Comparison of different predictors of exposure for modeling impacts of metal mixtures on macroinvertebrates in stream microcosms

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.

Bioavailability and phytotoxicity of rare earth metals to Triticum aestivum under various exposure scenarios

It is a daunting challenge to predict toxicity and accumulation of rare earth metals (REMs) in different exposure scenarios (e.g., varying water chemistry and metal combinations). Herein, we investigated the toxicity and uptake of La and Ce in the presence of various levels of Ca, Mg, Na, K, and at different pH values, as well as the combined effects of La and Ce in wheat Triticum aestivum. Major cations (Ca²⁺ and Mg²⁺) significantly mitigated the toxicity and accumulation of La³⁺/Ce³⁺. Toxicity and uptake of La, Ce, and La-Ce mixtures could be well quantified by the multi-metal biotic ligand model (BLM) and by the Langmuir-type uptake model with the consideration of the competitive effects of Ca²⁺ and Mg²⁺, with more than 85.1% of variations explained. The derived binding constants of Ca, Mg, La, and Ce to wheat root were respectively 3.87, 3.59, 6.97, and 6.48 on the basis of toxicity data, and 3.23, 2.84, 6.07, and 5.27 on the basis of uptake data. The use of the alternative WHAM-F_tox approach, requiring fewer model parameters than the BLM but with similar Akaike information criterion (AIC) values, successfully predicted the toxicity and accumulation of La/Ce as well as toxicity of La-Ce mixtures, with at least 76.4% of variations explained. However, caution should be taken when using this approach to explain the uptake of La-Ce mixtures. Our results provided promising tools for delineating REMs toxicity/uptake in the presence of other toxicity-modifying factors or in mixture scenarios.

Model-based rationalization of mixture toxicity and accumulation in Triticum aestivum upon concurrent exposure to yttrium, lanthanum, and cerium

Rare earth elements (REEs) often co-exist in the environment, but predicting their 'cocktail effects' is still challenging, especially for high-order mixtures with more than two components. Here, we systematically investigated the toxicity and accumulation of yttrium, lanthanum, and cerium mixtures in Triticum aestivum following a standardized bioassay. Toxic effects of mixtures were predicted using the reference model of Concentration Addition (CA), Ternary model, and Ternary-Plus model. Interactions between the REEs in binary and ternary mixtures were determined based on external and internal concentrations, and their magnitude estimated from the parameters deviated from CA. Strong antagonistic interactions were found in the ternary mixtures even though there were no significant interactions in the binary mixtures. Predictive ability increased when using the CA model, Ternary model, and Ternary-Plus model, with R²= 0.78, 0.80, and 0.87 based on external exposure concentrations, and R²= 0.72, 0.73, and 0.79, respectively based on internal concentrations. The bioavailability-based model WHAM-F_TOX explained more than 88 % and 85 % of the toxicity of binary and ternary REE treatments, respectively. Our result showed that the Ternary-Plus model and WHAM-F_TOX model are promising tools to account for the interaction of REEs in mixtures and could be used for their risk assessment.

Validation of Bioavailability-Based Toxicity Models for Metals

Regulatory jurisdictions worldwide are increasingly incorporating bioavailability-based toxicity models into development of protective values (PVALs) for freshwater and saltwater aquatic life (e.g., water quality criteria, standards, and/or guidelines) for metals. Use of such models for regulatory purposes should be contingent on their ability to meet performance criteria as specified through a model-validation process. Model validation generally involves an assessment of a model's appropriateness, relevance, and accuracy. We review existing guidance for validation of bioavailability-based toxicity models, recommend questions that should be addressed in model-validation studies, discuss model study type and design considerations, present several new ways to evaluate model performance in validation studies, and suggest a framework for use of model validation in PVAL development. We conclude that model validation should be rigorous but flexible enough to fit the user's purpose. Although a model can never be fully validated to a level of zero uncertainty, it can be sufficiently validated to fit a specific purpose. Therefore, support (or lack of support) for a model should be presented in such a way that users can choose their own level of acceptability. We recommend that models be validated using experimental designs and endpoints consistent with the data sets that were used to parameterize and calibrate the model and validated across a broad range of geographically and ecologically relevant water types. Environ Toxicol Chem 2019;39:101-117. © 2019 SETAC.

The Impact of Metal-Rich Sediments Derived from Mining on Freshwater Stream Life

Metal-rich sediments have the potential to impair life in freshwater streams and rivers and, thereby, to inhibit recovery of ecological conditions after any remediation of mine water discharges. Sediments remain metal-rich over long time periods and have long-term potential ecotoxicological interactions with local biota, unless the sediments themselves are physically removed or replaced by less metal-rich sediment. Laboratory-derived environmental quality standards are difficult to apply to the field situation, as many complicating factors exist in the real world. Therefore, there is a strong case to consider other, field-relevant, measures of toxic effects as alternatives to laboratory-derived standards and to seek better biological tools to detect, diagnose and ideally predict community-level ecotoxicological impairment. Hence, this review concentrated on field measures of toxic effects of metal-rich sediment in freshwater streams, with less emphasis on laboratory-based toxicity testing approaches. To this end, this review provides an overview of the impact of metal-rich sediments on freshwater stream life, focusing on biological impacts linked to metal contamination.

Quantifying Differences in Responses of Aquatic Insects to Trace Metal Exposure in Field Studies and Short-Term Stream Mesocosm Experiments

Characterizing macroinvertebrate taxa as either sensitive or tolerant is of critical importance for investigating impacts of anthropogenic stressors in aquatic ecosystems and for inferring causality. However, our understanding of relative sensitivity of aquatic insects to metals in the field and under controlled conditions in the laboratory or mesocosm experiments is limited. In this study, we compared the response of 16 lotic macroinvertebrate families to metals in short-term (10-day) stream mesocosm experiments and in a spatially extensive field study of 154 Colorado streams. Comparisons of field and mesocosm-derived EC₂₀ (effect concentration of 20%) values showed that aquatic insects were generally more sensitive to metals in the field. Although the ranked sensitivity to metals was similar for many families, we observed large differences between field and mesocosm responses for some groups (e.g., Baetidae and Heptageniidae). These differences most likely resulted from the inability of short-term experiments to account for factors such as dietary exposure to metals, rapid recolonization in the field, and effects of metals on sensitive life stages. Understanding mechanisms responsible for differences among field, mesocosm, and laboratory approaches would improve our ability to predict contaminant effects and establish ecologically meaningful water-quality criteria.

Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity

One of the primary goals of biological assessment of streams is to identify which of a suite of chemical stressors is limiting their ecological potential. Elevated metal concentrations in streams are often associated with low pH, yet the effects of these two potentially limiting factors of freshwater biodiversity are rarely considered to interact beyond the effects of pH on metal speciation. Using a dataset from two continents, a biogeochemical model of the toxicity of metal mixtures (Al, Cd, Cu, Pb, Zn) and quantile regression, we addressed the relative importance of both pH and metals as limiting factors for macroinvertebrate communities. Current environmental quality standards for metals proved to be protective of stream macroinvertebrate communities and were used as a starting point to assess metal mixture toxicity. A model of metal mixture toxicity accounting for metal interactions was a better predictor of macroinvertebrate responses than a model considering individual metal toxicity. We showed that the direct limiting effect of pH on richness was of the same magnitude as that of chronic metal toxicity, independent of its influence on the availability and toxicity of metals. By accounting for the direct effect of pH on macroinvertebrate communities, we were able to determine that acidic streams supported less diverse communities than neutral streams even when metals were below no-effect thresholds. Through a multivariate quantile model, we untangled the limiting effect of both pH and metals and predicted the maximum diversity that could be expected at other sites as a function of these variables. This model can be used to identify which of the two stressors is more limiting to the ecological potential of running waters.

Modeling whole body trace metal concentrations in aquatic invertebrate communities: A trait-based approach

Trace metal risk assessment and environmental quality standard definition require realistic models that quantify metal exposure and accumulation by biota. In the present study we propose a novel trait-based approach to predict whole body concentrations of metals in aquatic invertebrates from concentrations measured in different environmental compartments. Field data from a large riverine floodplain was used to calibrate and test the model. The prediction performance of the trait-based model was unbiased and uncertainty was below the twofold of measured concentrations for the four studied metals (Ni, Cu, Cd, Pb). The relative contribution of feeding, respiration and locomotion patterns as well as metal concentrations in three environmental compartments provided insights into the importance of different uptake pathways. The relation with the sediment (i.e., to what degree taxa live in or directly on the sediment) was shown to be the most important trait to predict metal accumulation. Overall, this study demonstrated the potential use of bioecological traits for the modeling of whole body metal concentrations of entire aquatic invertebrate communities.

Comparison of four methods for bioavailability-based risk assessment of mixtures of Cu, Zn, and Ni in freshwater

Although chemical risk assessment is still mainly conducted on a substance-by-substance basis, organisms in the environment are typically exposed to mixtures of substances. Risk assessment procedures should therefore be adapted to fit these situations. Four mixture risk assessment methodologies were compared for risk estimations of mixtures of copper (Cu), zinc (Zn), and nickel (Ni). The results showed that use of the log-normal species sensitivity distribution (SSD) instead of the best-fit distribution and sampling species sensitivities independently for each metal instead of using interspecies correlations in metal sensitivity had little impact on risk estimates. Across 4 different monitoring datasets, between 0% and 52% of the target water samples were estimated to be at risk, but only between 0% and 15% of the target water samples were at risk because of the mixture of metals and not any single metal individually. When a natural baseline database was examined, it was estimated that 10% of the target water samples were at risk because of single metals or their mixtures; when the most conservative method was used (concentration addition [CA] applied directly to the SSD, i.e., CA_SSD ). However, the issue of metal mixture risk at geochemical baseline concentrations became relatively small (2% of target water samples) when a theoretically more correct method was used (CA applied to individual dose response curves, i.e., CA_DRC ). Finally, across the 4 monitoring datasets, the following order of conservatism for the 4 methods was shown (from most to least conservative, with ranges of median margin of safety [MoS] relative to CA_SSD ): CA_SSD > CA_DRC (MoS = 1.17-1.25) > IA_DRC (independent action (IA) applied to individual dose-response curves; MoS = 1.38-1.60) > IA_SSD (MoS = 1.48-1.72). Therefore, it is suggested that these 4 methods can be used in a general tiered scheme for the risk assessment of metal mixtures in a regulatory context. In this scheme, the CA_SSD method could serve as a first (conservative) tier to identify situations with likely no potential risk at all, regardless of the method used (the sum toxic unit expressed relative to the 5% hazardous concentration [SumTU_HC5 ] < 1) and the IA_SSD method to identify situations of potential risk, also regardless of the method used (the multisubstance potentially affected fraction of species using the IA_SSD method [msPAF_IA,SSD ] > 0.05). The CA_DRC and IA_DRC methods could be used for site-specific assessment for situations that fall in between (SumTU_HC5  > 1 and msPAF_IA,SSD  < 0.05). Environ Toxicol Chem 2017;36:2123-2138. © 2017 SETAC.

Causes of highway road dust toxicity to an estuarine amphipod: Evaluating the effects of nicotine

Urban road dust can potentially have adverse effects on ecosystems if it is discharged into receiving waters. This study investigated the causes of highway road dust toxicity by performing sediment toxicity identification evaluation (TIE) tests with an estuarine amphipod, Grandidierella japonica. In addition to metals and polycyclic aromatic hydrocarbons, which are traditionally considered to be the major toxicants in road runoff, we focused on dissolved nicotine as a causative toxicant. The sediment TIE results suggested that organic contaminants contributed to the majority of toxicity, and that the contribution of unionized nicotine to the toxicity was the highest among the chemicals considered. However, additional mortality tests with 48-h pulsed nicotine exposure demonstrated that exposure to nicotine at the same concentration as the baseline level in TIE tests did not cause significant 10-day amphipod mortality. Thus, the road dust toxicity could not be explained only by unionized nicotine, thereby suggesting contributions from joint effects of the measured toxicants and the presence of other unmeasured factors.

A structural equation model of soil metal bioavailability to earthworms: confronting causal theory and observations using a laboratory exposure to field-contaminated soils

Structural equation models (SEM) are increasingly used in ecology as multivariate analysis that can represent theoretical variables and address complex sets of hypotheses. Here we demonstrate the interest of SEM in ecotoxicology, more precisely to test the three-step concept of metal bioavailability to earthworms. The SEM modeled the three-step causal chain between environmental availability, environmental bioavailability and toxicological bioavailability. In the model, each step is an unmeasured (latent) variable reflected by several observed variables. In an exposure experiment designed specifically to test this SEM for Cd, Pb and Zn, Aporrectodea caliginosa was exposed to 31 agricultural field-contaminated soils. Chemical and biological measurements used included CaC12-extractable metal concentrations in soils, free ion concentration in soil solution as predicted by a geochemical model, dissolved metal concentration as predicted by a semi-mechanistic model, internal metal concentrations in total earthworms and in subcellular fractions, and several biomarkers. The observations verified the causal definition of Cd and Pb bioavailability in the SEM, but not for Zn. Several indicators consistently reflected the hypothetical causal definition and could thus be pertinent measurements of Cd and Pb bioavailability to earthworm in field-contaminated soils. SEM highlights that the metals present in the soil solution and easily extractable are not the main source of available metals for earthworms. This study further highlights SEM as a powerful tool that can handle natural ecosystem complexity, thus participating to the paradigm change in ecotoxicology from a bottom-up to a top-down approach.

Interactions and Toxicity of Cu-Zn mixtures to Hordeum vulgare in Different Soils Can Be Rationalized with Bioavailability-Based Prediction Models

Soil contamination with copper (Cu) is often associated with zinc (Zn), and the biological response to such mixed contamination is complex. Here, we investigated Cu and Zn mixture toxicity to Hordeum vulgare in three different soils, the premise being that the observed interactions are mainly due to effects on bioavailability. The toxic effect of Cu and Zn mixtures on seedling root elongation was more than additive (i.e., synergism) in soils with high and medium cation-exchange capacity (CEC) but less than additive (antagonism) in a low-CEC soil. This was found when we expressed the dose as the conventional total soil concentration. In contrast, antagonism was found in all soils when we expressed the dose as free-ion activities in soil solution, indicating that there is metal-ion competition for binding to the plant roots. Neither a concentration addition nor an independent action model explained mixture effects, irrespective of the dose expressions. In contrast, a multimetal BLM model and a WHAM-Ftox model successfully explained the mixture effects across all soils and showed that bioavailability factors mainly explain the interactions in soils. The WHAM-Ftox model is a promising tool for the risk assessment of mixed-metal contamination in soils.

Incorporating bioavailability into toxicity assessment of Cu-Ni, Cu-Cd, and Ni-Cd mixtures with the extended biotic ligand model and the WHAM-F(tox) approach

There are only a limited number of studies that have developed appropriate models which incorporate bioavailability to estimate mixture toxicity. Here, we explored the applicability of the extended biotic ligand model (BLM) and the WHAM-F(tox) approach for predicting and interpreting mixture toxicity, with the assumption that interactions between metal ions obey the BLM theory. Seedlings of lettuce Lactuca sativa were exposed to metal mixtures (Cu-Ni, Cu-Cd, and Ni-Cd) contained in hydroponic solutions for 4 days. Inhibition to root elongation was the endpoint used to quantify the toxic response. Assuming that metal ions compete with each other for binding at a single biotic ligand, the extended BLM succeeded in predicting toxicity of three mixtures to lettuce, with more than 82% of toxicity variation explained. There were no significant differences in the values of f(mix50) (i.e., the overall amounts of metal ions bound to the biotic ligand inducing 50% effect) for the three mixture combinations, showing the possibility of extrapolating these values to other binary metal combinations. The WHAM-F(tox) approach showed a similar level of precision in estimating mixture toxicity while requiring fewer parameters than the BLM-f(mix) model. External validation of the WHAM-F(tox) approach using literature data showed its applicability for other species and other mixtures. The WHAM-F(tox) model is suitable for delineating mixture effects where the extended BLM also applies. Therefore, in case of lower data availability, we recommend the lower parameterized WHAM-F(tox) as an effective approach to incorporate bioavailability in quantifying mixture toxicity.

Delineating the dynamic uptake and toxicity of Ni and Co mixtures in Enchytraeus crypticus using a WHAM-FTOX approach

Uptake and toxicity of Ni, Co and their mixtures in Enchytraeus crypticus after different exposure times (4, 7, 10 and 14d) were predicted using the WHAM-FTOX model, which incorporates the effects of metal speciation, affinity and competition of metals for binding sites. The combined toxicity of metals was quantified by the toxicity function (FTOX), a linear combination of the amount of metal binding to non-specific ligand sites (vi) and a toxicity coefficient (αi). Observed body concentrations of Ni and Co in the animals correlated well with the WHAM-calculated amounts binding to humic acid, supporting the use of humic acid as a surrogate for metal binding sites of E. crypticus. The toxicity of metals at different exposure times was well predicted by the WHAM-FTOX model. The derived αNi increased with time and reached equilibrium after approximately 14d, while αCo remained almost independent of time. This suggests for Ni more time is needed than for Co to reach equilibrium of body concentrations, so the toxicity of Ni is much more time-dependent. The WHAM-FTOX model provides a new tool for evaluating the potential mixture toxicity of metals to soil organisms in a dynamic environment. However, as αi varied with exposure time, caution is warranted when using the parameters estimated from acute toxicity experiments for predicting the chronic toxicity of metal mixtures.

Subcellular partitioning of metals in Aporrectodea caliginosa along a gradient of metal exposure in 31 field-contaminated soils

Subcellular fractionation of metals in organisms was proposed as a better way to characterize metal bioaccumulation. Here we report the impact of a laboratory exposure to a wide range of field-metal contaminated soils on the subcellular partitioning of metals in the earthworm Aporrectodea caliginosa. Soils moderately contaminated were chosen to create a gradient of soil metal availability; covering ranges of both soil metal contents and of several soil parameters. Following exposure, Cd, Pb and Zn concentrations were determined both in total earthworm body and in three subcellular compartments: cytosolic, granular and debris fractions. Three distinct proxies of soil metal availability were investigated: CaCl2-extractable content dissolved content predicted by a semi-mechanistic model and free ion concentration predicted by a geochemical speciation model. Subcellular partitionings of Cd and Pb were modified along the gradient of metal exposure, while stable Zn partitioning reflected regulation processes. Cd subcellular distribution responded more strongly to increasing soil Cd concentration than the total internal content, when Pb subcellular distribution and total internal content were similarly affected. Free ion concentrations were better descriptors of Cd and Pb subcellular distribution than CaCl2 extractable and dissolved metal concentrations. However, free ion concentrations and soil total metal contents were equivalent descriptors of the subcellular partitioning of Cd and Pb because they were highly correlated. Considering lowly contaminated soils, our results raise the question of the added value of three proxies of metal availability compared to soil total metal content in the assessment of metal bioavailability to earthworm.

Modelling metal accumulation using humic acid as a surrogate for plant roots

Metal accumulation in roots was modelled with WHAM VII using humic acid (HA) as a surrogate for root surface. Metal accumulation was simulated as a function of computed metal binding to HA, with a correction term (E(HA)) to account for the differences in binding site density between HA and root surface. The approach was able to model metal accumulation in roots to within one order of magnitude for 95% of the data points. Total concentrations of Mn in roots of Vigna unguiculata, total concentrations of Ni, Zn, Cu and Cd in roots of Pisum sativum, as well as internalized concentrations of Cd, Ni, Pb and Zn in roots of Lolium perenne, were significantly correlated to the computed metal binding to HA. The method was less successful at modelling metal accumulation at low concentrations and in soil experiments. Measured concentrations of Cu internalized in L. perenne roots were not related to Cu binding to HA modelled and deviated from the predictions by over one order of magnitude. The results indicate that metal uptake by roots may under certain conditions be influenced by conditional physiological processes that cannot simulated by geochemical equilibrium. Processes occurring in chronic exposure of plants grown in soil to metals at low concentrations complicate the relationship between computed metal binding to HA and measured metal accumulation in roots.

Application of a generalized linear mixed model to analyze mixture toxicity: survival of brown trout affected by copper and zinc

Increased concerns about the toxicity of chemical mixtures have led to greater emphasis on analyzing the interactions among the mixture components based on observed effects. The authors applied a generalized linear mixed model (GLMM) to analyze survival of brown trout (Salmo trutta) acutely exposed to metal mixtures that contained copper and zinc. Compared with dominant conventional approaches based on an assumption of concentration addition and the concentration of a chemical that causes x% effect (ECx), the GLMM approach has 2 major advantages. First, binary response variables such as survival can be modeled without any transformations, and thus sample size can be taken into consideration. Second, the importance of the chemical interaction can be tested in a simple statistical manner. Through this application, the authors investigated whether the estimated concentration of the 2 metals binding to humic acid, which is assumed to be a proxy of nonspecific biotic ligand sites, provided a better prediction of survival effects than dissolved and free-ion concentrations of metals. The results suggest that the estimated concentration of metals binding to humic acid is a better predictor of survival effects, and thus the metal competition at the ligands could be an important mechanism responsible for effects of metal mixtures. Application of the GLMM (and the generalized linear model) presents an alternative or complementary approach to analyzing mixture toxicity.

Relating metal exposure and chemical speciation to trace metal accumulation in aquatic insects under natural field conditions

The present study investigated to what extent measured dissolved metal concentrations, WHAM-predicted free metal ion activity and modulating water chemistry factors can predict Ni, Cu, Zn, Cd and Pb accumulation in various aquatic insects under natural field conditions. Total dissolved concentrations and accumulated metal levels in four taxa (Leuctra sp., Simuliidae, Rhithrogena sp. and Perlodidae) were determined and free metal ion activities were calculated in 36 headwater streams located in the north-west part of England. Observed invertebrate body burdens were strongly related to free metal ion activities and competition among cations for uptake in the biota. Taking into account competitive effects generally provided better fits than considering uptake as a function of total dissolved metal levels or the free ion alone. Due to the critical importance and large range in pH (4.09 to 8.33), the H(+) ion activity was the most dominant factor influencing metal accumulation. Adding the influence of Na(+) on Cu(2+) accumulation improved the model goodness of fit for both Rhithrogena sp. and Perlodidae. Effects of hardness ions on metal accumulation were limited, indicating the minor influence of Ca(2+) and Mg(2+) on metal accumulation in soft-water streams (0.01 to 0.94 mM Ca; 0.02 to 0.39 mM Mg). DOC levels (ranging from 0.6 to 8.9 mg L(-1)) significantly affected Cu body burdens, however not the accumulation of the other metals. Our results suggest that 1) uptake and accumulation of free metal ions are most dominantly influenced by competition of free H(+) ions in low-hardness headwaters and 2) invertebrate body burdens in natural waters can be predicted based on the free metal ion activity using speciation modelling and effects of H(+) competition.

Lead toxicity to Lemna minor predicted using a metal speciation chemistry approach

In the present study, predictive measures for Pb toxicity and Lemna minor were developed from bioassays with 7 surface waters having varied chemistries (0.5-12.5 mg/L dissolved organic carbon, pH of 5.4-8.3, and water hardness of 8-266 mg/L CaCO3 ). As expected based on water quality, 10%, 20%, and 50% inhibitory concentration (IC10, IC20, and IC50, respectively) values expressed as percent net root elongation (%NRE) varied widely (e.g., IC20s ranging from 306 nM to >6920 nM total dissolved Pb), with unbounded values limited by Pb solubility. In considering chemical speciation, %NRE variability was better explained when both Pb hydroxides and the free lead ion were defined as bioavailable (i.e., f{OH} ) and colloidal Fe(III)(OH)3 precipitates were permitted to form and sorb metals (using FeOx as the binding phase). Although cause and effect could not be established because of covariance with alkalinity (p = 0.08), water hardness correlated strongly (r(2)  = 0.998, p < 0.0001) with the concentration of total Pb in true solution ([Pb]T_True solution ). Using these correlations as the basis for predictions (i.e., [Pb]T_True solution vs water hardness and %NRE vs f{OH} ), IC20 and IC50 values produced were within a factor of 2.9 times and 2.2 times those measured, respectively. The results provide much needed effect data for L. minor and highlight the importance of chemical speciation in Pb-based risk assessments for aquatic macrophytes.

The life-table demographic response of freshwater rotifer Brachionus calyciflorus to multi-metal (Cu, Zn, Cd, Cr, and Mn) mixture interaction

The effects of multi-metal mixtures on the life-table demography of rotifers are not well known. In this study, the freshwater rotifer Brachionus calyciflorus was exposed to mixture of Cu, Zn, Cd, Cr, and Mn, and the life-table demographic parameters including net reproductive rate, generation time, life expectancy at hatching, and intrinsic rate of population increase were calculated. The results showed that interactions between a given element concentration, except Mn, and the other four elements mixture concentration affected the intrinsic rate of population increase (p < 0.01). Interactions between Zn concentration, as well as Mn, and the other four elements mixture concentration affected the net reproductive rate and the life expectancy at hatching, respectively (p < 0.05). The variation of parameters with the rise of the other four elements mixture concentrations from 0 to high was mainly attributed to the difference of interaction among the five metals mixture with different ratio of concentrations.

Metal and proton toxicity to lake zooplankton: a chemical speciation based modelling approach

The WHAM-FTOX model quantifies the combined toxic effects of protons and metal cations towards aquatic organisms through the toxicity function (FTOX), a linear combination of the products of organism-bound cation and a toxic potency coefficient for each cation. We describe the application of the model to predict an observable ecological field variable, species richness of pelagic lake crustacean zooplankton, studied with respect to either acidification or the impacts of metals from smelters. The fitted results give toxic potencies increasing in the order H(+) < Al < Cu < Zn < Ni. In general, observed species richness is lower than predicted, but in some instances agreement is close, and is rarely higher than predictions. The model predicts recovery in agreement with observations for three regions, namely Sudbury (Canada), Bohemian Forest (Czech Republic) and a subset of lakes across Norway, but fails to predict observed recovery from acidification in Adirondack lakes (USA).

The rhizotoxicity of metal cations is related to their strength of binding to hard ligands

Mechanisms whereby metal cations are toxic to plant roots remain largely unknown. Aluminum, for example, has been recognized as rhizotoxic for approximately 100 yr, but there is no consensus on its mode of action. The authors contend that the primary mechanism of rhizotoxicity of many metal cations is nonspecific and that the magnitude of toxic effects is positively related to the strength with which they bind to hard ligands, especially carboxylate ligands of the cell-wall pectic matrix. Specifically, the authors propose that metal cations have a common toxic mechanism through inhibiting the controlled relaxation of the cell wall as required for elongation. Metal cations such as Al(3+) and Hg(2+), which bind strongly to hard ligands, are toxic at relatively low concentrations because they bind strongly to the walls of cells in the rhizodermis and outer cortex of the root elongation zone with little movement into the inner tissues. In contrast, metal cations such as Ca(2+), Na(+), Mn(2+), and Zn(2+) , which bind weakly to hard ligands, bind only weakly to the cell wall and move farther into the root cylinder. Only at high concentrations is their weak binding sufficient to inhibit the relaxation of the cell wall. Finally, different mechanisms would explain why certain metal cations (for example, Tl(+), Ag(+), Cs(+), and Cu(2+)) are sometimes more toxic than expected through binding to hard ligands. The data presented in the present study demonstrate the importance of strength of binding to hard ligands in influencing a range of important physiological processes within roots through nonspecific mechanisms.

Metal mixture toxicity to aquatic biota in laboratory experiments: application of the WHAM-FTOX model

The WHAM-FTOX model describes the combined toxic effects of protons and metal cations towards aquatic organisms through the toxicity function (FTOX), a linear combination of the products of organism-bound cation and a toxic potency coefficient (αi) for each cation. Organism-bound, metabolically-active, cation is quantified by the proxy variable, amount bound by humic acid (HA), as predicted by the WHAM chemical speciation model. We compared published measured accumulations of metals by living organisms (bacteria, algae, invertebrates) in different solutions, with WHAM predictions of metal binding to humic acid in the same solutions. After adjustment for differences in binding site density, the predictions were in reasonable line with observations (for logarithmic variables, r(2)=0.89, root mean squared deviation=0.44), supporting the use of HA binding as a proxy. Calculated loadings of H(+), Al, Cu, Zn, Cd, Pb and UO2 were used to fit observed toxic effects in 11 published mixture toxicity experiments involving bacteria, macrophytes, invertebrates and fish. Overall, WHAM-FTOX gave slightly better fits than a conventional additive model based on solution concentrations. From the derived values of αi, the toxicity of bound cations can tentatively be ranked in the order: H<Al<(Zn-Cu-Pb-UO2)<Cd. The WHAM-FTOX analysis indicates much narrower ranges of differences amongst individual organisms in metal toxicity tests than was previously thought. The model potentially provides a means to encapsulate knowledge contained within laboratory data, thereby permitting its application to field situations.