A Weight-of-Evidence Framework for Assessing Sediment (Or Other) Contamination: Improving Certainty in the Decision-Making Process

A basic framework is presented for the ecological weight-of-evidence (WOE) process for sediment assessment that clearly defines its essential elements and will improve the certainty of conclusions about whether or not impairment exists due to sediment contamination, and, if so, which stressors and biological species (or ecological responses) are of greatest concern. The essential “Certainty Elements” are addressed in a transparent best professional judgment (BPJ) process with multiple lines-of-evidence (LOE) ultimately quantitatively integrated (but not necessarily combined into a single value). The WOE Certainty Elements include: (1) Development of a conceptual model (showing linkages of critical receptors and ecosystem quality characteristics); (2) Explanation of linkages between measurement endpoint responses (direct and indirect with associated spatial/temporal dynamics) and conceptual model components; (3) Identification of possible natural and anthropogenic stressors with associated exposure dynamics; (4) Evaluation of appropriate and quantitatively based reference (background) comparison methods; (5) Consideration of advantages and limitations of quantification methods used to integrate LOE; (6) Consideration of advantages and limitations of each LOE used; (7) Evaluation of causality criteria used for each LOE during output verification and how they were implemented; and (8) Combining the LOE into a WOE matrix for interpretation, showing causality linkages in the conceptual model. The framework identifies several statistical approaches for integrating within LOE, the suitability of which depends on physical characteristics of the system and the scale/nature of impairment. The quantification approaches include: (1) Gradient (regression methods); (2) Paired reference/test (before/after control impact and ANOVA methods); (3) Multiple reference (ANOVA and multivariate methods); and 4) Gradient with reference (regression, ANOVA and multivariate methods). This WOE framework can be used for any environmental assessment and is most effective when incorporated into the initial and final study design stages (e.g., the Problem Formulation and Risk Characterization stages of a risk assessment) with reassessment throughout the project and decision-making process, rather than in a retrospective data analysis approach where key certainty elements cannot be adequately addressed.

[1]  V. Resh,et al.  Water quality monitoring and aquatic organisms: the importance of species identification. , 1975, Journal - Water Pollution Control Federation.

[2]  Joseph S. Meyer,et al.  The utility of the terms "bioavailability" and "bioavailable fraction" for metals. , 2002, Marine environmental research.

[3]  P. J. den Besten,et al.  Sediment quality assessment in the delta of rivers Rhine and Meuse based on field observations, bioassays and food chain implications , 1995 .

[4]  W. Landis,et al.  A Regional Multiple-Stressor Rank-Based Ecological Risk Assessment for the Fjord of Port Valdez, Alaska , 1998 .

[5]  Mike T. Furse,et al.  The reference condition: problems and solutions. , 2000 .

[6]  Robert C. Bailey,et al.  Biological guidelines for freshwater sediment based on BEnthic Assessment of SedimenT (the BEAST) using a multivariate approach for predicting biological state , 1995 .

[7]  P. Chapman,et al.  Assessing sediment contamination in estuaries , 2001, Environmental toxicology and chemistry.

[8]  Valery E. Forbes,et al.  Applying Weight-of-Evidence in Retrospective Ecological Risk Assessment When Quantitative Data Are Limited , 2002 .

[9]  R. Bailey,et al.  Does taxonomic resolution affect the multivariate description of the structure of freshwater benthic macroinvertebrate communities , 1997 .

[10]  Rick Gunn,et al.  Macroinvertebrate frequency data for the RIVPACS III sites in Great Britain and their use in conservation evaluation , 1996 .

[11]  Michaela Aschan,et al.  Analysis of community attributes of the benthic macrofauna of Frierfjord/Langesundfjord and in a mesocosm experiment , 1988 .

[12]  D. Mitchell,et al.  Special report of the Massachusetts weight‐of‐evidence workgroup A weight‐of‐evidence approach for evaluating ecological risks , 1996 .

[13]  Robert B. Wenger,et al.  A method for assessing environmental risk: A case study of Green Bay, Lake Michigan, USA , 1994 .

[14]  D. Ellis Taxonomic sufficiency in pollution assessment , 1985 .

[15]  Charles P. Hawkins,et al.  Evaluation of the use of landscape classifications for the prediction of freshwater biota: synthesis and recommendations , 2000, Journal of the North American Benthological Society.

[16]  A. John Bailer,et al.  A Pooled Response Strategy for Combining Multiple Lines of Evidence to Quantitatively Estimate Impact , 2002 .

[17]  R. Warwick The level of taxonomic discrimination required to detect pollution effects on marine benthic communities , 1988 .

[18]  Trefor B. Reynoldson,et al.  Integrating Multiple Toxicological Endpoints in a Decision-Making Framework for Contaminated Sediments , 2002 .

[19]  Peter M. Chapman,et al.  A Sediment Quality Triad: Measures of sediment contamination, toxicity and infaunal community composition in Puget Sound , 1985 .

[20]  Gary Johnson,et al.  A Decision Making Framework for Sediment Assessment Developed for the Great Lakes , 2002 .

[21]  P. Chapman Ecotoxicology and pollution—Key issues , 1995 .

[22]  Wellesley Site,et al.  What is an Ecological Risk Assessment ? , 2004 .

[23]  Robert Pitt,et al.  Stormwater Effects Handbook: A Toolbox for Watershed Managers, Scientists, and Engineers , 2001 .

[24]  P M Chapman,et al.  Presentation and interpretation of Sediment Quality Triad data , 1996, Ecotoxicology.

[25]  P. J. Besten Concepts for the implementation of biomarkers in environmental monitoring , 1998 .

[26]  R. Warwick Analysis of community attributes of the macro-benthos of Frierfjord/Langesundfjord at taxonomic levels higher than species , 1988 .

[27]  Peter M. Chapman,et al.  The sediment quality triad approach to determining pollution-induced degradation , 1990 .

[28]  Wayne G. Landis,et al.  A Regional Multiple Stressor Risk Assessment of the Codorus Creek Watershed Applying the Relative Risk Model , 2002 .

[29]  Wayne G. Landis,et al.  Design criteria and derivation of indicators for ecological position, direction, and risk , 2000 .

[30]  J. F. Wright,et al.  Development and use of a system for predicting the macroinvertebrate fauna in flowing waters , 1995 .

[31]  B. Hattum,et al.  Bioavailability, Uptake and Effects of PAHs in Aquatic Invertebrates in Field Studies , 2003 .

[32]  R. Peterman Statistical Power Analysis can Improve Fisheries Research and Management , 1990 .

[33]  G. Allen Burton,et al.  Weight-of-Evidence Approaches for Assessing Ecosystem Impairment , 2002 .

[34]  Eric P. Smith BACI design , 2001 .

[35]  G. Burton,et al.  A tiered, weight-of-evidence approach for evaluating aquatic ecosystems , 2003, Sediment Quality Assessment and Management.

[36]  L. Kapustka,et al.  Effects‐initiated assessments are not risk assessments , 1997 .