Predicting amphipod toxicity from sediment chemistry using logistic regression models

Authors

  • L. Jay Field,

    Corresponding author
    1. Coastal Protection and Restoration Division, Office of Response and Restoration, National Oceanic and Atmospheric Administration, 7600 Sand Point Way North East, Seattle, Washington 98115, USA
    • Coastal Protection and Restoration Division, Office of Response and Restoration, National Oceanic and Atmospheric Administration, 7600 Sand Point Way North East, Seattle, Washington 98115, USA
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  • Donald D. MacDonald,

    1. MacDonald Environmental Sciences, 4800 Island Highway N Nanaimo British Columbia V9T 1W6 Canada
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  • Susan B. Norton,

    1. National Center for Environmental Assessment, U.S. Environmental Protection Agency, 1200 Pennsylvania Avenue NW Washington, DC 20460
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  • Christopher G. Ingersoll,

    1. Columbia Environmental Research Center, U.S. Geological Survey, 4200 New Haven Road, Columbia, Missouri 65201
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  • Corinne G. Severn,

    1. Premier Environmental Services, 10999 Pumpkin Ridge Avenue, Las Vegas, Nevada, 89135, USA
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  • Dawn Smorong,

    1. MacDonald Environmental Sciences, 4800 Island Highway N Nanaimo British Columbia V9T 1W6 Canada
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  • Rebekka Lindskoog

    1. MacDonald Environmental Sciences, 4800 Island Highway N Nanaimo British Columbia V9T 1W6 Canada
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  • The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the National Oceanic and Atmospheric Administration, the U.S. Environmental Protection Agency, or the U.S. Geological Survey.

Abstract

Individual chemical logistic regression models were developed for 37 chemicals of potential concern in contaminated sediments to predict the probability of toxicity, based on the standard 10-d survival test for the marine amphipods Ampelisca abdita and Rhepoxynius abronius. These models were derived from a large database of matching sediment chemistry and toxicity data, which includes contaminant gradients from a variety of habitats in coastal North America. Chemical concentrations corresponding to a 20, 50, and 80% probability of observing sediment toxicity (T20, T50, and T80 values) were calculated to illustrate the potential for deriving application-specific sediment effect concentrations and to provide probability ranges for evaluating the reliability of the models. The individual chemical regression models were combined into a single model, using either the maximum (PMax model) or average (PAvg model) probability predicted from the chemicals analyzed in a sample, to estimate the probability of toxicity for a sample. The average predicted probability of toxicity (from the PMax model) within probability quartiles closely matched the incidence of toxicity within the same ranges, demonstrating the overall reliability of the PMax model for the database that was used to derive the model. The magnitude of the toxic effect (decreased survival) in the amphipod test increased as the predicted probability of toxicity increased. Users have a number of options for applying the logistic models, including estimating the probability of observing acute toxicity to estuarine and marine amphipods in 10-d toxicity tests at any given chemical concentration or estimating the chemical concentrations that correspond to specific probabilities of observing sediment toxicity.

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