance improvement to 2020s

Germplasm development with greater adaptation to water deficit

Objective: to develop new synthetic population through Recurrent Selection (RS) breeding with particular attention for yield under water deficit and good agronomic traits (Productivity & Quality)

Phenotyping and breeding for yield under water deficit

Santa Rosa, Colombia 2008-2009 (Sowing Nov 12th - Stress Jan 12th) Water deficit conditions applied at panicle initiation stage for 15 days

• 4 populations of 100 S1 lines + 6 contrasting checks

Evaluated lines (495)

0 50 100 150 200 250 300 350 400 450 500

Cano

py te

mpe

ratu

re (°

C)

26

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32

34

36

38

better lines in stress condition

Best material selected for developing a new population

La variabilidad genetic existe….

• Intercambiar materiales y practicas dentro del pais….• ….y por fuera del pais:• N22 la mas tolerante• IR64 tiene cierta tolerancia • IR6 por muchos anos ha sido sembrada en Pakistan en

donde se presentan temperaturas altas en epoca de floracion de 45 grados centigrados

• En CIAT y FLAR estamos probando y desarrollando nuevos materiales, y evaluando los retos para el Arroz en Colombia y America Latina

Message 3

Los impactos pueden ser enfrentados con la diversidad de materiales

existentes, o por medio de mejoramiento, pero hay que

empezar ya

Como adaptamos?

• Necesitamos saber que hacemos, como lo hacemos, cuando lo hacemos y donde?

• Primero paso es analisar el problema• Segundo, analisar opciones de

adaptacion• Evaluar costo-beneficio para el sector• Implementar

INVE

STIG

ACIO

N Y

DES

ARRO

LLO

TE

CNO

LOG

ICO

POLI

TICA

S PU

BLIC

OS

Y PR

IVAD

OS

BUEN AGRONOMIA

[email protected]