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MULTICRITERIA BAYESIAN ANALYSIS OF LOWER TROPHIC LEVEL UNCERTAINTIES AND VALUE OF RESEARCH IN LAKE ERIE. (R825150)
Citation:
Kim, J. B., B. F. Hobbs, AND J. F. Koonce. MULTICRITERIA BAYESIAN ANALYSIS OF LOWER TROPHIC LEVEL UNCERTAINTIES AND VALUE OF RESEARCH IN LAKE ERIE. (R825150). HUMAN AND ECOLOGICAL RISK ASSESSMENT. American Chemical Society, Washington, DC, 9(4):1023-1057, (2003).
Description:
Human activities have severely disrupted the Lake Erie ecosystem. Recent changes in the structure of the lower trophic level associated with exotic species invasions and reduced nutrient loading have created ecological uncertainties for fisheries management. Decisions that naïvely assume certainty may be different and suboptimal compared to choices that consider uncertainty. Here we illustrate how multiobjective Bayesian decision analysis can recognize the multiple goals of management in evaluations of the effect of ecological uncertainties on management and the value of information from ecological research. Value judgments and subjective probabilities required by the decision analysis were provided by six Lake Erie fishery agency biologists. The Lake Erie Ecological Model was used to project the impacts of each combination of management actions and lower trophic level parameter values. The analysis shows that explicitly considering lower trophic level uncertainties can alter decisions concerning Lake Erie fishery harvests. Of the research projects considered, investigation of goby predation of zebra mussels (Dreissena sp.) and lakewide estimation of secondary production appear to have the greatest expected value for fisheries management. We also find that changes in the weights assigned to management goals affects decisions and value of information more than do changes in probability judgments.
Author Keywords: Bayesian analysis; decision trees; multicriteria decision making; zebra mussels; ecosystem modeling; Lake Erie; ecosystem management; fisheries management