An empirical comparison of effective concentration estimators for evaluating aquatic toxicity test responses

Authors

  • A. John Bailer,

    Corresponding author
    1. Center for Environmental Toxicology and Statistics, Miami University, Oxford, Ohio 45056-1641, USA
    2. Department of Mathematics and Statistics Miami University, Oxford, Ohio 45056-1641, USA
    • Center for Environmental Toxicology and Statistics, Miami University, Oxford, Ohio 45056-1641, USA
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  • Michael R. Hughes,

    1. Center for Environmental Toxicology and Statistics, Miami University, Oxford, Ohio 45056-1641, USA
    2. Department of Mathematics and Statistics Miami University, Oxford, Ohio 45056-1641, USA
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  • Debra L. Denton,

    1. U.S. Environmental Protection Agency, Region IX, 75 Hawthorne Street, WTR-5, San Francisco, California 94105-3901
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  • James T. Oris

    1. Center for Environmental Toxicology and Statistics, Miami University, Oxford, Ohio 45056-1641, USA
    2. Department of Zoology, Miami University, Oxford, Ohio 45056, USA
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  • Although the research described in this article was funded wholly or in part by the U.S. Environmental Protection Agency (contract 68-C4-0034) and Science Applications International Corporation (subcontract 4500145731), it was not reviewed by either entity and therefore does not necessarily reflect their views. No official endorsement should be inferred.

Abstract

Aquatic toxicity tests are statistically evaluated by either hypothesis testing procedures to derive a no-observed-effect concentration or by inverting regression models to calculate the concentration associated with a specific reduction from the control response. These latter methods can be described as potency estimation methods. Standard U.S. Environmental Protection Agency (U.S. EPA) potency estimation methods are based on two different techniques. For continuous or count response data, a nominally nonparametric method that assumes monotonic decreasing responses and piecewise linear patterns between successive concentration groups is used. For quantal responses, a probit regression model with a linear dose term is fit. These techniques were compared with a recently developed parametric regression-based estimator, the relative inhibition estimator, RIp. This method is based on fitting generalized linear models, followed by estimation of the concentration associated with a particular decrement relative to control responses. These estimators, with levels of inhibition (p) of 25 and 50%, were applied to a series of chronic toxicity tests in a U.S. EPA region 9 database of reference toxicity tests. Biological responses evaluated in these toxicity tests included the number of young produced in three broods by the water flea (Ceriodaphnia dubia) and germination success and tube length data from the giant kelp (Macrocystis pyrifera). The greatest discrepancy between the RIp and standard U.S. EPA estimators was observed for C. dubia. The concentration–response pattern for this biological endpoint exhibited nonmonotonicity more frequently than for any of the other endpoint. Future work should consider optimal experimental designs to estimate these quantities, methods for constructing confidence intervals, and simulation studies to explore the behavior of these estimators under known conditions.

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