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Integrating Ecological Risk Assessment and Economic Analysis in Watersheds

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Title: Integrating Ecological Risk Assessment and Economic Analysis in Watersheds


1
Integrating Ecological Risk Assessment and
Economic Analysis in Watersheds
  • Randall Bruins
  • National Center for Environmental Assessment
  • EPA Research and Development

2
Topics
  • I. Ecological risk assessment and ecosystem
    valuation
  • II. Clinch Valley case study
  • Watershed Ecological Risk Assessment
  • Economic Analysis
  • III. A proposed integration approach
  • IV. Ongoing applications

3
I. Ecological Risk and Ecosystem Valuation
  • Ecological risk reduction
  • A key focus of many EPA actions
  • A central component of ecological benefits
    assessment
  • Ecological risk assessment (ERA)
  • EPAs approach for determining or predicting
    risks
  • Guidelines for Ecological Risk Assessment (1998)

4
Watersheds
  • Unit for analysis and management
  • Five ERA case studies (1993 2000)
  • Three economic studies (1999 2003)

5
Case Study Goals
  • Ecological risk assessment
  • Identify key sources, stressors, ecological
    endpoints
  • Characterize risks
  • Economic analysis
  • Use risk assessment findings
  • Conduct decision-relevant analyses

6
Economic Case Studies
  • Big Darby Creek, Ohio
  • O.H. Erekson, O.L. Loucks, Miami University
    (Ohio)
  • Contingent valuation of suburban development
    alternatives
  • Hedonic value (still ongoing)
  • Middle Platte River, NE
  • R. Supalla, University of Nebraska
  • Game theory model of interstate conflict over
    water for endangered bird species

7
II. Clinch Valley Case Study
8
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9
Watershed Ecological Risk Assessment
  • Assessment Team
  • U.S. Environmental Protection Agency
  • U.S. Fish and Wildlife Service
  • The Nature Conservancy
  • Tennessee Valley Authority
  • U.S. Geological Survey
  • Assessment Report
  • U.S. EPA (2002). Clinch and Powell Valley
    watershed ecological risk assessment. National
    Center for Environmental Assessment, Washington,
    DC EPA/600/R-01/050. Available at
    lthttp//www.epa.gov/nceagt

10
Conceptual ModelSources and Stressors
11
Conceptual ModelEffects on One Endpoint
12
Riparian zone analysis
Fish index of biotic integrity (IBI) at this
sampling point,
Min 500 m
Max 1500 m
100 m
was optimally explained by land cover in
a riparian area of this size
13
Risk Characterization
  • Up to 55 of stream fauna variability explained
    by land uses
  • Sedimentation, habitat degradation and toxics
    most important stressors
  • Forested riparian areas associated with higher
    biological condition
  • Native fish and mussels are geographically
    restricted and highly vulnerable

14
Economic Study Team
  • University of Tennessee (grantee)
  • James Kahn (economist)
  • Steven Stewart (economist)
  • Oak Ridge National Laboratory
  • Robert V. ONeill (ecologist)
  • Amy Wolf (anthropologist)
  • Held several meetings with ecological risk
    assessment team

15
Economic Analysis Goal and Rationale
  • Goal
  • Value biodiversity changes for risk-relevant
    management scenarios
  • Rationale for method
  • People lack experience in buying environmental
    goods
  • People do evaluate real-world choices as
    alternative attribute-bundles

16
Conjoint Analysis Method
  • Describes a choice in terms of 3 6 attributes
  • Survey presents a series of choice sets in which
    attribute levels vary independently
  • Model estimates each attributes contribution to
    probability of a choice
  • Inclusion of a payment attribute enables WTP
    estimates

17
Approach
  • Define hypothetical policy
  • Define ecological, recreational and economic
    (i.e., agricultural) attributes affected
  • Mail survey to sample of valley residents
  • Estimate conjoint model

18
Choice Attributes
19
Sample Choice Set
Please check the option that you would choose
Option A Option B Option C ? ? ?
20
Advantage of Conjoint Approach
21
Ways to Build Upon This Demonstration
  • Clarify the usefulness of welfare estimates in
    Clinch Valley management decisions
  • Quantitatively link the risk and conjoint models
  • Estimate impacts of the riparian policies on the
    attributes
  • Make attributes and levels more precise

22
III. Proposed Integration Approach
  • Interdisciplinary planning and problem
    formulation
  • Decision context determines tools
  • Use integrated conceptual models
  • Specify management alternatives to allow
    interdisciplinary analysis
  • Quantitatively relate ecological and economic
    endpoints

23
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24
Analysis Approaches1. Monetize All Changes
25
Analysis Approaches2. Integrate Using Stated
Preference
ANALYSIS CHARACTERIZATION OF ALTERNATIVES
Ecological Risk
Health or Sociocultural
Economics
Quantify endpoint changes where feasible
Quantify endpoint changes where feasible
Quantify financial costs and market-based economi
c effects
Qualitatively describe other changes
Qualitatively describe other changes
Qualitatively analyze equity, economic impact
Express equity effects, impacts in common language
Express primary changes in common language
Express primary changes in common language
Stated preference study
Estimate net social benefits
COMPARISON OF ALTERNATIVES
26
Limitations of Clinch Valley Application
27
ANALYSIS CHARACTERIZATION OF ALTERNATIVES
Economics
Ecological Risk
Health or Scoiocultural
Quantify endpoint changes where feasible
Create linked model allowing feedbacks
Qualitatively describe other changes
Adjust management alternatives, reiterate
Qualitatively describe all unmodeled changes
Compare quantified and nonquantified endpoint
changes
Compare quantified and nonquantified endpoint
changes
Compare economic equity, impact
COMPARISON OF ALTERNATIVES
28
IV. Ongoing Applications
  • Integrated conceptual models
  • Sources, stressors, ecological endpoints
  • Ecosystem services and economic values
  • Management alternatives
  • National rule application
  • Site specific application for water quality
    standards (designated use attainment)

29
D r a f t
30
Watershed Conceptual Model Template
30
31
D r a f t
31
32
D r a f t
32
33
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