Agriculture and Forest Sector Long-Term Outlook from GLOBIOM

Ulrich Kleinwechter

Ecosystems Services & Management ProgrammeInternational Institute for Applied Systems Analysis (IIASA), Austria

in collaboration with the IIASA Environmental Resources and Development (ERD) Group

Strategic Foresight ConferenceIFPRI, 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

GLOBIOMModel overview

5

GLOBIOM

Global scale agriculture and forest sector model based on detailedspatial 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 & BuffaloSheep & Goat

PigPoultry

8 different systems

Downscaled FAO FRA at grid level

AreaCarbon stock

AgeTree sizeSpecies

Rotation timeThinning

Land

use Land suitable for

PoplarPillow

Eucalyptus

Productivity from literature

Cropland Grassland Managed forest

Global Land Cover 2000

Short rotation plantations

Other naturalland

Natural forest

Land

cov

er

ECONOMIC MARKET + Spatial equilibrium trade PRICES

Mar

kets

Food Fibers EnergyDem

and

Industry

Population, GDP, preferences

BIOENERGYProcessing

MJ biofuelMJ bioelectricCoproducts

G4MGlobal Forest model

Harvestable wood Harvesting costs

EPIC

Rain, Snow, Chemicals

Subsurface Flow

Surface Flow

Below Root Zone

Evaporation and

Transpiration

RUMINANTDigestibility model

Feed intake Animal production GHG emissions

Pro

duct

ion

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

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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