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Building capacity to assess the impact of climate change/variability and

Building capacity to assess the impact of climate change/variability and develop adaptive responses for the mixed crop/livestock production systems in the Argentinean , Brazilian and Uruguayan Pampas. Principal Scientists  Graciela Magrin, INTA, Argentina

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Building capacity to assess the impact of climate change/variability and

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  1. Building capacity to assess the impact of climate change/variability and develop adaptive responses for the mixed crop/livestock production systems in the Argentinean , Brazilian and Uruguayan Pampas • Principal Scientists  • Graciela Magrin, INTA, Argentina • María I. Travasso, INTA, Argentina • Osvaldo Canziani, Argentina • Gilberto Cunha, Brazil • Mauricio Fernandes, Brazil • Agustin Gimenez, GRAS- INIA, Uruguay • Walter E. Baethgen, IFDC, Uruguay • Holger Meinke, APSRU, DPI, Australia

  2. Project Premise One of the most effective manners for assisting agricultural stakeholders to be prepared and adapt to possible climate change scenarios, is by helping them to better cope with current climate variability

  3. CLIMATE VARIABILITY in the Pampas Region ENSO and other sources

  4. CLIMATE and VARIABILITY Example: Climatology in La Estanzuela, Uruguay Mean Rainfall in EELE (1915-2000) MONTH

  5. CLIMATE and VARIABILITY Example: Observed Monthly Rainfall Monthly Rainfall in EELE MONTH

  6. CLIMATE and VARIABILITY Example: Monthly rainfall in 12 years (La Estanzuela) Monthly Rainfall in EELE MEAN None of the years shows monthly rainfall similar to the long-term values Still, planning is based on long-term values (Probability  0) MONTH

  7. Currently planning for conditions that will not exist (Probability = 0) Can we plan for conditions with Probability > 0 ? Improve Planning and Decision Making RESEARCH PROJECTS INIA – INTA - IFDC

  8. Chance of having precipitations higher (blue) or lower (red) than normal during "El Niño" and “La Niña” years. "El Niño" 2.80 2.60 2.40 2.20 2.00 1.80 1.60 1.40 0.00 2.80 2.60 2.40 2.20 2.00 1.80 1.60 1.40 0.00 “La Niña”

  9. Differences in three-monthly Precipitation (mm) and MaximumTemperature (ºC) During “EL NIÑO” and “LA NIÑA” years.

  10. Probability of having high yields (blue) or low yields (red) during El Niño and La Niña years.

  11. October 1997 November 1997 January 1998 February 1998 December 1997 OND 1997 SST

  12. October 1999 November 1999 January 2000 February 2000 December 1999 OND 1999 SST

  13. October 1998 November 1998 January 1999 February 1999 December 1998 OND 1998 SST

  14. ENSO-related Forecasts are Poor in January and February Pantanal: 150,000 km2 of Wetlands

  15. Sources of Interannual Climate Variability other than ENSO Correlation Between Rainfall in November in the Pantanal And Rainfall in Jan-Feb in SE South America r = 0.6 – 0.8

  16. South Atlantic SST impacts on summer precipitation and crops yield SST-SA (May) and Precipitation (January + February) Soybean Yield

  17. Gross Margins for Rainfed Maize (1960 – 2001) CERES Model CV = 128% 9 years in 30: result ( 0) 60% of Total Income in 6 years

  18. Gross Margins for Rainfed vs Irrigated Maize (1960 – 2001) CERES Model

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