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Asunción Paraguay. August 14-18, 2006

Vulnerability and Adaptation Assessments Hands-On Training Workshop Impact, Vulnerability and Adaptation Assessment for the Agriculture Sector – Part 1. Asunción Paraguay. August 14-18, 2006. Graciela O. Magrin INTA-Instituto de Clima y Agua (Argentina). Outline.

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Asunción Paraguay. August 14-18, 2006

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  1. Vulnerability and Adaptation Assessments Hands-On Training WorkshopImpact, Vulnerability and Adaptation Assessmentfor the Agriculture Sector – Part 1 Asunción Paraguay. August 14-18, 2006 Graciela O. Magrin INTA-Instituto de Clima y Agua (Argentina)

  2. Outline 1- Climate change, agriculture and food security 2- Climatic variability Climatic trends Climate Change 3- Methods and tools Datasets Practical applications

  3. Concepts Vulnerability

  4. Land degradation Desertification

  5. Had CM2 model, 2050s Temperature Precipitation

  6. Barros, 2004

  7. Figure: Percentage of total county area devoted to wheat (Wh), maize (Mz), sunflower (Su) and soybean (Sb), during 20’ to 90’ decades in the last century. Argentina Pampas Region Magrin et al., 2005

  8. Policy makers Civil stakeholders Scientists

  9. Lobell and Monasterio, 2006 The example shows the impact of different irrigation scheduling in wheat in the Yaqui Valley of Mexico. Average wheat yield loss relative to the five irrigation regime for each of the other six regimes, are plotted as a function of initial available water for available water holding capacity of 15% (Lobell & Monasterio, 2006).

  10. Limits to Adaptation • Technological limits (e.g., crop tolerance to water-logging or high temperature; water reutilization) • Social limits (e.g., acceptance of biotechnology) • Political limits (e.g., rural population stabilization may not be optimal land use planning) • Cultural limits (e.g., acceptance of water price and tariffs)

  11. Climate IMPACTS CO2 Temperature Precipitation • Changes in biophysical conditions • Changes in socioeconomic conditions in response to changes in crop productivity (farmers’ income; markets and prices; poverty; malnutrition and risk of hunger; migration)

  12. Agriculture and Climatic Variability

  13. Droughts affecting the agricultural sector of LA since 2003

  14. Floods affecting the agricultural sector of LA since 2003 Flood Argentina 2003 Flood Bolivia 2006 Soybean monoculture Flooding affecting the agricultural sector of LA since 2003

  15. Other extreme events affecting the agricultural sector of LA since 2003

  16. Impacts of interanual climatic variability related to ENSO

  17. 0 - 3 5 0 - 3 5 3 5 - 4 5 3 5 - 4 5 4 5 - 5 5 4 5 - 5 5 5 5 - 6 5 5 5 - 6 5 6 5 - 7 5 6 5 - 7 5 7 5 - 8 5 7 5 - 8 5 8 5 - 1 0 0 8 5 - 1 0 0 S D S D La Niña El Niño Impacts of interanual climatic variability related to ENSO Soybean yield, Argentina Probability of having high/low yields during El Nino/La Nina years

  18. 100 90 80 Yield 70 Low 60 Med. High 50 40 30 20 Frequency (%) 10 0 All Years El Niño "Neutral" La Niña Impacts of interanual climatic variability related to ENSO Adaptation: Optimizing crop management Fertilizer amount Planting dates Maize production Uruguay Baethgen et al., 1998

  19. Pergamino Pilar Santa Rosa 100% 75% 50% 25% 0% Mod. Risk aversion Niña Neutro Niño Clim Niña Neutro Niño Clim Niña Neutro Niño Clim ENSO Phases Maize Soybean Wheat Peanut Wheat – Soybean Sunflower Adaptation: Argentina. Crop mix

  20. Agriculture and Climatic Trends

  21. Trends in total and extreme rainfall 1960-2000 Haylock et al., 2006 Annual days RR>20mm Total precipitation Sign of the linear trend in rainfall indices as measured by Kendall’s Tau. An increase is shown by a plus symbol, a decrease by a circle. Bold values indicate significant at p 0.05.

  22. Trends in temperature 1960-2000 Indice based on daily minimum temperature: cold and warm nights (Vincent et al, 2005)

  23. Impacts of climatic trends in SESA Changes in crop and pastures production (Argentina-Uruguay) between 1930-1960 and 1970-2000 due to climate change (Magrin et al, 2005; Baethgen et al, 2006) Pastures Crops

  24. Impacts of climatic trends in SESA Fusarium incidence in La Estanzuela Uruguay Mauricio Fernandes AIACC-LA27 1931-1965 1966-1999 Fusarium incidence

  25. Agriculture and Climate Change

  26. How Might Global Climate Change Affect Crop Production? Maize Sunflower Soybean Wheat Uncertainty? GFDL -16% +3% -3% UKMO -8% -22% -8% GISS -8% +18% -3% MPI-ds +2% +21% +7% Magrin & Travasso 2002

  27. How Might Global Climate Change Affect small farmers Food Production? Jones & Thornton, 2003 Overall reduction: 10% Simulated maize yields (baseline) and changes to 2055 for Latin America.

  28. How Might Global Climate Change Affect small farmers Food Production? Jones & Thornton, 2003 Eastern Brazil: an area with moderate predicted maize yield changes in 2055, of a size that could readily be handled through agronomy and/or breeding.

  29. How Might Global Climate Change Affect small farmers Food Production? Jones & Thornton, 2003 Venezuela: a case where maize yields to 2055 are predicted to be almost eliminated, indicating that maize production may have to be shifted into wetter areas (for example, to the south-west).

  30. How Might Global Climate Change Affect Food Production? Potential changes (%) in national cereal yields for the 2020s, 2050s and 2080s (compared with 1990) under the HadCM3 SRES A2a and B2 scenarios with and without CO2 effects. Parry et al., 2004

  31. Developed-Developing Country Differences • Potential change (%) in national cereal yields for the 2080s (compared with 1990) using the HadCM3 GCM and SRES scenarios (Parry et al., 2004)

  32. Additional People at Risk of Hunger Parry et al., 2004

  33. Conclusions • Although global production appears stable . . . • . . . regional differences in crop production are likely to grow stronger through time, leading to a significant polarization of effects . . . • . . . with substantial increases in prices and risk of hunger amongst the poorer nations • Most serious effects are at the margins (vulnerable regions and groups)

  34. Methods, Tools, and Datasets • The framework • The choice of the research methods and tools

  35. Frameworks • Adaptation Policy Framework (APF), US Country Studies, IPCC, seven steps • All have the essential common elements • Problem definition • Selection and testing of methods • Application of scenarios (climate and socioeconomic) • Evaluation of vulnerability and adaptation • The studies may want to use a framework as guidance or draw from the best elements of all of them

  36. Quantitative Methods and Tools • Experimental • Analogues (spatial and temporal) • Production functions (statistically derived) • Agroclimatic indices • Crop simulation models (generic and crop-specific) • Economic models (farm, national, and regional) – Provide results that are relevant to policy • Social analysis tools (surveys and interviews) – Allow the direct input of stakeholders (demand-driven science), provide expert judgment • Integrators: GIS

  37. http://www.whitehouse.gov/media/gif/Figure4.gif Experimental: Effect of Increased C02 Near Phoenix, Arizona, scientists measure the growth of wheat surrounded by elevated levels of atmospheric CO2. The study, called Free Air Carbon Dioxide Enrichment (FACE), is to measure CO2 effects on plants. It is the largest experiment of this type ever undertaken. http://www.ars.usda.gov

  38. Experimental Example: growth chambers, experimental fields.

  39. January 1998 January 2000 Analogues: Drought, Floods Uruguay Uruguay Vegetation Index Vegetation Source: INIA-IFDC

  40. Analogues (space and time) Example: existing climate in another area or in previous time

  41. Production Functions Precipitation Relationship between wheat yields and precipitation during the period from 60 days before to 10 days after flowering in two sites in Argentina. (Calviño & Sadras, 2002)

  42. Production Functions Example: Derived with empirical data.

  43. Agroclimatic Indices Length of the growing periods (reference climate, 1961-1990). IIASA-FAO, AEZ

  44. Agroclimatic Indices Example: FAO, etc.

  45. Based on Understanding of plants, soil, weather, management Calculate Water Growth, yield, fertilizer & water requirements, etc Carbon Require Information (inputs): weather, management, etc Nitrogen Crop Models

  46. Models – Advantages • Models are assisting tools, stakeholder interaction is essential • Models allow to ask “what if” questions, the relative benefit of alternative management can be highlighted: • Improve planning and decision making • Assist in applying lessons learned to policy issues • Models permit integration across scales, sectors, and users

  47. Models – Limitations • Models need to be calibrated and validated to represent reality • Models need data and technical expertise • Models alone do not provide an answer, stakeholder interaction is essential

  48. Can Optimal Management be an Adaptation Option for Maize Production in Argentina? Source Argentina 2º National communication

  49. Adaptation: Argentina Adaptation strategies in two locations of Argentina Increased inputs and improve management: • Planting date • Fertilizer • Irrigation Travasso et al., 2006

  50. Can Adaptation be Achieved by Optimizing Crop Varieties? Optimizing crop varieties Maize >P1 Juvenile phase Wheat >P1D photoperiodic sensitivity

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