Research Product

Ecological risks to aquatic organisms are typically assessed using toxicity data for relatively few species and with limited understanding of relative species sensitivity. We developed a comprehensive set of interspecies correlation estimation (ICE) models for aquatic organisms and evaluated three key sources of model uncertainty: taxonomic relatedness, chemical mode of action (MOA), and model parameters. Models are least squares regressions of acute toxicity of surrogate and predicted species. A total of 780 models were derived from EC/LC50 values for 77 species of aquatic organisms and over 550 chemicals. Cross-validation of models showed that the frequency of accurate model prediction was greatest for models between closely related surrogate and predicted taxa. Recursive partitioning provided user guidance for selection of robust models. Models built with a single MOA were more robust than models built using toxicity values with multiple MOAs, specifically for species pairs with large taxonomic distance (e.g., within phylum). These results indicate that between-species toxicity extrapolation can be improved using MOA-based models for taxa pairs of limited relatedness and for those MOAs specific mechanisms of action. Validated models are available in the U.S. EPA’s toxicity estimation tool, Web-ICE (http://www.epa.gov/ceampubl/fchain/webice/)