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OBJECTIVES : To establish the structure of an ecological/economic model of the Chesapeake Bay that employs a general equilibrium ecosystem model (GEEM) coupled with a computable general equilibrium (CGE) economic model. The proposed work will indicate the feasibility of turning this structure into a working model suitable for Ecosystem Based Fishery Management (EBFM). The primary goals of this proposal tie directly to the first and third objectives listed in the original request for proposals. The project will also assess how CGE models could be integrated with existing ecosystems models being used in the Chesapeake Bay, tying in to the second objective. Completion of this report and data assessment will allow Maryland Sea Grant to assemble both the GEEM and CGE.
METHODOLOGY: The project will be divided into four parts: I) building a GEEM, II) building a CGE model, III) integrating GEEM and a CGE, and IV) comparisons to existing integrated economic/ecological modeling. In the first part a food web will be constructed for the Bay built on existing work, and the data needed to implement the food web in GEEM will be indicated. The second part will indicate the geographic region to be included in the CGE, and again data needs will be indicated. The third part will show how GEEM and CGE would be integrated. The fourth part will begin a literature search on the relevant existing models. John Tschirhart and David Finnoff will bring their considerable experience to bear on the GEEM and CGE. Additionally, Brad Gentner will bring his publication and practical experience building custom economic impact models for fisheries to bear on developing the CGE road map.
RATIONALE: This project directly addresses two of the objectives identified in the request for proposals. Many view CGE models as the perfect component that can be added to any ecosystem model to quantify human dimensions. Because they are built using federally collected state level economic data, they are very flexible and can be easily updated annually. The outputs from CGE models include changes in overall economic value and distributional metrics such as income and jobs. These flows represent a big step forward from input/output models as CGE models capture adaptive human behavior. Additionally, GEEMs represent a novel way of modeling ecosystems that dovetail extremely well with CGE models. They also represent a step forward from less adaptive ecosystem models currently in use. Combined, this project represents an opportunity to examine the feasibility of a suite of models that will allow policy changes to be analyzed in a forward thinking, adaptive and consistent way.
This section describes how this project has advanced scientific knowledge and made a difference in the lives of coastal residents, communities, and environments. Maryland Sea Grant has reported these details to the National Oceanic and Atmospheric Administration (NOAA), one of our funding sponsors.
SUMMARY: This project demonstrated that coupled ecosystem and economic models have the potential for providing sophisticated assessments of the effects of alternative fisheries management policies.
RELEVANCE: Traditional fisheries management largely regulates harvests by setting limits on catch sizes and quantities. Because such limits do not account for the impacts on food web and predator-prey interactions, natural resource agencies have been moving towards Ecosystem Based Fishery Management (EBFM), which aims to account for the effects of policy on harvests, habitat, and water quality. However, EBFM does not consider the economic impacts of fisheries management in policy, for example, on employment, income, and business profits. The ability to couple ecosystem models with economic models could provide decision makers with sophisticated tools for assessing trade-offs of alternative fisheries management policies.
RESPONSE: Scientists from the University of Wyoming and the Bradner Consulting Group Inc. studied the feasibility of combining an ecological model with an economic model for Ecosystem Based Fishery Management, both based on data from the Chesapeake Bay.
RESULTS: The research team demonstrated that by coupling economic and ecological models, decision makers will have the ability to assess tradeoffs between alternative fisheries and habitat policies in a way that captures both direct and indirect consequences throughout the regional economy.
The researchers presented the results of this study to the Chesapeake Bay Program's Sustainable Fisheries Goal Implementation Team, composed of state fisheries managers and a diverse group of scientists. Discussion of the presentation indicated that other fisheries and ecosystem models currently available or being used in Chesapeake Bay decision making could be coupled to the research team’s economic model.
The research team showed that fishery management decisions based on a single species modeling approach can differ significantly from decisions based on coupled models. The team encouraged further development of these types of models for Chesapeake Bay management.