This document summarizes a presentation given by Ulrich Kleinwechter on the GLOBIOM model for long-term global agricultural and forestry sector outlook. GLOBIOM is a global partial equilibrium model that integrates agricultural and forest markets with biophysical crop, livestock, and forest models. IIASA has used GLOBIOM to conduct various foresight activities exploring the effects of socioeconomic drivers and climate change on agricultural production, trade, prices, land use and food availability through 2050 and 2100. The results show positive outlooks for food availability but increased emissions without mitigation efforts, and that socioeconomic factors have a greater influence on outcomes than climate impacts alone.
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4 Kleinwechter- Agriculture and Forest Sector Long-Term Outlook from GLOBIOM
1. Agriculture and Forest Sector
Long-Term Outlook from
GLOBIOM
Ulrich Kleinwechter
Ecosystems Services & Management Programme
International Institute for Applied Systems Analysis (IIASA), Austria
in collaboration with the IIASA Environmental Resources and
Development (ERD) Group
Strategic Foresight Conference
IFPRI, Washington D.C., 7 November 2014
2. Outline
1. Introduction
2. Model overview
3. Foresight activities with GLOBIOM
4. Results: Foresight for socio-economic and climatic drivers
5. Summary and conclusion
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4. IIASA
Founded in 1972 to use scientific
cooperation to build bridges across the
Cold War divide
Non-governmental institute: 22
National Member Organizations
representing Africa, Asia, Europe, and
the Americas
International interdisciplinary staff of
~150 Researchers
Construction and exploration of
models of complex socio-economic and
environmental systems to answer
global challenges
Laxenburg, (close toVienna), Austria
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6. GLOBIOM
Global scale agriculture and forest sector model based on detailed
spatial resolution (>200k cells)
Partial equilibrium
Agricultural, wood and bioenergy markets
30 world regions
Bilateral trade
Bottom-up approach
Explicit description of production technologies a la Leontief
Technologies specified by production system and grid cell
Main data source
FAOSTAT, complemented with bottom-up sectoral models for
production parameters
Base year: 2000
Time step: 10 years, time horizon: 2030/2050 but also 2100
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7. 7
18 crops (FAO + SPAM)
Wheat, Rice, Maize, Soybean,
Barley, Sorghum, Millet,
Cotton, Dry beans, Rapeseed,
Groundnut, Sugarcane,
Potatoes, Cassava,
Sunflower, Chickpeas, Palm
Fruit, Sweet potatoes
3 different systems
7 animals
(FAO + Gridded livestock)
Cattle & Buffalo
Sheep & Goat
Pig
Poultry
8 different systems
Downscaled FAO FRA at
grid level
Area
Carbon stock
Age
Tree size
Species
Rotation time
Thinning
Landuse
Land suitable for
Poplar
Pillow
Eucalyptus
Productivity from
literature
Cropland Grassland Managed forest
Global Land Cover 2000
Short rotation
plantations
Other natural
land
Natural
forest
Landcover
ECONOMIC MARKET + Spatial equilibrium trade PRICES
Markets
Food Fibers Energy
Demand
Industry
Population, GDP, preferences
BIOENERGY
Processing
MJ biofuel
MJ bioelectric
Coproducts
G4M
Global Forest model
Harvestable wood
Harvesting costs
EPIC
Rain, Snow,
Chemicals
Subsurface
Flow
Surface
Flow
Below Root
Zone
Evaporation
and
Transpiration
RUMINANT
Digestibility model
Feed intake
Animal production
GHG emissions
Production
9. Global and regional foresight activities
LEDPathways
Regional
scenarios
Regional food security under conditions of global
environmental and socio-economic change-
Livestock sector futures
Low emissions agricultural development pathways and
priorities for mitigation in agriculture
Global and EU food security
OECD Long term scenarios Model intercomparisons
IPCC scenario analysis
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22. 22
Generally positive outlook for food availability by 2050 under SSP 2
Albeit at cost of LUC and high emissions, if unabated
Contingency of agricultural development on SSP
Market effects of climate change mitigation
Price increases & reductions in calorie availability
Production effects of climate change mitigation
Changes in production levels, production system transitions, spatial
reallocation
Effects of socio-economic development dominate climate change
impacts
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GLOBIOM provides integration of agriculture and forest
sectors in a comprehensive framework
Links with biophysical models (EPIC, RUMINANT, G4M)
Extensions: GHG emissions accounting, input use (fertilizer,
water), food security
Possibility for regional zooming-in
E.g. Congo Basin, Brazil
Disaggregation of production with high spatial resolution
and along production systems
=> Potential for applications to technology assessment and
priority setting