Modeling Land Competition Modeling Land Competition Ron Sands Ron - - PowerPoint PPT Presentation

Modeling Land Competition

Ron Sands Man-Keun Kim Joint Global Change Research Institute Battelle – PNNL – University of Maryland AIM International Workshop Tsukuba, Japan 19-21 February 2007

Modeling Land Competition

Ron Sands Man-Keun Kim Joint Global Change Research Institute Battelle – PNNL – University of Maryland AIM International Workshop Tsukuba, Japan 19-21 February 2007

2

Objectives Objectives

Extend partial equilibrium land use framework to general equilibrium

Forestry identified as a priority model development item in review

• f PNNL general equilibrium framework (Second Generation

Model) by U.S. EPA Science Advisory Board

What is the right level of abstraction for a recursive CGE model?

Forest dynamics Number of crops, animal products, forest products Geographic detail

Improve ability to simulate impact of carbon price on land use

Biofuel incentive Forest management (increased tree rotation age) Value carbon in unmanaged land

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Overview Overview

Modeling Approaches

Forestry optimization Partial and general equilibrium economics

PNNL Agriculture and Land Use Model (AgLU)

Brief history Land allocation mechanism

Disaggregation of US region into land subregions Forest dynamics

Determination of optimal tree rotation age Carbon price and rotation age

Steady-state simulation What Next?

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Modeling Approaches Modeling Approaches

Intertemporal Optimization

Typical for sector-specific models (e.g. forestry)

Intertemporal Equilibrium (perfect foresight)

Efficiency conditions (first order necessary conditions) from

intertemporal optimization model become system equations

Allows integration with other types of economic systems (such as

agriculture)

Recursive Equilibrium

Absence of look-ahead capability makes it difficult to model

forestry

Steady-State Equilibrium

Exploratory tool Steady-state modeling of forestry may be able to inform recursive

models

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partial general equilibrium equilibrium intertemporal

• ptimization

TSM, FASOM Ramsey growth model intertemporal equilibrium AgLU 2 intertemporal CGE recursive equilibrium recursive CGE steady-state equilibrium AgLU 2x

Relationship to Specialized Forestry Models

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Brief History of AgLU Brief History of AgLU

First version completed in 1996 Design

Top-down Partial equilibrium Can be run stand-alone or as part of MiniCAM

Studies

Role of biomass in carbon policy Impact of ENSO on North America U.S. climate impacts

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15-year Time Steps from 1990 through 2095 Land Allocation

Land owners compare economic returns across

crops, biomass, pasture, and future trees

Underlying probability distribution of yields per

hectare

Forest Dynamics

Trees in AgLU grow for 45 years Two forest markets (current and future) needed for

model stability

Methodology Highlights Methodology Highlights

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Products in AgLU Products in AgLU

Crops (calories)

Rice and Wheat Coarse Grains Oil Crops Other Crops

Processed Crops (calories)

Vegetable Oils Sweeteners and Alcoholic Beverages

Animal Products (calories)

Beef and other Ruminant Livestock Pork and Poultry

Commercial Biomass (calories or metric tons) Forest Products (cubic meters)

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Food Consumption by AgLU Region

1,000 2,000 3,000 4,000 United States Canada OECD Europe Japan Australia and New Zealand Former Soviet Union China and Centrally Planned Asia Middle East Africa Latin America Other Asia Eastern Europe Korea India kcal per person per day Crops Processed Crops Animal Products

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Land Allocation Land Allocation

cropland crops wheat rice coarse crops grains

• ther food

sugar crops unmanaged hay

• il

nonfood biomass crops managed forest grassland crops

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Agriculture-Forestry Data Agriculture-Forestry Data

Agriculture-Forestry Data

Food balances Land use data Forest and agricultural production

United Nations Food and Agriculture Organization (FAO) is the primary source of data Global Trade Analysis Project (GTAP) provides land use and agricultural production data for land classes within a country

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US Land Classes US Land Classes

Why Disaggregate?

Capture geographical heterogeneity Terrestrial mitigation opportunities vary by land class Climate impacts will vary by land class

Hydrologic Unit Areas (HUAs)

18 two-digit water basins in US Fixed location Useful for climate impact studies Link to water supply will be important for future work on water and potential

for biofuels

Base-Year Calibration

No unique way to calibrate base year (calibration is something of an art) Not easy to calibrate all of the following: land area by product and land

class, output by product and land class, prices, costs of production

Exact calibration doesn’t tell you where your model structure can be

improved

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Major Water Resource Regions

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Forest Dynamics Forest Dynamics

Tree growth curves vary across United States Calibration of growth curve to data provided through GTAP Response of forest production to carbon incentive

Optimal tree rotation age increases with carbon price Faustmann equation (modified by carbon incentive) is an extra

system equation paired with unknown rotation age

Modified Faustmann equation includes term that integrates carbon

stock or increment of carbon sequestered over tree growth curve

Can calculate carbon incentive either as a rental paid for carbon

storage or as full payment for increment sequestered

Computational burden can be reduced by selecting functional form

for tree growth curve that has closed-form integral

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200 400 600 800 1000

20 40 60 80 100 GTAP Yield C1 age^C2 exp(-C3*age)

Tree growth curve for southeastern pine plantations (yield in cubic meters as a function of tree age)

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200 400 600 800 1000 1200 1400 1600 1800 2000 20 40 60 80 100 GTAP Yield C1 age^C2 exp(-C3*age)

Tree growth curve for Pacific Northwest (yield in cubic meters as a function of tree age)

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LNPV with C Incentive

100 200 300 400 500 20 40 60 80 100 120 Age in years LNPV ($/ha)

Pc=0 Pc=50 Pc=100 Pc=150 Pc=200 Pc=250 Pc=300 Pc=350 Pc400

Levelized net present value per hectare at various carbon prices: southern pine plantation trees Assumptions: pt = $49 per cubic meter, cg = $1,000 per hectare, k = 0.2 metric tons carbon per cubic meter of wood, r = 3%, all stored carbon is released to the atmosphere at harvest

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Levelized net present value per hectare at various carbon prices: Pacific Northwest trees

LNPV with C Incentive

100 200 300 400 500 600 700 800 20 40 60 80 100 120 Age in years LNPV ($/ha)

Pc=0 Pc=50 Pc=100 Pc=150 Pc=200 Pc=250 Pc=300 Pc=350 Pc400

Assumptions: pt = $49 per cubic meter, cg = $750 per hectare, k = 0.2 metric tons carbon per cubic meter of wood, r = 3%, all stored carbon is released to the atmosphere at harvest

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Steady-State Land Use Simulation Steady-State Land Use Simulation

United States

Land use as function of carbon price (up to US$ 300 per

ton of carbon)

All other drivers held constant: population growth,

agricultural productivity, income

India

Land use over time is sensitive to difference in growth

rates between agricultural productivity and population growth

Three baselines

Agricultural productivity < population growth Agricultural productivity = population growth Agricultural productivity > population growth

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US Land Simulation with Varying Carbon Prices

50 100 150 200 250 300 350 400 450 500 25 50 75 100 125 150 175 200 225 250 275 300 carbon price (US$ per t) land area (million ha) unmanaged forest managed forest biomass pasture and fallow crop land

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India Land Simulation with Agricultural Productivity Growing Slower than Population

50 100 150 200 250 300 350 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 simulation year land area (million ha) unmanaged forest managed forest biomass crop land

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India Land Simulation with Agricultural Productivity Same as Population Growth Rate

50 100 150 200 250 300 350 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 simulation year land area (million ha) unmanaged forest managed forest biomass crop land

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India Land Simulation with Agricultural Productivity Growing Faster than Population

50 100 150 200 250 300 350 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 simulation year land area (million ha) unmanaged forest managed forest biomass crop land

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What Next? What Next?

Near Term

Alternative biofuel pathways Enhancements to India model

Demand and supply of fuelwood Land subregions

Longer Term

International trade and food security Valuing carbon in unmanaged land Crop rotation and multiple crops per year Water as a limiting resource