Ecotoxicity of Lead to a Phytoplankton Community: Effects of pH and Phosphorus Addition and Implications for Risk Assessment.

Ecological risk assessment and water quality criteria for lead (Pb) are increasingly making use of bioavailability-based approaches to account for the impact of toxicity-modifying factors, such as pH and dissolved organic carbon. For phytoplankton, which are among the most Pb-sensitive freshwater species, a Pb bioavailability model has previously been developed based on standard single-species exposures at a high phosphorus (P) concentration and pH range of 6.0 to 8.0. It is well known that P can affect metal toxicity to phytoplankton and that the pH of many surface waters can be above 8.0. We aimed to test whether the single-species bioavailability model for Pb could predict the influence of pH on Pb toxicity to a phytoplankton community at both low and high P supply. A 10-species phytoplankton community was exposed to Pb for 28 days at two different pH levels (7.2 and 8.4) and two different P supply levels (low and high, i.e., total P input 10 and 100 µg/L, respectively) in a full factorial 2 × 2 test design. We found that the effects of total Pb on three community-level endpoints (biodiversity, community functioning, and community structure) were highly dependent on both pH and P supply. Consistent lowest-observed-effect concentrations (LOECs) ranged between 21 and >196 µg total Pb/L and between 10 and >69 µg filtered Pb/L. Long-term LOECs were generally higher, that is, 69 µg total Pb/L (42 µg filtered Pb/L) or greater, across all endpoints and conditions, indicating recovery near the end of the exposure period, and suggesting the occurrence of acclimation to Pb and/or functional redundancy. The highest toxicity of Pb for all endpoints was observed in the pH 7.2 × low P treatment, whereas the pH 8.4 × low P and pH 8.4 × high P treatment were the least sensitive treatments. At the pH 7.2 × high P treatment, the algal community showed an intermediate Pb sensitivity. The effect of pH on the toxicity of filtered Pb could not be precisely quantified because for many endpoints no effect was observed at the highest Pb concentration tested. However, the long-term LOECs (filtered Pb) at low P supply suggest a decrease in Pb toxicity of at least 1.6-fold from pH 7.2 to 8.4, whereas the single-species algal bioavailability model predicted a 2.5-fold increase. This finding suggests that bioavailability effects of pH on Pb toxicity cannot be extrapolated as such from the single species to the community level. Overall, our data indicate that, although the single-species algal Pb bioavailability model may not capture pH effects on Pb ecotoxicity in multispecies systems, the bioavailability-based hazardous concentration for 5% of the species was protective of long-term Pb effects on the structure, function, and diversity of a phytoplankton community in a relevant range of pH and P conditions. Environ Toxicol Chem 2023;42:2684-2700. © 2023 SETAC.

Using a dynamic energy budget model to investigate the physiological mode of action of lead (Pb) to Lymnaea stagnalis.

Lymnaea stagnalis is a notably sensitive species for a variety of metals, including lead (Pb). However, the mechanism(s) of lead toxicity to L. stagnalis currently remain incompletely understood. Under dynamic energy budget (DEB) theory, different physiological modes of action (PMoAs) result in the emergence of distinct changes to the life histories of exposed organisms. This work aims to better understand the PMoA of lead toxicity to L. stagnalis by applying DEB modeling to previously published datasets. After calibration, the model was utilized to evaluate the relative likelihood of several PMoAs. Assuming decreased assimilation, the L. stagnalis DEB model was able to capture most, but not all, trends in experimentally observed endpoints, including growth, reproduction, and food ingestion. The weight-of-evidence suggests that decreased assimilation via a decrease in food ingestion is the most plausible PMoA for chronic lead toxicity in L. stagnalis. Collectively, our results illustrate how mechanistic modeling can create added value for conventional individual-level toxicity test data by enabling inferences about potential physiological mechanisms of toxicity.

Predicting Combined Effects of Chemical Stressors: Population-Level Effects of Organic Chemical Mixtures with a Dynamic Energy Budget Individual-Based Model.

Most regulatory ecological risk-assessment frameworks largely disregard discrepancies between the laboratory, where effects of single substances are assessed on individual organisms, and the real environment, where organisms live together in populations and are often exposed to multiple simultaneously occurring substances. We assessed the capability of individual-based models (IBMs) with a foundation in the dynamic energy budget (DEB) theory to predict combined effects of chemical mixtures on populations when they are calibrated on toxicity data of single substances at the individual level only. We calibrated a DEB-IBM for Daphnia magna for four compounds (pyrene, dicofol, α-hexachlorocyclohexane, and endosulfan), covering different physiological modes of action. We then performed a 17-week population experiment with D. magna (designed using the DEB-IBM), in which we tested mixture combinations of these chemicals at relevant concentrations, in a constant exposure phase (7-week exposure and recovery), followed by a pulsed exposure phase (3-day pulse exposure and recovery). The DEB-IBM was validated by comparing blind predictions of mixture toxicity effects with the population data. The DEB-IBM accurately predicted mixture toxicity effects on population abundance in both phases when assuming independent action at the effect mechanism level. The population recovery after the constant exposure was well predicted, but recovery after the pulse was not. The latter could be related to insufficient consideration of stochasticity in experimental design, model implementation, or both. Importantly, the mechanistic DEB-IBM performed better than conventional statistical mixture assessment methods. We conclude that the DEB-IBM, calibrated using only single-substance individual-level toxicity data, produces accurate predictions of population-level mixture effects and can therefore provide meaningful contributions to ecological risk assessment of environmentally realistic mixture exposure scenarios. Environ Toxicol Chem 2022;41:2240-2258. © 2022 SETAC.

Interactive Metal Mixture Toxicity to Daphnia magna Populations as an Emergent Property in a Dynamic Energy Budget Individual-Based Model.

Environmental risk assessment of metal mixtures is challenging due to the large number of possible mixtures and interactions. Mixture toxicity data cannot realistically be generated for all relevant scenarios. Therefore, methods for prediction of mixture toxicity from single-metal toxicity data are needed. We tested how well toxicity of Cu-Ni-Zn mixtures to Daphnia magna populations can be predicted based on the Dynamic Energy Budget theory with an individual-based model (DEB-IBM), assuming non-interactivity of metals on the physiological level. We exposed D. magna populations to Cu, Ni, and Zn and their mixture at a fixed concentration ratio. We calibrated the DEB-IBM with single-metal data and generated blind predictions of mixture toxicity (population size over time), with account for uncertainty. We compared the predictive performance of the DEB-IBM with respect to mixture effects on population density and population growth rates with that of two reference models applied on the population level, independent action and concentration addition. Our inferred physiological modes of action (pMoA) differed from literature-reported pMoAs, raising the question of whether this is a result of different model selection approaches, intraspecific variability, or whether different pMoAs might actually drive toxicity in a population context. Observed mixture effects were concentration- and endpoint-dependent. The independent action was overall more accurate than the concentration addition but concentration addition-predicted effects on population growth rate were slightly better. The DEB-IBM most accurately predicted effects on 6-week density, including antagonistic effects at high concentrations, which emerged from non-interactivity at the physiological level. Mixture effects on initial population growth rate appear to be more difficult to predict. To explain why model accuracy is endpoint-dependent, relationships between individual-level and population-level endpoints should be illuminated. Environ Toxicol Chem 2021;40:3034-3048. © 2021 SETAC.

Development and Validation of a Mixture Toxicity Implementation in the Dynamic Energy Budget-Individual-Based Model: Effects of Copper and Zinc on Daphnia magna Populations.

Mechanistic population models are gaining considerable interest in ecological risk assessment. The dynamic energy budget approach for toxicity (DEBtox) and the general unified threshold model for survival (GUTS) are well-established theoretical frameworks that describe sublethal and lethal effects of a chemical stressor, respectively. However, there have been limited applications of these models for mixtures of chemicals, especially to predict long-term effects on populations. We used DEBtox and GUTS in an individual-based model (IBM) framework to predict both single and combined effects of copper and zinc on Daphnia magna populations. The model was calibrated based on standard chronic toxicity test results with the single substances. A mixture toxicity implementation based on the general independent action model for mixtures was developed and validated with data from a population experiment with copper and zinc mixtures. Population-level effects of exposure to individual metals were accurately predicted by DEB-IBM. The DEB-IBM framework also allowed us to identify the potential mechanisms underlying these observations. Under independent action the DEB-IBM was able to predict the population dynamics observed in populations exposed to the single metals and their mixtures (R2 > 65% in all treatments). Our modeling shows that it is possible to extrapolate from single-substance effects at the individual level to mixture toxicity effects at the population level, without the need for mixture toxicity data at the individual level from standard mixture toxicity tests. The application of such modeling techniques can increase the ecological realism in risk assessment. Environ Toxicol Chem 2021;40:513-527. © 2020 SETAC.

A margin of safety approach for the assessment of environmentally realistic chemical mixtures in the marine environment based on combined passive sampling and ecotoxicity testing.

Organisms in the marine environment are being exposed to an increasing variety of chemicals. This research presents an effect-based monitoring method for the derivation of a margin of safety for environmentally realistic chemical mixtures. The method is based on a combination of passive sampling and ecotoxicity testing. First, passive sampling was performed using H2O-philic divinylbenzene Speedisks during 3 sampling campaigns between 2016 and 2018 at 4 sampling locations in the Belgian part of the North Sea. Next, we exposed the marine diatom Phaeodactylum tricornutum to Speedisk extracts that were reconstituted in HPLC-grade water and defined the MoS of each sample as the highest no-observed effect concentration, expressed as relative enrichment factor (REF). A REF was defined by comparing the concentrations of 89 personal care products, pesticides and pharmaceuticals in the biotest medium with those measured in water grab samples to relate exposure concentrations in the tests to environmental concentrations. Across eight marine samples, diatom growth inhibition was observed at REF ≥ 3.2 and margins of safety were found between REF 1.1-11.0. In addition, we found that reconstitution of extracts in HPLC-water was suitable to overcome the solvent-related challenges in biotesting that are usually associated with passive sampler extract spiking, whilst it still allowed REFs up to 44 in the biotest medium to be achieved. This method, however, likely covers mainly the polar fraction of environmentally realistic chemical mixtures and less the non-polar fraction. Nevertheless, for 5 out of 8 samples, the Margin of Safety (MoS) was found to be lower than 10, which represents the typically lowest possible assessment factor applied to no effects ecotoxicological data in conventional environmental risk assessments, suggesting ecological risks for these samples.

The Unexpected Absence of Nickel Effects on a Daphnia Population at 3 Temperatures is Correctly Predicted by a Dynamic Energy Budget Individual-Based Model.

Recent studies have shown that temperature affects chronic nickel (Ni) toxicity to Daphnia magna at the individual (apical) level. However, the effect of temperature on Ni toxicity to D. magna at the population level is unknown. The present study investigated whether the effect of temperature on chronic Ni toxicity to D. magna assessed on apical endpoints can be extrapolated to the population level. The results of the population experiment showed no consistent Ni effects on total D. magna population abundance at 15, 20, and 25 °C, although the Ni concentrations tested were previously reported to significantly reduce reproduction in D. magna individuals. This result supports the idea that ecological risk assessment should not extrapolate as such from apical endpoints to the population level. A dynamic energy budget individual-based model (DEB-IBM) was calibrated using apical Ni toxicity data at 15, 20, and 25 °C. The goal was to investigate whether the calibrated DEB-IBM would be able to predict the unexpected absence of effects at the population level and to further investigate the effect of temperature on Ni toxicity to a D. magna population. At the population level, the calibrated DEB-IBM correctly predicted the unexpected absence of an effect of Ni on a D. magna population. Detailed analysis of simulation output suggests that the predicted lower Ni sensitivity at the population level occurs because Ni-induced mortality is compensated by reduced starvation (less intraspecific competition). Extrapolated median effective concentration (EC50) values for population density predicted that the effect of temperature on Ni toxicity to D. magna populations was smaller (1.9-fold higher at 25 °C than at 15 °C) than on Ni toxicity to D. magna apical reproduction (the EC50 is 6.5-fold higher at 25 °C than at 15 °C). These results show that the DEB-IBM can help to replace population experiments by in silico simulations and to optimize the experimental design of population studies. Environ Toxicol Chem 2019;38:1423-1433. © 2019 SETAC.

The Use of Mechanistic Population Models in Metal Risk Assessment: Combined Effects of Copper and Food Source on Lymnaea stagnalis Populations.

Environmental risk assessment (ERA) of chemicals aims to protect populations, communities, and ecosystems. Population models are considered more frequent in ERA because they can bridge the gap between the individual and the population level. Lymnaea stagnalis (the great pond snail) is an organism that is particularly sensitive to various metals, including copper (Cu). In addition, the sensitivity of this species to Cu differs between food sources. The first goal of the present study was to investigate whether we could explain the variability in sensitivity between food sources (lettuce and fish flakes) at the individual level with a dynamic energy budget (DEB) model. By adapting an existing DEB model and calibrating it with Cu toxicity data, thereby combining information from 3 studies and 2 endpoints (growth and reproduction), we put forward inhibition of energy assimilation as the most plausible physiological mode of action (PMoA) of Cu. Furthermore, the variation in Cu sensitivity between both food sources was considerably lower at the PMoA level than at the individual level. Higher Cu sensitivity at individual level under conditions of lower food quality or availability appears to emerge from first DEB principles when inhibition of assimilation is the PMoA. This supports the idea that DEB explained Cu sensitivity variation between food sources. Our second goal was to investigate whether this food source effect propagated to the population level. By incorporating DEB in an individual-based model (IBM), population-level effects were predicted. Based on our simulations, the food source effect was still present at the population level, albeit less prominently. Finally, we compared predicted population-level effect concentration, x% (ECx) values with individual-level ECx values for different studies. Using the DEB-IBM, the range of effect concentrations decreased significantly: at the individual level, the difference in chronic EC10 values between studies was a factor of 70 (1.13-78 µg dissolved Cu/L), whereas at the population level the difference was a factor of 15 (2.9-44.6 µg dissolved Cu/L). To improve interstudy comparability, a bioavailability correction for differences in water chemistry was performed with a biotic ligand model. This further decreased the variation, down to a factor of 7.4. Applying the population model in combination with a bioavailability correction thus significantly decreased the variability of chronic effect concentrations of Cu for L. stagnalis. Overall, the results of the present study illustrate the potential usefulness of transitioning to a more modeling-based environmental risk assessment. Environ Toxicol Chem 2019;00:1-16. © 2019 SETAC.

Aquatic exposures of chemical mixtures in urban environments: Approaches to impact assessment.

Urban regions of the world are expanding rapidly, placing additional stress on water resources. Urban water bodies serve many purposes, from washing and sources of drinking water to transport and conduits for storm drainage and effluent discharge. These water bodies receive chemical emissions arising from either single or multiple point sources, diffuse sources which can be continuous, intermittent, or seasonal. Thus, aquatic organisms in these water bodies are exposed to temporally and compositionally variable mixtures. We have delineated source-specific signatures of these mixtures for diffuse urban runoff and urban point source exposure scenarios to support risk assessment and management of these mixtures. The first step in a tiered approach to assessing chemical exposure has been developed based on the event mean concentration concept, with chemical concentrations in runoff defined by volumes of water leaving each surface and the chemical exposure mixture profiles for different urban scenarios. Although generalizations can be made about the chemical composition of urban sources and event mean exposure predictions for initial prioritization, such modeling needs to be complemented with biological monitoring data. It is highly unlikely that the current paradigm of routine regulatory chemical monitoring alone will provide a realistic appraisal of urban aquatic chemical mixture exposures. Future consideration is also needed of the role of nonchemical stressors in such highly modified urban water bodies. Environ Toxicol Chem 2018;37:703-714. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

A framework for ecological risk assessment of metal mixtures in aquatic systems.

Although metal mixture toxicity has been studied relatively intensely, there is no general consensus yet on how to incorporate metal mixture toxicity into aquatic risk assessment. We combined existing data on chronic metal mixture toxicity at the species level with species sensitivity distribution (SSD)-based in silico metal mixture risk predictions at the community level for mixtures of Ni, Zn, Cu, Cd, and Pb, to develop a tiered risk assessment scheme for metal mixtures in freshwater. Generally, independent action (IA) predicts chronic metal mixture toxicity at the species level most accurately, whereas concentration addition (CA) is the most conservative model. Mixture effects are noninteractive in 69% (IA) and 44% (CA) and antagonistic in 15% (IA) and 51% (CA) of the experiments, whereas synergisms are only observed in 15% (IA) and 5% (CA) of the experiments. At low effect sizes (∼ 10% mixture effect), CA overestimates metal mixture toxicity at the species level by 1.2-fold (i.e., the mixture interaction factor [MIF]; median). Species, metal presence, or number of metals does not significantly affect the MIF. To predict metal mixture risk at the community level, bioavailability-normalization procedures were combined with CA or IA using SSD techniques in 4 different methods, which were compared using environmental monitoring data of a European river basin (the Dommel, The Netherlands). We found that the simplest method, in which CA is directly applied to the SSD (CASSD ), is also the most conservative method. The CASSD has median margins of safety (MoS) of 1.1 and 1.2 respectively for binary mixtures compared with the theoretically more consistent methods of applying CA or IA to the dose-response curve of each species individually prior to estimating the fraction of affected species (CADRC or IADRC ). The MoS increases linearly with an increasing number of metals, up to 1.4 and 1.7 for quinary mixtures (median) compared with CADRC and IADRC , respectively. When our methods were applied to a geochemical baseline database (Forum of European Geological Surveys [FOREGS]), we found that CASSD yielded a considerable number of mixture risk predictions, even when metals were at background levels (8% of the water samples). In contrast, metal mixture risks predicted with the theoretically more consistent methods (e.g., IADRC ) were very limited under natural background metal concentrations (<1% of the water samples). Based on the combined evidence of chronic mixture toxicity predictions at the species level and evidence of in silico risk predictions at the community level, a tiered risk assessment scheme for evaluating metal mixture risks is presented, with CASSD functioning as a first, simple conservative tier. The more complex, but theoretically more consistent and most accurate method, IADRC , can be used in higher tier assessments. Alternatively, the conservatism of CASSD can be accounted for deterministically by incorporating the MoS and MIF in the scheme. Finally, specific guidance is also given related to specific issues, such as how to deal with nondetect data and complex mixtures that include so-called data-poor metals. Environ Toxicol Chem 2018;37:623-642. © 2017 SETAC.

Mixture toxicity in the marine environment: Model development and evidence for synergism at environmental concentrations.

Little is known about the effect of metal mixtures on marine organisms, especially after exposure to environmentally realistic concentrations. This information is, however, required to evaluate the need to include mixtures in future environmental risk assessment procedures. We assessed the effect of copper (Cu)-Nickel (Ni) binary mixtures on Mytilus edulis larval development using a full factorial design that included environmentally relevant metal concentrations and ratios. The reproducibility of the results was assessed by repeating this experiment 5 times. The observed mixture effects were compared with the effects predicted with the concentration addition model. Deviations from the concentration addition model were estimated using a Markov chain Monte-Carlo algorithm. This enabled the accurate estimation of the deviations and their uncertainty. The results demonstrated reproducibly that the type of interaction-synergism or antagonism-mainly depended on the Ni concentration. Antagonism was observed at high Ni concentrations, whereas synergism occurred at Ni concentrations as low as 4.9 µg Ni/L. This low (and realistic) Ni concentration was 1% of the median effective concentration (EC50) of Ni or 57% of the Ni predicted-no-effect concentration (PNEC) in the European Union environmental risk assessment. It is concluded that results from mixture studies should not be extrapolated to concentrations or ratios other than those investigated and that significant mixture interactions can occur at environmentally realistic concentrations. This should be accounted for in (marine) environmental risk assessment of metals. Environ Toxicol Chem 2017;36:3471-3479. © 2017 SETAC.

Systematic Evaluation of Chronic Metal-Mixture Toxicity to Three Species and Implications for Risk Assessment.

Metal contamination generally occurs as mixtures. However, it is yet unresolved how to address metal mixtures in risk assessment. Therefore, using consistent methodologies, we have set up experiments to identify which mixture model applies best at low-level effects, i.e., the independent action (IA) or concentration addition (CA) reference model. The toxicity of metal mixtures (Ni, Zn, Cu, Cd, and Pb) to Daphnia magna, Ceriodaphnia dubia, and Hordeum vulgare was investigated in different waters or soils, totaling 30 different experiments. Some mixtures of different metals, each individually causing <10% inhibition, yielded much larger inhibition (up to 66%) when dosed in combination. In general, IA was most accurate in predicting mixture toxicity, while CA was the most conservative. At low-effect levels important in risk assessments, CA overestimated mixture toxicity to daphnids and H. vulgare, on average, with a factor 1.4 to 3.6. Observed mixture interactions could be related to bioavailability or by competition interactions, either for binding sites of dissolved organic carbon or for biotic ligand sites. Our study suggests that the current metal-by-metal approach in risk evaluations may not be conservative enough for metal mixtures.

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., CASSD ). 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., CADRC ). 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 CASSD ): CASSD > CADRC (MoS = 1.17-1.25) > IADRC (independent action (IA) applied to individual dose-response curves; MoS = 1.38-1.60) > IASSD (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 CASSD 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 [SumTUHC5 ] < 1) and the IASSD method to identify situations of potential risk, also regardless of the method used (the multisubstance potentially affected fraction of species using the IASSD method [msPAFIA,SSD ] > 0.05). The CADRC and IADRC methods could be used for site-specific assessment for situations that fall in between (SumTUHC5 > 1 and msPAFIA,SSD < 0.05). Environ Toxicol Chem 2017;36:2123-2138. © 2017 SETAC.

A microcosm study to support aquatic risk assessment of nickel: Community-level effects and comparison with bioavailability-normalized species sensitivity distributions.

The aquatic risk assessment for nickel (Ni) in the European Union is based on chronic species sensitivity distributions and the use of bioavailability models. To test whether a bioavailability-based safe threshold of Ni (the hazardous concentration for 5% of species [HC5]) is protective for aquatic communities, microcosms were exposed to 5 stable Ni treatments (6-96 µg/L) and a control for 4 mo to assess bioaccumulation and effects on phytoplankton, periphyton, zooplankton, and snails. Concentrations of Ni in the periphyton, macrophytes, and snails measured at the end of the exposure period increased in a dose-dependent manner but did not indicate biomagnification. Abundance of phytoplankton and snails decreased in 48 µg Ni/L and 96 µg Ni/L treatments, which may have indirectly affected the abundance of zooplankton and periphyton. Exposure up to 24 µg Ni/L had no adverse effects on algae and zooplankton, whereas the rate of population decline of the snails at 24 µg Ni/L was significantly higher than in the controls. Therefore, the study-specific overall no-observed-adverse-effect concentration (NOAEC) is 12 µg Ni/L. This NOAEC is approximately twice the HC5 derived from a chronic species sensitivity distribution considering the specific water chemistry of the microcosm by means of bioavailability models. Thus, the present study provides support to the protectiveness of the bioavailability-normalized HC5 for freshwater communities.

An approach to assess the regulatory relevance of microevolutionary effects in ecological risk assessment of chemicals: a case study with cadmium.

The authors suggest an approach to assess the regulatory relevance of microevolutionary effects of chemicals based on a comparison of concentrations at which microevolutionary effects have been reported in the literature and conventionally derived ecotoxicological threshold concentrations. The authors found reports of microevolutionary effects of cadmium in freshwater organisms at hardness-normalized concentrations between 0.5 µg Cd L(-1) and 6290 µg Cd L(-1) (normalized to a hardness of 50 mg CaCO3 L(-1)). These concentrations were at least 1.5 times higher than the hardness-normalized hazardous concentration for 5% of the organisms of 0.34 µg Cd L(-1). This suggests that there is no immediate need to consider microevolutionary effects of Cd in environmental risk assessments of freshwater environments. However, some other aspects should be kept in mind as well. First, microevolutionary effects have so far only been investigated at few, relatively high concentrations of Cd and not encompassing the 5% hazardous concentration. Second, different types of microevolutionary effects or investigated ecotoxicological end points may influence the conclusions of the suggested comparative approach. Finally, factors influencing the bioavailability of Cd were not commonly reported in the literature, which made normalization of concentrations at which evolutionary effects occurred impossible and affected the number of studies that could be evaluated in the suggested approach.

Regulatory consideration of bioavailability for metals: simplification of input parameters for the chronic copper biotic ligand model.

The chronic Cu biotic ligand model (CuBLM) provides a means by which the bioavailability of Cu can be taken into account in assessing the potential chronic risks posed by Cu at specific freshwater locations. One of the barriers to the widespread regulatory application of the CuBLM is the perceived complexity of the approach when compared to the current systems that are in place in many regulatory organizations. The CuBLM requires 10 measured input parameters, although some of these have a relatively limited influence on the predicted no-effect concentration (PNEC) for Cu. Simplification of the input requirements of the CuBLM is proposed by estimating the concentrations of the major ions Mg2+, Na+, K+, SO4(2-), Cl- , and alkalinity from Ca concentrations. A series of relationships between log10 (Ca, mg l(-1)) and log10 (major ion, mg l(-1)) was established from surface water monitoring data for Europe, and applied in the prediction of Cu PNEC values for some UK freshwater monitoring data. The use of default values for major ion concentrations was also considered, and both approaches were compared to the use of measured major ion concentrations. Both the use of fixed default major ion concentrations, and major ion concentrations estimated from Ca concentrations, provided Cu PNEC predictions which were in good agreement with the results of calculations using measured data. There is a slight loss of accuracy when using estimates of major ion concentrations compared to using measured concentration data, although to a lesser extent than when fixed default values are applied. The simplifications proposed provide a practical evidence-based methodology to facilitate the regulatory implementation of the CuBLM.

Do we have to incorporate ecological interactions in the sensitivity assessment of ecosystems? An examination of a theoretical assumption underlying species sensitivity distribution models.

Species sensitivity distributions (SSDs) are statistical distributions which extrapolate single-species toxicity test results to ecosystem effects. This SSD approach assumes that ecological interactions between populations, such as grazing and competition, do not influence the sensitivity of ecosystems. The validity of this assumption in a simple freshwater pelagic ecosystem was tested using ecosystem modelling. For each of a 1000 hypothetical toxicants, a lognormal SSD was fitted to chronic single-species EC10s of the species present. As such, these distributions did not account for ecological interactions and were therefore termed 'conventional SSDs' (cSSDs). Next, sensitivity distributions that did take into account ecological interactions were constructed (eco-SSD) for the same 1000 toxicants, using an ecosystem model. For 254 of the 1000 hypothetical toxicants, mean and/or variance of the cSSD were significantly higher than mean and/or variance of the eco-SSD, as such rejecting the general validity of the tested assumption. A classification tree approach indicated that especially toxicants which directly affect phytoplankton (i.e. herbicides) may have a higher mean for cSSD than for eco-SSD. Conversely, means of eco-SSD and cSSD tend to be equal for toxicants directly affecting zooplankton and fish, e.g. insecticides. For the 254 hypothetical toxicants for which the tested assumption was false, a predicted no effect concentration (PNEC) calculated as the lowest single-species EC10 divided by an application factor of 10 was on average a factor 10 lower than the corresponding ecosystem-NOEC calculated by the ecosystem model.

Chronic toxicity of copper to five benthic invertebrates in laboratory-formulated sediment: sensitivity comparison and preliminary risk assessment.

Five benthic organisms commonly used for sediment toxicity testing were chronically (28 to 35 days) exposed to copper in standard laboratory-formulated sediment (following Organization for Economic Cooperation and Development guidelines) and lethal and sub-lethal toxicities were evaluated. Sub-lethal endpoints considered were reproduction and biomass production for Lumbriculus variegatus, growth and reproduction for Tubifex tubifex, growth and emergence for Chironomus riparius, and growth for Gammarus pulex and Hyalella azteca. Expressed on whole-sediment basis the observed lethal sensitivity ranking (from most to least sensitive) was: G. pulex>L. variegatus>H. azteca=C. riparius=T. tubifex, with median chronic lethal concentrations (LC50) between 151 and 327 mg/kg dry wt. The sub-lethal sensitivity ranking (from most to least sensitive, with the most sensitive endpoint between parentheses): C. riparius (emergence)>T. tubifex (reproduction)=L. variegatus (reproduction)>G. pulex (growth)>H. azteca (growth), with median effective concentrations (EC50) between 59.2 and 194 mg/kg dry wt. No observed effect concentrations (NOEC) or 10% effective concentrations (EC10) for the five benthic invertebrates were used to perform a preliminary risk assessment for copper in freshwater sediment by means of (a) the "assessment factor approach" or (b) the statistical extrapolation approach (species sensitivity distribution). Depending on the data (NOEC or EC10) and the methodology used, we calculated a Predicted No Effect Concentration (PNEC) for sediment between 3.3 and 47.1 mg Cu/dry wt. This range is similar to the range of natural (geochemical) background concentrations of copper in sediments in Europe, i.e. 90% of sediments have a concentration between 5 and 49 mg Cu/kg dry wt. A detailed analysis of the outcome of this preliminary exercise highlighted that multiple issues need to be explored for achieving a scientifically more sound risk assessment and for the development of robust sediment quality criteria for copper, including (i) the use of the assessment factor approach vs. the statistical extrapolation approach, (ii) the importance of bioavailability modifying factors (e.g., organic carbon, acid volatile sulfide), and (iii) the influence of prevailing geochemical (bioavailable) background concentrations on the copper sensitivity of local benthic biota.