Black P and Stockton T. 2009. Chapter 1- Basic Steps for the Development of Decision Support Systems. In: A. Marcomini et al. (eds.), Decision Support Systems for Risk-Based Management of Contaminated Sites, Springer Science Business Media, LLC. There is a growing desire to develop effective and efficient computational methods and tools that facilitate environmental analysis, evaluation and problem solving. Environmental problems of interest may include concerns as apparently dissimilar as revitalization of contaminated land, and effective management of inland and coastal waters. The approach to effective problem solving in both of these examples can involve the development of what are commonly called Decision Support Systems (DSSs). This chapter lays out the rationale for a DSS, the types of DSSs and the steps for developing a DSS. ESC Folder: Reading Room\Decision Support Literature\Decision Analysis Folder (contact: Brian Dyson, dyson.brian@epa.gov)
Borsuk M, Clemen R, Maguire L and Reckhow K. 2001. Stakeholder Values and Scientific Modeling in the Neuse River Watershed. Group Decision and Negotiation 10: 355–373. In 1998, the North Carolina Legislature mandated a 30% reduction in the nitrogen loading in the Neuse River in an attempt to reduce undesirable environmental conditions in the lower river and estuary. The paper describes a decision-analytic approach to modeling the Neuse River nutrient-management problem, focusing on linking scientific assessments to stakeholder objectives. The paper also discusses how the model can then be used by local decision makers as a tool for adaptive management of the Neuse River system. ESC Folder: Reading Room\Decision Support Literature\Objectives Hierarchy (contact: Brian Dyson, dyson.brian@epa.gov)
Bruins RJF, Franson SE, Foster WE, Daniel FB and Woodbury PB. 2009. A Methodology for the Preliminary Scoping of Future Changes in Ecosystem Services, With an Illustration from the Future Midwestern Landscapes Study. US Environmental Protection Agency, EPA/600/R-09/134. This paper presents a new methodology for constructing hypotheses about the potential effects of future change scenarios on ecosystem services. This new methodology offers a well-defined procedure for managing ecological complexity and improving study design. ESC Folder: Reading Room\Decision Support Literature\Objectives Hierarchy (contact: Brian Dyson, dyson.brian@epa.gov)
Keeney RL. 1988. Structuring Objectives for Problems of Public Interest. Operations Research 36(3):396-405. The analysis of problems of public interest requires a broad range of objectives. This paper outlines and illustrates a procedure to constructively involve stakeholders in the process of identifying these objectives. Objectives hierarchies were developed to represent various stakeholders. From these, a combined hierarchy was structured that addressed health and safety; economics; equity; environmental, social, and political impacts; flexibility; and scheduling. ESC Folder: Reading Room\Decision Support Literature\Objectives Hierarchy (contact: Brian Dyson, dyson.brian@epa.gov)
Labiosa WB, Leckie JO, Mumley T, Rytuba J, and Bernknopf R. 2003. A Decision Analysis Approach to TMDL Implementation Decisions: Mercury TMDLS in the San Francisco Bay Area. Proceedings of the National TMDL Science and Policy 2003 Specialty Conference. Water Environment Federation. Environmental decision situations (such as TMDL load allocation) are often rife with uncertainty and controversy, requiring the integration of diverse kinds of information and compromises between diverse interests. This paper describes a decision analysis approach to TMDL implementation decisions for mercury using a hypothetical mine-impacted tributary in the San Francisco Bay as an example. The paper focuses on the use of the Bayesian (subjective) definition of probability, which treats uncertainty as a probability and allows the decision maker to combine various kinds of information into a unified probabilistic framework. ESC Folder: Reading Room\Decision Support Literature\Decision Analysis Folder (contact: Brian Dyson, dyson.brian@epa.gov)
Maguire LA. 2004. What Can Decision Analysis Do for Invasive Species Management? Risk Analysis 24(4) 859-868. Decisions about management of invasive species are difficult for all the reasons typically addressed by multi-attribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multi-attribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. ESC Folder: Reading Room\Decision Support Literature\Decision Analysis Folder (contact: Brian Dyson, dyson.brian@epa.gov)
Maloney KA, Maguire LA and Lind EA. 2000.Neuse River Estuary Modeling and Monitoring Project Stage 1: Assessment of Stakeholder Interest and Concerns to Inform Long-Term Modeling. Nicholas School of the Environment, Duke University, Durham, North Carolina. As input to water quality management models of nutrient cleanup in the Neuse, the authors used public meetings, written questionnaires, and personal and telephone interviews to learn what goals stakeholders have for the cleanup and how they would measure achievement of those goals. ESC Folder: Reading Room\Decision Support Literature\Objectives Hierarchy (contact: Brian Dyson, dyson.brian@epa.gov)
Maxim L, Spangenberg JH and O’Connor M. 2009.An analysis of risks for biodiversity under the DPSIR framework. Ecological Economics 69:12–23. This paper reviews definitions and uses of the Driving Forces–Pressures–State–Impacts–Responses (DPSIR) framework and reframes ‗DPSIR‘ using a complex system methodology based on the distinction between four ‗spheres‘ of sustainability (environmental, economic, social and political) and the analysis of their functioning and relationships. Within the resulting conceptual framework, each of the five D, P, S, I and R concepts are specified, for application in integrative analysis of relationships between policy, society, economy and biodiversity in one of the world’s largest European integrated research projects on biodiversity (ALARM). ESC Folder: Reading Room\Decision Support Literature\Decision Analysis Folder (contact: Brian Dyson, dyson.brian@epa.gov)
Reckhow KH.A Primer on Decision Analysis. Nicholas School of the Environment and Earth Sciences, Duke University, Durham, NC. Decision analysis provides a prescriptive approach for analyzing decisions when outcomes are uncertain. This paper uses everyday and hypothetical examples to illustrate the techniques for rigorous quantitative analysis of decision problems. ESC Folder: Reading Room\Decision Support Literature\Decision Analysis Folder (contact: Brian Dyson, dyson.brian@epa.gov)
Rehr A. 2010. The Decision Landscape. This is a graphic of the generic decision landscape. ESC Folder: Reading Room\Decision Support Literature\Decision Landscape (contact: Brian Dyson, dyson.brian@epa.gov)
Rehr A and Small M. Decision Landscape Primer: A Tool for Structuring a Multi-Stakeholder Decision Problem. This document provides a suite of questions that can be used to help develop a decision landscape, and a decision landscape schematic. ESC Folder: Reading Room\Decision Support Literature\Decision Landscape (contact: Brian Dyson, dyson.brian@epa.gov)
Rehr A and Small M. 2010. Decision Landscape for Implementing Additional Wastewater Treatment in the Florida Keys to Reduce Nutrient Loading to Nearshore Waters. This document provides an example of how the questions in the Decision Landscape Primer can be answered, using information contained in the Florida Keys National Marine Sanctuary (FKNMS) Management Plan. ESC Folder: Reading Room\Decision Support Literature\Decision Landscape (contact: Brian Dyson, dyson.brian@epa.gov)
Smeets E and Weterings R. 1999. Environmental Indicators: Typology and Overview. Technical report No 25. European Environment Agency (EEA). The purpose of this paper is to introduce the EEA ‗Typology of indicators‘ and the DPSIR framework (Driving forces, Pressure, State, Impact, Response) used by the European Environment Agency in its reporting activities. This report should help policy-makers to understand the meaning of the information in indicator reports. In addition, we hope the paper will be useful in helping to define common standards for future indicator reports from the EEA and its member states. ESC Folder: Reading Room\Decision Support Literature\Decision Analysis Folder (contact: Brian Dyson, dyson.brian@epa.gov)
Von Winterfeldt. 2000. Developing Performance Measures for Complex Evaluations: An Introduction and an Application to Upgrading Infrastructure Systems (draft). School of Policy, Planning, and Development University of Southern California. Performance measures define how decision alternatives should be measured to determine how well they achieve decision making objectives. This paper describes some concepts, suggests some guidelines, and illustrates their use for performance measurement. Throughout the paper, the concepts and guidelines are illustrated with an example that illustrates that the choice of a performance measure can have a powerful effect on the analysis results. The paper concludes by suggesting that the development and choice of appropriate performance measures for complex decisions should be a deliberate step, involving technical experts, decision makers, and external stakeholders. ESC Folder: Reading Room\Decision Support Literature\Objectives Hierarchy (contact: Brian Dyson, dyson.brian@epa.gov)