Grantee Research Project Results
2003 Progress Report: Future Growth of the U.S. Marine Aquaculture Industry and Associated Environmental Quality Issues: A Comprehensive Assessment
EPA Grant Number: R829804Title: Future Growth of the U.S. Marine Aquaculture Industry and Associated Environmental Quality Issues: A Comprehensive Assessment
Investigators: Jin, Di , Powell, Hauke Kite , Hoagland, Porter
Institution: Woods Hole Oceanographic Institution
EPA Project Officer: Hahn, Intaek
Project Period: October 1, 2002 through September 30, 2005
Project Period Covered by this Report: October 1, 2002 through September 30, 2003
Project Amount: $282,191
RFA: Futures: Research in Socio-Economics (2001) RFA Text
Research Category: Environmental Justice
Objective:
We are developing a framework to project the future long-term growth of the U.S. marine aquaculture industry and the effects of this growth on marine environmental quality. Our framework is being designed to capture the key components of the economic-environmental-regulatory system, including economic growth and demand for seafood; supply of seafood from fisheries, imports, and aquaculture; future technological and policy impacts on the aquaculture industry; and marine environmental quality variables.
Progress Summary:
The first year of the project has involved four efforts: a literature review, conceptual modeling, data collection, and computer programming. These efforts are discussed below.
Literature Review
We have carried out a comprehensive literature review of recent papers, books, and reports on aquaculture and the environment. The review covers seven areas: (1) aquaculture economics, including production and market demand models; (2) stochastic firm-level investment and production (e.g., input and output price uncertainties); (3) the environmental effects associated with aquaculture operations (e.g., nutrient and sediment loadings); (4) strategies to achieve sustainable aquaculture (i.e., ways to reduce environmental impacts); (5) models used in environmental planning for aquaculture development; (6) the measurement of the environmental costs of aquaculture, including both theoretical frameworks and empirical studies; and (7) environmental management policy instruments. We have identified a number of highly relevant papers. The methods described in these papers have been incorporated into our conceptual modeling, which is discussed in the next section.
Conceptual Modeling
We are developing a synthetic model for projecting the future long-term growth of the U.S. marine aquaculture industry and the effects of this growth on marine environmental quality. To achieve the objective, one key task is to model the relationship between aquaculture production and pollution.
Marine aquaculture poses a potentially significant threat to the marine environment and the ecosystem in four ways:
(1) Aquaculture facilities are sources of nutrient and sediment loads. Feces and unused food increase biological oxygen demand and the potential for eutrophication, thereby diminishing water quality.
(2) The usage of therapeutics and pesticides results in chemical pollution.
(3) Farm species may affect adjacent wildstocks through diseases and other negative interactions.
(4) Farming carnivorous species may require large inputs of wild fish for feed, putting further stress on wildstocks and their ecosystems.
Our modeling efforts during the first year have focused on nutrient pollution (nitrogen and phosphorous). If sufficient information is available, we plan to incorporate other environmental effects at a subsequent stage. The amount of pollutants produced at an aquaculture facility is a function of the fish species, type of production system, and type and quality of feed. How much of this pollution reaches the environment, and in what concentrations, depends in turn on factors such as location, whether or not a pollution control system is used, characteristics of the water flow, and the water temperature. We have identified a number of models that provide useful information (such as functional forms and parameters) for us to develop our synthetic model.
Because nutrient pollution is influenced by the scale of production, modeling future demand for aquaculture products is another key task of our study. We have developed models to illustrate a case where aquaculture and commercial fishery uses interact in the ocean and compete in the product market (Hoagland, et al., 2003; Jin, et al., 2003). These models will be used to determine the likely future shares of U.S. seafood supply from aquaculture, wild harvest fisheries, and imports.
In the United States and in many other countries, increased aquaculture production has been accompanied by growing concerns about its environmental impacts. Environmentalists, consumers, and members of the general public have expressed concerns about aquaculture’s use or degradation of natural resources, such as clean water and wild fish stocks for feed, and have demanded a better accounting of its general environmental sustainability. To make our synthetic model policy relevant for environmental management, we need to assess the external costs associated with nutrient pollution from aquaculture. The existing literature suggests that economic assessment embracing wider measures of social and environmental costs and benefits might provide different and possibly more critical perspectives of the economic value of aquaculture development. Typically, the total external cost is calculated as the sum of costs related to specific externalities, such as impacts on water quality and local fisheries, as well as neighboring aquaculture operations. Some cost items may be quantified using techniques of environmental economics (e.g., travel cost models, hedonic property value models, and contingent valuation methods). Although these techniques hold promise for environmental analyses for aquaculture development, their development and application in this area is as yet limited. We have identified and carefully reviewed several papers on the assessment of environmental costs associated with aquaculture, and we plan to use these approaches in our synthetic model.
Data Collection
We have identified and obtained a substantial amount of economic, biological, and environmental data from the literature and other sources. Based on a survey of more than 40 empirical models of salmon demand in the economics literature, we have assembled key parameters (e.g., elasticities) for demand modeling at the regional, national, and international levels. An accurate projection of future demand for seafood is crucial for predicting future production levels in the aquaculture industry (Hessert, 2003). In the process of testing an existing model of the environmental impact of aquaculture, we have assembled environmental data (e.g., temperature, water depth, current, and area) for representative salmon production sites in coastal Maine. These types of models and data are essential for us to establish the link between production and environmental effects in our synthetic model (Douthitt, 2003).
Computer Programming
A key component of our synthetic model is a firm-level aquaculture investment and production model (Kite-Powell, et al., 2003). The model was originally developed in Microsoft Excel and has been used successfully in economic feasibility studies of several finfish and shellfish species. For the purpose of the current study, the firm-level model has been reprogrammed using Matlab. This will significantly improve our ability to simulate different economic and environmental conditions. In addition, stochastic components have been added to the firm-level model. We now are extending the model to include pollution discharge associated with fish production at different levels.
Future Activities:
In the next year, we will complete data collection and further develop the theoretical and simulation models.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
| Other project views: | All 19 publications | 4 publications in selected types | All 2 journal articles |
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Hoagland P, Jin D, Kite-Powell H. The optimal allocation of ocean space: aquaculture and wild-harvest fisheries. Marine Resource Economics 2003;18(2):129-147. |
R829804 (2003) R829804 (Final) |
Exit Exit |
Supplemental Keywords:
estuary, effluent, discharge, aquatic, integrated assessment, public policy, socioeconomic, social science, northeast, Atlantic coast, modeling, economic, behavioral science, ecosystem protection, environmental exposure, risk, aquatic ecosystem, aquatic ecosystems, estuarine research, ecology, ecosystems, economics, decision making, oceanography, aquaculture, aquatic resources, assessing ecosystem vulnerability, deliberative policy, econometric analysis, economic research, ecosystem response, ecosystem valuation, environmental decision making, environmental policy, environmental policy impact, fish communities, fisheries, marine biogeochemistry, policy impact, policy making, water quality., RFA, Ecosystem Protection/Environmental Exposure & Risk, Scientific Discipline, Economic, Social, & Behavioral Science Research Program, Aquatic Ecosystem, Economics & Decision Making, Aquatic Ecosystems & Estuarine Research, Ecological Risk Assessment, Economics, Oceanography, decision-making, Social Science, Ecology and Ecosystems, watershed management, economic research, marine biogeochemistry, aquaculture, water quality, deliberative policy, ecosystem valuation, policy making, aquatic resources, environmental policy impact, environmental decision making, ecosystem response, policy impact, fisheries, fish communities, aquatic ecosystems, environmental policy, decision making, econometric analysisRelevant Websites:
http://www.whoi.edu/science/MPC/dept/ Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.