Brief introduction to Ecocrop as a tool for crop suitability analysis to climate change

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Slides from Training on Mozambique as part of IIAM-CCAFS Project

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  • Those change are happening and are affecting crop around the world. We need to know how and how much climate change is going to have an impact on crops to be able to build adaptation strategy and decrease the potential impact of CC on crops and agricultural systems.
  • Brief introduction to Ecocrop as a tool for crop suitability analysis to climate change

    1. 1. Carlos Navarro, Patricia Moreno, Maputo, Mozambique IIAM 26/02/2013Julián Ramírez, Osana Bonilla, Andy Jarvis
    2. 2. 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 riceyield variables (Peng et al., 2004).
    3. 3. Scenarios selection • Quality check: simulations with hindcasts vs. historical climate • Present, 2030 pessimistic, 2030 optimistic? • Establishment of operational scenario databaseGlobal study • Simple model • Spatial gridded approach • Global mapping of crop response to CCZoom-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
    4. 4. • 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
    5. 5. MaxEnt Application on Kenyan coffee Main 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-NzoiaNew marketsManagement Alternatives to tea
    6. 6. • So, how does it work?It evaluates on monthly basis if thereare adequate climatic conditionswithin a growing season for …and calculates the climatic suitability of thetemperature and precipitation… resulting interaction between rainfall and temperature…
    7. 7. Kiling temperature (°C) Tkill(initial) 2.2Minimum absolute temperature (°C) Tmin 10.0Minimum optimum temperature (°C) Topmin 14.6Maximum optimum temperature (°C) Topmax 30.0Maximum absolute temperature (°C) Tmax 40.0Growing season (days) (average) 150Minimum absolute rainfall (mm) Pmin 60Minimum optimum rainfall (mm) Popmin 360Maximum optimum rainfall (mm) Popmax 1500Maximum absoluterainfall (mm) Pmax 3000
    8. 8. Changes in climate affect the adaptability of crops… There will be winners… Number of crops with more than 5% gain…But muchmore losers indevelopingcountries Number of crops with more than 5% loss
    9. 9. Kiling temperature (°C) 0 Growing season (days) 240Minimum absolute temperature (°C) 15 Minimum absolute rainfall (mm) 300Minimum optimum temperature (°C) 22 Minimum optimum rainfall (mm) 800Maximum optimum temperature (°C) 32 Maximum optimum rainfall (mm) 2200Maximum absolute temperature (°C) 45 Maximum absolute rainfall (mm) 2800
    10. 10. 2030s SRES-A1B2030s SRES-A1B
    11. 11. 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
    12. 12. What will this mean for cassava?
    13. 13. Cassava suitability change compared with other staples• Cassava consistently outperforms other staples in terms of changes in suitability
    14. 14. Genetic breeding as strategy of adaptation and mitigation of climate change5% (Craufurd et al., 2011). Evaluation of sensitivity and threshold variations of adaptation (Jarvis et al., 2012). 0.5 °CFigure 3. Diagram of model used to evaluatesuitability (Ramirez-Villegas et al., 2011). Simulate possible scenarios of breeding. Different suitability predictions  Quantify possible benefits Figure 4. Potential benefits of a new combination of parameters reflecting scenarios of cassava improvement (Jarvis et al., 2012).
    15. 15. AND Andean Region EAS East Asia NEU North Europe WAF West Africa BRA Brazil EAF East Africa SAF South Africa WEU West Europe CAC Cen. America and Caribean EEU East Europe SAH Sahel OCE Oceania CAF Central Africa WAS West Asia SAS South Asia SAM South Latin America CAS Central Asia NAF North Africa SEA Southeast Asia CEU Central Europe NAM North America SEU South EuropeChange in Suitable Area Overall Suitability Change PIA/NIA ratio

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