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

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.

Modeling Full Life-Cycle Effects of Copper on Brook Trout (Salvelinus fontinalis) Populations

Population models are increasingly used to predict population-level effects of chemicals. For trout, most toxicity data are available on early-life stages, but this may cause population models to miss true population-level effects. We predicted population-level effects of copper (Cu) on a brook trout (Salvelinus fontinalis) population based on individual-level effects observed in either a life-cycle study or an early-life stage study. We assessed the effect of Cu on predicted trout densities (both total and different age classes) and the importance of accounting for effects on the full life cycle compared with only early-life stage effects. Additionally, uncertainty about the death mechanism and growth effects was evaluated by comparing the effect of different implementation methods: individual tolerance (IT) versus stochastic death (SD) and continuous versus temporary growth effects. For the life-cycle study, the same population-level no-observed-effect concentration (NOECpop) was predicted as the lowest reported individual-level NOEC (NOECind; 9.5 µg/L) using IT. For SD, the NOECpop was predicted to be lower than the NOECind for young-of-the-year and 1-year-old trout (3.4 µg/L), but similar for older trout (9.5 µg/L). The implementation method for growth effects did not affect the NOECpop of the life-cycle study. Simulations based solely on the early-life stage effects within the life-cycle study predicted unbounded NOECpop values (≥32.5 µg/L), that is, >3.4 times higher than the NOECpop based on all life-cycle effects. For the early-life stage study, the NOECpop for both IT and SD were predicted to be >2.6 times higher than the lowest reported NOECind. Overall, we demonstrate that effects on trout populations can be underestimated if predictions are solely based on toxicity data with early-life stages. Environ Toxicol Chem 2024;43:1662-1676. © 2024 SETAC.

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.

Extrapolation of Metal Toxicity Data for the Rotifer Brachionus calyciflorus Using an Individual-Based Population Model

Ecological risk assessment (ERA) of metals typically starts from standardized toxicity tests, the data from which are then extrapolated to derive safe concentrations for the envisioned protection goals. Because such extrapolation in conventional ERA lacks ecological realism, ecological modeling is considered as a promising new approach for extrapolation. Many published population models are complex, that is, they include many processes and parameters, and thus require an extensive dataset to calibrate. In the present study, we investigated how individual-based models based on a reduced version of the Dynamic Energy Budget theory (DEBkiss IBM) could be applied for metal effects on the rotifer Brachionus calyciflorus. Data on survival over time and reproduction at different temperatures and food conditions were used to calibrate and evaluate the model for copper effects. While population growth and decline were well predicted, the underprediction of population density and the mismatch in the onset of copper effects were attributed to the simplicity of the approach. The DEBkiss IBM was applied to toxicity datasets for copper, nickel, and zinc. Predicted effect concentrations for these metals based on the maximum population growth rate were between 0.7 and 3 times higher in all but one case (10 times higher) than effect concentrations based on the toxicity data. The size of the difference depended on certain characteristics of the toxicity data: both the steepness of the concentration-effect curve and the relative sensitivity of lethal and sublethal effects played a role. Overall, the present study is an example of how a population model with reduced complexity can be useful for metal ERA. Environ Toxicol Chem 2024;43:324-337. © 2023 SETAC.

Mortality Pattern of Poecilus cupreus Beetles after Repeated Topical Exposure to Insecticide─Stochastic Death or Individual Tolerance?

The mortality of organisms exposed to toxicants has been attributed to either stochastic processes or individual tolerance (IT), leading to the stochastic death (SD) and IT models. While the IT model follows the principles of natural selection, the relevance of the SD model has been debated. To clarify why the idea of stochastic mortality has found its way into ecotoxicology, we investigated the mortality of Poecilus cupreus (Linnaeus, 1758) beetles from pesticide-treated oilseed rape (OSR) fields and unsprayed meadows, subjected to repeated insecticide treatments. We analyzed the mortality with the Kaplan-Meier estimator and general unified threshold model for survival (GUTS), which integrates SD and IT assumptions. The beetles were exposed three times, ca. monthly, to the same dose of Proteus 110 OD insecticide containing thiacloprid and deltamethrin, commonly used in the OSR fields. Kaplan-Meier analysis showed that the mortality of beetles from meadows was much higher after the first treatment than after the next two, indicating the IT model. Beetles from the OSR displayed approximately constant mortality after the first and second treatments, consistent with the SD model. GUTS analysis did not conclusively identify the better model, with the IT being marginally better for beetles from meadows and the SD better for beetles from OSR fields.

A Toxicokinetic-Toxicodynamic Modeling Workflow Assessing the Quality of Input Mortality Data

Toxicokinetic-toxicodynamic (TKTD) models simulate organismal uptake and elimination of a substance (TK) and its effects on the organism (TD). The Reduced General Unified Threshold model of Survival (GUTS-RED) is a TKTD modeling framework that is well established for aquatic risk assessment to simulate effects on survival. The TKTD models are applied in three steps: parameterization based on experimental data (calibration), comparing predictions with independent data (validation), and prediction of endpoints under environmental scenarios. Despite a clear understanding of the sensitivity of GUTS-RED predictions to the model parameters, the influence of the input data on the quality of GUTS-RED calibration and validation has not been systematically explored. We analyzed the performance of GUTS-RED calibration and validation based on a unique, comprehensive data set, covering different types of substances, exposure patterns, and aquatic animal species taxa that are regularly used for risk assessment of plant protection products. We developed a software code to automatically calibrate and validate GUTS-RED against survival measurements from 59 toxicity tests and to calculate selected model evaluation metrics. To assess whether specific survival data sets were better suited for calibration or validation, we applied a design in which all possible combinations of studies for the same species-substance combination are used for calibration and validation. We found that uncertainty of calibrated parameters was lower when the full range of effects (i.e., from high survival to high mortality) was covered by input data. Increasing the number of toxicity studies used for calibration further decreased parameter uncertainty. Including data from both acute and chronic studies as well as studies under pulsed and constant exposure in model calibrations improved model predictions on different types of validation data. Using our results, we derived a workflow, including recommendations for the sequence of modeling steps from the selection of input data to a final judgment on the suitability of GUTS-RED for the data set. Environ Toxicol Chem 2024;43:197-210. © 2023 Bayer AG and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Daphnia's phototaxis as an indicator in ecotoxicological studies: A review

Animal-based sensors have been increasingly applied to many water monitoring systems and ecological studies. One of the staple organisms used as living sensors for such systems is Daphnia. This organism has been extensively studied and, with time, used in many toxicological and pharmaceutical bioassays, often used for exploring the ecology of freshwater communities. One of its behaviours used for evaluating the state of the aquatic environment is phototaxis. A disruption in the predicted behaviour is interpreted as a sign of stress and forms the basis for further investigation. However, phototaxis is a result of complex processes counteracting and interacting with each other. Predator presence, food quality, body pigmentation and other factors can greatly affect the predicted phototactic response, hampering its reliability as a bioindicator. Therefore, a holistic approach and meticulous documentation of the methods are needed for the correct interpretation of this behavioural indicator. In this review, we present the current methods used for studying phototaxis, the factors affecting it and proposed ways to optimise the reliability of the results.

Impact of the antidepressant Bupropion on the Dynamic Energy Budget of Daphnia magna

Psychiatric drugs are considered among the emerging contaminants of concern in ecological risk assessment, due to their potential to disrupt homeostasis in aquatic organisms. Bupropion is an antidepressant that acts by selective reuptake inhibition of norepinephrine and dopamine. Little is known about this compound's effects on aquatic organisms, despite being detected in significant concentrations in both water and biota close to waste-water treatment plants and densely populated areas. Dynamic Energy Budget (DEB) models are flexible mechanistic tools that can be applied to understand toxic effects and extrapolate individual responses to higher biological levels and under untested environmental conditions. In this work, we used the stdDEB-TKTD (an application of the DEB theory to ecotoxicology) approach to investigate the possible physiological mode of action of Bupropion on the model organism Daphnia magna. Next, Dynamic Energy Budget Individual-Based Models (DEB-IBM) were used to extrapolate the results to the population level and to predict the combined effects of Bupropion exposure and food availability on the daphnids. Our results revealed an increasing negative effect of this antidepressant on the reproduction and survival of the animals with increasing concentration (0.004, 0.058, 0.58 and 58 μM). At the population level, we found that even the lowest used doses of Bupropion could reduce the population density and its reproductive output. The impacts are predicted to be stronger under limited food conditions.

Sublethal effects of binary mixtures of Cu2+ and Cd2+ on Daphnia magna: Standard Dynamic Energy Budget (DEB) model analysis

Dynamic Energy Budget theory (DEB) describes mass and energy fluxes that occur in living organisms. DEB models were successfully used to assess the influence of stress, including toxic substances, and changes in pH and temperature, on different organisms. In this study, the Standard DEB model was used to evaluate the toxicity of copper and cadmium ions and their binary mixtures on Daphnia magna. Both metal ions have a significant influence on daphnia growth and reproduction. Different physiological modes of action (pMoA) were applied to primary DEB model parameters. Model predictions for chosen modes of interaction of mixture components were evaluated. The goodness of model fit and the model prediction was assessed to indicate the most likely pMoA and interaction mode. Copper and cadmium influence more than one DEB model primary parameter. Different pMoAs can result in similar model fits, and therefore it is difficult to identify pMoA only by evaluation of the goodness of fit of the model to the growth and reproduction data. Some critical discussion and ideas for model development are therefore provided.

Co-contaminants of ethinylestradiol and sulfamethoxazole in groundwater exacerbate ecotoxicity and ecological risk and compromise the energy budget of C. elegans

Ethinylestradiol (EE2) and sulfamethoxazole (SMX) are among pharmaceuticals and personal care products (PPCPs) and regarded as emerging contaminants in groundwater worldwide. However, the ecotoxicity and potential risk of these co-contaminants remain unknown. We investigated the effects of early-life long-term co-exposure to EE2 and SMX in groundwater on life-history traits of Caenorhabditis elegans and determined potential ecological risks in groundwater. L1 larvae of wild-type N2 C. elegans were exposed to measured concentrations of EE2 (0.001, 0.75, 5.1, 11.8 mg/L) or SMX (0.001, 1, 10, 100 mg/L) or co-exposed to EE2 (0.75 mg/L, no observed adverse effect level derived from its reproductive toxicity) and SMX (0.001, 1, 10, 100 mg/L) in groundwater. Growth and reproduction were monitored on days 0 - 6 of the exposure period. Toxicological data were analyzed using DEBtox modeling to determine the physiological modes of action (pMoAs) and the predicted no-effect concentrations (PNECs) to estimate ecological risks posed by EE2 and SMX in global groundwater. Early-life EE2 exposure significantly inhibited the growth and reproduction of C. elegans, with lowest observed adverse effect levels (LOAELs) of 11.8 and 5.1 mg/L, respectively. SMX exposure impaired the reproductive capacity of C. elegans (LOAEL = 0.001 mg/L). Co-exposure to EE2 and SMX exacerbated ecotoxicity (LOAELs of 1 mg/L SMX for growth, and 0.001 mg/L SMX for reproduction). DEBtox modeling showed that the pMoAs were increased growth and reproduction costs for EE2 and increased reproduction costs for SMX. The derived PNEC falls within the range of detected environmental levels of EE2 and SMX in groundwater worldwide. The pMoAs for EE2 and SMX combined were increased growth and reproduction costs, resulting in lower energy threshold values than single exposure. Based on global groundwater contamination data and energy threshold values, we calculated risk quotients for EE2 (0.1 - 123.0), SMX (0.2 - 91.3), and combination of EE2 and SMX (0.4 - 341.1). Our findings found that co-contamination by EE2 and SMX exacerbates toxicity and ecological risk to non-target organisms, suggesting that the ecotoxicity and ecological risk of co-contaminants of pharmaceuticals should be considered to sustainably manage groundwater and aquatic ecosystems.

Modelling the effects of the pyrethroid insecticide cypermethrin on the life cycle of the soil dwelling annelid Enchytraeus crypticus, an original experimental design to calibrate a DEB-TKTD model

The Dynamic Energy Budget theory (DEB) enables ecotoxicologists to model the effects of chemical stressors on organism life cycles through the coupling of toxicokinetic-toxicodynamic (TK-TD) models. While good progress has been made in the application of DEB-TKTD models for aquatic organisms, applications for soil fauna are scarce, due to the lack of dedicated experimental designs suitable for collecting the required time series effect data. Enchytraeids (Annelida: Clitellata) are model organisms in soil ecology and ecotoxicology. They are recognised as indicators of biological activity in soil, and chemical stress in terrestrial ecosystems. Despite this, the application of DEB-TKTD models to investigate the impact of chemicals has not yet been tested on this family. Here we assessed the impact of the pyrethroid insecticide cypermethrin on the life cycle of Enchytraeus crypticus. We developed an original experimental design to collect the data required for the calibration of a DEB-TKTD model for this species. E. crypticus presented a slow initial growth phase that has been successfully simulated with the addition of a size-dependent food limitation for juveniles in the DEB model. The DEB-TKTD model simulations successfully agreed with the data for all endpoints and treatments over time. The highlighted physiological mode of action (pMoA) for cypermethrin was an increase of the growth energy cost. The threshold for effects on survival was estimated at 73.14 mg kg^- 1, and the threshold for effects on energy budget (i.e., sublethal effects) at 19.21 mg kg^- 1. This study demonstrates that DEB-TKTD models can be successfully applied to E. crypticus as a representative soil species, and may improve the ecological risk assessment for terrestrial ecosystems, and our mechanistic understanding of chemical effects on non-target species.

Adverse Outcome Pathways for Chronic Copper Toxicity to Fish and Amphibians

In the present review, we synthesize information on the mechanisms of chronic copper (Cu) toxicity using an adverse outcome pathway framework and identify three primary pathways for chronic Cu toxicity: disruption of sodium homeostasis, effects on bioenergetics, and oxidative stress. Unlike acute Cu toxicity, disruption of sodium homeostasis is not a driving mechanism of chronic toxicity, but compensatory responses in this pathway contribute to effects on organism bioenergetics. Effects on bioenergetics clearly contribute to chronic Cu toxicity with impacts at multiple lower levels of biological organization. However, quantitatively translating these impacts into effects on apical endpoints such as growth, amphibian metamorphosis, and reproduction remains elusive and requires further study. Copper-induced oxidative stress occurs in most tissues of aquatic vertebrates and is clearly a significant driver of chronic Cu toxicity. Although antioxidant responses and capacities differ among tissues, there is no clear indication that specific tissues are more sensitive than others to oxidative stress. Oxidative stress leads to increased apoptosis and cellular damage in multiple tissues, including some that contribute to bioenergetic effects. This also includes oxidative damage to tissues involved in neuroendocrine axes and this damage likely alters the normal function of these tissues. Importantly, Cu-induced changes in hormone concentrations and gene expression in endocrine-mediated pathways such as reproductive steroidogenesis and amphibian metamorphosis are likely the result of oxidative stress-induced tissue damage and not endocrine disruption. Overall, we conclude that oxidative stress is likely the primary driver of chronic Cu toxicity in aquatic vertebrates, with bioenergetic effects and compensatory response to disruption of sodium homeostasis contributing to some degree to observed effects on apical endpoints. Environ Toxicol Chem 2022;41:2911-2927. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Extrapolating Contaminant Effects from Individuals to Populations: A Case Study on Nanoparticle Toxicity to Daphnia Fed Environmentally Relevant Food Levels

Ecological risk assessment (ERA) is charged with assessing the likelihood a chemical will have adverse environmental or ecological effects. When assessing the risk of a potential contaminant to biological organisms, ecologists are most concerned with the sustainability of populations of organisms, rather than protecting every individual. However, ERA most commonly relies on data on the effect of a potential contaminant on individuals because these experiments are more feasible than costly population-level exposures. In this work, we address the challenge of extrapolating these individual-level results to predict population-level effects. Previous per-capita population growth rate estimates calculated from individual-level exposures of Daphnia pulicaria to silver nanoparticles (AgNPs) at different food rations predict a critical daily food requirement for daphnid populations exposed to 200 μg/L AgNPs to avoid extinction. To test this, we exposed daphnid populations to the same AgNP concentration at three different food inputs, with the lowest ration close to the extinction threshold predicted from data on individuals. The two populations with the higher food inputs persisted, and the population with the lowest food input went extinct after 50 days but did persist through two generations. We demonstrate that we can extrapolate between these levels of biological organization by parameterizing an individual-level biomass model with data on individuals' response to AgNPs and using these parameters to predict the outcome for control and AgNP-exposed populations. Key to successful extrapolation is careful modeling of temporal changes in resource density, driven by both the experimental protocols and feedback from the consumer. The implication for ecotoxicology is that estimates of extinction thresholds based on studies of individuals may be reliable predictors of population outcomes, but only with careful treatment of resource dynamics.

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.

Impact of heavy metal exposure on biological control of a deadly amphibian pathogen by zooplankton

Despite devastating effects on global biodiversity, efficient mitigation strategies against amphibian chytridiomycosis are lacking. Since the free-living pathogenic zoospores of Batrachochytrium dendrobatidis (Bd), the infective stage of this disease, can serve as a nutritious food source for components of zooplankton communities, these groups may act as biological control agents by eliminating zoospores from the aquatic environment. Such pathogen-predator interaction is, however, embedded in the aquatic food web structure and is therefore affected by abiotic factors interfering with these networks. Heavy metals, released from both natural and anthropogenic sources, are widespread contaminants of aquatic ecosystems and may interfere with planktonic communities and thus pathogen elimination rates. We investigated the interaction between zooplankton communities and chytridiomycosis infections in a Flemish agricultural region. Moreover, we also investigated the impact of heavy metal contamination, that was previously investigated in the region and presented in recent work, on zooplankton assemblages and chytridiomycosis infections. Finally, we tested the effect of sublethal concentrations of copper and zinc on Bd removal rates by Daphnia magna in a laboratory assay. Although zinc, copper, nickel and chromium were widely abundant pollutants, heavy metals were no driving force for zooplankton assemblages at our study locations. Moreover, our field survey did not reveal indirect effects of zooplankton assemblages on chytridiomycosis infections. However, sampling occasions testing negative for Bd showed a higher degree of copper contamination compared to positive sampling occasions, indicating a potential inhibitory effect of copper on Bd prevalence. Finally, whereas D. magna significantly reduced zoospore densities in its environment, sublethal concentrations of copper and zinc showed no interference with pathogen removal in the laboratory assay. Our results provide perspectives for further research on such a biological control strategy against chytridiomycosis by optimizing environmental conditions for pathogen predation.

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.

Integrating Bioavailability of Metals in Fish Population Models

Population models are increasingly being used to extrapolate individual-level effects of chemicals, including metals, to population-level effects. For metals, it is also important to take into account their bioavailability to correctly predict metal toxicity in natural waters. However, to our knowledge, no models exist that integrate metal bioavailability into population modeling. Therefore, our main aims were to 1) incorporate the bioavailability of copper (Cu) and zinc (Zn) into an individual-based model (IBM) of rainbow trout (Oncorhynchus mykiss), and 2) predict how survival-time concentration data translate to population-level effects. For each test water, reduced versions of the general unified threshold model of survival (GUTS-RED) were calibrated using the complete survival-time concentration data. The GUTS-RED individual tolerance (IT) showed the best fit in the different test waters. Little variation between the different test waters was found for 2 GUTS-RED-IT parameters. The GUTS-RED-IT parameter "median of distribution of thresholds" (m_w ) showed a strong positive relation with the Ca²⁺ , Mg²⁺ , Na⁺ , and H⁺ ion activities. Therefore, m_w formed the base of the calibrated GUTS bioavailability model (GUTS-BLM), which predicted 30-d x% lethal concentration (LCx) values within a 2-fold error. The GUTS-BLM was combined with an IBM, inSTREAM-Gen, into a GUTS-BLM-IBM. Assuming that juvenile survival was the only effect of Cu and Zn exposure, population-level effect concentrations were predicted to be 1.3 to 6.2 times higher than 30-d laboratory LCx values, with the larger differences being associated with higher interindividual variation of metal sensitivity. The proposed GUTS-BLM-IBM model can provide insight into metal bioavailability and effects at the population level and could be further improved by incorporating sublethal effects of Cu and Zn. Environ Toxicol Chem 2021;40:2764-2780. © 2021 SETAC.