Asic2012 final

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  • Scenario A2Heterogeneous worldIncreasing global populationEconomics development is primarily regionally orientedTechnological change area more fragmented.
  • Verificar areas
  • El mapeo global (figura 2) indica que las zonas productoras de café con altos porcentajes de aptitud actualmente se distribuyen entre los rangos de 600 – 1900m.s.n.m, alturas superiores e inferiores presentan de medio a bajos promedios de aptitud dependiendo de la latitud del país y topografía del terrenoAccording  Temperatures increase and the average increase is 2 ºC passing through an increment of 1.2 ºC in 2030continua la variation de la estacionalidad de la precipitación. 
  • The summary climate characteristics for all coffee factory sites in Central America and MexicoMonthly precipitation is represented by bars and monthly mean temperatures by lines for the three time points (present, 2030 and 2050). The figure illustrates a constant increase of temperature through time. The plus (+) and minus (-) signs on the bars symbolize the increase and decrease of monthly precipitation for the year 2050 with reference to the present climate according to WorldClim (climate data for the period 1950 – 2000).
  • Relation between the suitability of the coffee production areas and the altitude for the current climate (blue line) and forecasts for 2050 (red line) in Central America. The gray lines indicate the projection of the different GCMs.
  • The regression analysis identified primarily the bioclimatic variables related to precipitation increase and the general increasing temperature as drivers of the predicted suitability shifts. This analysis was done taking into account presence points of the crops under study. Cannell, 1974, sugiere que el estado hídrico de la planta juega un papel predominante en la regulación del ciclo estacional del crecimiento y floración del café. Contribution of different bioclimatic variables to the predicted shift in suitability decrease for Arabica Coffee in Tanzania, between today and the 2050s. The value of R2 and the standardized coefficients β inform on the relative contribution and importance of each independent variable with respect to a specific region.
  • Asic2012 final

    1. 1. Global Impact of Climate Change on Coffee ProductionC Bunn and O Ovalle with P Läderach, A Mosnier, M ObersteinerThe 24th International Conference on Coffee Science ASIC, Costa Rica, November 2012 Pic by Neil Palmer (CIAT)
    2. 2. About CIAT International Center for Tropical Agriculture • CIAT: One of 15 CGIAR Centers • Mission: To reduce hunger and poverty, and improve human health in the tropics through research aimed at increasing the eco-efficiency of agriculture. • Coffee: About 35 researchers work in Leader DAPA: Dr. Andrew Jarvis two fields, access to high value markets and vulnerability to climate change. …about 100 researchers CIAT/DAPA - Lead Center of CCAFS
    3. 3. About CIAT
    4. 4. Intro Perceptions "El clima se ha convertido en impredecible, ahora llueve menos y muy irregular, mi rendimiento ha disminuido y tengo más problemas de plagas y enfermedades." Don Pedro, Nicaragua, Madriz, Enero, 2010 ©Neil Palmer
    5. 5. Intro Perceptions ©Neil Palmer
    6. 6. Outline• Global Impact of Climate Change on Coffee Suitability OVALLE-RIVERA, Oriana, LÄDERACH, Peter, BUNN, Christian• Integrated CC Impact Assessment of the Coffee sector BUNN, Christian, MOSNIER, Aline, OVALLE-RIVERA, Oriana, LÄDERACH, Peter, OBERSTEINER, Michael ©Neil Palmer
    7. 7. Outline Sequential Modelling approach • Spatially Explicit Impacts • Land Use Change
    8. 8. Outline Global Impact of Climate Change on Coffee Suitability OVALLE-RIVERA, Oriana, LÄDERACH, Peter, BUNN, Christian
    9. 9. Framework The socio-economic impact of climate changeCoffee Suitability production Global Impact of CC on on Mesoamerican coffee Objective Predict the global impact of climate change on coffee suitability. Area of study – GPS-referenced locations are distributed over 19 countries
    10. 10. Methodology Overall Approach change on Mesoamerican coffee production The socio-economic impact of climate Worldclim – Current Geo-referenced Climate Coffee farms. Global Climate ModelInputs (19 bioclimatic (GCM) Outputs – variables) SRES_A2 2030 2050 Species Distribution StatisticalProcess Modeling –MaxEnt Downscaling of β r=o.o5 Back =20000 Climate Information Future Climates Coffee Suitability at Local scaleOutput
    11. 11. Results socio-economic impactParameterizationMesoamerican coffee production The MaxEnt - of climate change on >10000 “background” may be needed if the number of presence points is large (Phillips & Dudı 2008)
    12. 12. Results socio-economic impact of climate change on Mesoamerican coffee production The
    13. 13. Results socio-economic impact of climate change on Mesoamerican coffee production The
    14. 14. Results socio-economic impact of climate change on Mesoamerican coffee production The Global Coffee Suitability Map
    15. 15. Results socio-economic impact of climate change on Mesoamerican coffee production The Global Coffee Suitability Map / Zone
    16. 16. Results socio-economic impact of climate change on Mesoamerican coffee production The Global Coffee Suitability Map / Zone 1. Central America and Mexico coffee farms 2030 2050 Annual average temperature change + 1,4 °C + 2,1°C Annual change in precipitation - 50 mm - 70 mm
    17. 17. Results socio-economic impact of climate change on Mesoamerican coffee production The Global Coffee Suitability Map / Zone 1
    18. 18. Results socio-economic impact Analysis of MaxEnt Mesoamerican multiple GCMs The Uncertainty of climate change on output using coffee production
    19. 19. Results socio-economic impact of climate change on Mesoamerican coffee production The Environmental factors which drive the suitability of coffee (Zone1) High Low  Regression analysis of variables: Higher temperature and Changes in Precipitation drive change Fore sign of impact depends on altitude
    20. 20. Summary The socio-economic impact of climate change on Mesoamerican coffee production Conclusions  Impacts are site specific Low altitudes lose most Countries with available area in high altitudes gain  Higher temperature and Changes in Precipitation patterns drive change  Maxent modeling should be done on a high resolution  For sub-regional impact assessments local models are recommended
    21. 21. Outline Integrated CC Impact Assessment of the Coffee sector BUNN, Christian, MOSNIER, Aline, OVALLE-RIVERA, Oriana, LÄDERACH, Peter, OBERSTEINER, Michael
    22. 22. Outline Sequential Modelling approach • Spatially Explicit Impacts • Land Use Change
    23. 23. Motivation The suitability for coffee production is changing How does Arabica production change relative to Robusta? Where are future production regions? Is there pressure on deforestation?
    24. 24. Objectives • Demonstrate SDM approach for integrated impact modeling • Combine impacts on coffee with impacts in other sectors to model interactions • Compare Scenarios, Policies and economic implications
    25. 25. Globiom Partial Equilibrium Modeling DEMAND Exogenous drivers Population, GDP Wood products Food Bioenergy Process PROCESS 28 Primary Crops regions wood SUPPLY products HRU = Altitude & Slope & Soil Aggregation in larger units Altitude class, Slope class, AGRICULTURE FORESTRY PX5 Soil Class (max 200*200 km) PX5 Altitude class (m): 0 – 300, 300 – 600, 600 – 1200, 1200 – 2500 and > 2500; Slope class (deg): 0 – 3, 3 – 6, 6 – 10, 10 – 15, 15 – 30, 30 – 50 and > 50; SPATIALLY EXPLICIT INPUT DATA Soil texture class: coarse, medium, fine, stony and peat; Biophysical EPIC G4M RUMINANT Between 10*10 km and 50*50 models km Managemen Land Climate Soil and topography t cover
    26. 26. Globiom Coffee Integration • Model impacts on Robusta – Similar to Arabica impact model • Model Spatially explicit area data – Downscaling of FAO data using USDA information • Model Spatially explicit yield data – Derive a function dependent on suitability
    27. 27. Robusta Global CC Impacts Ovalle et al 2012
    28. 28. Downscaling
    29. 29. Downscaling
    30. 30. Downscaling •
    31. 31. Yield Potential
    32. 32. Globiom Macro Scenario • A2 – Scenario Increasing Population Regional Economic development • Three climate models CNRM CM3 MRI CGCM 2.3.2 UKMO HadGem1 Baseline
    33. 33. Globiom Key Results
    34. 34. Globiom Key Results
    35. 35. Globiom Key Results
    36. 36. Next Steps Upcoming Projects Upcoming Projects • Evaluate Adaptation policies • Include a process model of coffee • Differentiate demand • More data • Data on CO2 stocks and Fertilizer use • Regional Trade-off model of Adaptation and Mitigation • Water constraint
    37. 37. SummarySummary Conclusion • Species distribution Modeling can be used for integrated CC Assessments with little prior knowledge • Without market differentiation Robusta will be the dominant crop • Asia may be a climate change winner, Brazil a loser • R&D in coffee will be the key to Adaptation
    38. 38. Global Impact of Climate Change on Coffee ProductionC Bunn and O Ovalle with P Läderach, A Mosnier, M ObersteinerThe 24th International Conference on Coffee Science ASIC, Costa Rica, November 2012 ¡Gracias!Peter Läderach (CIAT)p.laderach@cgiar.orgOriana Ovalle (CIAT)o.ovalle@cgiar.orgChristian Bunn (CIAT/HU Berlin)Christian.Bunn@HU-Berlin.de Pic by Neil Palmer (CIAT)

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