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GLOBIOM Methodology and implementation

GLOBIOM Methodology and implementation. P. Havlík , M. Herrero , H. Valin , M. Obersteiner International Institute for Applied Systems Analysis (IIASA), Austria International Livestock Research Institute (ILRI), Kenya.

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GLOBIOM Methodology and implementation

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  1. GLOBIOMMethodology and implementation P. Havlík, M. Herrero, H. Valin, M. Obersteiner International Institute for Applied Systems Analysis (IIASA), Austria International Livestock Research Institute (ILRI), Kenya • Agrimonde-Terra:Animal Productions. Food and feed future demand. CIRAD Paris, February 13, 2013

  2. Outline • Model overview • Livestock sector modelling • Scenarios (SSPs) • Results • 5. Conclusions

  3. 1. Model overview

  4. GLOBIOM: Global Biosphere Management Model Partial equilibrium model: Agriculture, Forestry, Bioenergy DEMAND SUPPLY

  5. GLOBIOM Spatial equilibrium model a la Takayama & Judge Maximization of the social welfare (PS + CS) Recursively dynamic (10 year periods) Supply functions implicit – based on spatially explicit Leontief production functions: production system 1 (grass based)  productivity 1 + constant cost 1 production system 2 (mixed)  productivity 2 + constant cost 2 Demand functions explicit: linearized non-linear functions

  6. Supply Chains Wood products Sawn wood Pulp LAND USE CHANGE Natural Forests Wood Processing Bioenergy Bioethanol Biodiesel Methanol Heat Electricity Biogas Managed Forests Short Rotation Tree Plantations Bioenergy Processing Crops Corn Wheat Cassava Potatoes Rapeseed etc… Cropland Grassland Livestock Feeding Livestock products Beef Lamb Pork Poultry Eggs Milk Other natural land

  7. Main exogenous drivers: Population GDP Technological change Bio-energy demand (POLES team) Diets (FAO, 2006) Output:Production Q - land use (change) - water use - GHG, - other environment (nutrient cycle, biodiversity,…) Consumption Q Prices Trade flows

  8. Spatial resolution Homogeneous response units (HRU) – clusters of 5 arcmin pixels Source: Skalský et al. (2008)

  9. Spatial resolution > 200 000 SimU Simulation Units (SimU) = HRU & PX30 & Country zone Source: Skalský et al. (2008)

  10. Crops - EPIC Processes • Weather • Hydrology • Erosion • Carbon sequestration • Crop growth • Crop rotations • Fertilization • Tillage • Irrigation • Drainage • Pesticide • Grazing • Manure Major outputs: Crop yields, Environmental effects (e.g. soil carbon, nitrogen leaching) 20 crops (>75% of harvested area) 4 management systems: High input, Low input, Irrigated, Subsistence

  11. Crops - EPIC Relative Difference in Means (2050/2100) in Wheat Yields [Data: Tyndall, Afi Scenario, simulation model: EPIC]

  12. Grasslands – CENTURY/EPIC Source: EPIC model (t/ha DM)

  13. Forests – G4M Downscaling FAO country level information and forest growth functions estimated from yield tables Source: Kindermann et al. (2008)

  14. 2. Livestock in GLOBIOM

  15. Gridded Livestock of the World – Robinson et al. (2011)

  16. Livestock production systems distribution Sere and Steinfeld (1996) classification updated by Robinson et al. (2011)

  17. Livestock sector coverage Livestock categories: Bovines: Dairy & Other Sheep & Goats: Dairy & Other Poultry: Laying hens, Broilers, Mixed Pigs Production systems: Ruminats Grass based: Arid, Humid, Temperate/Highlands Mixed crop-livestock: Arid, Humid, Temperate/Highlands Monogastrics Smallholders Industrial

  18. Production systems parameterization Herrero, Havlíket al. forthcoming

  19. Production systems parameters Herrero, Havlíket al. forthcoming

  20. Feed intensity of milk production Herrero, Havlik et al (forthcoming)

  21. Non-CO2 intensity of milk production Herrero, Havlik et al (forthcoming)

  22. 3. Scenarios

  23. IAM & IAV (“IPCC”)scenarios matrix approach SSPs x RCPs https://secure.iiasa.ac.at/web-apps/ene/SspDb/dsd?Action=htmlpage&page=about

  24. 5 SSPsalong 2 dimensions

  25. Shared Socioeconomic reference Pathways (SSPs). (O’Neil, 2012)

  26. World population

  27. World GDP per capita

  28. Semi-quantitative elements: Land use and Agriculture

  29. Crop yield development

  30. Projected feed conversion efficiencies [kg protein product / kg protein feed]

  31. Human diet preferences [kcal/cap/day]

  32. Losses and wastes development in the Oilseeds&Pulses sector [%]

  33. 4. Results

  34. Consumption per capita – Ruminant meat – World [kg/cap/y]

  35. Consumption per capita – Monogastric meat – World [kg/cap/y]

  36. Consumption per capita – Dairy – World [kg/cap/y]

  37. Animal calorie consumption in 2050 [kcal/cap/day]

  38. Production – Ruminant meat – World [000 tonnes]

  39. Production – Monogastric meat – World [000 tonnes]

  40. Production – Dairy – World [000 tonnes]

  41. Feed – Coarse grains – World [000 tonnes]

  42. Production – Coarse grains – World [000 tonnes]

  43. Area – Coarse grains – World [mio ha]

  44. Commodity price index

  45. Bovine meat exports [000 tonnes]

  46. Bovine meat imports [000 tonnes]

  47. Bovine meat production by system [000 tonnes]

  48. Average crop yield change over 2000-2050 [%]

  49. Additional nitrogen consumption compared to 2000 [%]

  50. Additional irrigation water consumption compared to 2000 [%]

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