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

Outline
1. Introduction
2. Model overview
3. Foresight activities with GLOBIOM
4. Results: Foresight for socio-economic and climatic drivers
5. Summary and conclusion
2

Introduction
3

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
4

GLOBIOM
Model overview
5

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
6

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

Foresight activities
with GLOBIOM
8

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
9

Socio-economic drivers: SSPs
10

Combined socio-economic and climatic drivers
11

Results:
Foresight for socio-economic and climatic
drivers
12

SSP2: Global and regional trends in
agricultural markets
 Demand
13

14
 Supply

 Prices
15

Socio-economic development:
Effects on agricultural markets
16

Socio-economic development:
Forest markets
17

Climate change mitigation:
Market effects
18

19
Climate change mitigation:
Production effects

20
Impacts of climate change:
Food availability in SSA [kcal/cap/day]

Summary and conclusion
21

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

23
 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

Thank you
for your attention!
kleinwec@iiasa.ac.at
www.globiom.org