004 climate change scenarios for lac and rice, andy jarvis

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004 climate change scenarios for lac and rice, andy jarvis

  1. 1. Escenarios de Cambio climático en Colombia y la  agricultura: con una mirada hacia el arroz g Andy Jarvis, Julian Ramirez, Emmanuel Zapata, Peter Laderach,  Edward Guevara Program Leader, Decision and Policy Analysis, CIAT
  2. 2. Contenido • Acerca de cambio climatico y los modelos GCM • El futuro de America Latina • Analisis de adaptabilidad global, y un ejemplo en  Colombia • Lo que se debe hacer
  3. 3. Sources of Agricultural Greenhouse Gases excluding land use change Mt CO2-eq Source: Cool farming: Climate impacts of agriculture and mitigation potential, Greenpeace, 07 January 2008
  4. 4. Arctic Ice is Melting Arctic Ice is Melting
  5. 5. Los modelos de pronostico de clima 
  6. 6. Usando el pasado para aprender del futuro Usando el pasado para aprender del futuro
  7. 7. Modelos GCM : “Global Climate Models” • 21 “global climate models” (GCMs) basados en ciencias 21  global climate models (GCMs) basados en ciencias atmosféricas, química, física, biología • Se corre desde el pasado hasta el futuro Se corre desde el pasado hasta el futuro • Hay diferentes escenarios de emisiones de gases INCERTIDUMBRE POLITICO (EMISIONES), Y  INCERTIDUMBRE POLITICO (EMISIONES) Y INCERTIDUMBRE CIENTIFICO (MODELOS)
  8. 8. Entonces, ¿qué es lo que dicen? Entonces, ¿qué es lo que dicen? Variaciones en la temperatura de la superficie de la tierra: de 1000 a 2100
  9. 9. Variabilidad y linea base y linea + Climate _ Timescale Short (change in baseline and variability) Long
  10. 10. Bases de Datos Bases de Datos • Bases de datos de CIAT para 2050 y 2020 • P Para elaboración de senderos de adaptacion l b ió d d d d i http://gisweb.ciat.cgiar.org/GCMPage/home.html
  11. 11. Cambio en Cambio en Region Departamento Temperatura Precipitacion media Amazonas Amazonas 12 2.9 Amazonas Caqueta 138 2.7 Amazonas Guania 55 2.9 Amazonas Guaviare 72 2.8 Amazonas Putumayo 117 2.6 Andina Antioquia q 18 2.1 Andina Boyaca 50 2.7 Andina Cundinamarca 152 2.6 Andina Huila 51 2.4 Andina Norte de santander 73 2.8 Andina Santander 51 2.7 Andina Tolima 86 2.4 Caribe Atlantico -74 2.2 Caribe Bolivar 90 2.5 Caribe Cesar -119 2.6 Caribe Cordoba -11 2.3 Caribe Guajira -69 2.2 Caribe Magdalena -158 2.4 Caribe Sucre 10 2.4 Eje Cafetero Caldas 252 2.4 Eje Cafetero Quindio 153 2.3 Eje Cafetero Ej C f t Risaralda Ri ld 158 2.4 24 Llanos Arauca -13 2.9 Llanos Casanare 163 2.8 Llanos Meta 10 2.7 Llanos Vaupes 46 2.8 Llanos Vichada 59 2.6 26 Pacifico Choco -157 2.2 Sur Occidente Cauca 172 2.3 Sur Occidente Narino 155 2.2 Sur Occidente Valle del Cauca 275 2.3
  12. 12. CCCMA‐CGCM3.1 BCCR‐BCM2.0 CCCMA‐CGCM2 CCCMA‐CGCM3.1‐T63 CNRM‐CM3 IAP‐FGOALS‐1.0G T47 GISS‐AOM GFDL‐CM2.1 GFDL‐CM2.0 CSIRO‐MK3.0 IPSL‐CM4 MIROC3.2‐HIRES MIROC3.2‐MEDRES MIUB‐ECHO‐G MPI‐ECHAM5 MRI‐CGCM2.3.2A NCAR‐PCM1 UKMO‐HADCM3
  13. 13. CCCMA‐CGCM3.1 BCCR‐BCM2.0 CCCMA‐CGCM2 CCCMA‐CGCM3.1‐T63 CNRM‐CM3 IAP‐FGOALS‐1.0G T47 GISS‐AOM GFDL‐CM2.1 GFDL‐CM2.0 CSIRO‐MK3.0 IPSL‐CM4 MIROC3.2‐HIRES MIROC3.2‐MEDRES MIUB‐ECHO‐G MPI‐ECHAM5 MRI‐CGCM2.3.2A NCAR‐PCM1 UKMO‐HADCM3
  14. 14. CCCMA‐CGCM3.1 CSIRO‐MK3.0 IPSL‐CM4 MPI‐ECHAM5 NCAR‐CCSM3.0 UKMO‐HADCM3 UKMO‐HADGEM1 2050 A1B 1
  15. 15. CCCMA‐CGCM3.1 CSIRO‐MK3.0 IPSL‐CM4 MPI‐ECHAM5 NCAR‐CCSM3.0 UKMO‐HADCM3 UKMO‐HADGEM1 2050 A1B 1
  16. 16. Distribución del arroz  Distribución del arroz en Colombia por  sistemas de producción
  17. 17. Climate General climate change description characteristic Average Climate Change Trends of The rainfall decreases from 1444 millimeters to 1411.75 millimeters General Temperatures increase and the average increase is 0.8 ºC climate The mean daily temperature range decreases from 11.3 ºC to 11.28 ºC y p g characteristics h t i ti The maximum number of cumulative dry months keeps constant in 4 months 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 Extreme 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 conditions The wettest month gets wetter with 253.5 millimeters instead of 252 millimeters, while the wettest quarter gets drier by 6.75 mm The driest month gets wetter with 41 millimeters instead of 39 millimeters while the driest quarter gets wetter by 20.75 mm Climate Overall this climate becomes more seasonal in terms of variability through the year in temperature and less seasonal in precipitation Seasonality The coefficient of variation of temperature predictions between models is 0.3% Variability Temperature predictions were uniform between models and thus no outliers were detected between The coefficient of variation of precipitation predictions between models is 5.16% models Precipitation predictions were uniform between models and thus no outliers were detected Current precipitation 300 40 Future precipitation Future mean temperature Current mean temperature 35 Future maximum temperature 250 Current maximum temperature Future minimum temperature 30 Current minimum temperature 200 Precipitation (mm) 25 Temperature (ºC) 150 20 15 P 100 10 50 5 Campoalegre a  0 0 2020 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Month 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
  18. 18. Climate General climate change description characteristic Average Climate Change Trends of Campoalegre The rainfall increases from 1444 millimeters to 1512.85 millimeters in 2050 passing through 1411.75 in 2020 General Temperatures increase and the average increase is 2.27 ºC passing through an increment of 0.8 ºC in 2020 climate The mean daily temperature range increases from 11.3 ºC to 11.82 ºC in 2050 C C h t i ti characteristics The maximum number of cumulative dry months keeps constant in 4 months 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 2050 Extreme The 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 2050 conditions The 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 driest month gets drier with 37.45 millimeters instead of 39 millimeters while the driest quarter gets wetter by 15.55 mm in 2050 Climate Overall this climate becomes more seasonal in terms of variability through the year in temperature and less seasonal in precipitation Seasonality The coefficient of variation of temperature predictions between models is 3% Variability Temperature predictions were uniform between models and thus no outliers were detected between The coefficient of variation of precipitation predictions between models is 12.03% models Precipitation predictions were uniform between models and thus no outliers were detected 300 40 Current precipitation Precipitation 2050 Precipitation 2020 35 250 Mean temperature 2020 Mean temperature 2050 30 Current mean temperature Maximum temperature 2020 200 Maximum temperature 2050 Precipitation (mm) 25 Temperature (ºC) Current maximum temperature Minimum temperature 2020 Minimum temperature 2050 150 20 Current minimum temperature 15 T 100 10 Campoalegre a  50 5 2020 y 2050 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Month 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
  19. 19. Climate General climate change description characteristic Average Climate Change Trends of Espinal The rainfall increases from 1409 millimeters to 1476.2 millimeters in 2050 passing through 1364.5 in 2020 General Temperatures increase and the average increase is 2.24 ºC passing through an increment of 0.72 ºC in 2020 climate The mean daily temperature range increases from 10 9 ºC to 11 38 ºC in 2050 10.9 11.38 characteristics The maximum number of cumulative dry months keeps constant in 3 months 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 2050 Extreme The 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 2050 conditions The wettest month gets wetter with 213.45 millimeters instead of 212 millimeters, while the wettest quarter gets wetter by 10.05 mm in 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 Climate Overall this climate becomes more seasonal in terms of variability through the year in temperature and less seasonal in precipitation Seasonality The coefficient of variation of temperature predictions between models is 3.03% Variability Temperature predictions were uniform between models and thus no outliers were detected between The coefficient of variation of precipitation predictions between models is 12.44% models Precipitation predictions were uniform between models and thus no outliers were detected 250 40 Current precipitation Precipitation 2050 Precipitation 2020 35 Mean temperature 2020 200 Mean temperature 2050 30 Current mean temperature Maximum temperature 2020 Maximum temperature 2050 ) 25 ) m C Current maximum temperature 150 º ( m ( Minimum temperature 2020 n e r o u Minimum temperature 2050 i t 20 t a a r Current minimum temperature t i e p i p c 100 m Espinal E i l e r e 15 T P 10 2020 y  50 5 0 1 2 3 4 5 6 Month 7 8 9 10 11 12 0 2050 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
  20. 20. Climate General climate change description characteristic Precipitation predictions were uniform between models and thus no outliers were detected Average Climate Change Trends of Sikasso The rainfall increases from 1061.65 millimeters to 1185.42 millimeters in 2050 passing through 1100.64 in 2020 General climate Temperatures increase and the average increase is 2.65 ºC passing through an increment of 1.05 ºC in 2020 characteristics The mean daily temperature range increases from 13.71 ºC to 13.75 ºC in 2050 C C The maximum number of cumulative dry months decreases from 8 months to 7 months 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 Extreme 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 conditions 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 Overall this climate becomes more seasonal in terms of variability through the year in temperature and less seasonal in precipitation Seasonality The coefficient of variation of temperature predictions between models is 4.37% Variability Temperature predictions were uniform between models and thus no outliers were detected between The coefficient of variation of precipitation predictions between models is 11.68% models Precipitation predictions were uniform between models and thus no outliers were detected 350 45 Current precipitation Precipitation 2050 40 Precipitation 2020 300 Mean temperature 2020 Mean temperature 2050 35 Current mean temperature 250 Maximum temperature 2020 30 Maximum temperature 2050 Precipitation (mm) Temperature (ºC) Current maximum temperature 200 25 Minimum temperature 2020 Minimum temperature 2050 Current minimum temperature 150 20 T P Sikasso, 15 100 10 Mali 50 5 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Month 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
  21. 21. Climate General climate change description characteristic Average Climate Change Trends of Villahermosa, Mexico The rainfall decreases from 1925 millimeters to 1776.89 millimeters in 2050 passing through 1903.75 in 2020 General Temperatures increase and the average increase is 2.39 ºC passing through an increment of 0.98 ºC in 2020 climate The Th mean daily temperature range increases from 11.3 ºC t 12 29 ºC i 2050 d il t t i f 11 3 to 12.29 in characteristics The maximum number of cumulative dry months keeps constant in 4 months The maximum temperature of the year increases from 35.7 ºC to 39.06 ºC while the warmest quarter gets hotter by 2.69 ºC in 2050 Extreme The minimum temperature of the year increases from 18.3 ºC to 19.67 ºC while the coldest quarter gets hotter by 1.99 ºC in 2050 conditions The wettest month gets wetter with 310.22 millimeters instead of 310 millimeters, while the wettest quarter gets drier by 28.5 mm in 2050 The driest month gets drier with 27.44 millimeters instead of 47 millimeters while the driest quarter gets drier by 47.39 mm in 2050 Climate Overall this climate becomes more seasonal in terms of variability through the year in temperature and more seasonal in precipitation Seasonality The coefficient of variation of temperature predictions between models is 3.43% Variability Temperature predictions were uniform between models and thus no outliers were detected between The coefficient of variation of precipitation predictions between models is 6.74% models Precipitation predictions were uniform between models and thus no outliers were detected p p 350 45 Current precipitation Precipitation 2050 Precipitation 2020 40 300 Mean temperature 2020 Mean temperature 2050 35 Current mean temperature 250 Maximum temperature 2020 30 Maximum temperature 2050 Current maximum temperature Precipi tation (mm) erature (ºC) Minimum temperature 2020 200 25 Minimum temperature 2050 Current minimum temperature Tempe 150 20 15 100 10 Villahermosa,  50 0 5 0 Mexico 1 2 3 4 5 6 7 8 9 10 11 12 Month
  22. 22. The Impacts on Crop Suitability The Impacts on Crop Suitability
  23. 23. Agricultural systems analysis Agricultural systems analysis • 50 target crops selected based on area harvested in  FAOSTAT Area Area N FAO name Scientific name harvested N FAO name Scientific name harvested (kha) (kha) 1 Alfalfa Medicago sativa L. 15214 26 African oil palm Elaeis guineensis Jacq. 13277 2 Apple Malus sylvestris Mill. 4786 27 Olive, Europaen Olea europaea L. 8894 3 Banana Musa acuminata Colla 4180 28 Onion Allium cepa L. v cepa 3341 4 Barley Hordeum vulgare L. 55517 29 Sweet orange Citrus sinensis (L.) Osbeck 3618 5 Bean, Common Phaseolus vulgaris L. 26540 30 Pea Pisum sativum L. 6730 6 Common buckwheat* Fagopyrum esculentum Moench 2743 31 Pigeon pea Cajanus cajan (L.) Mill ssp 4683 7 Cabbage C bb Brassica oleracea L capi. B i l L.v i 3138 32 Plantain bananas Pl t i b Musa b lbi i M balbisiana C ll Colla 5439 8 Cashew Anacardium occidentale L. 3387 33 Potato Solanum tuberosum L. 18830 9 Cassava Manihot esculenta Crantz. 18608 34 Swede rap Brassica napus L. 27796 10 Chick pea Cicer arietinum L. 10672 35 Rice paddy (Japonica) Oryza sativa L. s. japonica 154324 11 White clover Trifolium repens L. 2629 36 Rye Secale cereale L. 5994 12 Cacao Theobroma cacao L. 7567 37 Perennial reygrass Lolium perenne L. 5516 13 Coconut Cocos nucifera L L. 10616 38 Sesame seed Sesamum indicum L L. 7539 14 Coffee arabica Coffea arabica L. 10203 39 Sorghum (low altitude) Sorghum bicolor (L.) Moench 41500 15 Cotton, American upland Gossypium hirsutum L. 34733 40 Perennial soybean Glycine wightii Arn. 92989 16 Cowpea Vigna unguiculata unguic. L 10176 41 Sugar beet Beta vulgaris L. v vulgaris 5447 17 European wine grape Vitis vinifera L. 7400 42 Sugarcane Saccharum robustum Brandes 20399 18 Groundnut Arachis hypogaea L. 22232 43 Sunflower Helianthus annuus L v macro 23700 19 9 Lentil Lens culinaris Medikus 38 8 3848 44 S Sweet ppotato Ipomoea batatas ( ) Lam. p (L.) 8996 20 Linseed Linum usitatissimum L. 3017 45 Tea Camellia sinensis (L) O.K. 2717 21 Maize Zea mays L. s. mays 144376 46 Tobacco Nicotiana tabacum L. 3897 22 mango Mangifera indica L. 4155 47 Tomato Lycopersicon esculentum M. 4597 23 Millet, common Panicum miliaceum L. 32846 48 Watermelon Citrullus lanatus (T) Mansf 3785 24 Rubber * Hevea brasiliensis (Willd.) 8259 49 Wheat, common Triticum aestivum L. 216100 25 Oats Avena sativa L. 11284 50 White yam Dioscorea rotundata Poir. 4591
  24. 24. Average change in suitability for all crops in  2050s
  25. 25. Winners and losers Number of crops with more than 5% loss Number of crops with more than 5% gain
  26. 26. Message 1 Adaptabilidad global para la agricultura reduce un poco a 2050, y habra d 2050 h b problemas de distribucion de alimentos:  Opportunidades para arroz en America  pp p Latina
  27. 27. Un análisis sectorial para Colombia
  28. 28. Actual Temperatura (%) Precipitación (%) Cultivo Núm. Área (ha) Pdn (Ton) 2-2.5ºC 2.5-3ºC -3-0% 0-3% 3-5% Deptos 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 p 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 6 235,118 235 118 3,259,779 3 259 779 99.6 99 6 0.4 04 1.1 11 0.0 00 98.9 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 Plát t ió 1 19,187 19 187 209,647 209 647 100.0 100 0 0.0 00 0.0 00 100.0 100 0 0.0 00 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
  29. 29. Impactos en Colombia: cambio (%) en  productividad a nivel Nacional d d d l l Cambio adaptabilidad (%) 2050‐A2 4 2 0 ‐2 ‐4 ‐6 ‐8 ‐10 10 ‐12 ‐14 Cambio adaptabilidad (%) 2050 A2 Cambio adaptabilidad (%) 2050‐A2 ‐16 ‐18
  30. 30. Hacia adaptacion: Un ejemplo de frijol (buen adaptacion:  Un ejemplo de frijol (buen acompanante al arroz)
  31. 31. How are beans standing up currently? How are beans standing up currently? Minimum absolute Growing season (days) 90 Killing temperature (°C) 0 200 rainfall (mm) Minimum optimum Parameters determined  363 Minimum absolute rainfall (mm) 13.6 based on statistical  temperature (°C) Maximum optimum 450 rainfall (mm) y analysis of current bean  Minimum optimum 17.5 17 5 temperature (°C) Maximum absolute growing environments  Maximum optimum rainfall (mm) 710 from the Africa and LAC  23.1 temperature (°C) Bean Atlases. Maximum absolute 25.6 temperature (°C)
  32. 32. What will likely happen? 2020 – A2 2020 – A2 ‐ changes
  33. 33. Technology options: breeding for drought  and waterlogging tolerance d l i l 40 14 Change in suitable areas [>80% (%) Currently cropped lands res) Cropped lands 35 Drought  g 12 %] Some 22.8% (3.8 million  S 22 8% (3 8 illi Benefited areas (million hectar Non-cropped lands Not currently cropped lands 30 tolerance Global suitable areas 10 ha) would benefit from  25 8 Waterlogging  drought tolerance  20 tolerance 6 15 improvement to 2020s p 4 n 10 5 2 0 0 -25% -20% -15% -10% -5% None +5% +10% +15% +20% +25% Ropmin Ropmax Not benefited Crop resilience improvement
  34. 34. Technology options: breeding for heat and  cold tolerance ld l 14 70 Currently cropped lands 0%] (%) tares) Cropped lands 12 Not currently cropped lands 60 Some 42.7% (7.2  Some 42 7% (7 2 Non cropped Non-cropped lands Benefited areas (million hect Change in suitable areas [>80 50 Cold  Global suitable areas 10 million ha) would  40 tolerance 8 benefit from heat  30 6 tolerance  20 n 4 d improvement to  10 Heat  tolerance 2 2020s 0 -2.5ºC -2ºC -1.5ºC -1ºC -0.5ºC None +0.5ºC +1ºC +1.5ºC +2ºC +2.5ºC 0 Crop resilience improvement Topmin Topmax Not benefited
  35. 35. Adaptacion ideal CASE 1: Transition  (win‐win) Risk management g Progressive g adaptation Mitigation Potential examples: ecosystem service payments – risk manages by offering  immediate financial capital/relief, mitigates by reducing emissions, and adapts  by creating incentives/opportunities to diversity away from just agriculture by creating incentives/opportunities to diversity away from just agriculture
  36. 36. Climat CASE 2: Disjointed adaptation   (win‐win) Risk management (coping) C e ? Progressive adaptation  (transformational  (transformational change) Example: subsidies that would lower emissions and give farmers extra financial capital to invest in  higher production (risk management and mitigation, but not significant long term adaption  higher production (risk management and mitigation, but not significant long‐term adaption strategy) CASE 3: Disjointed adaptation   (no win‐win) ? Risk management Progressive adaptation (coping) (transformative change) Trade‐offs e.g.) Taxing fertilizers and pesticides  Trade‐offs –mitigates at farmer’s cost e.g.) Occupational change from agricultural to  industrial work– farmer “adapts” at potential cost to environment Mitigation
  37. 37. La variabilidad genetic existe en arroz…. La variabilidad genetic existe en arroz…. • Intercambiar materiales y practicas dentro del  te ca b a ate a es y p act cas de t o de pais…. • ….y por fuera del pais: yp p • 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
  38. 38. Y la heterogeneidad permite transferencia de practicas y  tecnologias de un de un  sitio al otro
  39. 39. Message 3 Los impactos pueden ser enfrentados con la diversidad de materiales con la diversidad de materiales existentes, o por medio de  mejoramiento, pero hay que mejoramiento pero hay que empezar ya
  40. 40. Como adaptamos? Como adaptamos? OS O  • Necesitamos saber que hacemos como saber que hacemos, como Y DESARROLLO RIVADO lo hacemos, cuando lo hacemos y  donde? COS Y PR OGICO • Primero paso es analisar el problema • Segundo analisar opciones de Segundo, analisar de  ECNOLO ACION Y ITICAS PUBLIC adaptacion • Evaluar costo‐beneficio para el sector costo beneficio el sector TE VESTIGA • Implementar INV POLI BUEN AGRONOMIA
  41. 41. a.jarvis@cgiar.org

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