Date Awarded


Document Type

Dissertation -- Access Restricted On-Campus Only

Degree Name

Doctor of Philosophy (Ph.D.)


Virginia Institute of Marine Science


Michael C. Newman


In decision problems that rely on technical or scientific data, values are often not explicitly considered, resulting in suboptimal environmental management decision-making. Yet, valuation is an integral part of the overall environmental management process. An environmental decision-making framework that places valuation at the forefront of the process is advocated. The application of values to environmental decisions should occur at every phase of analysis, not just the final weighing of decisions. Value-focused thinking will be used here to structure the problem and determine what is important. Management tasks, environmental or otherwise, cannot rely solely on objective criteria. Stakeholder input and values, and regulatory guidelines are normally considered along with relevant monitoring and modeling data output. Though formal risk management normally contains many decision tools, a unified procedure should exist to weigh evidence as well as formally integrate opinion and observation. A decision framework should be a helpful tool to bring together lines of evidence and values necessary to make important and costly decisions. If the decision-making consequences are detrimental, others can understand why a decision was made if a rationale is available. The best way to understand how a decision was made is to present the decision process from a value-focused perspective. Understanding the difference between objectives, alternatives, and criteria in a decision problem and placing value on features of interests should improve current informal environmental management decisions immensely. Though the current work will not explicitly evaluate costs and benefits, an approach that uses Bayesian Belief Networks (BBNs) and influence diagrams (IDs) is proposed. From the value-focused decision analysis, IDs will be created to weigh the evidence of the various alternative actions needed to reach items of value. An ID can be constructed once the major objectives, alternatives, and criteria are identified. The ID construction phase arranges the information determined in the decision analysis so that experts and lay people can evaluate what is important in a problem and how decisions and other factors influence it. Constructing an ID would include mapping the causal factors and decisions in a directed acyclic graph while preserving assumptions of conditional independence. The first three chapters of this thesis synthesized information from the decision analysis literature to establish an approach that will be beneficial to environmental management. The final two chapters developed examples of the approach that applies Bayesian decision networks in environmental management. Two topics in the final chapters were used to illustrate the framework's potential effectiveness: pesticide ecological risk assessment and natural resource management of Chesapeake Bay seagrass. The pesticide risk management scheme incorporated risk assessment evidence from various models to balance ecological risk management with spraying efficacy judgments. The seagrass assessment evaluated the ability of a BBN to assimilate water quality monitoring data in decision-making that reflect remedial goals. Assessing outcomes and the influences of future processes on restoration targets can be accomplished within the framework of a formal decision analysis with Bayesian networks.



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