Population Modeling in Metal Risk Assessment: Extrapolation of Toxicity Tests to the Population Level.

Population models can be a useful tool for ecological risk assessment to increase ecological realism. In the present study, population models were used to extrapolate toxicity test results of four metals (Ag, Cu, Ni, Zn) to the population level. In total, three primary producers, five invertebrate species, and five fish species were covered. The ecological modeling-based laboratory to population effect extrapolation factor (ECOPEX factor), defined as the ratio of the predicted 10% effect concentration (EC10) at the population level and the observed EC10 for the laboratory toxicity test, ranged from 0.7 to 78.6, with a median of 2.8 (n = 27). Population modeling indicated clearly higher effect concentrations in most of the cases (ECOPEX factor >2 in 14 out of 27 cases), but in some cases the opposite was observed (in three out of 27 cases). We identified five main contributors to the variability in ECOPEX factors: (1) uncertainty about the toxicity model, (2) uncertainty about the toxicity mechanism of the metal, (3) uncertainty caused by test design, (4) impact of environmental factors, and (5) impact of population endpoint chosen. Part of the uncertainty results from a lack of proper calibration data. Nonetheless, extrapolation with population models typically reduced the variability in EC10 values between tests. To explore the applicability of population models in a regulatory context, we included population extrapolations in a species sensitivity distribution for Cu, which increased the hazardous concentration for 5% of species by a factor 1.5 to 2. Furthermore, we applied a fish population model in a hypothetical Water Framework Directive case using monitored Zn concentrations. This article includes recommendations for further use of population models in (metal) risk assessment. Environ Toxicol Chem 2024;43:2308-2328. © 2024 SETAC.

Viaene KPJ ，Vlaeminck K ，Hansul S ，Janssen S ，Weighman K ，Van Sprang P ，De Schamphelaere KAC ... -  《-》

Sensitivity of a Large and Representative Sample of Antarctic Marine Invertebrates to Metals.

There are limited data on the sensitivity to contaminants of marine organisms in polar regions. Consequently, assessments of the risk of contaminants to marine biota in polar environments typically include extrapolations from temperate and/or tropical species. This is problematic because the taxonomic composition of organisms differs between polar and temperate/tropical waters, and both the toxicity of chemicals and the physiology of organisms are very different at the stable low temperatures experienced in polar marine systems. Collecting high-quality sensitivity data for a wide range of marine polar organisms using traditional toxicity assessment approaches is a time-consuming and difficult process, especially in remote and hostile environments. We applied a rapid toxicity testing approach, which allowed a much larger number of species to be tested than would be possible with traditional toxicity test methods, albeit with lower replications and fewer exposure concentrations. With this rapid approach, sensitivity estimates are less precise, but more numerous. This is important when constructing species sensitivity distributions (SSDs), which aim to represent the sensitivity of communities. We determined the approximate sensitivity (4- and 10-d median lethal concentration [LC50] values) of a large and representative sample of Antarctic marine invertebrates to copper (Cu), zinc (Zn), and cadmium (Cd). Up to 88 LC50 values (from 88 different taxa) were used in the construction of SSDs. The hazardous concentrations for 1% of taxa (HC1) based on 10-d LC50 values were 37, 346, and 792 μg/L for Cu, Zn, and Cd, respectively. Our results provide a basis for estimating the risk of exposure to metals for a large representative sample of marine polar invertebrates. Environ Toxicol Chem 2019;38:1560-1568. © 2019 SETAC.

Kefford BJ ，King CK ，Wasley J ，Riddle MJ ，Nugegoda D ... -  《-》

Extrapolating Metal (Cu, Ni, Zn) Toxicity from Individuals to Populations Across Daphnia Species Using Mechanistic Models: The Roles of Uncertainty Propagation and Combined Physiological Modes of Action.

Mechanistic effect modeling is a promising tool to improve the ecological realism of environmental risk assessment. An open question for the mechanistic modeling of metal toxicity is whether the same physiological mode of action (PMoA) could be assumed for closely related species. The implications of various modeling choices, such as the use of parameter point estimates and assumption of simplistic toxicodynamic models, are largely unexplored. We conducted life-table experiments with Daphnia longispina, Daphnia magna, and Daphnia pulex exposed to the single metals Cu, Ni, and Zn, and calibrated toxicokinetic-toxicodynamic (TKTD) models based on dynamic energy budget theory. We developed TKTD models with single and combined PMoAs to compare their goodness-of-fit and predicted population-level sensitivity. We identified the PMoA reproduction efficiency as most probable in all species for Ni and Zn, but not for Cu, and found that combined-PMoA models predicted higher population-level sensitivity than single-PMoA models, which was related to the predicted individual-level sensitivity, rather than to mechanistic differences between models. Using point estimates of parameters, instead of sampling from the probability distributions of parameters, could also lead to differences in the predicted population-level sensitivity. According to model predictions, apical chronic endpoints (cumulative reproduction, survival) are conservative for single-metal population effects across metals and species. We conclude that the assumption of an identical PMoA for different species of Daphnia could be justified for Ni and Zn, but not for Cu. Single-PMoA models are more appropriate than combined-PMoA models from a model selection perspective, but propagation of the associated uncertainty should be considered. More accurate predictions of effects at low concentrations may nevertheless motivate the use of combined-PMoA models. Environ Toxicol Chem 2024;43:338-358. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Hansul S ，Fettweis A ，Smolders E ，Schamphelaere K ... -  《-》

Characterizing toxicity of metal-contaminated sediments from the Upper Columbia River, Washington, USA, to benthic invertebrates.

Sediments from the Upper Columbia River, Washington, USA, are contaminated with metals from smelting operations. We conducted short-term and long-term tests with the midge Chironomus dilutus and the amphipod Hyalella azteca and short-term tests with the freshwater mussel Lampsilis siliquoidea with 54 sediments from the Upper Columbia River to characterize thresholds for toxicity of metals to benthic invertebrates. Test sediments were screened for toxicity by comparisons with low-metal reference sediments. Toxic effects on amphipods occurred primarily in sediments from the upstream (riverine) reach, and toxic effects on midges occurred in sediments from both the upstream reach and the downstream (reservoir) reach. Little toxicity was observed in mussel tests. Toxicity thresholds (20% effect concentrations [EC20s]) for metals in sediment and porewater were estimated from logistic concentration-response models. Copper (Cu) concentrations in the simultaneously extracted metal fraction of sediments and bioavailable Cu in porewater, as characterized by biotic ligand models, had consistent associations with toxicity endpoints. Concentration-response models for sediment Cu produced EC20s for 6 endpoints, with long-term amphipod survival and reproduction being the most sensitive. A logistic regression model fitted to an endpoint sensitivity distribution for sediment Cu predicted that approximately one-half of the sediments tested would be toxic to at least one endpoint and that approximately 20% of test sediments would be toxic to more than half of the endpoints. These results indicate that sediments from the upstream reach of the Upper Columbia River, which contain high concentrations of metals associated with slags, cause a wide range of toxic effects in laboratory tests and are likely to have adverse effects on benthic invertebrate communities. Environ Toxicol Chem 2018;37:3102-3114. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

Besser JM ，Steevens J ，Kunz JL ，Brumbaugh WG ，Ingersoll CG ，Cox S ，Mebane C ，Balistrieri L ，Sinclair J ，MacDonald D ... -  《-》

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.

Vlaeminck K ，Viaene KPJ ，Van Sprang P ，Baken S ，De Schamphelaere KAC ... -  《-》