Comparison of Multiple Linear Regression and Biotic Ligand Models for Predicting Acute and Chronic Zinc Toxicity to Freshwater Organisms.

Multiple linear regression (MLR) models for predicting zinc (Zn) toxicity to freshwater organisms were developed based on three toxicity modifying factors (TMFs): dissolved organic carbon (DOC), hardness, and pH. Species-specific, stepwise MLR models were developed to predict acute Zn toxicity to four invertebrates and two fish, and chronic toxicity to three invertebrates, a fish, and a green alga. Stepwise regression analyses found that hardness had the most consistent influence on Zn toxicity among species, while DOC and pH had a variable influence. Pooled acute and chronic MLR models were also developed, and a k-fold cross-validation was used to evaluate the fit and predictive ability of the pooled MLR models. The pooled MLR models and an updated Zn biotic ligand model (BLM) performed similarly based on: (1) R 2 , (2) percentage of ECX predictions within a factor of 2.0 of observed ECX, and (3) residuals of observed/predicted ECX vs. observed ECX, DOC, hardness, and pH. While fit of the pooled models to species-specific toxicity data differed among species, species-specific differences were consistent between the BLM and MLR models. Consistency in performance of the two models across species indicates that additional terms, beyond DOC, hardness, and pH, included in the BLM do not help explain the differences among species. The pooled acute and chronic MLR models and BLM both performed better than the US Environmental Protection Agency's (USEPA's) existing hardness-based model. Therefore, we conclude that both MLR models and the BLM provide an improvement over the existing hardness-only models and that either could be used for deriving ambient water quality criteria. This article is protected by copyright. All rights reserved. Environ Toxicol Chem 2022;00:0-0. © 2022 SETAC.