Glenn W. Suter

Assessing ecological risk on a regional scale

Society needs a quantitative and systematic way to estimate and compare the impacts of environmental problems that affect large geographic areas. This paper presents an approach for regional risk assessment that combines regional assessment methods and landscape ecology theory with an existing framework for ecological risk assessment. Risk assessment evaluates the effects of an environmental change on a valued natural resource and interprets the significance of those effects in light of the uncertainties identified in each component of the assessment process. Unique and important issues for regional risk assessment are emphasized; these include the definition of the disturbance scenario, the assessment boundary definition, and the spatial heterogeneity of the landscape.

Communicating Ecological Indicators to Decision Makers and the Public

Introduction EMAP’s Indicators A Region as a Case Study Development of Common-language Indicators Testing the Common-language Indicators From “values” to “valued aspects” Testing CLIs in relation to valued aspects of the environment Discussion Final thoughts Responses to this Article Acknowledgments Literature Cited Appendix 1 Appendix 2 Appendix 3

Applicability of indicator monitoring to ecological risk assessment

Abstract Although ecological risk assessment (ERA) and environmental monitoring would seem to be potentially complimentary activities, they have been disjunct in practice. This is because of differences in goals and products. Environmental monitoring determines status and trends in indicators to determine whether the environment is improving. ERA estimates effects of stressors on endpoint attributes to support decision making. Indicators are, by definition, indicative of some unmeasured condition. Assessment endpoints are valued properties of the environment that are susceptible to stressors of concern. Indicators are justified by the logic of the monitoring program, which may be self-referential. Assessment endpoints are justified by their potential susceptibility and by environmental policies and public values. Indicators are often expressed in terms of indices or scores that obscure the actual condition of the environment. Because assessment endpoints must be clear to decision makers and the public, they require real units of actual environmental properties. Monitoring programs are peripherally concerned about causal relationships, while risk assessment is devoted to elucidating causal relationships. As a result, risk assessments may use the results of monitoring studies, but only after disaggregating the indicators to their components and choosing those that are appropriate. Monitoring programs could be more useful if they used a risk-based approach to address important problems rather than simply tracking indicators.

Abuse of hypothesis testing statistics in ecological risk assessment

Abstract Statistical hypothesis testing is commonly used inappropriately to analyze data, determine causality, and make decisions about significance in ecological risk assessment. Hypothesis testing is conceptually inappropriate in that it is designed to test scientific hypotheses rather than to estimate risks. It is inappropriate for analysis of field studies because it requires replication and random assignment of treatments. It discourages good toxicity testing and field studies, it provides less protection to ecosystems or their components that are difficult to sample or replicate, and it provides less protection when more treatments or responses are used. It provides a poor basis for decision‐making because it does not generate a conclusion of no effect, it does not indicate the nature or magnitude of effects, it does not address effects at untested exposure levels, and it confounds effects and uncertainty. Attempts to make hypothesis testing less problematical cannot solve these problems. Rather, ri...

Derivation of a benchmark for freshwater ionic strength.

Because increased ionic strength has caused deleterious ecological changes in freshwater streams, thresholds for effects are needed to inform resource-management decisions. In particular, effluents from surface coal mining raise the ionic strength of receiving streams. The authors developed an aquatic life benchmark for specific conductance as a measure of ionic strength that is expected to prevent the local extirpation of 95% of species from neutral to alkaline waters containing a mixture of dissolved ions in which the mass of SO (4)2- + HCO (3)- ≥ Cl(-). Extirpation concentrations of specific conductance were estimated from the presence and absence of benthic invertebrate genera from 2,210 stream samples in West Virginia. The extirpation concentration is the 95th percentile of the distribution of the probability of occurrence of a genus with respect to specific conductance. In a region with a background of 116 µS/cm, the 5th percentile of the species sensitivity distribution of extirpation concentrations for 163 genera is 300 µS/cm. Because the benchmark is not protective of all genera and protects against extirpation rather than reduction in abundance, this level may not fully protect sensitive species or higher-quality, exceptional waters.

Framework for the Integration of Health and Ecological Risk Assessment

The World Health Organizations International Programme on Chemical Safety (IPCS), the Organization for Economic Cooperation and Development (OECD), and the U.S. Environmental Protection Agency have developed a collaborative partnership to foster integration of assessment approaches for human health and ecological risks. This paper presents the framework developed by that group. Integration provides coherent expressions of assessment results, incorporates the interdependence of humans and the environment, uses sentinel organisms, and improves the efficiency and quality of assessments relative to independent human health and ecological risk assessments. The paper describes how integration can occur within each component of risk assessment, and communicates the benefits of integration at each point. The goal of this effort is to promote the use of this internationally accepted guidance as a basis for harmonization of risk assessment.

Decision support systems for risk based management of contaminated sites

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). Standard DSSs might be characterized as computational systems that provide access to a wealth of information pertaining to a specific problem. The types of information that might be available include information content, maps, and data. This information can be contained in databases and geographic information systems (GIS). Access is often provided through interfaces to queries that ease the task of sifting through the often large amounts of information available. These DSSs facilitate some numerical analysis (e.g., overlays of data on GIS images, rudimentary statistical analysis of data), but usually only indirectly affect evaluation and problem solving. Currently, DSSs of this form are the most common. However, an option exists to incorporate evaluation and problem solving directly into a DSS by using statistical decision tools such as sensitivity analysis and multi-criteria decision analysis. These systems may be thought of as decision analysis (MCDA) support systems. Development of a DSS requires consideration of both the problem to be solved and the computational tools that are appropriate or needed. In terms of the problem, important components include: definition of objectives; links to the legislative or regulatory context; model structuring including identification of, and relationships between, parameters; cost factors; and value judgments. These should encompass environmental, economic and socio-political concerns. This is the standard approach to performing decision analysis using MCDA tailored specifically to environmental problem solving. A further P. Black (*) Neptune and Company, Inc., Denver Colorado and Los Alamos, New Mexico, US e-mail: www.neptune.com A. Marcomini et al. (eds.), Decision Support Systems for Risk-Based Management of Contaminated Sites, DOI 10.1007/978-0-387-09722-0_1, Springer ScienceþBusiness Media, LLC 2009 1 consideration is how to gather and present case studies, once the DSS is developed. Computational issues that are faced include: database management (e.g., information, data, GIS); analysis tools (statistics, fate and transport modeling, risk assessment, MCDA); visualization of the problem; presentation of results; document production; feedback mechanisms; help; and advice. The user interface to each of these components, the navigation through these components, and degree of openness of each component of the DSS must also be considered. Openness, including communication and stakeholder involvement, is very important for maintaining transparency and defensibility in all aspects of the DSS.

Why and how to combine evidence in environmental assessments: Weighing evidence and building cases

All types of environmental decisions benefit from assessments that assemble and analyze diverse evidence. The diversity of that evidence creates complexities that can be managed using an explicit, well-designed process. We suggest two adaptations from the legal lexicon, weight of evidence and building a case. When weighing evidence, weights are assigned to each piece of evidence, and then the body of evidence is weighed in favor of each hypothesis by amassing the weights. Finally, the total weights of evidence for the alternative hypotheses are compared to determine which alternative has the preponderance of evidence in its favor. When building a case, pieces of evidence are organized to show relationships among multiple hypotheses or complex interactions among agents, events, or processes. We provide processes for weighing evidence and building a case and illustrate both approaches in a case study involving the decline of a kit fox population. The general approach presented here is flexible, transparent, and defensible. During its development, it has been applied to risk assessments for contaminated sites and to causal assessments in aquatic and terrestrial systems. It is intended to balance the need for rigor and discipline with the need for sufficient flexibility to accept all relevant evidence and generate creative solutions to difficult environmental problems.

Developing Conceptual Models for Complex Ecological Risk Assessments

Conceptual models are representations of the assumed relationship between sources and effects. They serve three important purposes. (1) Their creation compels assessors to think through and clarify their assumptions concerning the activities being assessed. (2) They serve as a communication tool for conveying those assumptions to risk managers and stakeholders. (3) They provide a basis for organizing and conducting the risk assessment. Conceptual models for risk assessments of chemical contaminants have not been problematical because they simply portray the flow of the contaminant from a source to a receptor that experiences toxic effects. However, ecological risk assessments must increasingly deal with direct and indirect effects on multiple endpoint receptors and with multiple complex activities including both physical effects and toxic effects. This complexity may result in conceptual models that are incomplete, ambiguous, or simply too complex to be understood. This paper presents a strategy for creat...

Assessing causation of the extirpation of stream macroinvertebrates by a mixture of ions

Increased ionic concentrations are associated with the impairment of benthic invertebrate assemblages. However, the causal nature of that relationship must be demonstrated so that it can be used to derive a benchmark for conductivity. The available evidence is organized in terms of six characteristics of causation: co-occurrence, preceding causation, interaction, alteration, sufficiency, and time order. The inferential approach is to weight the lines of evidence using a consistent scoring system, weigh the evidence for each causal characteristic, and then assess the body of evidence. Through this assessment, the authors found that a mixture containing the ions Ca(+), Mg(+), HCO 3(-), and SO 4(-), as measured by conductivity, is a common cause of extirpation of aquatic macroinvertebrates in Appalachia where surface coal mining is prevalent. The mixture of ions is implicated as the cause rather than any individual constituent of the mixture. The authors also expect that ionic concentrations sufficient to cause extirpations would occur with a similar salt mixture containing predominately HCO 3(-), SO 4(2-), Ca(2+), and Mg(2+) in other regions with naturally low conductivity. This case demonstrates the utility of the method for determining whether relationships identified in the field are causal.