A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers–Pressures–States–Impacts–Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.     

Environmental management in an international consumer goods company

Many management processes and tools can provide companies with information to support their environmental decision making. Risk assessment, environmental auditing, life cycle assessment and environmental reporting are but a few examples. Each of these has typically evolved independently as the need for it has arisen. Today, however, this abundance of tools can lead to confusion: What is the exact objective of each tool? How do they differ? Are some ‘better’ than others? Should they be used in parallel, sequentially or in place of each other? More importantly, how do they fit together into a coherent environmental management framework that will ensure sound environmental and economic decision making in a company? This paper seeks to answer these questions. It describes the overall environmental framework that has been developed internally within Procter & Gamble and which allows the company to make coherent economically and environmentally sound decisions, in both the short- and long-term.     

Supporting multi-stakeholder environmental decisions

This paper examines how multiple criteria analysis (MCA) can be used to support multi-stakeholder environmental management decisions. It presents a study through which 48 stakeholders from environmental, primary production and community interest groups used MCA to prioritise 30 environmental management problems in the Mackay-Whitsunday region of Queensland, Australia. The MCA model, with procedures for aggregating multi-stakeholder output, was used to inform a final decision on the priority of the region's environmental management problems. The result was used in the region's environmental management plan as required under Australia's Natural Heritage Trust programme. The study shows how relatively simple MCA methods can help stakeholders make group decisions, even when they hold strongly conflicting preferences.     

Why not in your backyard? scientific data and nonrational decisions about risk

The siting of hazardous waste facilities constitutes a special case of the many no win environmental decisions we face. They share common features: (a) we must decide something; (b) the decision affects some people more than others; (c) as scientists we are not 100% confident of our research results; (d) elements of the decision remain unquantifiable; and (e) decisions combine both scientific and political elements. In this paper we attempt to illustrate and analyze several examples that combine all of these elements and to suggest methods which would lead toward a scientific valid and politically useful resolution. Using well-known examples such as the public's fear of death from nuclear power, snakebite, and smoking, we attempt to integrate public perception of risks into a decision-making model. Finally, the conclusions deal with the role of policy making, public perception, and science in resolving environmental controversies. We do not, however, solve this perplexing problem.     

Ecosystem Manipulation Experimentation as a Means of Testing a Biogeochemical Model

2 concentration, and global or regional temperature change. Such model projections are frequently used as the basis or justification for public policy decisions and legislation. A substantial need has therefore arisen to test and substantiate the veracity of mathematical model projections. Unfortunately, environmental models can never be truly validated because natural systems are never closed and model solutions are always nonunique. Partial model confirmation is possible, however, and entails demonstration of agreement between prediction and observation. Experimental ecosystem manipulation provides one of the best, and in many cases only, available basis for model confirmation. The use and potential misuse of data from experimental ecosystem manipulations for model testing is explored using examples drawn from the application of an acid–base chemistry model, MAGIC. As model projections provide an increasingly important basis for public policy decisions, and as both the scientific questions and the models become increasingly complex, it will become critical to provide data from a suite of well-designed ecosystem manipulation experiments in order to evaluate the quality and uncertainty of those model projections and the models upon which they are based.     

A practical real option methodology for the evaluation of farm-in/out joint venture agreements in mineral exploration

Although the “real option valuation” (ROV) methodology offers extremely valuable insights in optimising investment decisions in the face of uncertainty, its practical acceptance in the mining industry has until recently been slow because of its perceived computational complexity. Recent conceptual advances in the use of binomial lattices and software developments in the areas of decision trees and dynamic programming, have significantly simplified ROV analysis and made it of practical application in day-to-day financial evaluations and decisions involving uncertainty. This paper provides general background on the ROV methodology and an example of how a typical farm-in/out agreement, as a preliminary to the establishment of a joint venture (JV), can be valued as a series of sequential and compound real options. For illustrative and quality assurance purposes, a simple farm-in/out agreement is valued from the point of view of the party acquiring equity in the project (the farm-inee) using two distinct methods, i.e. (a) a binomial lattice and (b) a decision tree in combination with binomial stochastic processes, in both cases neutralising risk using the user-friendly “risk-neutral probability”. The fact that exactly the same ROV is obtained by both methods provides confidence in the modified decision tree approach, which opens up the capacity to value the more complex sequential/compound real options inherent in real-life farm-in/out agreements. The model is then modified to incorporate a number of realistic contractual conditions often encountered in typical exploration and mining farm-in/out deals. The paper demonstrates how the increased complexity of the model can be relatively easily addressed using a decision tree with dynamic programming capability.     

Adaptive management in the U.S. National Wildlife Refuge System: science-management partnerships for conservation delivery

Adaptive management is an approach to recurrent decision making in which uncertainty about the decision is reduced over time through comparison of outcomes predicted by competing models against observed values of those outcomes. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service is a large land management program charged with making natural resource management decisions, which often are made under considerable uncertainty, severe operational constraints, and conditions that limit ability to precisely carry out actions as intended. The NWRS presents outstanding opportunities for the application of adaptive management, but also difficult challenges. We describe two cooperative programs between the Fish and Wildlife Service and the U.S. Geological Survey to implement adaptive management at scales ranging from small, single refuge applications to large, multi-refuge, multi-region projects. Our experience to date suggests three important attributes common to successful implementation: a vigorous multi-partner collaboration, practical and informative decision framework components, and a sustained commitment to the process. Administrators in both agencies should consider these attributes when developing programs to promote the use and acceptance of adaptive management in the NWRS.     

An Analytical Review of Environmental Justice Research: What Do We Really Know?

This article presents a review of major empirical research on environmental justice. Forty-two empirical research studies spanning three decades were evaluated and categorized on the basis of how well they meet reasonable scientific standards. Twelve of those studies are described and critiqued in detail, and an overview of trends in the literature is presented. The author concludes that the empirical foundations of environmental justice are so underdeveloped that little can be said with scientific authority regarding the existence of geographical patterns of disproportionate distributions and their health effects on minority, low-income, and other disadvantaged communities. If environmental managers and policy-makers do not recognize the high levels of empirical uncertainty surrounding the issue, they are apt to attribute an empirically unwarranted level of concreteness to the empirical research findings, thus leading to poorly conceptualized and therefore potentially harmful policy and management decisions.     

A planning and decision-making framework for ecological restoration

A broad and objective perspective of ecological and socioenomic knowledge is required to underlie a scientific approach to the problems of terrestrial restoration ecology. Uncertainty associated with limited scientific knowledge highlights the crucial importance of the interaction between science and policy in weighing ecological restoration alternatives in relation to other management options. In this paper, we provide a pragmatic definition for restoration ecology that is suitable for extensive terrestrial applications and present a decision framework to help organize and clarify different phases of the decision process as it is related to ecological restoration. We argue that restoration planning should include a wider spectrum of participants and decisions than have traditionally been employed.     

Do statistical inferences allowing three alternative decisions give better feedback for environmentally precautionary decision-making?

Environmental policies and guidelines often specify standards for environmental indicators. The first part of this paper argues that, where compliance with these standards is assessed with the help of statistical inference, an inference employing a three-alternatives decision rule can provide more sensible feedback to environmental managers for precautionary decision-making. The second part of the paper shows how a three-alternatives statistical inference about compliance with a percentile standard might be applied to a small number of observations using a non-parametric binomial interval. This interval expression of uncertainty results in the sample size requirements for various percentile ranks becoming explicit.     

Trade-offs in assessing environmental impacts

Summary The evolution of the environmental issue has moved through the early stage of technological fixes and estimable economic costs into an area of larger uncertainty and higher information costs.The economic costs of pollution control are about one percent of the GNP. The technological fixes have improved air and water quality somewhat; but in air quality little reduction in nitrogen oxides has been achieved, and in water quality about 25 percent of the water is poor or worse, with high fecal coliform bacteria.The next stage of environmental improvement is to reduce hazardous chemical elements in the environment. In these areas, the health and biological effects are still uncertain, information costs are high, and subjective judgments are common.As uncertainty and qualitative judgments have become more prominent in environmental decisions, delays have been introduced into the decision loops, raising regulatory costs, and heightening adversary stresses between business and environmentalists. The stresses place an aura of arbitrariness over regulations in a milieu where the governability of society is already questioned. This is not the time to retreat from environmental improvement, but to try to simplify the decision process. Two possible alternatives are to codify court precedents into a more rigorous reliance on agency administration law, or to revert to the common rules of civil law that complainants must show damage and cause before an award is allowable by an administrative agency. Either of these options would free the decision making process of delays and allow it to function prospectively, while allowing environmental damages from inadequate decisions to be remedied retroactively. Potential liabilities may increase, but at least the decision process could move forward without being frustrated by regulatory delays.     

Application of Decision Analysis to Forest Road Deactivation in Unstable Terrain

Resource managers require objective methodologies to optimize decisions related to forest road deactivation and other aspects of road management, especially in steep terrain, where road-related slope failures inflict extensive environmental damage. Decision analysis represents a systematic framework that clearly identifies real options and critical decision points. This framework links current decisions with expected future outcomes and provides advantages such as a common currency to systematically explore the liability consequences of limited budget expenditures to road deactivation and other road-related activities. Furthermore, the decision framework prevents the analysis from becoming hopelessly entangled by the vast number of possibilities generated by the alternative occurrences, magnitudes, and consequences of landslide/debris flow events and provides the information required for the first step of an adaptive management process. Here, a structured analysis of potential environmental risks for a road deactivation project in coastal British Columbia, Canada is presented. The application of decision analysis generates a ranking of the expected benefits of proposed deactivation activities on various road sections. The ranking distinguishes between road sections that offer high expected benefit from those that offer moderate to low expected benefit. Seventeen of 171, 100–m road segments accounted for 18% of the cumulative cost and 98% of the cumulative expected net benefits from road deactivation. Furthermore, the cost of deactivating a section of road is related to the expected benefit from such deactivation, thus providing the basis for more effective resource allocation and budgeting decisions.     

The Decision-Identification Tree: A New NEPA Scoping Tool

decision-based scoping —provides an effective methodology for improving the EIS scoping process. Decision-based scoping, in conjunction with a new tool, the decision-identification tree (DIT), places emphasis on first identifying the potential decisions that may eventually need to be made. The DIT provides a methodology for mapping alternative courses of action as a function of fundamental decision points. Once these decision points have been correctly identified, the range of actions, alternatives, and impacts can be more accurately assessed; this approach can improve the effectiveness of EIS planning, while reducing the risk of future disconnects between the EIS analysis and reaching a final decision. This approach also has applications in other planning disciplines beyond that of the EIS.     

Environmental economic,political and ethical integration in a common decision-making framework

This article develops a decision-making framework for environmental management that integrates technical, economic, political and legal, and ethical decision levels. It attempts to show how these decision levels can be ordained, integrated and interconnected and postulates a hierarchic concentric sphere system that proposes an environmental management model for long-term solutions. This model can be used as a check list for environmental management decision-making and also as a guide for environmental conflict resolution where environmental problems necessitate several levels of decision making. It integrates various environmental ethical positions and evaluates political decisions into a comprehensive, broadly applicable multidisciplinary approach. The objective of this decision-making model is to interconnect into a simplified sequence different levels of environmental management processes in order to account for sustainability, efficacy, efficiency and the acceptability of environmental management processes in the long term. This is done by observing when an environmental problem needs to be solved within a certain sphere of solutions and when it requires wider frameworks, how these can be established and how this process proves that solidarity is the widest and most reasonable sphere.     

Limitations of an optimum sustainable population or potential biological removal approach for conserving marine mammals: Pacific walrus case study

Decision rules are the agreed-upon points at which specific management interventions are initiated. For marine mammal management under the U.S. Marine Mammal Protection Act (MMPA), decision rules are usually based on either a numeric population or biological-removal approach. However, for walrus and other ice-associated pinnipeds, the inability to reliably assess population numbers or biological removals highlights a significant gap in the MMPA, particularly when the Arctic environment is rapidly changing. We describe the MMPA's ecosystem-based management goals, and why managers have bypassed these goals in favor of an approach that depends upon numerical population assessment. We then revisit the statute's primary goals in light of current knowledge about the Pacific walrus ecosystem and new developments in environmental governance. We argue that to monitor and respond to changes in the walrus ecosystem, decision rules should be based on scientific criteria that depend less on the currently-impractical goal of accurately enumerating population size and trends, or removals from that population. Rather, managers should base decisions on ecological needs and observed ecological changes. To implement this approach would require an amendment to the MMPA that supports filling the gap in management with achievable decision rules. Alternatively, walrus and other ice-associated pinnipeds will remain largely unmanaged during a period of profound environmental change.     

Uncertainty and risk in wildland fire management: a review

Wildland fire management is subject to manifold sources of uncertainty. Beyond the unpredictability of wildfire behavior, uncertainty stems from inaccurate/missing data, limited resource value measures to guide prioritization across fires and resources at risk, and an incomplete scientific understanding of ecological response to fire, of fire behavior response to treatments, and of spatiotemporal dynamics involving disturbance regimes and climate change. This work attempts to systematically align sources of uncertainty with the most appropriate decision support methodologies, in order to facilitate cost-effective, risk-based wildfire planning efforts. We review the state of wildfire risk assessment and management, with a specific focus on uncertainties challenging implementation of integrated risk assessments that consider a suite of human and ecological values. Recent advances in wildfire simulation and geospatial mapping of highly valued resources have enabled robust risk-based analyses to inform planning across a variety of scales, although improvements are needed in fire behavior and ignition occurrence models. A key remaining challenge is a better characterization of non-market resources at risk, both in terms of their response to fire and how society values those resources. Our findings echo earlier literature identifying wildfire effects analysis and value uncertainty as the primary challenges to integrated wildfire risk assessment and wildfire management. We stress the importance of identifying and characterizing uncertainties in order to better quantify and manage them. Leveraging the most appropriate decision support tools can facilitate wildfire risk assessment and ideally improve decision-making.     

Applying the Precautionary Principle in Environmental Assessment: The Case of Reviews in British Columbia

This paper examines the application of the precautionary principle in environmental assessment, specifically using the Salmon Aquaculture Review and the Burns Bog Ecosystem Review in British Columbia as case studies. Lessons are drawn and advice is offered. A conceptual model is presented, framed according to the level of uncertainty regarding impacts and the likelihood of those impacts, as well as the irreversibility of impacts on the environmental system. A distinction is made between management strategies that should either avoid the activities in question or allow for adaptive management and, if implemented effectively, prevent or mitigate adverse effects. Applying the precautionary principle in environmental assessment requires, above all, clear communication and the development of a common understanding of the basis for decisions. The model presented in this paper is suggested as a tool from which a more specific methodological framework can be developed on a case by case basis.     

Water management decision makers' evaluations of uncertainty in a decision support system: the case of WaterSim in the Decision Theater

Model-based decision support systems are increasingly used to link knowledge to action for environmental decision making. How stakeholders perceive uncertainty in models and visualisations affects their perceptions of credibility, relevance and usability of these tools. This paper presents a case study of water decision makers’ evaluations of WaterSim, a dynamic water simulation model presented in an immersive decision theatre environment. Results reveal that decision makers’ understandings of uncertainty in their evaluations of decision support systems reflect both scientific and political discourse. We conclude with recommendations for design and evaluation of decision support systems that incorporate decision makers' views.     

Environmental portfolio analysis: An integrated strategic approach to environmental management

As businesses strive to reduce costs and become more competitive, environmental costs and potential future liability issues continue to raise overhead expenses. The decision process is further challenged by the various interpretations of existing laws and the uncertainty of future applicable regulations and their interpretation. To make more informed business decisions and bridge the gap between the environmental and business perspective, organizations need to be able to see the overall environmental picture and how it affects the current and future business operation. This article presents a systematic approach to developing an organization's integrated baseline “environmental portfolio” with various business risk levels and expected costs. Utilizing computer simulation, sensitivity iterations are performed to show the results of different scenarios. These scenarios can include various probabilities of cost levels, permitting strategies, and litigation, as well as the success of new technologies. Management can then focus attention on the main driving factors and avoid spending too much attention on lesser items. An additional benefit to this process is that communication between the various segments of an organization are enhanced since their perspectives are clearly articulated as part of the analysis. Sensitivity analysis also provides the framework for a sanity check of the process and results. Are projected levels of success reasonable? What levels would be required to change the decision, and how likely are they to occur? What level of overall business risk associated with environmental issues is prudent? In addition this article shows how computer modeling and simulation can bring a valuable perspective to the decision-making process.     

PART I: METHODOLOGY AND PROBLEMS IN AN URBANIZED ARID ENVIRONMENT1

The methodology of operations research is judged in relation to its utility to water resource management in an urbanized arid environment and to the study of worth of data for such management. Conditions for existence of a managerial problem are reviewed as is the multilevel structure of the decision process, including decisions on social goals for Western water use. Worth of data can only be judged in relation to a particular use to meet a social or managerial objective. The role of data uncertainty on the decision process is reviewed in the light of past water decisions and present and future problems.