EUFASOM – Inputs, Outputs, EUFASOM – Inputs, Outputs, Linkage OptionsLinkage Options

CCTAME – Kick-Off MeetingCCTAME – Kick-Off Meeting

Uwe A. SchneiderUwe A. Schneider

Research Unit Sustainability and Global Change, Hamburg UniversityResearch Unit Sustainability and Global Change, Hamburg University

Contributions fromContributions from

Contributors: E. Schmid, O. Franklin, C.I. Ramos, C. Schleupner, K. Contributors: E. Schmid, O. Franklin, C.I. Ramos, C. Schleupner, K. Jantke, R. Skalsky, J. Balkovic, P. Havlik, I. Huck, A. Moseyev, A.M.I. Jantke, R. Skalsky, J. Balkovic, P. Havlik, I. Huck, A. Moseyev, A.M.I.

Kallio, M. Obersteiner, S. de Cara, B. McCarl, S. FritzKallio, M. Obersteiner, S. de Cara, B. McCarl, S. Fritz

Forest and Agricultural Sector Forest and Agricultural Sector Optimization Model - FASOMOptimization Model - FASOM

Partial Equilibrium, Partial Equilibrium, Bottom-UpBottom-Up Model Model Maximizes sum of consumer and producer Maximizes sum of consumer and producer

surplussurplusConstrained by resource endowments, Constrained by resource endowments,

technologies, policiestechnologies, policiesSpatially explicit, discrete dynamicSpatially explicit, discrete dynamic Integrates environmental effectsIntegrates environmental effectsProgrammed in GAMSProgrammed in GAMS

Land use competition

FASOM HistoryFASOM History

US (1993)US (1993)

EU (2004)EU (2004)

Global (2006)Global (2006)

FASOM FASOM StructureStructure

Resources Land Use

Technologies

Processing Technologies

Products Markets

Inputs

Limits

Supply Functions

Limits

Demand Functions,Trade

Limits

Environmental Impacts

Scientific QuestionsScientific Questions

Mitigation Potential of Climate Policies?Mitigation Potential of Climate Policies?

Land Management Adaptation?Land Management Adaptation?

Commodity Market Impacts?Commodity Market Impacts?

Environmental Side Effects?Environmental Side Effects?

Social Side Effects?Social Side Effects?

ChallengesChallenges

Heterogeneity (Resources, Technologies)Heterogeneity (Resources, Technologies)

Complexity (Mitigation Options, Markets, Complexity (Mitigation Options, Markets, Externalities, Policies)Externalities, Policies)

Global ScopeGlobal Scope

FASOM - Spatial Resolution of Input DataFASOM - Spatial Resolution of Input Data

Soil textureSoil textureStone contentStone contentAltitude levelsAltitude levelsSlopesSlopesSoil stateSoil state

Political regionsPolitical regions Ownership (forests)Ownership (forests) Farm typesFarm types Farm sizeFarm size

Many crop and tree Many crop and tree speciesspecies

Tillage, planting Tillage, planting irrigation, fertilization irrigation, fertilization harvest regimeharvest regime

Altitude:1. < 300 m2. 300-600 m3. 600-1100 m4. >1100 m

Texture:1. Coarse2. Medium3. Medium-fine4. Fine 5. Very fine

Soil Depth:1. shallow2. medium3. deep

Stoniness:1. Low content2. Medium content3. High content

Slope Class:1. 0-3%2. 3-6%3. 6-10%4. 10-15%5. …

Homogeneous Homogeneous Response UnitsResponse Units

DE13

DE12

DE11

DE14

EUFASOM DynamicsEUFASOM Dynamics

5 (to 20) year time steps5 (to 20) year time stepsState of forests (and soil organic matter)State of forests (and soil organic matter)Technical progressTechnical progressDemand & industry growthDemand & industry growthResource and global changeResource and global changePolicy scenariosPolicy scenarios

EUFASOM – Input DataEUFASOM – Input Data

Resource DataResource Data

Technological DataTechnological Data

Market & Policy DataMarket & Policy Data

EUFASOM DataEUFASOM DataFOREST_DATA(PERIOD,REGION,SOILTYPE,SOILSTATE,SPECIES,FARM,AGE,ALLTECH,ALLITEM)

PEREN_DATA (PERIOD,REGION,SOILTYPE,SOILSTATE,SPECIES,FARM,AGE,ALLTECH,ALLITEM)

CROP_DATA (PERIOD,REGION,SOILTYPE,SOILSTATE,SPECIES,FARM,ALLTECH,ALLITEM)

ECO_DATA (PERIOD,REGION,SOILTYPE,SOILSTATE,ALLTECH,ALLITEM)

LIVE_DATA (PERIOD,REGION,ANIMAL,ALLTECH,ALLITEM)

FEED_DATA (PERIOD,REGION,PRODUCT,ALLTECH,ALLITEM)

PROCESS_DATA (PERIOD,REGION,ALLTECH,ALLITEM)

PRODUCT_DATA (PERIOD,REGION,PRODUCT,ALLITEM)

MARKET_DATA (PERIOD,REGION,ALLITEM,SDTYPE,SDITEM)

TRADE_DATA (PERIOD,REGION,REGION,PRODUCT,ALLITEM)

RESOURCE_DATA (PERIOD,REGION,ALLRESOURCE,SDITEM)

STOCK_DATA (PERIOD,REGION,PRODUCT,ALLITEM)

LUC_DATA (PERIOD,REGION,SOILTYPE,SPECIES,ALLCHANGE,ALLITEM)

Czec.2040_45.Spruce.200-205.NoThin.SWSawLogs 613.3046Czec.2040_45.Spruce.200-205.NoThin.SWSawLogs 613.3046Czec.2040_45.Spruce.200-205.NoThin.SWPulpLogs 32.2792Czec.2040_45.Spruce.200-205.NoThin.SWPulpLogs 32.2792Czec.2040_45.Spruce.200-205.NoThin.AgeValue 165.5000Czec.2040_45.Spruce.200-205.NoThin.AgeValue 165.5000Czec.2040_45.Spruce.200-205.NoThin.Area 2459.4700Czec.2040_45.Spruce.200-205.NoThin.Area 2459.4700Czec.2040_45.Spruce.200-205.NoThin.Carbon 183.1328Czec.2040_45.Spruce.200-205.NoThin.Carbon 183.1328Czec.2040_45.Spruce.200-205.NoThin.TreeNumber 146.4092Czec.2040_45.Spruce.200-205.NoThin.TreeNumber 146.4092Czec.2040_45.Spruce.200-205.NoThin.TotalBiomass 366.2655Czec.2040_45.Spruce.200-205.NoThin.TotalBiomass 366.2655Czec.2040_45.Spruce.200-205.NoThin.StemBiomass 245.3218Czec.2040_45.Spruce.200-205.NoThin.StemBiomass 245.3218Czec.2040_45.Spruce.200-205.NoThin.BranchBiomass 62.8024Czec.2040_45.Spruce.200-205.NoThin.BranchBiomass 62.8024Czec.2040_45.Spruce.200-205.NoThin.DeadWoodmass 37.5675Czec.2040_45.Spruce.200-205.NoThin.DeadWoodmass 37.5675Czec.2040_45.Spruce.200-205.NoThin.DecompRate 0.0440Czec.2040_45.Spruce.200-205.NoThin.DecompRate 0.0440Czec.2040_45.Spruce.200-205.NoThin.FinalHarvBiomass 245.3218Czec.2040_45.Spruce.200-205.NoThin.FinalHarvBiomass 245.3218Czec.2040_45.Spruce.200-205.NoThin.MeanTreeHarvBM 1.7540Czec.2040_45.Spruce.200-205.NoThin.MeanTreeHarvBM 1.7540Czec.2040_45.Spruce.200-205.NoThin.HarvestLabour 24.4956Czec.2040_45.Spruce.200-205.NoThin.HarvestLabour 24.4956Czec.2040_45.Spruce.200-205.NoThin.HarvestCost 2598.5695Czec.2040_45.Spruce.200-205.NoThin.HarvestCost 2598.5695Czec.2040_45.Spruce.200-205.NoThin.HarvestDiesel 1123.2615Czec.2040_45.Spruce.200-205.NoThin.HarvestDiesel 1123.2615

Forest Management DataForest Management Data

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Corn 9.4582FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Corn 9.4582

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Land 2959.6516FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Land 2959.6516

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Cost 559.7052FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Cost 559.7052

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.FarmLabour 61.6533FRAN.LT300.Crop.MDHG.Corn.RfCvSt.FarmLabour 61.6533

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.HiredLabour 35.7446FRAN.LT300.Crop.MDHG.Corn.RfCvSt.HiredLabour 35.7446

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Fertilizer 191.4397FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Fertilizer 191.4397

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Pesticides 110.2057FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Pesticides 110.2057

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Seed 121.9582FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Seed 121.9582

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Fuel 51.5004FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Fuel 51.5004

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Rent 127.1415FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Rent 127.1415

FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Wage 7.5052FRAN.LT300.Crop.MDHG.Corn.RfCvSt.Wage 7.5052

Crop Management DataCrop Management Data

EUFASOM – Output DataEUFASOM – Output Data

Resource UsageResource Usage

Land Use DistributionLand Use Distribution

Market Prices, TradeMarket Prices, Trade

EUFASOM EquationsEUFASOM EquationsOBJECTIVE_EQU

RESOURCEBAL_EQU (PERIOD,REGION,RESOURCE)

RESOURCEMAX_EQU (PERIOD,REGION,RESOURCE)

LUC_EQU (PERIOD,REGION,SOILTYPE,SPECIES,CHANGE)

LUCLIMIT_EQU (PERIOD,REGION,SOILTYPE,SPECIES,CHANGE)

SOILSTATE_EQU (PERIOD,REGION,SOILTYPE,SOILSTATE)

FORINVENT_EQU (PERIOD,REGION,SOILTYPE,SOILSTATE,SPECIES,OWNER,AGE,FORTECH)

STOCK_EQU (PERIOD,REGION,STOCK)

EMIT_EQU (PERIOD,REGION,SUBSTANCE)

PRODUCTBAL_EQU (PERIOD,REGION,PRODUCT)

MINFEED_EQU (PERIOD,REGION,ANIMAL,NUTRIENT)

MAXFEED_EQU (PERIOD,REGION,ANIMAL,NUTRIENT)

EUFASOM VariablesEUFASOM VariablesFOREST_VAR (PERIOD,REGION,SOILTYPE,SOILSTATE,SPECIES,OWNER,AGE,FORTECH)

PEREN_VAR (PERIOD,REGION,SOILTYPE,SOILSTATE,SPECIES,FARM,AGE,CROPTECH)

CROP_VAR (PERIOD,REGION,SOILTYPE,SOILSTATE,SPECIES,FARM,CROPTECH)

ECO_VAR (PERIOD,REGION,SOILTYPE,SOILSTATE,ECOTECH)

RESOURCE_VAR (PERIOD,REGION,RESOURCE)

LUC_VAR (PERIOD,REGION,SOILTYPE,SPECIES,CHANGE)

EMIT_VAR (PERIOD,REGION,SUBSTANCE)

LIVE_VAR (PERIOD,REGION,ANIMAL,LIVETECH)

FEED_VAR (PERIOD,REGION,ANIMAL,PRODUCT,FEEDTECH)

PROCESS_VAR (PERIOD,REGION,PROCTECH)

DEMAND_VAR (PERIOD,REGION,PRODUCT)

SUPPLY_VAR (PERIOD,REGION,PRODUCT)

TRADE_VAR (PERIOD,REGION,REGION,PRODUCT)

I I European Agricultural European Agricultural

Sector ResultsSector Results

2010 EU Bioenergy Targets2010 EU Bioenergy Targets

21% Renewable Electricity 21% Renewable Electricity

≈ ≈ 610 thousand GWh610 thousand GWh

≈ ≈ 300 million wet tons of 300 million wet tons of biomassbiomass

5.75% Bio-Fuels5.75% Bio-Fuels

Biomass Crop Share for 300 Mt TargetBiomass Crop Share for 300 Mt Target

0

25

50

75

100

Climate MitigationClimate Mitigationvs. vs.

BiodiversityBiodiversity ProtectionProtection

2010 EU Biodiversity Targets2010 EU Biodiversity Targets

2001: European Council committed to ‘2001: European Council committed to ‘halt the halt the decline of biodiversity by 2010decline of biodiversity by 2010’ in Europe ’ in Europe

2002: EU joined about 130 countries in 2002: EU joined about 130 countries in agreeing ‘agreeing ‘to significantly reduce the rate of to significantly reduce the rate of biodiversity loss by 2010biodiversity loss by 2010‘ worldwide‘ worldwide

BUTBUT

Biodiversity loss still accelerating Biodiversity loss still accelerating Reservation often ad hoc and uncoordinatedReservation often ad hoc and uncoordinated 2010 only three years away2010 only three years away

Habitat NeedsHabitat Needs

Simulations with the independent 69 species Simulations with the independent 69 species based habitat module of EUFASOM show based habitat module of EUFASOM show that 10, 20, 30, 40 viable populations for that 10, 20, 30, 40 viable populations for each species require 22, 35, 42, and 61 each species require 22, 35, 42, and 61 million hectares, respectively, in specific million hectares, respectively, in specific locationslocations

Wetland Area Share for a 40 Mha TargetWetland Area Share for a 40 Mha Target

0

25

50

75

100

Biomass Crop Share for 300 Mt TargetBiomass Crop Share for 300 Mt Target

0

25

50

75

100

EU25 Bioenergy PotentialsEU25 Bioenergy Potentials

0

100

200

300

400

500

600

0 50 100 150 200 250 300 350 400

Mar

gina

l Bio

mas

s C

osts

in E

uro/

ton

European Biomass Production in million wet tons

10 Mha

30 Mha

Wetland Requirement = 40 Mha

Wetland Wetland DownscalingDownscaling

Source: Schleupner and Schneider (2008), A cost-efficient spatial wetland site-selection model for European biotope restoration, http://www.fnu.zmaw.de/

Link to other modelsLink to other models

Climate Models Indirect link

Geographic Assessments upscaling downscaling

Biophysical Models Environmental impacts

Agro-Economic Models Consistency between farm level and sector level models

Full Economy Models Exogenous drivers Response functions

II II US Agricultural US Agricultural Sector ResultsSector Results

Mainly based on McCarl and Schneider (2001). Greenhouse Gas Mainly based on McCarl and Schneider (2001). Greenhouse Gas Mitigation in U.S.Agriculture and Forestry. Mitigation in U.S.Agriculture and Forestry. SCIENCESCIENCE 294:2481-2481. 294:2481-2481.

US Agricultural MitigationUS Agricultural Mitigation

0

50

100

150

200

250

300

350

400

450

500

0 100 200 300 400 500 600 700 800

Car

bon

pric

e (E

uro/

tce)

Greenhouse Gas Emission Mitigation (mmtce)

TechnicalPotential

CompetitiveEconomic Potential

US Mitigation Strategy MixUS Mitigation Strategy Mix

0

100

200

300

400

500

0 20 40 60 80 100 120 140 160 180 200

Car

bon

pri

ce (

$/tc

e)

Emission reduction (mmtce)

CH4 N2ODecrease

Tillage CarbonSink

AfforestationSink

Bioenergy EmissionOffsets

US Tillage Carbon SinkUS Tillage Carbon Sink

0

100

200

300

400

500

0 20 40 60 80 100 120 140 160

Car

bon

pric

e ($

/tce

)

Soil carbon sequestration (mmtce)

Technical Potential

Economic Potential

Competitive EconomicPotential

US Afforestation SinkUS Afforestation Sink

0

100

200

300

400

500

0 50 100 150 200 250 300

Car

bon

pric

e ($

/tce

)

Emission reduction (mmtce)

Technical Potential

Economic PotentialCompetitive

Economic Potential

US Bioenergy Emission OffsetsUS Bioenergy Emission Offsets

0

100

200

300

400

500

0 50 100 150 200 250 300 350

Car

bon

pric

e ($

/tce

)

Emission reduction (mmtce)

Technical Potential

Economic Potential

Competitive EconomicPotential

US Crop Management ImpactsUS Crop Management Impacts

75

80

85

90

95

100

105

110

115

0 100 200 300 400 500

Inte

nsit

y (B

ase

= 1

00%

)

Carbon equivalent price ($/mtce)

Fertilization

Tillage

Irrigation

US Agricultural MarketsUS Agricultural Markets

20

40

60

80

100

120

140

160

180

200

220

0 50 100 150 200 250 300

Fis

her

ind

ex

Carbon price ($/tce)

Crop prices

Livestock prices

Livestock production

Crop productionCrop exports

-10

-8

-6

-4

-2

0

2

4

6

8

0 20 40 60 80 100

Bil

lion

$

Carbon price ($/tce)

US Welfare ChangesUS Welfare Changes

Gross Producer Surplus

Emission Payments

Net Producer Surplus

Consumer Surplus

US Environmental Co-EffectsUS Environmental Co-Effects

40

50

60

70

80

90

100

0 50 100 150 200 250 300

Pol

luti

on (

%/a

cre)

Carbon price ($/tce)

N Percolation

N Subsurface Flow

Soil Erosion

P Loss

Emission LeakageEmission Leakage

90

100

110

120

130

140

150

160

0 20 40 60 80 100

Fis

her

’s I

dea

l In

dex

Carbon price ($/tce)

USA Only Annex I Countries

All Countries

Non-Annex I crop net exports foragricultural GHG mitigation policy in: