Andy J Climate Change And Cassava In Latin America July 2009
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Transcript of Andy J Climate Change And Cassava In Latin America July 2009
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
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
-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
23.0
23.5
24.0
24.5
25.0
25.5
26.0
26.5
27.0
27.5
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
2550
2600
2650
2700
2750
2800
2850
2900
2950
1870 1890 1910 1930 1950 1970 1990 2010 2030 2050 2070 2090
Año
Pre
cip
itac
ión
to
tal a
nu
al (
mm
)
Precipitación total anual (mm)Tendencia temporalIntervalo de confianza (95%)
Colombia compared to the world
Colombia
650
670
690
710
730
750
770
790
810
1870 1890 1910 1930 1950 1970 1990 2010 2030 2050 2070 2090
Año
Pre
cip
itac
ión
to
tal a
nu
al (
mm
)
Precipitación total anual (mm)Tendencia temporalIntervalo de confianza (95%)
6.0
7.0
8.0
9.0
10.0
11.0
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
50
100
150
200
250
300
350
400
1 2 3 4 5 6 7 8 9 10 11 12Month
Pre
cip
itat
ion
(m
m)
0
5
10
15
20
25
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
0
50
100
150
200
250
300
350
400
1 2 3 4 5 6 7 8 9 10 11 12Month
Pre
cip
itat
ion
(m
m)
0
5
10
15
20
25
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
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12Month
Pre
cip
itat
ion
co
eff
icie
nt
of
vari
ati
on
(%
)
0
2
4
6
8
10
12
14
Te
mp
era
ture
co
eff
icie
nt
of
va
ria
tio
n (
%)
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
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
-25% -20% -15% -10% -5% None +5% +10% +15% +20% +25%
Ropmin ------------------------------- Ropmax
Ch
ang
e in
are
a (%
) Waterlogging tolerance
Drought tolerance
0
20
40
60
80
100
120
140
160
180
200
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
0
5
10
15
20
25
30
35
-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
0
5
10
15
20
25
30
35
-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
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
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
0
2
4
6
8
10
12
-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
2
4
6
8
10
12
-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!!!!