Species Sensitivity Distributions in Ecotoxicology - Section 4 (end)

Section IV Evaluation and Outlook This final section presents an overview of the current field and of options for future developments. The concepts and data presented in the preceding chapters and in the literature have been analyzed in view of the criticisms of SSDs that have been voiced in the past, and during the Interactive Poster Session that was held in 1999 at the 20th Annual Meeting of the Society of Environmental Toxicology and Chemistry in Philadelphia, Pennsylvania. In the concluding outlook chapter, all preceding chapters have been reconsidered to determine the prospects for resolving the criticisms and problems of SSDs. Some of these issues, those that seem amenable to solution, have been extrapolated to the near future, to stimulate discussion and thought on further SSD evolution. © 2002 by CRC Press LLC 21 Issues and Practices in the Derivation and Use of Species Sensitivity Distributions Glenn W. Suter II, Theo P.Traas, and Leo Posthuma CONTENTS 21.1 The Uses of SSDs 21.1.1 SSDs for Derivation of Environmental Quality Criteria 21.1.2 SSDs for Ecological Risk Assessment 21.1.2.1 Assessment Endpoints and the Definition of Risk 21.1.2.2 Ecological Risk Assessment of Mixtures 21.1.3 Probability of Effects from SSDs 21.2 Statistical Model Issues 21.2.1 Selection of Distribution Functions and Goodness-of-Fit 21.2.2 Confidence Levels 21.2.3 Censoring and Truncation 21.2.4 Variance Structure 21.3 The Use of Laboratory Toxicity Data 21.3.1 Test Endpoints 21.3.2 Laboratory to Field Extrapolation 21.4 Selection of Input Data 21.4.1 SSDs for Different Media 21.4.2 Types of Data 21.4.3 Data Quality 21.4.4 Adequate Number of Observations 21.4.5 Bias in Data Selection 21.4.6 Use of Estimated Values 21.5 Treatment of Input Data 21.5.1 Heterogeneity of Media 21.5.2 Acute–Chronic Extrapolations 21.5.3 Combining Data for a Species 21.5.4 Combining Data across Species 21.5.5 Combining Taxa in a Distribution © 2002 by CRC Press LLC 21.5.6 Combining Data across Environments 21.5.7 Combining Data across Durations 21.5.8 Combining Chemicals in Distributions 21.6 Selection of Protection Levels 21.7 Risk Assessment Issues 21.7.1 Exposure 21.7.2 Ecological Issues 21.7.3 Joint Distributions of Exposure and Species Sensitivity 21.8 The Credibility of SSDs 21.8.1 Reasonable Results 21.8.2 Confirmation Studies 21.8.3 SSD vs. Alternative Extrapolation Models 21.9 Conclusions Abstract — As is clear from the preceding chapters, species sensitivity distributions (SSDs) have come to be commonly used in many countries for setting environmental quality criteria (EQCs) and assessing ecological risks (ERAs). However, SSDs have had their critics, and the critics and users of SSD models have raised conceptual and methodological concerns. This chapter evaluates issues raised in published critiques of SSDs (e.g., Forbes and Forbes, 1993; Hopkin, 1993; Smith and Cairns, 1993; Chapman et al., 1998), in a session at the 1999 SETAC Annual Meeting (Appendix A), and in the course of preparing this book. The issues addressed include conceptual issues, statistical issues, the utility of laboratory data, data selection, treatment of data, selec-tion of protection levels, and the validity of SSDs. When considering these issues, one should be aware that the importance and implications of these issues may depend on the context and use of an SSD. The consequences of this evaluation for further devel-opment of SSDs are elaborated in Chapter 22. 21.1 THE USES OF SSDS Models of species sensitivity distributions (SSDs) with respect to a toxic substance can be used in two conceptually distinct ways (Chapters 1 and 4). The first use is to estimate the concentration that affects a particular proportion of species, the HCp. This is the older so-called inverse use, and is employed in the derivation of envi-ronmental criteria. The second use is the forward use of SSDs, which estimates the potentially affected fraction (PAF) of species, or the probability of effects on a species (PES) at a given concentration. The PAF or PES can be calculated for single chemicals and these values can be aggregated to a single value for mixtures of chemicals. In any of these uses, it is assumed that protection of species and communities may be assured by considering the distribution of sensitivities of species tested individually. Although some regu-latory agencies have embraced the concept of risk embedded in the use of SSDs (Chapters 2 and 3) the assumption that SSD-derived criteria are protective is an open question. The definition and interpretation of risk as defined previously (Suter, 1993; Chapters 15 through 17) play a major part in the interpretation of the outcome of SSD methods, as discussed below. © 2002 by CRC Press LLC 21.1.1 SSDS FOR DERIVATION OF ENVIRONMENTAL QUALITY CRITERIA As discussed in the introductory chapters, SSDs were developed to derive criteria for the protection of ecological entities in contaminated media. That is, criteria are set at an HCp or an HCp modified by some factor. Such criteria may be interpreted as, literally, levels that will protect 1 – p% of species or simply as consistent values that provide reasonable protection from unspecified effects. If the criteria are interpreted as protecting 1 – p% of species from some effect with defined confidence, then they are potentially subject to scientific confirmation. Some studies have attempted to confirm SSD-based quality criteria in the last decade by comparing them to contaminant effects in the field (Chapter 9 and Section 21.8.2). However, if criteria derived from SSDs are inter-preted simply as reasonable and consistent values, their utility is confirmed in that sense by a record of use that has been politically and legally acceptable. That is, if they were not reasonable and consistent, they would be struck down by the courts or replaced due to pressures from industry or environmental advocacy groups. The U.S. Environmental Protection Agency (U.S. EPA) National Ambient Water Quality Criteria and the Dutch Environmental Risk Limits for water, soil, and sediment have achieved at least the latter degree of acceptance. A general acceptance of the SSD methodology is not necessarily negated by challenges incidentally posed to individual SSD-based criteria such as the challenge of the environmental quality criterion (EQC) for zinc by European industries (RIVM/TNO, 1999). The general acceptance of SSD-derived criteria should not suggest a uniformity of methods around the globe. Adopted methods for deriving EQCs vary in many ways among countries, including the choice and treatment of input data, statistical models, and choice of protection level (Chapters 10 through 20; Roux et al., 1996; Tsvetnenko, 1998; Vega et al., 1997; Tong et al., 1996; ANZECC 2000a,b; etc.). One homology is that SSDs defined by unimodal distribution functions are the basis for deriving EQC in several countries. Polymodality of the data may, however, occur for compounds with a taxon-specific toxic mode of action (TMoA) (Section 21.5.5), and Aldenberg and Jaworska (1999) suggested polymodal model for EQC derivation. The HCp values in the protective range of use (e.g., 5th percentile) estimated with this model were shown to be numerically fairly robust toward deviations from unimodality in some selected cases (Aldenberg and Jaworska, 1999). For compounds with a specific TMoA, it can be argued that the variance in species sensitivity as estimated from the total data set is larger and not representative of the variance of the target species. This would lead to overprotective criteria since the HCp is very sensitive to this variance. On the other hand, it can be argued that the total variance may lead to more protective criteria, providing some safety against unknown or unexpected side effects. Conclusive numerical data remain to be presented in this matter. On non-numerical grounds, but driven by considering the assessment end-points, the estimate of a specific HCp for a target taxon may be preferred over an HCp based on the total data set (Chapter 15). The diversity of operational details and the invention of new approaches like polymodal statistics suggest that discussions will proceed in the use of SSD for deriving environmental quality standards. The history of SSD use (Chapters 2 and 3) © 2002 by CRC Press LLC teaches that it is important to distinguish clearly in the discussion between issues related to assessment endpoints, methodological details of SSDs, and choices within the SSD concept related to the policy context. 21.1.2 SSDS FOR ECOLOGICAL RISK ASSESSMENT The goal of risk assessment is to estimate the likelihood of specified effects such as death of humans or sinking of a ship. The growing use of SSDs in ecological risk assessments and the diverse terminology used so far (Chapter 4; Chapters 15 through 20) necessitate a sharp definition of the outcome of SSDs in terms of predicted risks for specific ecological endpoints. Also, unlike criteria, risk assessments must deal with real sites, which requires modeling the effects of mixtures. SSDs have been incorporated into formal ecological risk assessment methods developed by the Water Environment Research Foundation (WERF, Parkhurst et al., 1996), the Aquatic Risk Assessment and Mitigation Dialog Group (ARAMDG, Baker et al., 1994), and the Ecological Committee on FIFRA Risk Assessment Methods (ECOFRAM, 1999a,b). 21.1.2.1 Assessment Endpoints and the Definition of Risk The appropriateness of SSDs in risk assessment depends on the endpoints of the assessment as well as the use of the SSDs in the inferential process. Assessment endpoints are the operational definition of the environmental values to be protected by risk-based environmental management (Suter, 1989; U.S. EPA, 1992). They consist of an ecological entity such as the fish assemblage of a stream and a property of that entity such as the number of species. Assessment endpoints are estimated from numerical summaries of tests (i.e., test endpoints such as LC50 values) or of observational studies (e.g., catch per unit effort). The extrapolation from these measures of effect to an assessment endpoint is performed using a model such as an SSD. If SSDs are used inferentially to estimate risks to ecological communities, it is necessary to define the relationship of the SSD to the assessment endpoint, given the input data (test endpoints). Currently, two types of test endpoints are most often used, acute LC50 values* and chronic no-observed-effects concentrations (NOECs) or chronic values (CVs), which yield acute (SSDLC50) and chronic (e.g., SSDNOEC) SSDs with different implications. The acute LC50 values are based on mortality or equivalent effects (i.e., immo-bilization) on half of exposed organisms. Hence, this test endpoint implies mass mortality of individuals. At the population level, it could be interpreted as approx-imately a 50% immediate reduction in abundance of an exposed population. As discussed in Chapter 15, some populations recover rapidly from this loss, but other populations are slow to recover. The immediate consequences of mass mortality are, however, often unacceptable in either case. Hence, if such SSDs are considered to be estimators of the distribution of severe effects among species in the field, then the acute SSDs (SSDLC50) may be considered to predict the proportion of species experiencing severe population reductions following short-term exposures. An example * For brevity, we use LC50 to signify both acute LC50 and EC50. © 2002 by CRC Press LLC ... - tailieumienphi.vn