Development of Multiple Linear Regression Models for Predicting Chronic Iron Toxicity to Aquatic Organisms
We developed multiple linear regression (MLR) models for predicting iron (Fe) toxicity to aquatic organisms for use in deriving site‐specific water quality guidelines (WQGs). The effects of dissolved organic carbon (DOC), hardness, and pH on Fe toxicity to three representative taxa (Ceriodaphnia dub...
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description | We developed multiple linear regression (MLR) models for predicting iron (Fe) toxicity to aquatic organisms for use in deriving site‐specific water quality guidelines (WQGs). The effects of dissolved organic carbon (DOC), hardness, and pH on Fe toxicity to three representative taxa (Ceriodaphnia dubia, Pimephales promelas, and Raphidocelis subcapitata) were evaluated. Both DOC and pH were identified as toxicity‐modifying factors (TMFs) for P. promelas and R. subcapitata, whereas only DOC was a TMF for C. dubia. The MLR models based on effective concentration 10% and 20% values were developed and performed reasonably well, with adjusted R2 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 to be representative of invertebrates, fish, and algae and were 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 approach for deriving WQGs, application of MLR models to this SSD resulted in WQGs 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 WQGs (199–910 μg l−1) derived using the US Environmental Protection Agency (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 WQGs using both European Union and USEPA approaches across a range of TMF conditions is provided. Environ Toxicol Chem 2023;42:1386–1400. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. |
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The effects of dissolved organic carbon (DOC), hardness, and pH on Fe toxicity to three representative taxa (Ceriodaphnia dubia, Pimephales promelas, and Raphidocelis subcapitata) were evaluated. Both DOC and pH were identified as toxicity‐modifying factors (TMFs) for P. promelas and R. subcapitata, whereas only DOC was a TMF for C. dubia. The MLR models based on effective concentration 10% and 20% values were developed and performed reasonably well, with adjusted R2 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 to be representative of invertebrates, fish, and algae and were 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 approach for deriving WQGs, application of MLR models to this SSD resulted in WQGs 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 WQGs (199–910 μg l−1) derived using the US Environmental Protection Agency (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 WQGs using both European Union and USEPA approaches across a range of TMF conditions is provided. Environ Toxicol Chem 2023;42:1386–1400. © 2023 The Authors. 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The effects of dissolved organic carbon (DOC), hardness, and pH on Fe toxicity to three representative taxa (Ceriodaphnia dubia, Pimephales promelas, and Raphidocelis subcapitata) were evaluated. Both DOC and pH were identified as toxicity‐modifying factors (TMFs) for P. promelas and R. subcapitata, whereas only DOC was a TMF for C. dubia. The MLR models based on effective concentration 10% and 20% values were developed and performed reasonably well, with adjusted R2 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 to be representative of invertebrates, fish, and algae and were 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 approach for deriving WQGs, application of MLR models to this SSD resulted in WQGs 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 WQGs (199–910 μg l−1) derived using the US Environmental Protection Agency (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 WQGs using both European Union and USEPA approaches across a range of TMF conditions is provided. Environ Toxicol Chem 2023;42:1386–1400. © 2023 The Authors. 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The effects of dissolved organic carbon (DOC), hardness, and pH on Fe toxicity to three representative taxa (Ceriodaphnia dubia, Pimephales promelas, and Raphidocelis subcapitata) were evaluated. Both DOC and pH were identified as toxicity‐modifying factors (TMFs) for P. promelas and R. subcapitata, whereas only DOC was a TMF for C. dubia. The MLR models based on effective concentration 10% and 20% values were developed and performed reasonably well, with adjusted R2 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 to be representative of invertebrates, fish, and algae and were 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 approach for deriving WQGs, application of MLR models to this SSD resulted in WQGs 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 WQGs (199–910 μg l−1) derived using the US Environmental Protection Agency (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 WQGs using both European Union and USEPA approaches across a range of TMF conditions is provided. Environ Toxicol Chem 2023;42:1386–1400. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>36988398</pmid><doi>10.1002/etc.5623</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0003-3127-7435</orcidid><orcidid>https://orcid.org/0000-0001-7937-7852</orcidid><orcidid>https://orcid.org/0000-0002-2049-2087</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algae Animals Aquatic insects Aquatic Organisms Bioavailability Dissolved organic carbon Environmental protection Fresh Water - chemistry Geographical distribution Hydrogen-Ion Concentration Insects Iron Iron - toxicity Linear Models Multiple linear regression Parameter sensitivity pH effects Regression analysis Regression models Sensitivity Statistical analysis Taxa Toxicity Toxicology Water Pollutants, Chemical - chemistry Water quality Water quality guidelines |
title | Development of Multiple Linear Regression Models for Predicting Chronic Iron Toxicity to Aquatic Organisms |
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