Acute toxicity prediction to threatened and endangered species using Interspecies Correlation Estimation (ICE) models
Citation:
Willming, M., C. Lilavois, M. Barron, AND Sandy Raimondo. Acute toxicity prediction to threatened and endangered species using Interspecies Correlation Estimation (ICE) models. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 50(19):10700-10707, (2016).
Impact/Purpose:
Reporting on the development and optimization of ICE models for listed species toxicity estimation
Description:
Evaluating contaminant sensitivity of threatened and endangered (listed) species and protectiveness of chemical regulations often depends on toxicity data for commonly tested surrogate species. The U.S. EPA’s Internet application Web-ICE is a suite of Interspecies Correlation Estimation (ICE) models that can extrapolate species sensitivity to listed taxa using least-squares regressions of the sensitivity of a surrogate species and a predicted taxon (species, genus, or family). Web-ICE was expanded with new models that can predict toxicity to over 250 listed species. A case study was used to assess protectiveness of genus and family model estimates derived from either geometric mean or minimum taxa toxicity values for listed species. Models developed from the most sensitive value for each chemical were generally protective of the most sensitive species within predicted taxa, including listed species, and were more protective than geometric means models. ICE model estimates were compared to HC5 values derived from Species Sensitivity Distributions for the case study chemicals to assess protectiveness of the two approaches. ICE models provide robust toxicity predictions and can generate protective toxicity estimates for assessing contaminant risk to listed species.
