Validation of Bioavailability-Based Toxicity Models for Metals

Recommended updates to the USEPA Framework for Metals Risk Assessment: Aquatic ecosystems

In 2007, the USEPA issued its "Framework for Metals Risk Assessment." The framework provides technical guidance to risk assessors and regulators when performing human health and environmental risk assessments of metals. This article focuses on advances in the science including assessing bioavailability in aquatic ecosystems, short- and long-term fate of metals in aquatic ecosystems, and advances in risk assessment of metals in sediments. Notable advances have occurred in the development of bioavailability models for assessing toxicity as a function of water chemistry in freshwater ecosystems. The biotic ligand model (BLM), the multiple linear regression model, and multimetal BLM now exist for most of the common mono- and divalent metals. Species sensitivity distributions for many metals exist, making it possible for many jurisdictions to develop or update their water quality criteria or guidelines. The understanding of the fate of metals in the environment has undergone significant scrutiny over the past 20 years. Transport and toxicity models have evolved including the Unit World Model allowing for estimation of concentrations of metals in various compartments as a function of loading and time. There has been significant focus on the transformation of metals in sediments into forms that are less bioavailable and on understanding conditions that result in resolubilization or redistribution of metals in and from sediments. Methods for spiking sediments have advanced such that the resulting chemistry in the laboratory mimics that in natural systems. Sediment bioavailability models are emerging including models that allow for prediction of toxicity in sediments for copper and nickel. Biodynamic models have been developed for several organisms and many metals. The models allow for estimates of transport of metals from sediments to organisms via their diet as well as their water exposure. All these advances expand the tool set available to risk assessors. Integr Environ Assess Manag 2024;20:924-951. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Updated Chronic Copper Bioavailability Models for Invertebrates and Algae

Chronic copper (Cu) bioavailability models have been successfully implemented in European risk assessment frameworks and compliance evaluations. However, they were developed almost two decades ago, which calls for an update. In the study, we present updated chronic Cu bioavailability models for invertebrates and algae. They consider recent ecotoxicity data sets and use the more recent speciation model Windermere Humic Aqueous Model (WHAM) VII and an optimized model structure (i.e., a generalized bioavailability model [gBAM]). Contrary to the classic biotic ligand model, a gBAM models the effect of pH on Cu2+ toxicity via a log-linear relationship parametrized through the pH slope SpH . The recalibrated SpH parameters are -0.208 for invertebrates (Daphnia magna, two clones) and -0.975 for algae (Raphidocelis subcapitata and Chlorella vulgaris). The updated models predict 80% to 100% of the observed effect levels for eight different species within a factor of 2. The only exception was one of the two data sets considering subchronic 7-day mortality to Hyalella azteca: the prediction performance of the updated invertebrate model at pH ≥ 8.3 was poor because the effect of pH on Cu2+ toxicity appeared to be dependent on the pH itself (with a steeper pH slope compared with the updated invertebrate model at pH ≥ 8.1). The prediction performance of the updated Cu bioavailability models was similar to or better than that of the models used for regulatory application in Europe until now, with one exception (i.e., H. azteca). Together with the recently published fish bioavailability model, the models developed in the present study constitute a complete, updated, and consistent bioavailability model set. Overall, the updated chronic Cu bioavailability model set is robust and can be used in regulatory applications. The updated bioavailability model set is currently used under the European Union Registration, Evaluation, Authorisation, and Restriction of Chemicals framework regulation to guide the safe use of Cu. Environ Toxicol Chem 2024;43:450-467. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The biotic ligand model as a promising tool to predict Cu toxicity in amazon blackwaters

The Rio Negro basin of Amazonia (Brazil) is a hotspot of fish biodiversity that is under threat from copper (Cu) pollution. The very ion-poor blackwaters have a high dissolved organic carbon (DOC) concentration. We investigated the Cu sensitivity of nine Amazonian fish species in their natural blackwaters (Rio Negro). The acute lethal concentration of Cu (96 h LC50) was determined at different dilutions of Rio Negro water (RNW) in ion-poor well water (IPW), ranging from 0 to 100%. The IPW was similar to RNW in pH and ionic composition but deficient in DOC, allowing this parameter to vary 20-fold from 0.4 to 8.3 mg/L in tests. The Biotic Ligand Model (BLM; Windward version 3.41.2.45) was used to model Cu speciation and toxicity over the range of tested water compositions, and to estimate lethal Cu accumulations on the gills (LA50). The modeling predicted a high relative abundance of Cu complexes with DOC in test waters. As these complexes became more abundant with increasing RNW content, a concomitant decrease in free Cu2+ was observed. In agreement with this modeling, acute Cu toxicity decreased (i.e. 96 h LC50 values increase) with increasing RNW content. The three most sensitive species (Hemigrammus rhodostomus, Carnegiella strigatta and Hyphessobrycon socolofi) were Characiformes, whereas Corydoras schwartzi (Siluriformes) and Apistogramma agassizii (Cichliformes) were the most tolerant. These sensitivity differences were reflected in the BLM-predicted lethal gill copper accumulation (LA50), which were generally lower in Characiformes than in Cichliformes. Using these newly estimated LA50 values in the BLM allowed for accurate prediction of acute Cu toxicity in the nine Amazonian fish. Our data emphasize that the BLM approach is a promising tool for assessing Cu risk to Amazonian fish species in blackwater conditions characterized by very low concentrations of major ions but high concentrations of DOC.

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.

Validation of Nickel Bioavailability Models for Algae, Invertebrates, and Fish in Chinese Surface Waters

Nickel (Ni) is used primarily in the production of alloys like stainless steel and is increasingly being used in the production of batteries for the electric vehicle market. Exposure of Ni to ecosystems is of concern because Ni can be toxic to aquatic organisms. The influence of water chemistry constituents (e.g., hardness, pH, dissolved organic carbon) on the toxicity of Ni has prompted the development and use of bioavailability models, such as biotic ligand models (BLMs), which have been demonstrated to accurately predict Ni toxicity in broadly different ecosystems, including Europe, North America, and Australia. China, a leading producer of Ni, is considering bioavailability-based approaches for regulating Ni emissions. Adoption of bioavailability-based approaches in China requires information to demonstrate the validity of bioavailability models for the local water chemistry conditions. The present study investigates the toxicity of Ni to three standard test species (Daphnia magna, Pseudokirchneriella subcapitata, and Danio rerio) in field-collected natural waters that are broadly representative of the range of water chemistries and bioavailabilities encountered in Chinese lakes and rivers. All experimental data are within a factor of 3 of the BLM predicted values for all tests with all species. For D. magna, six of seven waters were predicted within a factor of 2 of the experimental result. Comparison of experimental data against BLM predictions shows that the existing Ni bioavailability models are able to explain the differences in toxicity that result from water chemistry conditions in China. Validation of bioavailability models to water chemistries and bioavailability ranges within China provides technical support for the derivation of site-specific Ni water quality criteria in China. Environ Toxicol Chem 2023;42:1257-1265. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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.

Influence of Geochemical Fractionation of Fulvic Acid on its Spectral Characteristics and its Protection Against Copper Toxicity to Daphnia magna

Dissolved copper (Cu) can contribute to toxicity in aquatic systems impacted by acid mine drainage (AMD), and its bioavailability is influenced by aqueous complexation with organic ligands that predominantly include fulvic acids (FAs). Because the geochemical fractionation of FAs that accompanies sorption to hydrous aluminum oxides (HAOs) and hydrous iron oxides (HFOs) can alter Cu complexation with FA, we investigated FAs isolated from three categories of water (pristine, AMD, and in situ-fractionated mixtures of pristine and AMD collected at stream confluences) in three mining-impacted alpine watersheds in central Colorado, USA. We also conducted geochemical fractionation of field-collected FAs and Suwannee River FAs by precipitating HAOs and HFOs in the laboratory. Spectral properties of the FAs (e.g., UV-VIS absorbance) were altered by geochemical fractionation, and in acute toxicity tests with an aquatic invertebrate (Daphnia magna) Cu was more toxic in the presence of in situ- and laboratory-fractionated FAs (median effect concentration [EC50] 19-50 µg Cu L^-1 ) than in the presence of nonfractionated FAs (EC50 48-146 µg Cu L^-1 ). After adjusting for the strain-specific sensitivity of our D. magna, we improved the accuracy of Biotic Ligand Model predictions of Cu EC50 values for AMD-related FAs by using an "effective dissolved organic carbon" based on spectral properties that account for among-FA differences in protectiveness against Cu toxicity. However, some differences remained between predicted and measured EC50 values, especially for FAs from AMD-related waters that might contain important metal-binding moieties not accounted for by our measured spectral indices. Environ Toxicol Chem 2023;42:449-462. © 2022 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.

Variation in chronic nickel toxicity to Daphnia magna among Japanese river waters and performance evaluation of bioavailability models in predicting the toxicity

Nickel (Ni) ecotoxicity is dictated by water chemistry characteristics such as pH, water hardness, and amount of dissolved organic carbon. Bioavailability models have been developed to predict Ni toxicity and validated for European, Australian, and US natural waters. In this study, chronic toxicity tests in Ni-spiked Japanese river waters were conducted on a strain of Daphnia magna to test whether the chronic toxicity differs among Japanese natural waters with different water chemistries. Based on the results of chronic Ni toxicity tests, we assessed the performance of existing D. magna bioavailability models, which were developed in artificial waters (Model 1) and calibrated in European natural waters (Model 2), in terms of the accuracy and the bias of model predictions. Furthermore, we also calibrated the two models by using toxicity test results to develop a bioavailability model for Ni chronic toxicity to the strain of D. magna in Japanese river waters. The 10%, 20%, and 50% effect concentrations (EC₁₀, EC₂₀, and EC₅₀) of dissolved Ni on reproduction of the D. magna strain were within ranges from 8.1 to 44.9 μg/L, 9.0 to 57.1 μg/L, and 10.9 to 86.1 μg/L, respectively. Results indicate that differences in water chemistry among Japanese river waters influenced chronic Ni toxicity to the model organism. Model 1predicted 43% of the observed EC₁₀, EC₂₀, and EC₅₀ values within a factor of 2 and 100%, 100%, and 43% within a factor of 3, respectively. Model 2 predicted 14%, 14%, and 29% of the observed EC₁₀, EC₂₀, and EC₅₀ values within a factor of 2 and 43% within a factor of 3. The values of model bias based on the geometric mean of ratios of EC₁₀, EC₂₀ and EC₅₀ values predicted by each of the two models and observed EC₁₀, EC₂₀, and EC₅₀ values were 0.71, 0.65, and 0.62 for Model 1 and 0.27, 0.26, and 0.29 for Model 2, respectively. After calibrating two models using the results of toxicity tests, refined Model 1 predicted 71%, 57%, and 57% of observed EC₁₀, EC₂₀, and EC₅₀ values within a factor of 2 and 100%, 86%, and 100% within a factor of 3; refined Model 2 predicted 71% of observed EC₁₀, EC₂₀, and EC₅₀ values within a factor 2 and 100%, 86%, and 86% within a factor of 3, respectively. Our results indicate that calibrating the Ni bioavailability models in Japanese natural waters increased their predictive capacity by a factor of up to approximately five.

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.

Modeling the Bioavailability of Nickel and Zinc to Ceriodaphnia dubia and Neocloeon triangulifer in Toxicity Tests with Natural Waters

We studied biotic ligand model (BLM) predictions of the toxicity of nickel (Ni) and zinc (Zn) in natural waters from Illinois and Minnesota, USA, which had combinations of pH, hardness, and dissolved organic carbon (DOC) more extreme than 99.7% of waters in a nationwide database. We conducted 7-day chronic tests with Ceriodaphnia dubia and 96-hour acute and 14-day chronic tests with Neocloeon triangulifer and estimated median lethal concentrations and 20% effect concentrations for both species. Toxicity of Ni and Zn to both species differed among test waters by factors from 8 (Zn tests with C. dubia) to 35 (Zn tests with N. triangulifer). For both species and metals, tests with Minnesota waters (low pH and hardness, high DOC) showed lower toxicity than Illinois waters (high pH and high hardness, low DOC). Recalibration of the Ni BLM to be more responsive to pH-related changes improved predictions of Ni toxicity, especially for C. dubia. For the Zn BLM, we compared several input data scenarios, which generally had minor effects on model performance scores (MPS). A scenario that included inputs of modeled dissolved inorganic carbon and measured Al and Fe(III) produced the highest MPS values for tests with both C. dubia and N. triangulifer. Overall, the BLM framework successfully modeled variation in toxicity for both Zn and Ni across wide ranges of water chemistry in tests with both standard and novel test organisms. Environ Toxicol Chem 2021;40:3049-3062. © 2021 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Comparison of Multiple Linear Regression and Biotic Ligand Models to Predict the Toxicity of Nickel to Aquatic Freshwater Organisms

Toxicity-modifying factors can be modeled either empirically with linear regression models or mechanistically, such as with the biotic ligand model (BLM). The primary factors affecting the toxicity of nickel to aquatic organisms are hardness, dissolved organic carbon (DOC), and pH. Interactions between these terms were also considered. The present study develops multiple linear regressions (MLRs) with stepwise regression for 5 organisms in acute exposures, 4 organisms in chronic exposures, and pooled models for acute, chronic, and all data and compares the performance of the Pooled All MLR model to the performance of the BLM. Independent validation data were used for evaluating model performance, which for pooled models included data for organisms and endpoints not present in the calibration data set. Hardness and DOC were most often selected as the explanatory variables in the MLR models. An attempt was also made at evaluating the uncertainty of the predictions for each model; predictions that showed the most error tended to show the highest levels of uncertainty as well. The performances of the 2 models were largely equal, with differences becoming more apparent when looking at the performance within subsets of the data. Environ Toxicol Chem 2021;40:2189-2205. © 2021 SETAC.

Development of a bioavailability-based risk assessment framework for nickel in Southeast Asia and Melanesia

Nickel laterite ore deposits are becoming increasingly important sources of Ni for the global marketplace and are found mainly in tropical and subtropical regions, including Indonesia, the Philippines, Papua New Guinea, Cuba, and New Caledonia. There are few legislatively derived standards or guidelines for the protection of aquatic life for Ni in many of these tropical regions, and bioavailability-based environmental risk assessment (ERA) approaches for metals have mainly been developed and tested in temperate regions, such as the United States and Europe. This paper reports on a multi-institutional, 5-y testing program to evaluate Ni exposure, effects, and risk characterization in the Southeast Asia and Melanesia (SEAM) region, which includes New Caledonia, Papua New Guinea, the Philippines, and Indonesia. Further, we have developed an approach to determine if the individual components of classical ERA, including effects assessments, exposure assessments, and risk characterization methodologies (which include bioavailability normalization), are applicable in this region. A main conclusion of this research program is that although ecosystems and exposures may be different in tropical systems, ERA paradigms are constant. A large chronic ecotoxicity data set for Ni is now available for tropical species, and the data developed suggest that tropical ecosystems are not uniquely sensitive to Ni exposure; hence, scientific support exists for combining tropical and temperate data sets to develop tropical environmental quality standards (EQSs). The generic tropical database and tropical exposure scenarios generated can be used as a starting point to examine the unique biotic and abiotic characteristics of specific tropical ecosystems in the SEAM region. Integr Environ Assess Manag 2021;17:802-813. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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

An increasing number of metal bioavailability models are available for use in setting regulations and conducting risk assessments in aquatic systems. Selection of the most appropriate model is dependent on the user's needs but will always benefit from an objective, comparative assessment of the performance of available models. In 2017, an expert workshop developed procedures for assessing metal bioavailability models. The present study applies these procedures to evaluate the performance of biotic ligand models (BLMs) and multiple linear regression (MLR) models for copper. We find that the procedures recommended by the expert workshop generally provide a robust series of metrics for evaluating model performance. However, we recommend some modifications to the analysis of model residuals because the current method is insensitive to relatively large differences in residual patterns when comparing models. We also provide clarification on details of the evaluation procedure which, if not applied correctly, could mischaracterize model performance. We found that acute Cu MLR and BLM performances are quite comparable, though there are differences in performance on a species-specific basis and in the resulting water quality criteria as a function of water chemistry. In contrast, the chronic Cu MLR performed distinctly better than the BLM. Observed differences in performance are due to the smaller effects of hardness and pH on chronic Cu toxicity compared to acute Cu toxicity. These differences are captured in the chronic MLR model but not the chronic BLM, which only adjusts for differences in organism sensitivity. In general, we continue to recommend concurrent development of both modeling approaches because they provide useful comparative insights into the strengths, limitations, and predictive capabilities of each model. Environ Toxicol Chem 2021;40:1649-1661. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Application of Bioavailability Models to Derive Chronic Guideline Values for Nickel in Freshwaters of Australia and New Zealand

There has been an increased emphasis on incorporating bioavailability-based approaches into freshwater guideline value derivations for metals in the Australian and New Zealand water quality guidelines. Four bioavailability models were compared: the existing European biotic ligand model (European Union BLM) and a softwater BLM, together with 2 newly developed multiple linear regressions (MLRs)-a trophic level-specific MLR and a pooled MLR. Each of the 4 models was used to normalize a nickel ecotoxicity dataset (combined tropical and temperate data) to an index condition of pH 7.5, 6 mg Ca/L, 4 mg Mg/L, (i.e., approximately 30 mg CaCO₃ /L hardness), and 0.5 mg DOC/L. The trophic level-specific MLR outperformed the other 3 models, with 79% of the predicted 10% effect concentration (EC10) values within a factor of 2 of the observed EC10 values. All 4 models gave similar normalized species sensitivity distributions and similar estimates of protective concentrations (PCs). Based on the index condition water chemistry proposed as the basis of the national guideline value, a protective concentration for 95% of species (PC95) of 3 µg Ni/L was derived. This guideline value can be adjusted up and down to account for site-specific water chemistries. Predictions of PC95 values for 20 different typical water chemistries for Australia and New Zealand varied by >40-fold, which confirmed that correction for nickel bioavailability is critical for the derivation of site-specific guideline values. Environ Toxicol Chem 2021;40:100-112. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Empirical Bioavailability Corrections for Nickel in Freshwaters for Australia and New Zealand Water Quality Guideline Development

Bioavailability-based approaches have been developed for the regulation of metals in freshwaters in several countries. Empirical multiple linear regression (MLR) models have been developed for nickel that can be applied to aquatic organisms. The MLR models have been compared against the use of previously developed biotic ligand models (BLMs) for the normalization of an ecotoxicity dataset compiled for the derivation of a water quality guideline value that could be applied in Australia and New Zealand. The MLR models were developed from data for a number of specific species and were validated independently to confirm their reliability. An MLR modeling approach using different models for algae, plants, invertebrates, and vertebrates performed better than either a pooled MLR model for all taxa or the BLMs, in terms of its ability to correctly predict the results of the tests in the ecotoxicity database based on their water chemistry and a fitted species-specific sensitivity parameter. The present study demonstrates that MLR approaches can be developed and validated to predict chronic nickel toxicity to freshwater ecosystems from existing datasets. The MLR approaches provide a viable alternative to the use of BLMs for taking account of nickel bioavailability in freshwaters for regulatory purposes. Environ Toxicol Chem 2021;40:113-126. © 2020 SETAC.

Demonstrating the Reliability of bio-met for Determining Compliance with Environmental Quality Standards for Metals in Europe

The importance of considering the bioavailability of metals in understanding and assessing their toxicity in freshwaters has been recognized for many years. Currently, biotic ligand models (BLMs) are being applied for the derivation and implementation of environmental quality standards (EQS) for metals under the Water Framework Directive in Europe. bio-met is a simplified tool that was developed for implementing bioavailability-based EQS for metals in European freshwaters. We demonstrate the reliability of the relationship between the full BLM predictions and the thresholds (hazardous concentration affecting 5% of species [HC5] values) predicted by bio-met in 3 stages, for the metals copper, nickel, and zinc. First, ecotoxicity data for specific species from laboratory tests in natural waters are compared with predictions by the individual species BLMs included in the full BLMs. Second, the site-specific HC5 values predicted by bio-met for the natural waters used for ecotoxicity testing are compared with those provided by the full BLMs. The reliability of both relationships is demonstrated for all 3 metals, with more than 80% of individual species BLM predictions being within a factor of 3 of the experimental results, and 99% of bio-met local HC5 predictions being within a factor of 2 of the full BLM result. Third, using a larger set of European natural waters in addition demonstrates the reliability of bio-met over a broad range of water chemistry conditions. bio-met is therefore an appropriate tool for performing compliance assessments against EQS values in Europe, due to the demonstrated consistency with the toxicity test data. Environ Toxicol Chem 2020;39:2361-2377. © 2020 SETAC.

A Generalized Bioavailability Model (gBAM) for Predicting Chronic Copper Toxicity to Freshwater Fish

The generalized bioavailability model (gBAM) has been proposed as an alternative to the biotic ligand model (BLM) for modeling bioavailability and chronic toxicity of copper (Cu). The gBAM combines a log-linear effect of pH on free Cu²⁺ ion toxicity with BLM-type parameters for describing the protective effects of major cations (calcium [Ca]²⁺ , magnesium [Mg]²⁺ , and sodium [Na]⁺ ). In the present study, a Windermere Humic Aqueous Model (WHAM) VII-based gBAM for fish was parametrized based on an existing chronic (30-d) dataset of juvenile rainbow trout (Oncorhynchus mykiss). The model, with defined parameters (pH slope parameter [S_pH ] = 0.4449 and biotic ligand competition constants [log K_CaBL  = 4.0, log K_MgBL  = 3.4, and log K_NaBL  = 3.0]), was shown to accurately predict the effects of pH, dissolved organic carbon, Ca, and Mg on chronic Cu toxicity to juvenile rainbow trout at the effect levels relevant for environmental risk assessment (i.e., median prediction error of 1.3-fold for 10 and 20% lethal concentrations). The gBAM predicted the effect of pH more accurately than a previously published Cu BLM for juvenile rainbow trout, especially at pH > 8. We also evaluated the cross-species and cross-life stage applicability of the newly developed juvenile rainbow trout gBAM using existing chronic Cu toxicity data with early life stages of fathead minnow (Pimephales promelas) and rainbow trout. We did this because using a single bioavailability model for all fish species and life stages is practical from a regulatory point of view. Although the early life stage datasets exhibit considerable uncertainties, 91% of the considered toxicity values at the effect levels most relevant in European environmental regulations (10% effect on survival or growth) were predicted within a 2-fold error. Overall, the chronic Cu gBAM we developed is a valuable alternative for the existing chronic Cu BLM for rainbow trout and performs sufficiently well to be used in risk assessment according to currently accepted standards of bioavailability model performance (from the current European regulatory point of view). However, our analysis also suggests that bioavailability relations differ between different fish life stages and between endpoints (e.g., mortality vs growth), which is currently not accounted for in environmental risk assessments. Environ Toxicol Chem 2020;39:2424-2436. © 2020 SETAC.

Mean Species Abundance as a Measure of Ecotoxicological Risk

Chemical pollution of surface waters is considered an important driver for recent declines in biodiversity. Species sensitivity distributions (SSDs) are commonly used to evaluate the ecological risks of chemical exposure, accounting for variation in interspecies sensitivity. However, SSDs do not reflect the effects of chemical exposure on species abundance, considered an important endpoint in biological conservation. Although complex population modeling approaches lack practical applicability when it comes to the routine practice of lower tier chemical risk assessment, in the present study we show how information from widely available laboratory toxicity tests can be used to derive the change in mean species abundance (MSA) as a function of chemical exposure. These exposure-response MSA relationships combine insights into intraspecies exposure-response relationships and population growth theory. We showcase the practical applicability of our method for cadmium, copper, and zinc, and include a quantification of the associated statistical uncertainty. For all 3 metals, we found that concentrations hazardous for 5% of the species (HC₅ s) based on MSA relationships are systematically higher than SSD-based HC₅ values. Our proposed framework can be useful to derive abundance-based ecological protective criteria for chemical exposure, and creates the opportunity to assess abundance impacts of chemical exposure in the context of various other anthropogenic stressors. Environ Toxicol Chem 2020;39:2304-2313. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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

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 adjusted R² for the C. dubia 20% effect concentration (EC20) model increased from 0.71 to 0.92 with the additional toxicity data, and the predicted R² increased from 0.57 to 0.89. For P. promelas, the adjusted R² increased from 0.87 to 0.92 and the predicted R² increased from 0.72 to 0.87. The high predicted R² relative to the adjusted R² indicates that the models for both species are not overly parameterized. When data for C. dubia and P. promelas were pooled, the adjusted R² values were comparable to the species-specific models (0.90 and 0.88 for C. dubia and P. promelas, respectively). This indicates that chronic aluminum EC20s for C. dubia and P. promelas respond 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 the C. dubia tests and 94% of the P. promelas tests. Environ Toxicol Chem 2020;39:1724-1736. © 2020 SETAC.

Multiple Linear Regression Modeling Predicts the Effects of Surface Water Chemistry on Acute Vanadium Toxicity to Model Freshwater Organisms

Multiple linear regression (MLR) modeling has been successfully used to predict how water chemistry variables influence the toxicity of cationic metals to aquatic organisms, but no MLR model exists for vanadium (V). Recent research has indicated that an increase in pH (from 6 to 9), or high concentrations of sodium (473 mg Na⁺ /L), increase V toxicity to Daphnia pulex. In contrast, increases in alkalinity (>100 mg as CaCO₃ ) and sulfate (>100 mg SO₄^2- /L) reduce V toxicity. How these variables influence V toxicity to Oncorhynchus mykiss (rainbow trout) was still unknown. Our results show that increasing pH from 6.2 to 8.9 tended to decrease the 96-h median lethal concentration (LC50) for V toxicity to O. mykiss by 9.6 mg V/L. An alkalinity increase from 71 to 330 mg/L as CaCO₃ tended to increase the 96-h LC50 by 3.3 mg V/L, whereas when SO₄^2- rose from 150 to 250 mg/L, the LC50 significantly increased by 0.3 mg V/L followed by a significant decrease of 1 mg V/L when SO₄^2- was >250 mg/L. Sodium (between 100 and 336 mg/L) showed no effect on V toxicity to O. mykiss. The toxicity patterns for O. mykiss were similar to those observed for D. pulex, except for that of SO₄^2- , potentially indicating different mechanisms of V uptake or regulation in the 2 species. The LC50s and associated water chemistry were combined to develop an MLR model for O. mykiss and D. pulex. Alkalinity and pH modified V toxicity to both species, whereas SO₄^2- influenced V toxicity to D. pulex. Overall, MLR models should be considered for creating new local benchmarks or water quality guidelines for V. Environ Toxicol Chem 2020;39:1737-1745. © 2020 SETAC.

Bioavailability Assessment of Metals in Freshwater Environments: A Historical Review

Many metals (aluminum, cadmium, cobalt, copper, nickel, lead, zinc) are widely studied environmental contaminants because of their ubiquity, potential toxicity to aquatic life, and tendency for toxicity to vary widely as a function of water chemistry. The interactions between metal and water chemistry influence metal "bioavailability," an index of the rate and extent to which the metal reaches the site of toxic action. The implications of metal bioavailability for ecological risk assessment are large, with as much as a 100-fold variability across a range of water chemistries in surface waters. Beginning as early as the 1930s, considerable research effort was expended toward documenting and understanding metal bioavailability as a function of total and dissolved metal, water hardness, natural organic matter, pH, and other water characteristics. The understanding of these factors and improvements in both analytical and computational chemistry led to the development of modeling approaches intended to describe and predict the relationship between water chemistry and metal toxicity, including the free ion activity model, the gill surface interaction model, the biotic ligand model, and additional derivatives and regression models that arose from similar knowledge. The arc of these scientific advances can also be traced through the evolution of the US Environmental Protection Agency's ambient water quality criteria over the last 50 yr, from guidance in the "Green Book" (1968) to metal-specific criteria produced in the last decade. Through time, water quality criteria in many jurisdictions have incorporated increasingly sophisticated means of addressing metal bioavailability. The present review discusses the history of scientific understanding of metal bioavailability and the development and application of models to incorporate this knowledge into regulatory practice. Environ Toxicol Chem 2019;39:48-59. © 2019 SETAC.

Metal Bioavailability Models: Current Status, Lessons Learned, Considerations for Regulatory Use, and the Path Forward

Since the early 2000s, biotic ligand models and related constructs have been a dominant paradigm for risk assessment of aqueous metals in the environment. We critically review 1) the evidence for the mechanistic approach underlying metal bioavailability models; 2) considerations for the use and refinement of bioavailability-based toxicity models; 3) considerations for the incorporation of metal bioavailability models into environmental quality standards; and 4) some consensus recommendations for developing or applying metal bioavailability models. We note that models developed to date have been particularly challenged to accurately incorporate pH effects because they are unique with multiple possible mechanisms. As such, we doubt it is ever appropriate to lump algae/plant and animal bioavailability models; however, it is often reasonable to lump bioavailability models for animals, although aquatic insects may be an exception. Other recommendations include that data generated for model development should consider equilibrium conditions in exposure designs, including food items in combined waterborne-dietary matched chronic exposures. Some potentially important toxicity-modifying factors are currently not represented in bioavailability models and have received insufficient attention in toxicity testing. Temperature is probably of foremost importance; phosphate is likely important in plant and algae models. Acclimation may result in predictions that err on the side of protection. Striking a balance between comprehensive, mechanistically sound models and simplified approaches is a challenge. If empirical bioavailability tools such as multiple-linear regression models and look-up tables are employed in criteria, they should always be informed qualitatively and quantitatively by mechanistic models. If bioavailability models are to be used in environmental regulation, ongoing support and availability for use of the models in the public domain are essential. Environ Toxicol Chem 2019;39:60-84. © 2019 SETAC.

Development of Empirical Bioavailability Models for Metals

Recently, there has been renewed interest in the development and use of empirical models to predict metal bioavailability and derive protective values for aquatic life. However, there is considerable variability in the conceptual and statistical approaches with which these models have been developed. In the present study, we review case studies of empirical bioavailability model development, evaluating and making recommendations on key issues, including species selection, identifying toxicity-modifying factors (TMFs) and the appropriate environmental range of these factors, use of existing toxicity data sets and experimental design for developing new data sets, statistical considerations in deriving species-specific and pooled bioavailability models, and normalization of species sensitivity distributions using these models. We recommend that TMFs be identified from a combination of available chemical speciation and toxicity data and statistical evaluations of their relationships to toxicity. Experimental designs for new toxicity data must be sufficiently robust to detect nonlinear responses to TMFs and should encompass a large fraction (e.g., 90%) of the TMF range. Model development should involve a rigorous use of both visual plotting and statistical techniques to evaluate data fit. When data allow, we recommend using a simple linear model structure and developing pooled models rather than retaining multiple taxa-specific models. We conclude that empirical bioavailability models often have similar predictive capabilities compared to mechanistic models and can provide a relatively simple, transparent tool for predicting the effects of TMFs on metal bioavailability to achieve desired environmental management goals. Environ Toxicol Chem 2019;39:85-100. © 2019 SETAC.

State of the Science on Metal Bioavailability Modeling: Introduction to the Outcome of a Society of Environmental Toxicology and Chemistry Technical Workshop

A Society of Environmental Toxicology and Chemistry technical workshop was held in December 2017 to critically evaluate the current state of the science of metal bioavailability modeling. The availability of mechanistic models such as the biotic ligand model and the rapid development of empirical models such as multiple linear regressions means that choices are available in terms of bioavailability normalization approaches that can be used in metal risk assessments and the development of risk-based protective values for aquatic life. A key goal of the workshop was to provide potential users of metal bioavailability models with the information required to make appropriate decisions when choosing among mechanistic and empirical models. Workshop participants focused on the state of the science of metal bioavailability modeling, mechanistic and empirical model frameworks, validation of bioavailability models, and application of bioavailability models in risk-based decision-making approaches. The output of this workshop provides the necessary scientific information to incorporate bioavailability normalization in regulations pertaining to metals in freshwater systems. Environ Toxicol Chem 2019;39:42-47. © 2019 SETAC.

Best Practices for Derivation and Application of Thresholds for Metals Using Bioavailability-Based Approaches

The primary goal of the present study is to provide a broad view of best practices for evaluating bioavailability models for metals for use in the protection of aquatic life. We describe the state of the science regarding 1) the evaluation and selection of ecotoxicity data, 2) the selection of bioavailability models for use in normalization, and 3) subsequent application of bioavailability models. Although many examples of normalization steps exist worldwide, a scheme is proposed to evaluate and select a model that takes account of its representativeness (water chemistry and taxonomic coverage of the ecotoxicity data set) and validation performance. Important considerations for a suitable model are the quantity of inputs needed, accuracy, and ease of use, all of which are needed to set protective values for aquatic life and to use these values to evaluate potential risks to organisms in receiving waters. Although the end results of different model application approaches may be broadly similar, the differences in these application frameworks ultimately come down to a series of trade-offs between who needs to collect the data and use the bioavailability model, the different requirements of spatial scales involved (e.g., regional vs site-specific values), and model predictiveness and protectiveness. Ultimately, understanding the limits and consequences of these trade-offs allows for selection of the most appropriate model and application framework to best provide the intended levels of aquatic life protection. Environ Toxicol Chem 2019;39:118-130. © 2019 SETAC.