Carlos Navarro, Patricia Moreno, Julián Ramírez, Osana Bonilla, Andy Jarvis

Brief Introduction to EcoCrop as a tool for crop vulnerability to CC

Maputo, Mozambique IIAM26/02/2013

CLIMATE AND CROP MODELING

Important impact assessment of climate change in crop yield (Craufurd et al., 2011).

Increases in temperature, dry and extreme rainfall have a negative effect in crop yield (Craufurd et al., 2011; Auffhammer et al., 2012).

Generation of adaptation and mitigation strategies through ex ante modeling (Craufurd et al., 2011).

Figure 1. Effect of minimum temperature increase on rice yield variables (Peng et al., 2004).

CLIMATE AND CROP MODELINGScenarios selection• Quality check: simulations with hindcasts vs. historical climate• Present, 2030 pessimistic, 2030 optimistic?• Establishment of operational scenario database

Global study• Simple model• Spatial gridded approach• Global mapping of crop response to CC

Zoom-ins: Virtual experiments• Models G*E*M• Model calibration for kay varietal types• Identification of crop parameters ranges• Zooming in on TPEs for each crop• Sensitivity analyses: Trait variation vs. environment• Ideotype composition for adapted crops

Dingkuhn, 2011

MAXENT (MAXIMUM ENTROPY MODELLING)

• Model predicting the potential distribution of a species

Maxent use the principle of the maximum entropy

Maxent use only presence point of specific species and environmental variables

• One of the most accurate model for the prediction of shifts in suitable growth ranges of species

MaxEnt Application on Kenyan coffeeMain coffee-producing areas in Kenya are located in two areas:

- the central region around Mount Kanya - in the Rift Valley in the west

- The most suitable areas: in the higher areas of Bungoma, Embu, Kericho, Kiambu, Kirinyaga, Kisii, Machakos, Meru, Muranga, Nithi, Nyamira, Nyeri and Trans-Nzoia

Alternatives to tea

New markets

Management

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?

ECOCROP

Kiling temperature (°C) Tkill(initial) 2.2

Minimum absolute temperature (°C) Tmin 10.0

Minimum optimum temperature (°C) Topmin 14.6

Maximum optimum temperature (°C) Topmax 30.0

Maximum absolute temperature (°C) Tmax 40.0

Growing season (days) (average) 150

Minimum absolute rainfall (mm) Pmin 60

Minimum optimum rainfall (mm) Popmin 360

Maximum optimum rainfall (mm) Popmax 1500

Maximum absoluterainfall (mm) Pmax 3000

P

P

P

P

𝑇𝑘𝑖𝑙𝑙=4+Tkill ( initial )

𝑇𝑘𝑖𝑙𝑙𝑇𝑚𝑖𝑛

𝑇𝑜𝑝𝑚𝑖𝑛

𝑇𝑚𝑎𝑥

𝑇𝑜𝑝𝑚𝑎𝑥

𝑇 (𝑋 )−𝑇𝑚𝑖𝑛

𝑇𝑜𝑝𝑚𝑖𝑛−𝑇𝑚𝑖𝑛

=𝑇 𝑠𝑢𝑖𝑡 1−𝑇 (𝑋 )−𝑇 𝑜𝑝𝑚𝑎𝑥

𝑇𝑚𝑎𝑥−𝑇 𝑜𝑝𝑚𝑎𝑥

=𝑇 𝑠𝑢𝑖𝑡

𝑇 𝑠𝑢𝑖𝑡=0

𝑇 𝑠𝑢𝑖𝑡=100

ECOCROP

Changes in climate affect the adaptability of crops…

Number of crops with more than 5% loss

Number of crops with more than 5% gain

There will be winners…

…But much more losers in developing countries

CLIMATE AND CROP MODELING

Kiling temperature (°C) 0

Minimum absolute temperature (°C) 15

Minimum optimum temperature (°C) 22

Maximum optimum temperature (°C) 32

Maximum absolute temperature (°C) 45

Growing season (days) 240

Minimum absolute rainfall (mm) 300

Minimum optimum rainfall (mm) 800

Maximum optimum rainfall (mm) 2200

Maximum absolute rainfall (mm) 2800

CASSAVA CURRENT SUITABILITY

2030s SRES-A1B

2030s SRES-A1B

CASSAVA FUTURE SUITABILITY

Cassava – an exception to the rule?

•For example, US maize, soy, cotton yields fall rapidly when exposed to temperatures >30˚C

•In many cases, roughly 6-10% yield loss per degree

Schlenker and Roberts 2009 PNAS

What will this mean for cassava?

Cassava suitability change compared with other staples

• Cassava consistently outperforms other staples in terms of changes in suitability

CASSAVA IMPACTS BY AF REGIONS

0.5 °C

5%

BREEDING AND CROP MODELING

Genetic breeding as strategy of adaptation and mitigation of climate change (Craufurd et al., 2011).

Figure 3. Diagram of model used to evaluate suitability (Ramirez-Villegas et al., 2011).

Different suitability predictions Quantify possible benefits

Simulate possible scenarios of breeding.

Evaluation of sensitivity and threshold variations of adaptation (Jarvis et al., 2012).

Figure 4. Potential benefits of a new combination of parameters reflecting scenarios of cassava improvement (Jarvis et al., 2012).

Change in Suitable Area Overall Suitability Change PIA/NIA ratio

AND Andean Region EAS East Asia NEU North Europe WAF West AfricaBRA Brazil EAF East Africa SAF South Africa WEU West EuropeCAC Cen. America and Caribean EEU East Europe SAH Sahel OCE OceaniaCAF Central Africa WAS West Asia SAS South Asia SAM South Latin AmericaCAS Central Asia NAF North Africa SEA Southeast AsiaCEU Central Europe NAM North America SEU South Europe

Thanks!Contactc.e.navarro@cgiar.orgl.p.moreno@cgiar.org