Importance of scientific uncertainty in decision making

Uncertainty in environmental decision making should not be thought of as a problem that is best ignored. In fact, as is illustrated in a simple example, we often informally make use of awareness of uncertainty by hedging decisions away from large losses. This hedging can be made explicit and formalized using the methods of decision analysis. While scientific uncertainty is undesirable, it can still be useful in environmental management as it provides a basis for the need to fund additional monitoring, experimentation, or information acquisition to improve the scientific basis for decisions.     

Making decisions about environmental management when conventional economic analysis cannot be used

A process is described for making comparative valuations of a wide range of environmental management activities when the combined social, economic, managerial, and political benefits of some (but not all) of these activities cannot be adequately described in economic terms and when budgetary constraints do not permit funding of all activities under consideration. The process accounts for subjective judgment and contains a formal rigorous decision strategy that takes the place of intuition when quantitative and qualitative values of environmental activities need to be evaluated.     

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.     

Group utility indifference and resource management decision making

Natural resource managers often rely on the advice of specialists to aid decision making. However, disagreement among these specialists about the relative value of particular management objectives or the risks associated with implementing certain management strategies may complicate the decision effort. Multiattribute utility analysis can facilitate decision making by indicating how attributes of a problem are weighed by individual specialists. This information can then be used to outline bands of potential problem solutions that are acceptable to the advising group and may allow management to further its own objectives (possibly increased efficiency).An example is presented that relates to fire management planning efforts on national forests. Multiattribute utility functions developed from a survey of fire management professionals are used to identify utility-maximizing fire management strategies based on each strategy's level of economic efficiency and risk. Bands of utility-indifferent potential solutions are outlined based on measures of group consensus. It is pointed out that a subset of these would further management's goal (increased efficiency) without significantly altering the value assigned to the risk attribute by the specialists. Finally, the robustness of the technique is discussed with particular reference to environmental management problems and the role that proxy information often plays in decision making.     

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.     

Towards Participatory Geographic Information Systems for community-based environmental decision making

This article discusses the potential of Geographic Information Systems (GIS) to become an information technology enabling groups of people to participate in decisions shaping their communities and promoting sustainable use of natural resources. It explains the concept of participation in the context of planning and decision making. In this context Participatory GIS (PGIS) offers tools that can be used to help the public become meaningfully involved in decision making processes affecting their communities. Following an overview of research on PGIS and its current status the article presents two recent studies of PGIS in water resource planning; one involving the use of computer generated maps representing simple information structures and the other involving the use of more sophisticated information tools. The synthesis of both studies provides the bases for discussing the prospects of PGIS to empower citizens in making decisions about their communities and resources.     

Multicriteria analysis as a tool to investigate compatibility between conservation and development on Salina Island,Aeolian Archipelago,Italy

Several multicriteria evaluation techniques have been developed since the 1970s. The need to compare different territorial policies has justified their introduction into environmental research. These methods are based on the numerical manipulation of heterogeneous information, which varies in terms of reference scale and type of measure (continuous, ordinal, qualitative, binary, etc.). During recent years, diverse investigations have focused on general conditions on Salina, the “green island” of the Aeolian archipelago. Such studies, within an interdisciplinary project, aimed to explore the possibility of implementing conservation strategies that are compatible with human needs, landscape preservation, and sustainable economic development. Three different evaluation techniques are applied, namely multicriteria weighted concordance and discordance analysis and a qualitative procedure. They are used to compare four alternative plans for the socioeconomic development of Salina Island. These plans lie between extreme alternatives: total protection of natural resources and maximizing economic development based on tourism. The plans are compared to each other on the basis of 14 criteria that reflect the socioenvironmental perception of Salina's inhabitants. The approach used in this research seems particularly fruitful because of its flexibility: it offers decision makers the chance to manage heterogeneous data and information that is not easily quantifiable. Such “soft” information helps to evaluate environmental conditions more precisely, and to make a less damaging choice among alternative development plans.     

烟气脱硫技术的模糊评价

应用模糊数学原理，将素质决策与数量决策相结合，以三种典型烟气脱硫技术为例，对所涉及的定性和定量指标进行处理，经模糊线性加权变换，评估和优选出适合我国国情，具有较好的环境，社会，经济效益的烟气脱硫技术，比较表明，模糊决策方法在脱硫技术的评估和优选中优于单一的素质决策或数量决策方法，是一种有前途的科学的定量化决策方法。     

Assessing Risk in Operational Decisions Using Great Lakes Probabilistic Water Level Forecasts

/ A method adapted from the National Weather Service's Extended Streamflow Prediction technique is applied retrospectively to three Great Lakes case studies to show how risk assessment using probabilistic monthly water level forecasts could have contributed to the decision-mak-ing process. The first case study examines the 1985 International Joint Commission (IJC) decision to store water in Lake Superior to reduce high levels on the downstream lakes. Probabilistic forecasts are generated for Lake Superior and Lakes Michigan-Huron and used with riparian inundation value functions to assess the relative impacts of the IJC's decision on riparian interests for both lakes. The second case study evaluates the risk of flooding at Milwaukee, Wisconsin, and the need to implement flood-control projects if Lake Michigan levels were to continue to rise above the October 1986 record. The third case study quantifies the risks of impaired municipal water works operation during the 1964-1965 period of extreme low water levels on Lakes Huron, St. Clair, Erie, and Ontario. Further refinements and other potential applications of the probabilistic forecast technique are discussed.KEY WORDS: Great Lakes; Water levels; Forecasting; Risk; Decision making     

Human behavior incorporation into ecological computer simulations

The responses of ecological computer simulations are significantly changed by the inclusion of human behavior patterns. Two computer simulations illustrate this principle for internal and external decision making. The Northwest Educational Trawler Simulation (NETS) models the interaction between fish populations, fishing effort, markets, and a fishing community. This simulation includes an internal decision making submodel for changing fishing effort based on observed behaviors of fishermen. NOGERO, a simulation of a mythical coastal fishing culture, uses external decision making where simulation users act as stewards. The patterns of model response vary depending on the attitudes and goals of decision makers. This shows how human behavior interacts with ecosystem dynamics to produce a variety of results.     

Improving planning through interactive methodological research

The Hawaii Environmental Simulation Laboratory (HESL) was a three year experiment in improving governmental decision making by developing better research methodologies for use by public decision making bodies and community organizations. Funded through the University of Hawaii by the Ford Foundation (FF) and the National Science Foundation (NSF), HESL conducted its researchinteractively with the intended users of its products. This paper sets the HESL experiment in the context of recent trends in applying better methodology to environmental decision making and involving citizens in these decisions. It describes the HESL effort, and then draws conclusions about both the effectiveness of the experiment and the way it was conducted, providing information that may be useful in guiding university groups, public agencies, and community organizations pursuing similar objectives.     

Public reaction to the risks of energy technology

Implicit in every government decision on energy technology is a trade-off of a certain amount of risk in return for societal benefits. As a result of growing public concern over such risks, environmental analysts are increasingly being requested not only to describe potential adverse consequences but also to quantify their probability. However, this task is frustrated not only by inadequate experience with, and incomplete knowledge of, the causality of environmental impacts, but also by a disparity between individual and societal views of risk. While the societal view is based on objective risk functions andnet societal benefit, individuals tend to rely on subjective judgment, and consider the distribution as well as the amount of benefit. Thus, environmental risk assessments, produced by analysts on behalf of society as a whole, are likely to be quite speculative, and are unlikely to be reliable indicators of the acceptability of risk to the public.     

Decision making with option pricing and dynamic programming: development and application

In this study, an option pricing model and a dynamic programming model are developed. These models contribute to the improvement of the decision making process in two respects. First, these models allow for the own growth rate of mining costs to be incorporated into the analysis. Second, these models are developed to estimate the satisfactory gross revenue for investing, so that these models are helpful in analyzing multi-metal mines.The two models are applied to estimate the satisfactory revenue for investing in the Carlin east gold mine, Nevada, USA. The satisfactory revenue estimated by the option pricing model is found to be $42.2M, while that estimated by the dynamic programming model is found to be $44.4M. Since the revenue calculated on the basis of the current conditions is $36M, then the decision by option pricing and dynamic programming is to wait and not to invest now. Despite the difference between the two models in estimating and applying the discount rate, the two models generate the same decision.     

Decision making under uncertainty in case of soil remediation

Decisions on soil remediation are one of the most difficult management issues of municipal and state agencies. The assessment of contamination is uncertain, the costs of remediation are high, and the impacts on the environment are multiple. This paper presents a general, transparent, and consistent method for decision making among the remediation alternatives. Soil washing, phytoremediation, and no remediation are exemplarily considered. Multi-criteria utility functions including (a) the cost of remediation (b) the impact on human health and agricultural productivity, and (c) the economic gain after remediation are constructed using probability density functions representing contamination for all site coordinates. Herewith, the probability of different types of (i) correct decisions such as a hit or a true rejection and (ii) erroneous decisions such as a false alarm or miss are examined. The decision theoretic model is applied to a case study on heavy metal contaminated soil. This case study reveals the non-linear structure of multi-criteria-decision making. The case study shows that the geostatistical uncertainties of the log-normal distributed soil contamination must be taken into account: When uncertainties are not considered and the utilities are assessed according to the estimated value for a spatial unit, only few (N=26) spatial units result where the utility score of the alternative soil washing are higher than the utility score to the no remediation alternative. However, when taking into account geostatistical uncertainties of the log-normal soil distribution this number is about ten times greater (N=237). Furthermore, the use of 'maximizing expected utility' as decision rule is critical in that it may lead to a high probability of misses.     

Adaptive management of natural resources--framework and issues

Adaptive management, an approach for simultaneously managing and learning about natural resources, has been around for several decades. Interest in adaptive decision making has grown steadily over that time, and by now many in natural resources conservation claim that adaptive management is the approach they use in meeting their resource management responsibilities. Yet there remains considerable ambiguity about what adaptive management actually is, and how it is to be implemented by practitioners. The objective of this paper is to present a framework and conditions for adaptive decision making, and discuss some important challenges in its application. Adaptive management is described as a two-phase process of deliberative and iterative phases, which are implemented sequentially over the timeframe of an application. Key elements, processes, and issues in adaptive decision making are highlighted in terms of this framework. Special emphasis is given to the question of geographic scale, the difficulties presented by non-stationarity, and organizational challenges in implementing adaptive management.     

Using Multicriteria Methods in Environmental Planning and Management

In environmental planning and decision processes several alternatives are analyzed in terms of multiple noncommensurate criteria, and many different stakeholders with conflicting preferences are involved. Based on our experience in real-life applications, we discuss how multicriteria decision aid (MCDA) methods can be used successfully in such processes. MCDA methods support these processes by providing a framework for collecting, storing, and processing all relevant information, thus making the decision process traceable and transparent. It is therefore possible to understand and explain why, under several conflicting preferences, a particular decision was made. The MCDA framework also makes the requirements for new information explicit, thus supporting the allocation of resources for the process.     

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.     

INTEGRATING SCIENCE AND TECHNOLOGY TO SUPPORT STREAM NATURALIZATION NEAR CHICAGO,ILLINOIS1

ABSTRACT: Many urban and suburban communities in the Midwest are seeking to establish sustainable, morphologically and hydraulically varied, yet dynamically stable fluvial systems that are capable of supporting healthy, biologically diverse aquatic ecosystems — a process known as stream naturalization. This paper describes an integrated research program that seeks to develop a scientific and technological framework to support two stream naturalization projects near Chicago, Illinois. The research program integrates theory and methods in fluvial geomorphology, aquatic ecology, hydraulic engineering and social theory. Both the conceptual and the practical challenges of that integration are discussed. Scientific and technical support emphasize the development of predictive tools to evaluate the performance of possible naturalization designs at scales most appropriate to community based projects. Social analysis focuses on place based evaluations of how communities formulate an environmental vision and then, through decision making, translate this vision into specific stream naturalization strategies. Integration of scientific and technical with social components occurs in the context of community based decision making as the predictive tools are employed by project scientists to help local communities translate their environmental visions into concrete environmental designs. Social analysis of this decision making process reveals how the interplay between the community's vision of what they want the watershed to become, and the scientific perspective on what the watershed can become to achieve the community's environmental goals, leads to the implementation of specific stream naturalization practices.     

Passive and active adaptive management: approaches and an example

Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. Yet there remains considerable confusion about what adaptive management entails, and how to actually make resource decisions adaptively. A key but somewhat ambiguous distinction in adaptive management is between active and passive forms of adaptive decision making. The objective of this paper is to illustrate some approaches to active and passive adaptive management with a simple example involving the drawdown of water impoundments on a wildlife refuge. The approaches are illustrated for the drawdown example, and contrasted in terms of objectives, costs, and potential learning rates. Some key challenges to the actual practice of AM are discussed, and tradeoffs between implementation costs and long-term benefits are highlighted.