Comparative Performance of Multiple Linear Regression and Biotic Ligand Models for Estimating the Bioavailability of Copper in Freshwater

Development and Validation of Multiple Linear Regression Models for Predicting Chronic Zinc Toxicity to Freshwater Microalgae

Multiple linear regression (MLR) models were developed for predicting chronic zinc toxicity to a freshwater microalga, Chlorella sp., using three toxicity-modifying factors (TMFs): pH, hardness, and dissolved organic carbon (DOC). The interactive effects between pH and hardness and between pH and DOC were also included. Models were developed at three different effect concentration (EC) levels: EC10, EC20, and EC50. Models were independently validated using six different zinc-spiked Australian natural waters with a range of water chemistries. Stepwise regression found hardness to be an influential TMF in model scenarios and was retained in all final models, while pH, DOC, and interactive terms had variable influence and were only retained in some models. Autovalidation and residual analysis of all models indicated that models generally predicted toxicity and that there was little bias based on individual TMFs. The MLR models, at all effect levels, performed poorly when predicting toxicity in the zinc-spiked natural waters during independent validation, with models consistently overpredicting toxicity. This overprediction may be from another unaccounted for TMF that may be present across all natural waters. Alternatively, this consistent overprediction questions the underlying assumption that models developed from synthetic laboratory test waters can be directly applied to natural water samples. Further research into the suitability of applying synthetic laboratory water-based models to a greater range of natural waters is needed. Environ Toxicol Chem 2023;42:2630-2641. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Bioavailability and Toxicity Models of Copper to Freshwater Life: The State of Regulatory Science

Efforts to incorporate bioavailability adjustments into regulatory water quality criteria in the United States have included four major procedures: hardness-based single-linear regression equations, water-effect ratios (WERs), biotic ligand models (BLMs), and multiple-linear regression models (MLRs) that use dissolved organic carbon, hardness, and pH. The performance of each with copper (Cu) is evaluated, emphasizing the relative performance of hardness-based versus MLR-based criteria equations. The WER approach was shown to be inherently highly biased. The hardness-based model is in widest use, and the MLR approach is the US Environmental Protection Agency's (USEPA's) present recommended approach for developing aquatic life criteria for metals. The performance of criteria versions was evaluated with numerous toxicity datasets that were independent of those used to develop the MLR models, including olfactory and behavioral toxicity, and field and ecosystem studies. Within the range of water conditions used to develop the Cu MLR criteria equations, the MLR performed well in terms of predicting toxicity and protecting sensitive species and ecosystems. In soft waters, the MLR outperformed both the BLM and hardness models. In atypical waters with pH <5.5 or >9, neither the MLR nor BLM predictions were reliable, suggesting that site-specific testing would be needed to determine reliable Cu criteria for such settings. The hardness-based criteria performed poorly with all toxicity datasets, showing no or weak ability to predict observed toxicity. In natural waters, MLR and BLM criteria versions were strongly correlated. In contrast, the hardness-criteria version was often out of phase with the MLR and, depending on waterbody and season, could be either strongly overprotective or underprotective. The MLR-based USEPA-style chronic criterion appears to be more generally protective of ecosystems than other models. Environ Toxicol Chem 2023;42:2529-2563. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Acute Toxicity of Copper to Three Species of Pacific Salmon Fry in Water with Low Hardness and Low Dissolved Organic Carbon

Proposed development of a mine within Alaska's Bristol Bay watershed (USA) has raised concerns about the potential impact of copper (Cu) on Pacific salmon (Oncorhynchus spp.). We conducted 96-h flow-through bioassays using low-hardness and low dissolved organic carbon water to determine the acute lethal toxicity of Cu to sockeye (Oncorhynchus nerka), Chinook (Oncorhynchus tshawytscha), and coho salmon (Oncorhynchus kisutch) fry. We aimed to determine Cu toxicity under field-relevant water quality conditions and to assess three methods of calculating ambient Cu criteria: the biotic ligand model (BLM), a multiple linear regression model endorsed by the US Environmental Protection Agency, and the hardness-based model currently used by the State of Alaska. The criteria generated by all models were below 20% lethal Cu concentrations by factors ranging from 2.2 to 54.3, indicating that all criteria would be protective against mortality. The multiple linear regression-based criteria were the most conservative and were comparable to BLM-based criteria. The median lethal concentrations (LC50s) for sockeye, Chinook, and coho were 35.2, 23.9, and 6.3 µg Cu/L, respectively. We also used the BLM to predict LC50s for each species. Model predictions differed from empirical LC50s by factors of 0.7 for sockeye and Chinook salmon, and 1.1 for coho salmon. These differences fell within the acceptable range of ±2, indicating the model's accuracy. We calculated critical lethal Cu accumulation values for each species to account for differing water chemistry in each bioassay; the present study revealed that coho salmon were most sensitive to Cu, followed by sockeye and Chinook salmon. Our findings underscore the importance of considering site- and species-specific factors when modeling Cu toxicity. The empirical data we present may enhance Cu risk assessments for Pacific salmon. Environ Toxicol Chem 2023;42:2440-2452. © 2023 SETAC.

A modelling framework to assess multiple metals impacts on marine food webs: Relevance for assessing the ecological implications of deep-sea mining based on a systematic review

Industrial deep-sea mining will release plumes containing metals that may disperse over long distances; however, there is no general understanding of metal effects on marine ecosystems. Thus, we conducted a systematic review in search of models of metal effects on aquatic biota with the future perspective to support Environmental Risk Assessment (ERA) of deep-sea mining. According to results, the use of models to study metal effects is strongly biased towards freshwater species (83% freshwater versus 14% marine); Cu, Hg, Al, Ni, Pb, Cd and Zn are the best-studied metals, and most studies target few species rather than entire food webs. We argue that these limitations restrain ERA on marine ecosystems. To overcome this gap of knowledge, we suggest future research directions and propose a modelling framework to predict the effects of metals on marine food webs, which in our view is relevant for ERA of deep-sea mining.

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 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;00:1-15. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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: 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, whereas 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) R² , (2) the percentage of effect concentration (ECx) predictions within a factor of 2.0 of observed ECx, and (3) residuals of observed/predicted ECx versus observed ECx, DOC, hardness, and pH. Although 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 the 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 existing hardness-based model. We therefore 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. Environ Toxicol Chem 2023;42:393-413. © 2022 SETAC.

The influence of hardness at varying pH on zinc toxicity and lability to a freshwater microalga, Chlorella sp

Zinc is an essential element for aquatic organisms, however, activities such as mining and refining, as well as zinc's ubiquitous role in modern society can contribute to elevated environmental concentrations of zinc. Water hardness is widely accepted as an important toxicity modifying factor for metals in aquatic systems, though other factors such as pH are also important. This study investigated the influence of increasing water hardness, at three different pH values (6.7, 7.6 and 8.3), on the chronic toxicity of zinc to the growth rate of a microalgae, Chlorella sp. Zinc toxicity decreased with increasing hardness from 5 to 93 mg CaCO₃ L^-1 at all three pH values tested. The 72 h growth rate inhibition EC50 values ranged from 6.2 μg Zn L^-1 (at 5 mg CaCO₃ L^-1, pH 8.3) to 184 μg Zn L^-1 (at 92 mg CaCO₃ L^-1, pH 6.7). Increases in hardness from 93 to 402 mg CaCO₃ L^-1 generally resulted in no significant (p > 0.05) reduction in zinc toxicity. DGT-labile zinc measurements did not correspond with the observed changes in zinc toxicity as hardness was varied within a pH treatment. This suggests that cationic competition from increased hardness is decreasing zinc toxicity, rather than changes in metal lability. This study highlighted that current hardness algorithms used in water quality guidelines may not be sufficiently protective of sensitive species, such as Chlorella sp., in high hardness waters.

Stream Mesocosm Experiments Show no Protective Effects of Calcium on Copper Toxicity to Macroinvertebrates

Although the concept and modeling of metal bioavailability and toxicity have been well developed based largely on laboratory experiments with standard test species, additional evidence is required to demonstrate their applicability for macroinvertebrates typically found in natural lotic ecosystems. We conducted 10-day stream mesocosm experiments to test the hypothesis that increased water hardness (in the present study, the calcium [Ca] concentration was increased by adding CaCl₂ ) would mitigate the effects of copper (Cu) on natural benthic macroinvertebrate communities. Exposure of macroinvertebrate communities to 25 μg/L Cu for 10 days in stream mesocosm experiments resulted in significant decreases in total abundance, in number of taxa, and in abundance of many macroinvertebrate taxa. However, the addition of Ca to stream mesocosms and the associated increase in water hardness up to 250 mg/L CaCO₃ did not mitigate these effects of Cu on macroinvertebrate communities. The results showed that the hardness-based water quality criteria for Cu of the US Environmental Protection Agency were not protective under the conditions of relatively high hardness, low alkalinity, and circumneutral pH. In contrast, the water quality criteria based on the biotic ligand model predicted little protective effects of Ca on Cu toxicity, which is consistent with our results. Additional experiments are required to understand the influence of modifying factors on the toxicity of metals to macroinvertebrate communities. Environ Toxicol Chem 2022;41:1304-1310. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Development of Fluoride Protective Values for Aquatic Life Using Empirical Bioavailability Models

The derivation of protective values for aquatic life can be enhanced by the development and use of bioavailability models. Recent advances to metals bioavailability modeling are applicable to other analyte groups and should be widely considered. We conducted a meta-analysis of the available aquatic toxicity literature for fluoride to evaluate the utility of hardness, alkalinity, and chloride as toxicity-modifying factors (TMFs) in empirical bioavailability models of freshwater taxa. The resulting optimal multiple linear regression model predicting acute fluoride toxicity to the invertebrate Hyalella azteca included all three TMFs (observed vs. predicted 50% lethal concentrations, R²  = 0.88) and the optimal model predicting toxicity to the fish Oncorhynchus mykiss included alkalinity and hardness (R²  = 0.37). At >20 mg/L chloride, the preliminary final acute values for fluoride were within 1 order of magnitude and ranged from approximately 18.1 to 56.3 mg/L, depending on water chemistry. Sensitivity of H. azteca to low-chloride conditions increased model uncertainty when chloride was <20 mg/L. Because of limited toxicity data, chronic bioavailability models were not developed, and final chronic values were derived using an acute-to-chronic ratio (ACR) approach. Accounting for TMFs, the geometric mean ACR was 5.4 for fish and invertebrate taxa (n = 6). The present assessment highlights the need to expand bioavailability modeling to include inorganic anions, particularly fluoride, and demonstrates that existing promulgated protective values for fluoride are likely overly conservative. More toxicological studies are recommended to further refine multivariate empirical bioavailability models for inorganic anions. Environ Toxicol Chem 2022;41:396-409. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.