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.

Effects of Microplastic on the Population Dynamics of a Marine Copepod: Insights from a Laboratory Experiment and a Mechanistic Model.

Microplastic is ubiquitously and persistently present in the marine environment, but knowledge of its population-level effects is limited. In the present study, to quantify the potential theoretical population effect of microplastic, a two-step approach was followed. First, the impact of microplastic (polyethylene, 0.995 g cm-3 , diameter 10-45 µm) on the filtration rate of the pelagic copepod Temora longicornis was investigated under laboratory conditions. It was found that the filtration rate decreased at increasing microplastic concentrations and followed a concentration-response relationship but that at microplastic concentrations <100 particles L-1 the filtration rate was not affected. From the concentration-response relationship between the microplastic concentrations and the individual filtration rate a median effect concentration of the individual filtration rate (48 h) of 1956 ± 311 particles L-1 was found. In a second step, the dynamics of a T. longicornis population were simulated for realistic environmental conditions, and the effects of microplastics on the population density equilibrium were assessed. The empirical filtration rate data were incorporated in an individual-based model implementation of the dynamic energy budget theory to deduct potential theoretical population-level effects. The yearly averaged concentration at which the population equilibrium density would decrease by 50% was 593 ± 376 particles L-1 . The theoretical effect concentrations at the population level were 4-fold lower than effect concentrations at the individual level. However, the theoretical effect concentrations at the population level remain 3-5 orders of magnitude higher than ambient microplastic concentrations. Because the present experiment was short-term laboratory-based and the results were only indirectly validated with field data, the in situ implications of microplastic pollution for the dynamics of zooplankton field populations remain to be further investigated. Environ Toxicol Chem 2022;41:1663-1674. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of 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 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 [SpH ] = 0.4449 and biotic ligand competition constants [log KCaBL = 4.0, log KMgBL = 3.4, and log KNaBL = 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.

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.