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. 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

5. 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

9. Arctic Ice is Melting
Arctic Ice is Melting

10. Los modelos de pronostico de clima

11. Usando el pasado para aprender del futuro
Usando el pasado para aprender del futuro

12. 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)

15. 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

18. Variabilidad y linea base
y linea
+
Climate
_
Timescale
Short (change in baseline and variability) Long

19. 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

20. 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

21. 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

22. 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

23. CCCMA‐CGCM3.1 CSIRO‐MK3.0 IPSL‐CM4 MPI‐ECHAM5
NCAR‐CCSM3.0 UKMO‐HADCM3 UKMO‐HADGEM1
2050
A1B
1

24. CCCMA‐CGCM3.1 CSIRO‐MK3.0 IPSL‐CM4 MPI‐ECHAM5
NCAR‐CCSM3.0 UKMO‐HADCM3 UKMO‐HADGEM1
2050
A1B
1

25. Distribución del arroz
Distribución del arroz
en Colombia por
sistemas de producción

26. 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

27. 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

28. 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

29. 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

30. 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

31. The Impacts on Crop Suitability
The Impacts on Crop Suitability

32. 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

33. Average change in suitability for all crops in
2050s

34. Winners and losers
Number of crops with more than 5% loss
Number of crops with more than 5% gain

35. 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

36. Un análisis sectorial para Colombia

37. 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

38. 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

39. Hacia adaptacion: Un ejemplo de frijol (buen
adaptacion: Un ejemplo de frijol (buen
acompanante al arroz)

40. 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)

41. What will likely happen?
2020 – A2
2020 – A2 ‐ changes

42. 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

43. 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

44. 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

45. 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

46. 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

47. Y la heterogeneidad
permite transferencia
de practicas y
tecnologias de un
de un
sitio al otro

48. 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

50. 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

51. a.jarvis@cgiar.org