John Wiley & Sons, Ltd.

Assessment of hazard metrics for predicting field benthic invertebrate toxicity in the Detroit River, Ontario, Canada

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Numerical sediment quality guidelines (SQGs) are frequently used to interpret site specific sediment chemistry and predict potential toxicity to benthic communities. These SQGs are useful for a screening line of evidence (LOE) that can be combined with other LOEs in a full weight of evidence (WOE) assessment of impacted sites. Three common multi‐chemical hazard quotient methods (PEC‐Qavg, PEC‐Qmet and PEC‐Qsum) and a novel (Hazard Score; HZD) approach were used in conjunction with a consensus based set of SQGs to evaluate the ability of different scoring metrics to predict the biological effects of sediment contamination under field conditions. Multivariate analyses were first used to categorize river sediments into distinct habitats based on a set of physicochemical parameters to include gravel, low and high flow sand and silt. For high flow sand and gravel, no significant dose‐response relationships between numerically dominant species and various toxicity metric scores were observed. Significant dose‐response relationships were observed for Chironomid abundances and toxicity scores in low flow sand and silt habitats. For silt habitats the HZD scoring metric provided the best predictor of Chironomid abundances compared to various PEC‐Q methods according to goodness of fit tests. For low flow sand habitats, PEC‐Qsum followed by HZD, provided the best predictors of Chironomid abundance. Differences in apparent Chironomid toxicity between the two habitats suggest habitat specific differences in chemical bioavailability and indicator taxa sensitivity. Using an index of biological integrity (IBI) method, the HZD, PEC‐Qavg and PEC‐Qmet approaches provided reasonable correlations with calculated IBI values in both silt and low flow sand habitats but not for gravel or high flow sands. Computation differences between the various multi‐chemical toxicity scoring metrics and how this contributes to bias in different estimates of chemical mixture toxicity scores are discussed and compared. This article is protected by copyright. All rights reserved

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