evaluating ecosystem service trade-offs associated with...

www.epa.gov/researchSustainable and Healthy Communities Research

U.S. Environmental Protection AgencyOffice of Research and Development

Evaluating ecosystem service trade-offs associated

with biofuel feedstock production in the Midwest

Randy Bruins and Betsy SmithNational Exposure Research Laboratory

ACES 2010

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Sustainable and Healthy Communities Research

U.S. EPA’s Ecosystem Services Research Program• Program goal:

To transform decision-making by showing how society’s choices affect the type, quality and sustainability of services we receive from ecosystems

• Program emphases:– Develop ecological production functions

– Consider whole systems, examine trade-offs

– Learn how to support decisions

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Future Midwestern Landscapes Study:Change drivers of interest

• Biofuels– Potential for rapid, large-scale

changes in land use or land management

– Implicit trade-offs among ecosystem services

• Agricultural conservation practices– Existing area of large investment,

uncertain benefit– Increasing interest in ecosystem

service-based incentives and markets

Locations of ethanol biorefineries and FML boundary

Conservation Reserve Program Participation($/acre)

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Future Midwestern Landscapes Study:Decision-makers’ questions

• How will today's land use decisions affect trade-offs of future ecosystem services?

• What land-use configurations afford the best combinations of ecosystem services?

• What indicators of ecosystem service changes communicate the vulnerabilities and opportunities?

• How can we facilitate conservation and restoration of ecosystem services?

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• Production of food, fiber and fuel• Clean air• Climate moderation (via carbon sequestration)• Water provision• Flood moderation• Aquatic habitat to support wildlife-based

recreation • Terrestrial habitat to support wildlife-based

recreation

Future Midwestern Landscapes Study:Ecosystem service trade-offs of interest

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Overview of present FML alternative-futures research approach

ScenarioDefinition

LandscapeConstruction

Landscape Analysis

Assessment& Management

Base Year

BiofuelTargets

Multiple Services

Socio/Economicprojection

Landscapedevelopment

Adapt/applymodels

Evaluateservices

Online “EnvironmentalDecision Toolkit”

Testing withuser groups

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(Megan Mehaffey)

Enhanced Land Cover Data for FML– Combines the best of NLCD, NASS Crop Data Layer, and LANDFIRE using a set of rules

Includes crop type as well as rotation

Implications for better estimation of nutrients and pesticides loads/export

Better assessment of crop yields

Base Year Scenario Landscape (2001-2)

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FML Base Year Landscape – Enhanced NLCD 2001/2002:Comparison of Traditional and Expanded NLCD Agriculture Classes

Traditional NLCD classes do not distinguish crop types.

Between 2006 and 2007, there was a 19% increase in corn plantings nationwide, mostly from conversion of soybean plantings.

N fertilizer need for corn is ~ 8 times that of soybeans.

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Biofuel Targets Scenario (2022)

0

5

10

15

20

25

30

35

40

Bill

ions

of G

allo

ns

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Calendar Year

Renewable Fuel StandardEnergy Independence and Security Act of 2007

Cellulosic biofuel

BiodieselAdditional advanced biofuel

Additional renewable biofuel

Market Allocation (MARKAL) econometric model• Energy supply and demand

Sets conditions for:

Food and Agricultural Policy Research Institute (FAPRI) econometric model

• Agricultural supply and demand• Projects crop acres / region

Results disaggregated using soils data, tillage practices, etc.

Tim JohnsonRebecca DodderOzge Kaplan& ISU/CARD

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Base Year (2001) Biofuel Targets (2022)

Continuouscorn

Detail for Corn Belt area in Illinois

In the Corn Belt, corn/soybean rotation will change to continuous corn, requiring greater chemical inputs and depleting soil productivity

Corn/soybeanrotation

Projection of 2022 landscape changes due to biofuel targets:Parcel change from corn/soybean to continuous corn

(Megan Mehaffey)

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Development of “Multiple Services” Landscapevia a two-stage optimization

Spatially-explicitES production

functions

Optimize % land-use

Select optimal parcels

for reassignment

HUC8 Level Parcel Level

Iterate annually

2001-2Base Year Landscape

2022 Multiple Services

Landscape

Increases in conservation

practices

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Air emissions

Atmospheric concentration& deposition

Watershedprocesses

Lake/Coastalprocesses

Terrestrialwildlife habitat

Climate mitigation

Clean air

FoodFiber

Energy

Potable water

Flood control

Recreation

Aesthetics

Existence value

Models Services or proxies

BaseyearLandscape

MultipleServices

Landscape

Biofuel TargetsLandscape

ScenarioAnalysis Field-level

processes

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Air emissions


Watershedprocesses



Climate mitigation

Clean air

FoodFiber

Energy

Potable water

Flood control

Recreation

Aesthetics

Existence value


BaseyearLandscape

MultipleServices

Landscape


ScenarioAnalysis EPIC,

Advanced EPIC

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CMAQ

CMAQ

Watershedprocesses



Climate mitigation

Clean air

FoodFiber

Energy

Potable water

Flood control

Recreation

Aesthetics

Existence value


BaseyearLandscape

MultipleServices

Landscape



processes

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Air emissions


SWAT/AnnAGNPSRHYME2S



Climate mitigation

Clean air

FoodFiber

Energy

Potable water

Flood control

Recreation

Aesthetics

Existence value


BaseyearLandscape

MultipleServices

Landscape



processes

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Air emissions


Watershedprocesses

Lake ErieGulf of Mexico


Climate mitigation

Clean air

FoodFiber

Energy

Potable water

Flood control

Recreation

Aesthetics

Existence value


BaseyearLandscape

MultipleServices

Landscape



processes

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Air emissions


Watershedprocesses


Bird habitat modelsGUIDOS

Climate mitigation

Clean air

FoodFiber

Energy

Potable water

Flood control

Recreation

Aesthetics

Existence value


BaseyearLandscape

MultipleServices

Landscape



processes

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Ecosystem Services Framework (Wainger and Boyd)and ESRP programmatic emphasis

Natural features

Ecological endpoints*

Ecological Production Function

Economic Demand Function

Ecosystem-derived benefits

Complementary goods and services(Technological Production Function)

Social values

*A biophysical feature, quantity or quality that requires little further translationto make clear its relevance to human well-being

Population served,Available substitutes

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ReVA’s Environmental Decision Toolkit (EDT)

• User-friendly tool for decision-makers

• Structured around resources and ES themes to promote problem solving

• Reduce complex information into useable performance metrics

• Promote understanding of cause/effects resulting from policy choices

http://reva.waratah.com user:[email protected] pass:vulnerability

% Continuous Corn, Base Year

Continuous corn

comparison


Map 1 higher

Map 2 higher

Same


Map 1 higher

Map 2 higher

Same

Corn production comparison


Map 1 higher

Map 2 higher

Same

Nitrogen application comparison


Map 1 higher

Map 2 higher

Same

Nitrogen loading to streams

comparison

Atrazine application + individual surface water use + population density

Creating Indices within the EDT

Weighted Ecosystem Services Map for FML Region

Clean Air

Climate Mitigation

Food Production

Fiber Production

Energy Production

Potable Water

Land Value

Flood Control

Wildlife-based Recreation

Aesthetics

Cultural Value

Biodiversity Existence Value

room for improvement

relatively good provision of services

Future capability: Build an ecosystem service index (ESI) combining user-weighted values

High ESI

Low ESI

Future capability for evaluation of user-generated scenarios

Services

GIS Server

•Goal programming•Compromise programming•Adaptive weighted sum

Multi-Objective Optimization Programming (MOOP) Module

•SMARTS•SMARTER•Analytical Hierarchical Process (AHP)

Multi-criteria Decision-Making (MCDM) Module

Intra-/Inter-Network

User Interface/Abilities

•Create new or use/modify existing MCDM models•Apply different MCDM methods (e.g., SMARTS, AHP)•Connect to MOOP models

•Run MOOP model in independent mode•Run MOOP model using weights from MCDM models•Connect MOOP to GIS Server to explore results

•Interactive map display•Scenario comparison•Geospatial analyses•Multiple-user geodatabase

Liem TranMark RidgleyRobert O’Neill

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For more information contact:

Betsy [email protected]

Randy [email protected]

mailto:[email protected]�

mailto:[email protected]�

evaluating ecosystem service trade-offs associated with...

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