Estimation of Wildlife Hazard Levels Using Interspecies Correlation Models and Standard Laboratory Rodent Toxicity Data

Abstract

Toxicity data from laboratory rodents are widely available and frequently used in human health assessments as animal model data. This study explores the possibility of using single rodent acute toxicity values to predict chemical toxicity to a diversity of wildlife species and estimate hazard levels from modeled species sensitivity distributions (SSD). Interspecies correlation estimation (ICE) models predict toxicity values for untested species using the sensitivity relationship between measured toxicity values of two species. Predicted toxicity values can subsequently populate SSD for application in ecological risk assessments. Laboratory mouse and rat toxicity values were used to estimate toxicity to wildlife and the predicted values then were used to derive SSD hazard dose levels. Toxicity values were predicted within fivefold of measured toxicity values for 78% of ICE models using laboratory rat or mouse toxicity as a surrogate value. Hazard dose levels (HD5) were within fivefold of measured estimates for 72% of SSD developed using laboratory rodent ICE models. Rodents were most often in the least sensitive quartile of species sensitivity distributions, and therefore toxicity values alone may not adequately represent the toxicity to many species of concern without appropriate safety or assessment factors. Laboratory rodent toxicity data offer an additional source of information that can be used to predict hazard levels for wildlife species, and thus offer a starting point for both health and ecological risk assessment.

Acknowledgements

For database development and maintenance, we thank Brian Montague (U.S. EPA, Office of Pesticide Programs), and Pierre Mineau, Alain Baril, and Brian Collins (Environment Canada). We are also grateful to support personnel: Deborah Vivian, Marion Marchetto, Anthony DiGirolamo, Christel Chancy, Nathan Lemoine, Nicole Allard, and Cheryl McGill (U.S. EPA, Gulf Ecology Division). Joel Chaney shared examples of S-plus code. We thank Don Rodier and four anonymous reviewers for comments on an earlier draft of the article. Support for manuscript preparation was provided by the U.S. EPA, National Health and Environmental Effects Research Laboratory. This is GED contribution number 1362. Although this article was submitted for internal review within the U.S. EPA and approved for publication, it does not reflect the views of the agency or constitute an endorsement of any trade names or commercial products mentioned.