Development of Multiple Linear Regression Models for Predicting Chronic Iron Toxicity to Aquatic Organisms.

In this study, we developed multiple linear regression (MLR) models for predicting Fe toxicity to aquatic organisms for use in deriving site-specific water quality guidelines (WQG). The effects of DOC, hardness, and pH on Fe toxicity to three representative taxa (Ceriodaphnia dubia, Pimephales promelas, and Raphidocelis subcapitata) were evaluated. DOC and pH were identified as toxicity modifying factors (TMFs) for P. promelas and R. subcapitata, while only DOC was a TMF for C. dubia. MLR models based on EC10s and EC20s were developed and perform reasonably well with adjusted R 2 of 0.68-0.89 across all species and statistical endpoints. Differences among species in the MLR models precluded development of a pooled model. Instead, the species-specific models were assumed representative of invertebrates, fish, and algae and applied accordingly to normalize toxicity data. The species sensitivity distribution (SSD) included standard laboratory toxicity data and effects data from mesocosm experiments on aquatic insects, with aquatic insects being the predominant taxa in the lowest quartile of the SSD. Using the European Union (EU) approach for deriving WQG, application of MLR models to this SSD results in WQG ranging from 114 to 765 μg l -1 Fe across the TMF conditions evaluated (DOC: 0.5-10 mg l -1 , pH: 6.0-8.4), with slightly higher WQG (199-910 μg l -1 ) derived using the USEPA methodology. An important uncertainty in these derivations is the applicability of the C. dubia MLR model (no pH parameter) to aquatic insects and understanding the pH sensitivity of aquatic insects to Fe toxicity is a research priority. An Excel-based tool for calculating Fe WQG using both EU and USEPA approaches across a range of TMF conditions is provided. This article is protected by copyright. All rights reserved. Environ Toxicol Chem 2023;00:0-0. © 2023 SETAC.