GLOBIOM Methodology and implementation
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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 Agrimonde-Terra: Animal Productions. Food and feed future demand. CIRAD Paris, February 13, 2013
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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. - PowerPoint PPT Presentation
Transcript of GLOBIOM Methodology and implementation
GLOBIOMMethodology and implementation
P. Havlík, M. Herrero, H. Valin, M. ObersteinerInternational Institute for Applied Systems Analysis (IIASA), AustriaInternational Livestock Research Institute (ILRI), Kenya
Agrimonde-Terra: Animal Productions. Food and feed future demand. CIRAD Paris, February 13, 2013
Havlík et al. GLOBIOM: Methodology and implementationAgrimonde-Terra, CIRAD Paris, February 13, 2013
Outline
1. Model overview
2. Livestock sector modelling
3. Scenarios (SSPs)
4. Results
5. Conclusions
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1. Model overview
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Havlík et al. GLOBIOM: Methodology and implementationAgrimonde-Terra, CIRAD Paris, February 13, 2013
GLOBIOM: Global Biosphere Management ModelPartial equilibrium model: Agriculture, Forestry, Bioenergy
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DEMAND
SUPPLY
Havlík et al. GLOBIOM: Methodology and implementationAgrimonde-Terra, CIRAD Paris, February 13, 2013
Supply functionsimplicit – based on spatially explicit Leontief production functions:
production system 1 (grass based) productivity 1 + constant cost 1production system 2 (mixed) productivity 2 + constant cost 2
Demand functions explicit: linearized non-linear functions
GLOBIOM
Spatial equilibrium model a la Takayama & Judge
Maximization of the social welfare (PS + CS)
Recursively dynamic (10 year periods)
eqqpp /1)ˆ/(*ˆ
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Havlík et al. GLOBIOM: Methodology and implementationAgrimonde-Terra, CIRAD Paris, February 13, 2013
Supply Chains
Natural Forests
Managed Forests
Short Rotation Tree Plantations
Cropland
Grassland
Other natural land
Bioenergy
Bioethanol Biodiesel MethanolHeatElectricityBiogas
Wood products
Sawn woodPulp
Livestock products
BeefLambPorkPoultryEggsMilk
CropsCornWheatCassavaPotatoesRapeseedetc…
LAND
USE
CHA
NGE
Wood Processing
Bioenergy Processing
Livestock Feeding
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Output: Production Q - land use (change) - water use- GHG, - other environment (nutrient cycle, biodiversity,…)
Consumption QPricesTrade flows
Main exogenous drivers: PopulationGDPTechnological changeBio-energy demand (POLES team)Diets (FAO, 2006)
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Havlík et al. GLOBIOM: Methodology and implementationAgrimonde-Terra, CIRAD Paris, February 13, 2013
PX5
Altitude class, Slope class, Soil Class
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;Soil texture class: coarse, medium, fine, stony and peat;
HRU = Altitude & Slope & Soil
Spatial resolutionHomogeneous response units (HRU) – clusters of 5 arcmin pixels
Source: Skalský et al. (2008)
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Havlík et al. GLOBIOM: Methodology and implementationAgrimonde-Terra, CIRAD Paris, February 13, 2013
Simulation Units (SimU) = HRU & PX30 & Country zone
Source: Skalský et al. (2008)
Country HRU*PX30
PX5
SimU delineation relatedstatistics on LC classes and
Cropland management systems
reference for geo-coded data on crop management;
input statistical data for LC/LU economic optimization;
LC&LUstat> 200 000 SimU
Spatial resolution
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EPIC
Rain, Snow, Chemicals
Subsurface FlowSurface
Flow
Below Root Zone
Evaporation and
Transpiration
• Weather• Hydrology• Erosion• Carbon sequestration• Crop growth• Crop rotations• Fertilization• Tillage• Irrigation• Drainage• Pesticide• Grazing• Manure
Processes
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
Crops - EPIC
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Relative Difference in Means (2050/2100) in Wheat Yields[Data: Tyndall, Afi Scenario, simulation model: EPIC]
Crops - EPIC
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Source: EPIC model(t/ha DM)
Grasslands – CENTURY/EPIC
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Downscaling FAO country level information and forest growthfunctions estimated from yield tables
Source: Kindermann et al. (2008)
Forests – G4M
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2. Livestock in GLOBIOM
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Gridded Livestock of the World – Robinson et al. (2011)
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Livestock production systems distributionSere and Steinfeld (1996) classification updated by Robinson et al. (2011)
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Livestock sector coverage
Livestock categories: Bovines: Dairy & OtherSheep & Goats: Dairy & OtherPoultry: Laying hens, Broilers, MixedPigs
Production systems:
Ruminats Grass based: Arid, Humid, Temperate/HighlandsMixed crop-livestock: Arid, Humid, Temperate/Highlands
MonogastricsSmallholdersIndustrial
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Herrero, Havlík et al. forthcoming
Production systems parameterization
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Livestock numbers 1000TLUProductivity kg/tlu/yFEED GHG emissionsGRAZING kgDM/tlu/y Manure kgDM/tlu/ySTOVER kgDM/tlu/y N_Excretion kg/tlu/yOCCASIONAL kgDM/tlu/y Entferm_CH4 kgCO2eq/tlu/yGRAINS kgDM/tlu/y ManmgtTot_CH4 kgCO2eq/tlu/yBarl kgDM/tlu/y ManmgtTot_N2O kgCO2eq/tlu/yCorn kgDM/tlu/y MansolTot_N2O kgCO2eq/tlu/yPuls kgDM/tlu/y ManaplTot_N2O kgCO2eq/tlu/yRice kgDM/tlu/y ManprpTot_N2O kgCO2eq/tlu/ySgMi kgDM/tlu/ySoya kgDM/tlu/yWhea kgDM/tlu/yCerO kgDM/tlu/yOlsO kgDM/tlu/yCrpO kgDM/tlu/yAnim kgDM/tlu/y
Production systems parameters
Herrero, Havlík et al. forthcoming
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Herrero, Havlik et al (forthcoming)
Feed intensity of milk production
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Herrero, Havlik et al (forthcoming)
Non-CO2 intensity of milk production
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3. Scenarios
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IAM & IAV (“IPCC”)scenarios matrix approach SSPs x RCPs
https://secure.iiasa.ac.at/web-apps/ene/SspDb/dsd?Action=htmlpage&page=about
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5 SSPs along 2 dimensions
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Shared Socioeconomic reference Pathways (SSPs).
(O’Neil, 2012)
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World population
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World GDP per capita
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Semi-quantitative elements: Land use and Agriculture
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Crop yield development
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Projected feed conversion efficiencies
[kg
prot
ein
prod
uct /
kg
prot
ein
feed
]
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Human diet preferences [kcal/cap/day]
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Losses and wastes development in the Oilseeds&Pulses sector [%]
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4. Results
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Consumption per capita – Ruminant meat – World [kg/cap/y]
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Consumption per capita – Monogastric meat – World [kg/cap/y]
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Consumption per capita – Dairy – World [kg/cap/y]
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Animal calorie consumption in 2050 [kcal/cap/day]
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Production – Ruminant meat – World [000 tonnes]
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Production – Monogastric meat – World [000 tonnes]
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Production – Dairy – World [000 tonnes]
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Feed – Coarse grains – World [000 tonnes]
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Production – Coarse grains – World [000 tonnes]
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Area – Coarse grains – World [mio ha]
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Commodity price index
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LatinAmericaCarib NorthAmerica Europe Oceania0
1000
2000
3000
4000
5000
6000
7000
SSP1SSP2SSP3
Bovine meat exports [000 tonnes]
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Bovine meat imports [000 tonnes]
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Bovine meat production by system [000 tonnes]
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Average crop yield change over 2000-2050 [%]
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Additional nitrogen consumption compared to 2000 [%]
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Additional irrigation water consumption compared to 2000 [%]
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Cropland expansion 2000-2050 [Mio Ha]
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Grassland expansion 2000-2050 [Mio Ha]
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Net forest area change 2000-2050 [Mio Ha]
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Greenhouse gas emissions - World [Mio tonnes CO2eq]
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5. Conclusions
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Further reading
AnimalChange deliverablesD2.1. Storylines for livestock sector scenarios in EU, studied SICA regions and global level, consistent with the IPCC AR5 detailed for the livestock sector
D2.2. Preliminary scenarios of the developments in agricultural commodity markets, livestock production systems, and land use and land cover
Journal articlesHavlík, P., Valin, H., Mosnier, A., Obersteiner, M., Baker, J. S., Herrero, M., Rufino, M. C. & Schmid, E. (2013). Crop Productivity and the Global Livestock Sector: Implications for Land Use Change and Greenhouse Gas Emissions. American Journal of Agricultural Economics 95 (2), 442—448.
Valin, H., Havlík, P., Mosnier, A., Herrero, M., Schmid E. and Obersteiner M. Agricultural productivity and greenhouse gas emissions: trade-offs or synergies between mitigation and food security? Environmental Research Letters, under review.
Havlík et al. GLOBIOM: Methodology and implementationAgrimonde-Terra, CIRAD Paris, February 13, 2013
Thank you !
