Updated Multiple Linear Regression Models for Predicting Chronic Aluminum Toxicity to Freshwater Aquatic Organisms and Developing Water Quality Guidelines

摘要

Multiple linear regression (MLR) models for predicting chronic aluminum toxicity to a cladoceran (Ceriodaphnia dubia) and a fish (Pimephales promelas) as a function of 3 toxicity-modifying factors (TMFs)-dissolved organic carbon (DOC), pH, and hardness-have been published previously. However, the range over which data for these TMFs were available was somewhat limited. To address this limitation, additional chronic toxicity tests with these species were subsequently conducted to expand the DOC range up to 12 mg/L, the pH range up to 8.7, and the hardness range up to 428 mg/L. The additional toxicity data were used to update the chronic MLR models. The adjustedR(2)for theC. dubia20% effect concentration (EC20) model increased from 0.71 to 0.92 with the additional toxicity data, and the predictedR(2)increased from 0.57 to 0.89. ForP. promelas, the adjustedR(2)increased from 0.87 to 0.92 and the predictedR(2)increased from 0.72 to 0.87. The high predictedR(2)relative to the adjustedR(2)indicates that the models for both species are not overly parameterized. When data forC. dubiaandP. promelaswere pooled, the adjustedR(2)values were comparable to the species-specific models (0.90 and 0.88 forC. dubiaandP. promelas, respectively). This indicates that chronic aluminum EC20s forC. dubiaandP. promelasrespond similarly to variation in DOC, pH, and hardness. Overall, the pooled model predicted EC20s that were within a factor of 2 of observed in 100% of theC. dubiatests and 94% of theP. promelastests.Environ Toxicol Chem2020;00:1-13. (c) 2020 SETAC