Agricultural Data and Informatics Crucial for Climate Change Adaptation
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Presentation made in the Generation Challenge Program (GCP) General Research Meeting held in Hyderabad, India in September 2011.
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Agricultural Data and Informatics Crucial for Climate Change Adaptation
- 1. The Importance of Agricultural Data and Informatics for Climate Change Adaptation Andy Jarvis, Julian Ramirez, Glenn Hyman, Jacob van Etten CCAFS
- 3. The concentration of GHGs is rising Long-term implications for the climate and for crop suitability
- 4. Historical impacts on food security % Yield impact for wheat Observed changes in growing season temperature for crop growing regions,1980-2008. Lobell et al (2011)
- 5. Average projected % change in suitability for 50 crops, to 2050 Crop suitability is changing
- 6. 0 0.25 0.50 0.75 1 Exacerbating the yield gap From Licker et al, 2010 Climate change will likely pose additional difficulties for resource-poor farmers (e.g., in Africa), thereby increasing the yield gap
- 8. “ Unchecked climate change will result in a 20% increase in malnourished children by 2050 ,” relative to the full mitigation scenario. -Gerald Nelson, IFPRI/CCAFS
- 14. >> Multi-site agricultural trial database(agtrial.org) 20,000+ maize trials in 123 research sites Effect of +1ºC warming on yield Sites with >23ºC would suffer even if optimally managed More than 20% loss in sites with >20ºC, under drought Lobell et al. 2011
- 17. >> Multi-site agricultural trial database(agtrial.org) 20,000+ maize trials in 123 research sites Effect of +1ºC warming on yield Sites with >23ºC would suffer even if optimally managed More than 20% loss in sites with >20ºC, under drought Lobell et al. 2011
- 18. GxE: OPV vs hybrid
- 19. GxE: duration
- 24. Benefits of breeding options
- 30. Adaptation to progressive climate change · 1 >> Spotlight on: The AMKN Platform It links farmers’ realities on the ground with promising scientific research outputs, to inspire new ideas and highlight current challenge. Why is it useful? The Climate Change Adaptation and Mitigation Knowledge Network platform is a portal for accessing and sharing agricultural A&M knowledge. What CCAFS output?
- 31. AN EXAMPLE OF USING THE SOME OF THESE APPROACHES TO LINK KNOWLEDGE AND DATA
- 33. Change in climate, 2020 – Kaffrine , Senegal Average Climate Change Trends: - Decrease in precipitation from 660 mm to 590.58 mm - Increase of mean temperature of 0.344°C
- 34. Crop suitability – Kaffrine , Senegal
- 36. Zoom on high similarity climate of CCAFS sites CCAFS site with minimum value of dissimilarity with the climate of Kaffrine, Senegal = Tougou, Burkina Faso Best consistency between the 24 GCM’s = Fakara , Niger The current climate of Fakara is similar to the future projected climate in Kaffrine Fakara is the most likely analogue of Kaffrine
- 40. Agtrial database - Application Kontela, Mali is another potential analogue to Kaffrine, Senegal The sorghum yield data in Kontela, Mali could help us to know the future sorghum yield in Kaffrine, Senegal. Yield data available in the Agtrials database: http://www.agtrials.org:85/ Sorghum yield data Sorghum Variety K (kg/ha) N (kg/ha) P (kg/ha) Lime (kg/ha) Manure (kg/ha) Grain yield (t/ha) CSM63E 0 0 0 0 0 0.68 CSM63E 0 0 0 0 0 0.10 CSM63E 60 0 30 0 0 0.55 CSM63E 60 100 0 0 0 0.33 CSM63E 0 100 30 0 0 0.38 CSM63E 60 100 30 0 0 1.40 CSM63E 60 100 30 0 0 0.54 CSM63E 60 100 30 500 0 1.68 CSM63E 60 100 30 0 10000 1.06 CSM63E 60 100 30 0 0 0.08
- 41. Agtrial database - Application Senegal Hombolo, Tanzania is another potential analogue to Kaffrine, Senegal Yield data available in the Agtrial database: http://www.agtrials.org:85/ The MILLET yield data in Homboro, Tanzania could help us to know the future millet yield in Kaffrine, Senegal. Millet Yield data Variety name Grain Yield (t/ha) Nyamkombo 0.87 Okashana-2 1.09 PMV-2 0.78 PMV-3 0.86 SDMV89003 0.88 SDMV89007 0.82 SDMV90031 1.16 SDMV91018 0.91 SDMV92033 0.75 SDMV92038 0.82 SDMV95032 1.03 SDMV95033 0.93 SDMV95045 1.13 SDMV96075 0.89 SDMV97007 0.87 SDMV97011 0.87 TSPM91018 0.69 SDMV89005 0.90 SDMV92035 0.51 SDMV92037 1.01 SDMV95009 0.77 SDMV95014 0.68 SDMV95025 0.73 ZPMV92005 0.50 ZPMV94001 0.60
- 42. stay in touch www.ccafs.cgiar.org sign up for science, policy and news e-bulletins follow us on twitter @cgiarclimate
Editor's Notes
- For Lobell map: Values show the linear trend in temperature for the main crop grown in that grid cell, and for the months in which that crop is grown. Values indicate the trend in terms of multiples of the standard deviation of historical year-to-year variation. ** A 1˚C rise tended to lower yields by up to 10% except in high latitude countries, where in particular rice gains from warming. ** In India, warming may explain the recently slowing of yield gains. For yield graph: Estimated net impact of climate trends for 1980-2008 on crop yields for major producers and for global production. Values are expressed as percent of average yield. Gray bars show median estimate and error bars show 5-95% confidence interval from bootstrap resampling with 500 replicates. Red and blue dots show median estimate of impact for T trend and P trend, respectively. ** At the global scale, maize and wheat exhibited negative impacts for several major producers and global net loss of 3.8% and 5.5% relative to what would have been achieved without the climate trends in 1980-2008. In absolute terms, these equal the annual production of maize in Mexico (23 MT) and wheat in France (33 MT), respectively. Source: Climate Trends and Global Crop Production Since 1980 David B. Lobell 1 , , Wolfram Schlenker 2 , 3 , and Justin Costa-Roberts 1 Science magazine
- Where the bar shows yield gap fractions, so green (0) = no gap between actual production and potential production; and red (1) = complete yield gap.
- Why focus on Food security And climate change has to be set in the context of growing populations and changing diets 60-70% more food will be needed by 2050 because of population growth and changing diets – and this is in a context where climate change will make agriculture more difficult.
- The current suitability is closed to 100% because we are only using a range of temperature and precipitation and we don’t consider other parameters as soil,…. We did the ecocrop analysis with the average of annual precipitation and not with taking in account the crop seasonnality (which could be more exact).