Modelling survival: exposure pattern, species sensitivity and uncertainty

Comparative temporal response of toxicity for the neonicotinoid clothianidin and organophosphate dimethoate insecticides in two species of solitary bee (Osmia bicornis and Osmia cornuta)

Solitary bees provide essential pollination services. Concerns for the decline of these wild bee species have led to calls for their inclusion in pesticide risk assessment. Solitary bees differ from honey bees in their physiology and ecology and this may affect how they respond to pesticide exposure. Here we investigate the life-time toxicity of two insecticides, the organophosphate dimethoate and neonicotinoid clothianidin, for two mason bee species, Osmia bicornis and O. cornuta using a toxicokinetic/toxicodynamic stochastic death model taken from Dynamic Energy Budget (DEBtox) theory. Both species showed concentration and exposure duration dependent effects for each chemical. LC50 values estimated from the model parameters at 48 h were ≥ 14 fold and 6 fold those at 480 h for dimethoate and clothianidin respectively. Survival modelling indicated greater sensitivity in O. bicornis than for O. cornuta to dimethoate, whilst for clothianidin, O. cornuta females but not males, were more sensitive than both sexes of O. bicornis. These sensitivity differences were not related to body size. Toxicokinetic and toxicodynamic traits derived from modelling indicated lower elimination rates in O. bicornis and higher killing rates for O. cornuta females for dimethoate and lower elimination rates for clothianidin in O. cornuta females that were related to sensitivity. This study shows the near life-time testing is possible for solitary bees and that combining adult life-time toxicity tests with toxicokinetic/toxicodynamic modelling provides a more mechanistic understanding of pesticide effects in solitary bee species.

Comparison of visual assessment and quantitative goodness-of-fit metrics on GUTS model fits

For the application of toxicokinetic-toxicodynamic (TKTD) models in the European environmental risk assessment (ERA) of plant protection products, it is recommended to evaluate model predictions of the calibration as well as the independent validation data set based on qualitative criteria (visual assessment) and quantitative goodness-of-fit (GoF) metrics. The aims of this study were to identify whether quantitative criteria coincide with human visual perception of model performance and which evaluator characteristics influence their perception. In an anonymous online survey, > 70 calibration and validation general unified threshold models of survival (GUTS) fits were ranked by 64 volunteers with a professional interest in ecotoxicology and TKTD modeling. Participants were asked to score model fits to the time resolved survival data from toxicity experiments and to an aggregated dose-response curve representation. Dose-response curve plots tended to be scored better than time series, although both representations were based on the same toxicity test data and model results. For the time series, quantitative indices and visual assessments generally agreed on model performance. However, rankings varied with individual perceptions of the participants. Visual assessment scores were best predicted using a combination of GoF metrics. From the survey participants' majority agreement on fit acceptance, GoF cut-off criteria could be derived that indicated sufficient fit performance. The most conservative GoF criterion well resembled current suggestions by the European Food Safety Authority. Hence, the survey results provide evidence that current quantitative GUTS assessment practice in ERA is consistent with perceptions of fit quality based on visual judgements of the dynamic model behavior by a large number of practitioners. Thus, our study fosters trust in model performance assessment.

Integrating Time-Resolved nrf2 Gene-Expression Data into a Full GUTS Model as a Proxy for Toxicodynamic Damage in Zebrafish Embryo

The immense production of the chemical industry requires an improved predictive risk assessment that can handle constantly evolving challenges while reducing the dependency of risk assessment on animal testing. Integrating omics data into mechanistic models offers a promising solution by linking cellular processes triggered after chemical exposure with observed effects in the organism. With the emerging availability of time-resolved RNA data, the goal of integrating gene expression data into mechanistic models can be approached. We propose a biologically anchored TKTD model, which describes key processes that link the gene expression level of the stress regulator nrf2 to detoxification and lethality by associating toxicodynamic damage with nrf2 expression. Fitting such a model to complex data sets consisting of multiple endpoints required the combination of methods from molecular biology, mechanistic dynamic systems modeling, and Bayesian inference. In this study, we successfully integrate time-resolved gene expression data into TKTD models and thus provide a method for assessing the influence of molecular markers on survival. This novel method was used to test whether nrf2 can be applied to predict lethality in zebrafish embryos. With the presented approach, we outline a method to successfully approach the goal of a predictive risk assessment based on molecular data.

Bee sensitivity derived from acute contact tests biased by standardised protocols?

In an acute contact test with bees the compound of interest is dissolved in a carrier solvent (frequently acetone) and then a droplet of the solution is placed on the dorsal thorax of the bee. The volume of the droplet is standardised to 1 µL for honeybees and to 2 µL for bumblebees. In practice the same droplet volume is used for bees with very different sizes. In this research the effect of the droplet volume was evaluated with acute contact tests with dimethoate for the alfalfa leafcutter bee, the red mason bee, the honeybee and the bumblebee. The results were analysed with a ToxicoKinetic ToxicoDynamic (TKTD) model to separate kinetic from dynamic effects. This allows to compare the sensitivity of the bee based on the effect threshold and not on the time, species and test dependent LD50s. The analysis of the test results indicates that the magnitude of the response of the bees increased with increasing droplet size. The results also showed that the manifestation of effects over time is slower for the red mason bee and the bumblebee compared to the honeybee and the alfalfa leafcutter bee. This implies that the result of a 2 day test with a fixed dosing volume results in different response for a bumblebee compared to the alfalfa leafcutter bee, not because of different sensitivities of the bees involved but due to the difference of relative dosed surface ratio. So comparing the sensitivity of bee species, based on standardised tests is biased and amplifies the sensitivity for the smaller bee species.

Effects of α-olefin sulfonate (AOS) on Tubifex tubifex: toxicodynamic-toxicokinetic inferences from the general unified threshold (GUTS) model, biomarker responses and molecular docking predictions

We investigated the potential ecological risks and harm to aquatic organisms posed by anionic surfactants such as α-olefin sulfonate (AOS), which are commonly found in industrial and consumer products, including detergents. This study assessed acute (96-h) and subchronic (14-day) responses using antioxidant activity, protein levels, and histopathological changes in Tubifex tubifex exposed to different AOS concentrations (10% of the LC50, 20% of the LC50, and a control). Molecular docking was used to investigate the potential interactions between the key stress biomarker enzymes (superoxide dismutase, catalase, and cytochrome c oxidase) of Tubifex tubifex. Acute AOS exposure showed a concentration-dependent decrease in survival, and the general unified threshold (GUTS) model revealed that survivorship is linked to individual response patterns rather than random (stochastic) fluctuations. The GUTS model also revealed dose-dependent toxicity patterns in Tubifex tubifex exposed to α-olefin sulfonate (AOS), with adaptive mechanisms at lower concentrations but significant increases in mortality beyond a certain threshold, emphasizing the role of the AOS concentration in shaping its toxicological impact. Exposure to AOS disrupted antioxidant activity, inducing oxidative stress, with GST and GPx showing positive associations with surfactant concentration and increased lipid peroxidation (elevated MDA levels); moreover, AOS exposure decreased protein concentration, signifying disturbances in vital cellular processes. Histopathological examinations revealed various tissue-level alterations, including cellular vacuolation, cytoplasmic swelling, inflammation, necrosis, and apoptosis. Molecular docking analysis demonstrated interactions between AOS and enzymes (-catalase, superoxide dismutase, and cytochrome c oxidase) in Tubifex tubifex, including hydrophobic and hydrogen bond interactions, with the potential to disrupt enzyme structures and activities, leading to cellular process disruptions, oxidative stress, and tissue damage. According to the species sensitivity distribution (SSD), the difference in toxicity between Tilapia melanopleura (higher sensitivity) and Daphnia magna (low sensitivity) to AOS suggests distinct toxicokinetic and toxicodynamic mechanisms attributable to more complex physiology in Tilapia and efficient detoxification in Daphnia due to its smaller size.

Application of toxicokinetic-toxicodynamic models in the aquatic ecological risk assessment of metals: A review

The issue of toxic metal pollution is a considerable environmental concern owing to its complex nature, spatial and temporal variability, and susceptibility to environmental factors. Current water quality criteria and ecological risk assessments of metals are based on single-metal toxicity data from short-term, simplified indoor exposure conditions, ignoring the complexity of actual environmental conditions. This results in increased uncertainty in predicting toxic metal toxicity and risk assessment. Using appropriate bioavailability and effect modeling of metals is critical for establishing environmental quality standards and performing risk assessments for metals. Traditional dose-effect models are based on a static statistical relationship and fall short of revealing the bioavailability and effect processes of metals and do not effectively assess ecological impacts under complex exposure conditions. This paper summarizes the toxicokinetic-toxicodynamic (TK-TD) model, which is gaining interest in environmental and ecotoxicological research. The key concepts, and theories of its construction theories, are discussed and the application of the TK-TD model in toxicity prediction and risk assessment of different metals in the aquatic environment, and trends in the development of the TK-TD model are highlighted. The findings of our review prove that the TK-TD model can effectively predict toxic metal toxicity in real time and under complex exposure conditions in the future.

Pathological and ultrastructural changes of Bellamya bengalensis under chronic carboxylic acid exposure at environmentally relevant levels: Inferences from general unified threshold model for survival (GUTS) predictions and hepatopancreatic integrity assessment

This study aimed to understand the effects of freshwater acidification, driven by industrial runoff, agricultural activities, and atmospheric deposition, on the freshwater mollusk Bellamya bengalensis. By systematically investigating the impact of two common carboxylic acids, acetic acid (AA) and benzoic acid (BA), this research employed diverse toxicological, pathological, and ecological assessments. We explored survival predictions through the generic unified threshold model of survival (GUTS-SD), examined oxidative stress responses, and investigated hepatopancreatic alterations. In the experimental design, Bellamya bengalensis were subjected to environmentally relevant sublethal concentrations (10%, 20% LC50) of AA (39.77 and 79.54 mg/l) and BA (31.41 and 62.82 mg/l) over 28 days. Acute toxicity tests revealed increased LC50 values, indicating heightened toxicity with prolonged exposure, particularly due to the greater potency of benzoic acid compared to acetic acid. The GUTS-SD model provided accurate predictions of time-specific effects on populations, presenting long-term exposure (100 days) LC50 values for AA (263.7 mg/l) and BA (330.9 mg/l). Sequentially, the integrated biomarker response (IBR) analysis across study intervals highlighted the 28-day interval as the most sensitive, with GST emerging as the most responsive enzyme to oxidative stress induced by AA and BA. Histopathological and ultrastructural assessments of the hepatopancreas showed severe alterations, including necrosis, vacuolation and disrupted micro-villi, which were especially pronounced in higher BA exposure concentrations. These findings highlight the health and survival impacts of carboxylic acid toxicity on Bellamya bengalensis, emphasizing the need for proactive measures to mitigate acidification in aquatic ecosystems. The broader ecological implications underscore the importance of effective management and conservation strategies to address ongoing environmental challenges.

Identifying and Predicting Delayed Mortality with Toxicokinetic-Toxicodynamic Models

The prevalence of standardized toxicity testing in ecotoxicology has largely obscured the notion that toxicity is a function of time as well. The necessity of considering time is vividly demonstrated by observations of delayed mortality, that is, deaths continue to occur even when animals are no longer exposed to a toxicant. In this contribution, I explore to what extent toxicokinetic-toxicodynamic (TKTD) models from the framework of the General Unified Threshold model for Survival (GUTS) can capture delayed mortality, and to what extent this phenomenon can be predicted from short-term standard tests. I use a previously published data set for fluoroquinolones in Daphnia magna that shows strongly delayed mortality (using immobilization as a proxy for death). The model analysis shows that the GUTS stochastic death models can capture delayed mortality in the complete data set with a long recovery phase, but that the delayed effects would not have been predicted from a 2-day standard test. The study underlines the limited information content of standard acute test designs. Toxicokinetic-toxicodynamic modeling offers a handle on the time aspects of toxicity but cannot always be relied on to provide accurate extrapolations based on severely limited standard tests. The phenomenon of delayed toxicity requires more structured study to clarify its prevalence and impact; I discuss several avenues for further investigation. Environ Toxicol Chem 2024;43:1030-1035. © 2024 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.

Chemical Mixtures and Multiple Stressors: Same but Different?

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Three perspectives on the prediction of chemical effects in ecosystems

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

Modeling Time-Dependent Aquatic Toxicity of Hydrocarbons: Role of Organism Weight, Temperature, and Substance Hydrophobicity

Oil spill exposures are highly dynamic and are not comparable to laboratory exposures used in standard toxicity tests. Toxicokinetic-toxicodynamic (TKTD) models allow translation of effects observed in the laboratory to the field. To improve TKTD model calibration, new and previously published data from 148 tests were analyzed to estimate rates characterizing the time course of toxicity for 10 fish and 42 invertebrate species across 37 hydrocarbons. A key parameter in the TKTD model is the first-order rate that incorporates passive elimination, biotransformation, and damage repair processes. The results indicated that temperature (4-26 °C), organism size (0.0001-10 g), and substance log octanol-water partition coefficient (2-6) had limited influence on this parameter, which exhibited a 5th to 95th percentile range of 0.2-2.5 day-1 (median 0.7 day-1 ). A species sensitivity distribution approach is proposed to quantify the variability of this parameter across taxa, with further studies needed for aliphatic hydrocarbons and plant species. Study findings allow existing oil spill models to be refined to improve effect predictions. Environ Toxicol Chem 2022;41:3070-3083. © 2022 ExxonMobil Biomedical Science Inc. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

An annual profile of the impacts of simulated oil spills on the Northeast Arctic cod and haddock fisheries

We simulate the combined natural and pollutant-induced survival of early life stages of NEA cod and haddock, and the impact on the adult populations in response to the time of a major oil spill in a single year. Our simulations reveal how dynamic ocean processes, controlling both oil transport and fate and the frequency of interactions of oil with drifting fish eggs and larvae, mediate the magnitude of population losses due to an oil spill. The largest impacts on fish early life stages occurred for spills initiated in Feb-Mar, concomitant with the initial rise in marine productivity and the earliest phase of the spawning season. The reproductive health of the adult fish populations was maintained in all scenarios. The study demonstrates the application of a simulation system that provides managers with information for the planning of development activities and for the protection of fisheries resources from potential impacts.

Physiological Dependency Explains Temperature Differences in Sensitivity Towards Chemical Exposure

In chemical risk assessment, extrapolations from laboratory tests to more realistic conditions are essential to address the toxic effects of pesticides on individuals and populations under field conditions. To transfer toxicological laboratory tests to differing temperature conditions, or outdoor field scenarios, the consideration of temperature dependence is essential and increases realism. Special consideration is given to the impact of temperature on direct sensitivity of organisms to pesticides, for which there are only few modelling approaches available so far. We present a concept for applying physiological temperature dependencies to toxicokinetic-toxicodynamic (TKTD) parameters in the General Uniformed Threshold model of Survival (GUTS). To test this approach in an exemplary study, temperature dependencies from studies on the developmental rate of the mayfly Cloeon dipterum were applied to the parameters of a previously parameterised TKTD model of this species after exposure to imidacloprid. Using a physiologically derived temperature correction for the TKTD rate constants, model predictions for independently conducted toxicology experiments with temperature ranges between 7.8 and 26.4 °C were performed for validation. Our approach demonstrates the successful transfer of a physiological observed temperature dependency on toxicity parameters and survival patterns for Cloeon dipterum and imidacloprid as a case study.

BeeGUTS-A Toxicokinetic-Toxicodynamic Model for the Interpretation and Integration of Acute and Chronic Honey Bee Tests

Understanding the survival of honey bees after pesticide exposure is key for environmental risk assessment. Currently, effects on adult honey bees are assessed by Organisation for Economic Co-operation and Development standardized guidelines, such as the acute and chronic oral exposure and acute contact exposure tests. The three different tests are interpreted individually, without consideration that the same compound is investigated in the same species, which should allow for an integrative assessment. In the present study we developed, calibrated, and validated a toxicokinetic-toxicodynamic model with 17 existing data sets on acute and chronic effects for honey bees. The model is based on the generalized unified threshold model for survival (GUTS), which is able to integrate the different exposure regimes, taking into account the physiology of the honey bee: the BeeGUTS model. The model is able to accurately describe the effects over time for all three exposure routes combined within one consistent framework. The model can also be used as a validity check for toxicity values used in honey bee risk assessment and to conduct effect assessments for real-life exposure scenarios. This new integrative approach, moving from single-point estimates of toxicity and exposure to a holistic link between exposure and effect, will allow for a higher confidence of honey bee toxicity assessment in the future. Environ Toxicol Chem 2022;41:2193-2201. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Antioxidant enzyme activity and pathophysiological responses in the freshwater walking catfish, Clarias batrachus Linn under sub-chronic and chronic exposures to the neonicotinoid, Thiamethoxam®

The hydrophilic nature and resultant persistence of neonicotinoids in aquatic systems increase the exposure duration for non-target organisms. The sublethal toxicity of the neonicotinoid Thiamethoxam® spanning sub-chronic and chronic durations was investigated in Clarias batrachus, a non-target freshwater fish species. 96 h LC₅₀ value of Thiamethoxam® on Clarias batrachus was 138.60 mg L^-1. Pre-determined exposure concentrations of Thiamethoxam® (6.93 and 13.86 mg L^-1) were used and effects were assessed at days 15, 30, and 45 exposure intervals. Biomarker effects were evaluated using antioxidant enzyme responses (CAT, SOD) neurotransmission (acetylcholinesterase activity), haematological and serum biochemistry changes (including haemoglobin content, total erythrocyte count, and serum albumin total leukocyte count, total serum protein, serum globulin, triglyceride, cholesterol, high-density lipoprotein, very low-density lipoprotein, low-density lipoprotein, phospholipid, and total serum glucose), histopathological alterations (gill and liver). Thiamethoxam®-exposed fish showed a marked reduction in haemoglobin content, total erythrocyte count, and serum albumin levels compared to control fish. Similarly, gill and liver antioxidant enzyme activity (CAT, SOD) and neurotransmission (acetylcholinesterase) also showed altered responses between sub-chronic exposure on day-15 and chronic responses on day-45. Histopathological observations in gill tissue revealed alterations ranging from vacuolation, hypertrophy, disruption of primary lamellar architecture, haemorrhage, the fusion of secondary lamella, and sloughing of outer epithelia. For liver tissue of exposed fish histopathological observations included increased sinusoidal spaces (ISS), necrosis of hepatocytes (NOH), nuclear degeneration (ND), disruption of architecture (DOA), macrophage infiltration of the central vein, vacuolation (V), hypertrophied hepatocytes, and haemorrhages. The gradients of toxic responses across exposure concentrations and depictions of impaired fish health with increasing thiamethoxam® exposure duration portend lowered physiological capacity for survival in the wild.

Fish Species Sensitivity Ranking Depends on Pesticide Exposure Profiles

In the regulatory environmental risk assessment of plant protection products, the exposure tested in standard toxicity tests assumes simple exposure dynamics, such as constant exposure at the first stage of testing. However, environmental exposure can be highly dynamic. A species response to exposure is governed by toxicokinetics (TK) and toxicodynamics (TD). Therefore, it can be expected that the sensitivity of a species to a substance is dependent on the interplay of TKTD processes with the dynamics of the exposure. We investigated whether exposure dynamics affects species sensitivity of five fish species and if their sensitivity rankings differ among exposure profiles. We analyzed individual survival under projected surface water exposure to benzovindiflupyr. For this purpose, we calibrated compound- and species-specific reduced general unified threshold models of survival (GUTS-RED) models from standard laboratory toxicity data with the assumptions of stochastic death and individual tolerance. Using the calibrated models, we generated species sensitivity distributions based on median lethal profile multiplication factors for three characteristic exposure profiles. The analysis was performed using different GUTS-RED implementations: openGUTS (MATLAB® and Windows® versions) and the R package morse. The sensitivity rankings of the fish species changed as a function of exposure profile. For a multiple-peak scenario, rainbow trout was the most sensitive species. For a single peak followed by a slow concentration decline the most sensitive species was the fathead minnow (GUTS-RED-stochastic death) or the common carp (GUTS-RED-individual tolerance). Our results suggest that a single most sensitive species cannot be defined for all situations, all exposure profiles, and both GUTS-RED variants. Environ Toxicol Chem 2022;41:1732-1741. © 2022 Syngenta. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

TWAc-Check: A New Approach to Determine the Appropriate Use of Time-Weighted Average Concentration in Aquatic Risk Assessment

In pesticide risk assessment, regulatory acceptable concentrations for surface water bodies (RACsw,ch) are used that are derived from standard studies with continuous exposure of organisms to a test compound for days or months. These RACsw,ch are compared with the maximum tested concentration of more realistic exposure scenarios. However, the actual exposure duration could be notably shorter (e.g., hours) than the standard study, which intentionally leads to an overly conservative Tier 1 risk assessment. This discrepancy can be addressed in a risk assessment using the time-weighted average concentration (TWAc). In Europe, the applicability of TWAc for a particular risk assessment is evaluated using a complex decision scheme, which has been controversial; thus we propose an alternative approach: We used TWAc-check (which is based on the idea that the TWAc concept is just a model for aquatic risk assessment) to test whether the use of a TWAc is appropriate for such assessment. The TWAc-check method works by using predicted-measured diagrams to test how well the TWAc model predicts experimental data from peak exposure experiments. Overestimated effects are accepted because the conservatism of the TWAc model is prioritized over the goodness of fit. We illustrate the applicability of TWAc-check by applying it to various data sets for different species and substances. We demonstrate that the applicability is case dependent. Specifically, TWAc-check correctly identifies that the use of TWAc is not appropriate for early onset of effects or delayed effects. The proposed concept shows that the time window is a decisive factor as to whether or not the model is acceptable and that this concept can be used as a potential refinement option prior to the use of toxicokinetic-toxicodynamic models. Environ Toxicol Chem 2022;41:1778-1787. © 2022 Bayer AG. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The application and limitations of exposure multiplication factors in sublethal effect modelling

Thanks to growing interest and research in the field, toxicokinetic–toxicodynamic (TKTD) models are close to realising their potential in environmental risk assessment (ERA) of chemicals such as plant protection products. A fundamental application is to find a multiplicative scale factor which—when applied to an exposure profile—results in some specified effect relative to a control. The approach is similar to applying assessment factors to experimental results, common in regulatory frameworks. It also relies on the same core assumption: that increasing the scaling always produces more extreme effects. Unlike experimental approaches, TKTD models offer an opportunity to interrogate this assumption in a mathematically rigorous manner. For four well-known TKTD models we seek to prove that the approach guarantees a unique scale factor for any percentage effect. Somewhat surprisingly, certain model configurations may have multiple scale factors which result in the same percentage effect. These cases require a more cautious regulatory approach and generate open biological and mathematical questions. We provide examples of the violations and suggest how to deal with them. Mathematical proofs provide the strongest possible backing for TKTD modelling approaches in ERA, since the applicability of the models can be determined exactly.

Multi- and Trans-Generational Effects on Daphnia Magna of Chlorpyrifos Exposures

Chlorpyrifos, a broad-spectrum neurotoxic organophosphate insecticide, is subject to atmospheric and hydrolytic transport from application sites to aquatic ecosystems. Across the landscape, concentrations in surface water can vary spatially and temporally according to seasonal use practices. Standardized bioassays can provide a screening-level understanding of aquatic receptor acute and chronic toxicity. However, these bioassays do not address ecologically relevant exposure patterns that may impact fitness and survival within and across generations. The aim of the present study was to evaluate the utility of a second-tier, screening-level methodology employing Daphnia magna multi- and transgenerational bioassays spanning four generations to investigate the effect of variable chronic chlorpyrifos exposure. The multigenerational assay consisted of continuous chlorpyrifos exposure across four consecutive 21-day bioassays using progeny from the previous assay for each successive generation. In the transgenerational assay, only the parent (F0) generation was exposed. For both assays, survival and reproduction were assessed across treatments and generations. Results indicated that (1) following continuous chlorpyrifos exposure at ecologically relevant concentrations to four generations of D. magna, the highest treatment showed an apparent tolerance response for both survival and reproductive success in the F3 generation, and (2) chlorpyrifos exposure to the F0 generation did not result in treatment effects in the unexposed F1, F2, and F3 generations in the apical endpoints of survival and reproduction. Employing a suite of acute and chronic bioassays, including chronic exposures spanning multiple generations, allows for a more robust screening-level evaluation of the potential impact of chlorpyrifos on aquatic receptors for variable periods of exposure. Environ Toxicol Chem 2022;41:1054-1065. © 2021 SETAC.

Terrestrial organisms react differently to nano and non-nano Cu(OH)2 forms

The application of nanomaterials in agriculture is deemed as a promising strategy to increase the sector's sustainability. Nanopesticides are expected to improve solutions for pest/disease management, while reducing adverse effects to ecosystems, in accordance with the European Green Deal strategy. Hitherto, nanopesticide research has mostly focused on assessing effects to target species or crops, and less attention has been devoted to non-target soil species. In this study, we explored whether three copper hydroxide-based forms (nano and non-nano) show different toxicity and accumulation patterns in two terrestrial invertebrates, the isopod Porcellionides pruinosus and the mealworm larvae Tenebrio molitor. Toxicity and bioaccumulation experiments were performed and time-course toxicity and toxicokinetics analyzed and modelled. We found important differences in copper sensitivity and accumulation: T. molitor was more resistant and able to eliminate copper compared to P. pruinosus. The nanopesticide mostly elicited lower effects for both species. Slower toxicokinetics by the nanopesticide and lower bioaccumulative potential to P. pruinosus must be partially responsible for the differences in toxicity. Although no toxicokinetics differences were found in T. molitor between Cu forms, distinct negative effects on growth must reflect different energetic costs for copper regulation. Even though effects on toxicity and bioaccumulation are species-specific, copper hydroxide-based nanopesticides may cause less adverse effects to soil organisms than conventional products, being a good solution for reducing the environmental impact. CAPSULE: Copper hydroxide-based nanopesticide was less toxic and bioaccumulative to soil organisms than conventional copper hydroxide products, being a good solution for reducing the environmental impact.

Continuous high-frequency pesticide monitoring to observe the unexpected and the overlooked

Synthetic Plant Protection Products (PPPs) are a key element for a large part of today's global food systems. However, the transport of PPPs and their transformation products (TPs) to water bodies has serious negative effects on aquatic ecosystems. Small streams in agricultural catchments may experience pronounced concentration peaks given the proximity to fields and poor dilution capacity. Traditional sampling approaches often prevent a comprehensive understanding of PPPs and TPs concentration patterns being limited by trade-offs between temporal resolution and duration of the observation period. These limitations result in a knowledge gap for accurate ecotoxicological risk assessment and the achievement of optimal monitoring strategies for risk mitigation. We present here high-frequency PPPs and TPs concentration time-series measured with the autonomous MS²Field platform that combines continuous sampling and on-site measurements with a high-resolution mass spectrometer, which allows for overcoming temporal trade-offs. In a small agricultural catchment, we continuously measured 60 compounds at 20 minutes resolution for 41 days during the growing season. This observation period included 8 large and 15 small rain events and provided 2560 concentration values per compound. To identify similarities and differences among the compound-specific concentration time-series, we analysed the entire dataset with positive matrix factorisation. Six factors sufficiently captured the overall complexity in concentration dynamics. While one factor reflected dilution during rainfall, five factors identified PPPs groups that seemed to share a common history of recent applications. The investigation per event of the concentration time-series revealed a surprising complexity of dynamic patterns; physico-chemical properties of the compounds did not influence the (dis)similarity of chemographs. Some PPPs concentration peaks led while others lagged by several hours the water level peaks during large events. During small events, water level peaks always preceded concentration peaks, which were generally only observed when the water levels had almost receded to pre-event levels. Thus, monitoring schemes relying on rainfall or water level as proxies for triggering sampling may lead to systematic biases. The high temporal resolution revealed that the Swiss national monitoring integrating over 3.5 days underestimated critical concentration peaks by a factor of eight to more than 32, captured 3 out of 11 exceedances of legal acute quality standards (the relevant values in the Swiss Water Protection Law) and recorded 1 out of 9 exceedances of regulatory acceptable concentrations (the relevant values for the PPPs registration process). MS²Field allowed for observing unexpected and overlooked pesticide dynamics with consequences for further research but also for monitoring. The large variability in timing of concentration peaks relative to water level calls for more in-depth analyses regarding the respective transport mechanisms. To perform these analyses, spatially distributed sampling and time-series of geo-referenced PPPs application data are needed.

The toxicity and toxicokinetics of imidacloprid and a bioactive metabolite to two aquatic arthropod species

Previous studies have explored effects of imidacloprid and its metabolites on terrestrial species, such as bees, and indicated the importance of some active metabolites. However, the biotransformation of IMI and the toxicity of its metabolites to aquatic arthropods are largely unknown, especially the mechanisms driving species sensitivity differences and time-cumulative toxicity effects. To assess the potential effects of the metabolization of IMI and the toxicokinetics and toxicity of the metabolite(s) on aquatic arthropods, we first studied the acute toxicity of IMI and relevant metabolites to the mayfly species Cloen dipterum (sensitive to IMI) and the amphipod species Gammarus pulex (less sensitive to IMI). Secondly, toxicokinetic experiments were conducted using both the parent compound and imidacloprid-olefin (IMI-ole), a metabolite assessed as toxic in the acute tests and defined as bioactive. Of the four tested metabolites, only IMI-ole was readily biotransformed from the parent IMI and showed similar toxicity to C. dipterum as IMI. However, C. dipterum was hardly able to eliminate IMI-ole from its body. For G. pulex, IMI-ole was also the only detected metabolite causing toxicity, but the biotransformation of IMI to IMI-ole was slower and lower in G. pulex compared to C. dipterum, and G. pulex eliminated IMI-ole quicker than C. dipterum. Our results on internal kinetics of IMI and IMI-ole, and on biotransformation of IMI indicated that the metabolite IMI-ole was toxic and was rather persistent inside the body tissue of both invertebrate species, especially for C. dipterum. In conclusion, as IMI and IMI-ole have similar toxicity and IMI was replaced rapidly by IMI-ole which in turn was poorly eliminated by C. dipterum, the overall toxicity is a function of dose and time. As a result, no long-term threshold of effects of IMI may exist for C. dipterum as the poor elimination results in an ongoing increase of toxicity over time for mayflies as also found experimentally in previous published papers.

Mechanistic Effect Modeling of Earthworms in the Context of Pesticide Risk Assessment: Synthesis of the FORESEE Workshop

Earthworms are important ecosystem engineers, and assessment of the risk of plant protection products toward them is part of the European environmental risk assessment (ERA). In the current ERA scheme, exposure and effects are represented simplistically and are not well integrated, resulting in uncertainty when the results are applied to ecosystems. Modeling offers a powerful tool to integrate the effects observed in lower tier laboratory studies with the environmental conditions under which exposure is expected in the field. This paper provides a summary of the (In)Field Organism Risk modEling by coupling Soil Exposure and Effect (FORESEE) Workshop held 28-30 January 2020 in Düsseldorf, Germany. This workshop focused on toxicokinetic-toxicodynamic (TKTD) and population modeling of earthworms in the context of ERA. The goal was to bring together scientists from different stakeholder groups to discuss the current state of soil invertebrate modeling and to explore how earthworm modeling could be applied to risk assessments, in particular how the different model outputs can be used in the tiered ERA approach. In support of these goals, the workshop aimed at addressing the requirements and concerns of the different stakeholder groups to support further model development. The modeling approach included 4 submodules to cover the most relevant processes for earthworm risk assessment: environment, behavior (feeding, vertical movement), TKTD, and population. Four workgroups examined different aspects of the model with relevance for risk assessment, earthworm ecology, uptake routes, and cross-species extrapolation and model testing. Here, we present the perspectives of each workgroup and highlight how the collaborative effort of participants from multidisciplinary backgrounds helped to establish common ground. In addition, we provide a list of recommendations for how earthworm TKTD modeling could address some of the uncertainties in current risk assessments for plant protection products. Integr Environ Assess Manag 2021;17:352-363. © 2020 SETAC.

Fiproles as a proxy for ecological risk assessment of mixture of fipronil and its degradates in effluent-dominated surface waters

Environmental risk assessment of complex chemical mixtures has increasingly been prioritized as a management goal, especially in the regulatory sector. Although fipronil and its three degradates (-sulfone, -sulfide and -desulfinyl) have been frequently quantified in waterways, little information is available about the likelihood and magnitude of ecological risk posed by these chemical mixtures - collectively known as fiproles - in surface water. In the present study, a probabilistic risk assessment of mixtures of fipronil and its three degradates was conducted for three effluent-dominated southern California rivers: Los Angeles River (LAR), San Gabriel River (SGR) and Santa Clara River (SCR), California, USA. The assessments, which used fiproles as an integrated proxy, were based on three levels of toxicity endpoints: median lethal concentration (LC50), half-maximal effective concentration (EC50), and lowest observed effect concentration (LOEC), to gain comprehensive assessment information. Probabilistic approaches based on species sensitivity distribution (SSD) and exposure concentration distribution (ECD) were developed with the log-logistic model by pooling the toxicity and occurrence data, respectively. The 5th percentile hazardous concentrations (HC5s) were calculated to be at low parts per billion levels, enabling these values to be used to estimate the chemical-specific benchmarks for components that lack ecotoxicity data. The single substance potentially affected fraction (ssPAF) of fiproles revealed risk levels for the three rivers in descending order: LAR ≥ SGR > SCR. The overall risk probability estimated from the joint probability curve (JPC) by Monte Carlo simulation was 1.13 ± 0.20% (LC50), 9.31 ± 1.46% (EC50), and 6.58 ± 1.43% (LOEC) for the three rivers collectively. These results derived from the fiproles indicates that fipronil and its degradates pose risks to the aquatic organisms in the surface water of the three rivers. The present study provides a methodology for the use of a proxy in the risk assessment of chemical mixtures.

Application of General Unified Threshold Models of Survival Models for Regulatory Aquatic Pesticide Risk Assessment Illustrated with an Example for the Insecticide Chlorpyrifos

Mathematical models within the General Unified Threshold models of Survival (GUTS) framework translate time-variable chemical exposure information into expected survival of animals. The GUTS models are species and compound specific and explicitly describe the internal exposure dynamics in an organism (toxicokinetics) and the related damage and effect dynamics (toxicodynamics), thereby connecting the external exposure concentration dynamics with the simulated mortality or immobility over time. In a recent scientific opinion on toxicokinetic-toxicodynamic (TKTD) models published by the European Food Safety Authority (EFSA), the GUTS modeling framework was considered ready for use in the aquatic risk assessment for pesticides and aquatic fauna. The GUTS models are suggested for use in risk assessment, if they are sufficiently validated for a specific substance-species combination. This paper aims to illustrate how they can be used in the regulatory environmental risk assessment for pesticides for a specific type of refinement, that is, when risks are triggered by lower tiers in acute as well as in chronic risk assessment and mortality or immobility is the critical endpoint. This approach involves the evaluation of time-variable exposure regimes in a so-called "Tier-2C" assessment. The insecticide chlorpyrifos was selected as an example compound because a large data set was available. The GUTS models for 13 different freshwater arthropods and 8 different theoretical aquatic exposure profiles were used to calculate a series of GUTS-based risk estimates, including exposure profile-specific multiplication factors leading to 50% mortality or immobility at the end of the tested profile (LP50/EP50) as "margins of safety." To put the use of GUTS models within the tiered aquatic risk assessment into perspective, GUTS models for the 13 aquatic arthropods were also used to predict the environmental risks of a measured chlorpyrifos exposure profile from an experimental ditch study (Tier-3 approach), and the results are discussed in the context of calibration of the tiered approach. Integr Environ Assess Manag 2021;17:243-258. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Life cycle bioenergetics of the gray seal (Halichoerus grypus) in the Baltic Sea: Population response to environmental stress

Wildlife population dynamics are shaped by multiple natural and anthropogenic factors, including predation, competition, stressful life history events, and external environmental stressors such as diseases and pollution. Marine mammals such as gray seals rely on extensive blubber layers for insulation and energy storage, making this tissue critical for survival and reproduction. This lipid rich blubber layer also accumulates hazardous fat soluble pollutants, such as polychlorinated biphenyls (PCBs), that can directly impact adipose function or be mobilized during periods of negative energy balance or transferred to offspring to exert further impacts on target tissues or vulnerable life stages. To predict how marine mammals will respond to ecological and anthropogenic stressors, it is necessary to use process-based modelling approaches that integrate environmental inputs, full species life history, and stressor impacts with individual dynamics of energy intake, storage, and utilization. The purpose of this study was to develop a full lifecycle dynamic energy budget and individual based model (DEB-IBM) that captured Baltic gray seal physiology and life history, and showcase potential applications of the model to predict population responses to select stressors known to threaten gray seals and other marine mammals around the world. We explore variations of three ecologically important stressors using phenomenological simulations: food limitation, endocrine disrupting chemicals that reduce fertility, and infectious disease. Using our calibrated DEB-IBM for Baltic gray seals, we found that continuous incremental food limitation can be more detrimental to population size than short random events of starvation, and further, that the effect of endocrine disruptors on population growth and structure is delayed due to bioaccumulation, and that communicable diseases significantly decrease population growth even when spillover events are relatively less frequent. One important finding is the delayed effect on population growth rate from some stressors, several years after the exposure period, resulting from a decline in somatic growth, increased age at maturation and decreased fecundity. Such delayed responses are ignored in current models of population viability and can be important in the correct assessment of population extinction risks. The model presented here provides a test bed on which effects of new hazardous substances and different scenarios of future environmental change affecting food availability and/or seal energetic demands can be investigated. Thus, the framework provides a tool for better understanding how diverse environmental stressors affect marine mammal populations and can be used to guide scientifically based management.

Effect Modeling Quantifies the Difference Between the Toxicity of Average Pesticide Concentrations and Time-Variable Exposures from Water Quality Monitoring

Synthetic chemicals are frequently detected in water bodies, and their concentrations vary over time. Water monitoring programs typically employ either a sequence of grab samples or continuous sampling, followed by chemical analysis. Continuous time-proportional sampling yields the time-weighted average concentration, which is taken as proxy for the real, time-variable exposure. However, we do not know how much the toxicity of the average concentration differs from the toxicity of the corresponding fluctuating exposure profile. We used toxicokinetic-toxicodynamic models (invertebrates, fish) and population growth models (algae, duckweed) to calculate the margin of safety in moving time windows across measured aquatic concentration time series (7 pesticides) in 5 streams. A longer sampling period (14 d) for time-proportional sampling leads to more deviations from the real chemical stress than shorter sampling durations (3 d). The associated error is a factor of 4 or less in the margin of safety value toward underestimating and an error of factor 9 toward overestimating chemical stress in the most toxic time windows. Under- and overestimations occur with approximate equal frequency and are very small compared with the overall variation, which ranged from 0.027 to 2.4 × 10¹⁰ (margin of safety values). We conclude that continuous, time-proportional sampling for a period of 3 and 14 d for acute and chronic assessment, respectively, yields sufficiently accurate average concentrations to assess ecotoxicological effects. Environ Toxicol Chem 2020;39:2158-2168. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Simulating Honey Bee Large-Scale Colony Feeding Studies Using the BEEHAVE Model-Part I: Model Validation

In pesticide risk assessments, semifield studies, such as large-scale colony feeding studies (LSCFSs), are conducted to assess potential risks at the honey bee colony level. However, such studies are very cost and time intensive, and high overwintering losses of untreated control hives have been observed in some studies. Honey bee colony models such as BEEHAVE may provide tools to systematically assess multiple factors influencing colony outcomes, to inform study design, and to estimate pesticide impacts under varying environmental conditions. Before they can be used reliably, models should be validated to demonstrate they can appropriately reproduce patterns observed in the field. Despite the recognized need for validation, methodologies to be used in the context of applied ecological models are not agreed on. For the parameterization, calibration, and validation of BEEHAVE, we used control data from multiple LSCFSs. We conducted detailed visual and quantitative performance analyses as a demonstration of validation methodologies. The BEEHAVE outputs showed good agreement with apiary-specific validation data sets representing the first year of the studies. However, the simulations of colony dynamics in the spring periods following overwintering were identified as less reliable. The comprehensive validation effort applied provides important insights that can inform the usability of BEEHAVE in applications related to higher tier risk assessments. In addition, the validation methodology applied could be used in a wider context of ecological models. Environ Toxicol Chem 2020;39:2269-2285. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Sampling rates for passive samplers exposed to a field-relevant peak of 42 organic pesticides

Pesticide concentrations in agricultural streams are often characterised by a low level of baseline exposure and episodic peak concentrations associated with heavy rainfall events. Traditional sampling methods such as grab sampling, which are still largely used in governmental monitoring, typically miss peak concentrations. Passive sampling represents a cost-efficient alternative but requires the additional determination of sampling rates to calculate time-weighted average (TWA) water concentrations from the accumulated pesticide mass in the sampler. To date, sampling rates have largely been determined in experiments with constant exposure, which does not necessarily reflect field situations. Using Empore styrene-divinylbenzene (SDB) passive sampler disks mounted in metal holders, we determined sampling rates for 42 organic pesticides, of which 27 sampling rates were lacking before. The SDB disks were in an artificial channel system exposed to a field-relevant pesticide peak. We used an open-source algorithm to estimate coefficients of equations for the accumulated pesticide mass in disks and to determine exposure time-dependent sampling rates. These sampling rates ranged from 0.02 to 0.98 L d^-1 and corresponded to those from previous studies determined with constant exposure. The prediction of sampling rates using compound properties was unreliable. Hence, experiments are required to determine reliable sampling rates. We discuss the use of passive sampling to estimate peak concentrations. Overall, our study provides sampling rates and computer code to determine these under peak exposure designs and suggests that passive sampling is suitable to estimate peak pesticide concentrations in field studies.

Modeling Sublethal Effects of Chemicals: Application of a Simplified Dynamic Energy Budget Model to Standard Ecotoxicity Data

To assess ecological risks from chemical exposure, we need tools to extrapolate from the sublethal effects observed in the laboratory under constant exposure to realistic time-varying exposures. Dynamic energy budget (DEB) theory offers a mechanistic modeling approach to describe the entire life history of a single organism and the effects of toxicant exposure. We use a simplified model, which can be wholly calibrated from standard chronic bioassay data. Case studies on standard test organisms (Americamysis bahia and Pimephales promelas) are presented to demonstrate the calibration procedure, and for the second case, data are available to pseudovalidate model performance. We use these results to highlight gaps and shortcomings in the current state of the science, and we discuss how these can be overcome to maximize the potential of DEB theory in ecological risk assessment.

Different decreasing rates of chemical threshold concentrations can be explained by their toxicokinetic and toxicodynamic characteristics

To protect ecosystems, threshold concentrations (e.g., HC₅) for chemicals are often derived using the toxicity data obtained at fixed times. Since the toxicity (e.g., LC₅₀) usually decreases with exposure time, the threshold concentrations are expected to be time-dependent, giving rise to the uncertainty in the chemical environmental criteria. Here, using the LC₅₀ data with at least 3 different exposure durations (24, 48 and 96 h) for compounds, we explored the time evolutions of HC₅ across 20 chemicals. Results showed that all chemical's HC₅ decreased with time, but their decreasing rates of HC₅ (k) are significantly different: for some chemicals the k are lower than 0.001 (e.g., methoxychlor and dieldrin), while for some chemicals the k are higher than 0.05 (e.g., PCP and aldicarb). Furthermore, we found that k is negatively related to the bioconcentration factors (BCF), and positively related to the damage recovery rates (k_R). Our work demonstrated that time is an important source of the ecological threshold uncertainty, and this uncertainty is associated with chemical-specific toxicokinetic and toxicodynamic characteristics. We recommend that to effectively protect the ecological communities, higher assessment factor should be adopted in deriving the acute environmental criteria for these chemicals with high BCF and low k_R, fluoranthene and diazinon.

Higher than … or lower than ….? Evidence for the validity of the extrapolation of laboratory toxicity test results to predict the effects of chemicals and ionising radiation in the field

Single species laboratory tests and associated species sensitivity distributions (SSDs) that utilise the resulting data can make a key contribution to efforts to prospective hazard assessments for pesticides, biocides, metals and ionising radiation for research and regulatory risk assessment. An assumption that underlies the single species based toxicity testing approach when combined in SSD models is that the assessments of sensitivities to chemical and ionising radiation measured across a range of species in the laboratory can inform on the likely effects on communities present in the field. Potential issues with the validity of this assumption were already recognised by Van Straalen and Denneman (1989) in their landmark paper on the SSD methodology. In this work, they identified eight major factors that could potentially compromise the extrapolation of laboratory toxicity data to the field. Factors covered a range of issues related to differences in chemistry (e.g. bioavailability, mixtures); environmental conditions (optimal, variable), ecological (compensatory, time-scale) and population genetic structure (adaptation, meta-population dynamics). This paper outlines the evidence pertaining to the influence of these different factors on toxicity in the laboratory as compared to the field focussing especially on terrestrial ecosystems. Through radiological and ecotoxicological research, evidence of the influence of each factor on the translation of observed toxicity from the laboratory to field is available in all cases. The importance of some factors, such as differences in chemical bioavailability between laboratory tests and the field and the ubiquity of exposure to mixtures is clearly established and has some relevance to radiological protection. However, other factors such as the differences in test conditions (optimal vs sub-optimal) and the development of tolerance may be relevant on a case by case basis. When SSDs generated from laboratory tests have been used to predict chemical and ionising radiation effects in the field, results have indicated that they may often seem to under-predict impacts, although this may also be due to other factors such as the effects of other non-chemical stressors also affecting communities at polluted sites. A better understanding of the main factors affecting this extrapolation can help to reduce uncertainty during risk assessment.

Exposure pattern-specific species sensitivity distributions for the ecological risk assessments of insecticides

In the higher tiers of pesticide risk assessment, the Species Sensitivity Distribution (SSD) concept is often used to establish the effect threshold defined as the concentration protecting 95% of the species (Hazardous Concentration 5%, HC5). The toxicity data included in SSDs are normally established using a constant exposure regime. However, the exposure of pesticides in the field is often characterised by a variable exposure regime. Toxicokinetic-toxicodynamic (TKTD) models can be used to extrapolate the toxic effects of a chemical to a specific, time-variable exposure regime. The aim of this paper was to develop Exposure Pattern Specific SSDs (EPS-SSDs) for three insecticides using TKTD models and to compare the HC5 of different exposure patterns with the same time-weighted average concentration to evaluate whether the use of EPS-SSDs would change the outcome of the ecological risk assessment. The EPS-SSDs were developed by estimating TKTD parameters for the compounds chlorpyrifos, imidacloprid and lambda-cyhalothrin using results from standard, 96 h, single species tests. These parameter estimates were used for TKTD modelling to determine toxicity thresholds (e.g. LC10 and LC50) for contrasting exposure patterns after certain evaluation times (4, 10 or 100 days). HC5 values were constructed with TKTD-predicted LC10- and LC50- values for different exposure patterns characterised by similar time-weighted average concentrations. Differences between those HC5 values ranged from a factor 1 to a factor 2.3 for the short evaluation period (4 d). This difference was smaller when using an evaluation period of 10 days instead of 4 days and selecting the TKTD-predicted LC10 instead of TKTD-predicted LC50 based HC5s. For the long term evaluation period (100 d), a maximum difference of a factor of 30 was found.

Mechanistic Effect Modeling Approach for the Extrapolation of Species Sensitivity

In the higher-tier environmental risk assessment of chemicals, species sensitivity distributions (SSDs) are used to statistically describe differences in sensitivity between species and derive community level endpoints. SSDs are usually based on the results from short-term laboratory experiments performed under constant environmental conditions. However, different species may be kept at different "optimal" temperatures, which influence their apparent sensitivity and thus the derivation of endpoints. Also, the extrapolation capacity of SSDs is largely limited to the tested species and conditions. Time-variable exposures and effects at higher levels of biological organization, including biological interactions, are not considered. The quantitative effect prediction at higher tiers would ultimately require the extrapolation of toxicokinetics and toxicodynamics to untested species and the involvement of population and community modeling. In this regard, we tested a toxicokinetic-toxicodynamic modeling approach to mechanistically consider and correct endpoints for ambient temperature and demonstrate the significance for SSDs. We explored correlations in toxicokinetic-toxicodynamic model parameters which would allow for the extrapolation of sensitivities to untested species. Finally, we illustrate the applicability of the approach for higher level effect predictions using an individual-based model. Our results suggest that mechanistic effect modeling approaches can reduce the uncertainties in higher tier effect assessments related to knowledge gaps.

Recommendations to address uncertainties in environmental risk assessment using toxicokinetic-toxicodynamic models

Providing reliable environmental quality standards (EQSs) is a challenging issue in environmental risk assessment (ERA). These EQSs are derived from toxicity endpoints estimated from dose-response models to identify and characterize the environmental hazard of chemical compounds released by human activities. These toxicity endpoints include the classical x% effect/lethal concentrations at a specific time t (EC/LC(x, t)) and the new multiplication factors applied to environmental exposure profiles leading to x% effect reduction at a specific time t (MF(x, t), or denoted LP(x, t) by the EFSA). However, classical dose-response models used to estimate toxicity endpoints have some weaknesses, such as their dependency on observation time points, which are likely to differ between species (e.g., experiment duration). Furthermore, real-world exposure profiles are rarely constant over time, which makes the use of classical dose-response models difficult and may prevent the derivation of MF(x, t). When dealing with survival or immobility toxicity test data, these issues can be overcome with the use of the general unified threshold model of survival (GUTS), a toxicokinetic-toxicodynamic (TKTD) model that provides an explicit framework to analyse both time- and concentration-dependent data sets as well as obtain a mechanistic derivation of EC/LC(x, t) and MF(x, t) regardless of x and at any time t of interest. In ERA, the assessment of a risk is inherently built upon probability distributions, such that the next critical step is to characterize the uncertainties of toxicity endpoints and, consequently, those of EQSs. With this perspective, we investigated the use of a Bayesian framework to obtain the uncertainties from the calibration process and to propagate them to model predictions, including LC(x, t) and MF(x, t) derivations. We also explored the mathematical properties of LC(x, t) and MF(x, t) as well as the impact of different experimental designs to provide some recommendations for a robust derivation of toxicity endpoints leading to reliable EQSs: avoid computing LC(x, t) and MF(x, t) for extreme x values (0 or 100%), where uncertainty is maximal; compute MF(x, t) after a long period of time to take depuration time into account and test survival under pulses with different periods of time between them.

Physiologically based toxicokinetic and toxicodynamic (PBTK-TD) modelling of Cd and Pb exposure in adult zebrafish Danio rerio: Accumulation and toxicity

Accurately predicting the accumulation and toxicity of metals in organisms is a challenging work in ecotoxicology. Here, we developed and validated a physiologically based toxicokinetic and toxicodynamic (PBTK-TD) model for adult zebrafish exposed to Cd and Pb. The model included the gill, liver, intestine, gonad, carcass, and brain, which were linked by blood circulation in the PBTK process and by dynamic relationships between the target organ concentrations and mortality in the TD process. Results showed that the PBTK sub-model can accurately describe and predict the uptake, distribution and disposition kinetics of Cd and Pb in zebrafish. The exchange rates and the accumulation of the metals in the organs were significantly different. For Cd, the highest exchange rate was between blood and liver, and the greatest accumulation of Cd occurred in the liver. For Pb, the greatest accumulation occurred in the gill. The TD sub-model further indicated that metal concentrations in the gill may effectively act as more suitable indicator of Cd and Pb toxic effect than whole body or other organs. The proposed PBTK-TD model is helpful to understanding the fundamental processes by which zebrafish regulate the uptake and disposition of metal and to quantitatively predicting metal toxicity.

Exploring inter-species sensitivity to a model hydrocarbon, 2-Methylnaphtalene, using a process-based model

We compared inter-species sensitivity to a model narcotic compound, 2-Methylnaphthalene, to test if taxonomical relatedness, feeding guilds, and trophic level govern species sensitivities on species distributed in different regions. We fitted a toxicokinetic-toxicodynamic model to survival patterns over time for 26 species using new and raw data from the literature. Species sensitivity distributions provided little insight into understanding patterns in inter-species sensitivity. The range of no-effect concentrations (NEC) obtained for 26 species showed little variation (mean 0.0081 mM; SD 0.009). Results suggest that the NEC alone does not explain the complexity of the species tolerances. The dominant rate constant and the derived time to observe an effect (t₀), a function of concentration, might provide the means for depicting patterns in sensitivity and better ecotoxicological testing. When comparing the t₀ functions, we observed that Arctic species have shorter time frames to start showing effects. Mollusks and second trophic level species took longer to build up a lethal body burden than the rest. Coupling our results with fate and transport models would allow forecasting narcotic compounds toxicity in time and thus improve risk assessment.

Short-term to long-term extrapolation of lethal effects of an herbicide on the marine mysid shrimp Americamysis Bahia by use of the General Unified Threshold Model of Survival (GUTS)

Risk assessments for plant protection products and their active ingredients that are based on standard laboratory tests performed under constant exposure conditions may result in an overestimation of risks because exposure in the environment is often characterized by a few short peaks. Here, the General Unified Threshold Model of Survival (GUTS) was used to conduct a refined risk assessment for the herbicide tembotrione and its effects on the marine invertebrate Americamysis bahia, for which the standard chronic effect assessment failed. The GUTS model was first calibrated with time-to-effect and concentration-response data from 2 independent acute experiments with A. bahia. Model parameters for both toxicodynamic assumptions of stochastic death (SD) and individual tolerance (IT) were estimated with the reduced GUTS model (GUTS-RED) using the scaled internal concentration as a dose metric. Both the calibrated GUTS-RED-SD and GUTS-RED-IT models described survival dynamics well. Model validation using datasets of 2 independent chronic tests yielded robust predictions of long-term toxicity of tembotrione on A. bahia, with GUTS-RED-IT being more reliable than GUTS-RED-SD. The validated model was subsequently used to predict survival from time-variable exposure profiles, as derived from the FOrum for Co-ordination of pesticide fate models and their USe (FOCUS). Because ecotoxicological independence of peaks had not been empirically verified, the link between exposure and effects was assessed with complete exposure profiles. Effect thresholds resulting from different peak exposure concentrations and durations were determined with GUTS and directly compared with the exposure concentrations from the FOCUS surface water scenarios. The derived values were higher than the predicted FOCUS critical concentrations. Additionally, comparing the areas under the curve (AUCs) derived with GUTS for multiple peak exposure profiles to those from FOCUS revealed significant additional safety margins, demonstrating that only unrealistically high exposure concentrations would produce significant effects. In conclusion, no unacceptable effects of tembotrione on aquatic invertebrates under realistic environmental exposure conditions are expected. Integr Environ Assess Manag 2019;15:29-39. © 2018 SETAC.

Calibration and validation of toxicokinetic-toxicodynamic models for three neonicotinoids and some aquatic macroinvertebrates

Exposure patterns in ecotoxicological experiments often do not match the exposure profiles for which a risk assessment needs to be performed. This limitation can be overcome by using toxicokinetic-toxicodynamic (TKTD) models for the prediction of effects under time-variable exposure. For the use of TKTD models in the environmental risk assessment of chemicals, it is required to calibrate and validate the model for specific compound-species combinations. In this study, the survival of macroinvertebrates after exposure to the neonicotinoid insecticide was modelled using TKTD models from the General Unified Threshold models of Survival (GUTS) framework. The models were calibrated on existing survival data from acute or chronic tests under static exposure regime. Validation experiments were performed for two sets of species-compound combinations: one set focussed on multiple species sensitivity to a single compound: imidacloprid, and the other set on the effects of multiple compounds for a single species, i.e., the three neonicotinoid compounds imidacloprid, thiacloprid and thiamethoxam, on the survival of the mayfly Cloeon dipterum. The calibrated models were used to predict survival over time, including uncertainty ranges, for the different time-variable exposure profiles used in the validation experiments. From the comparison between observed and predicted survival, it appeared that the accuracy of the model predictions was acceptable for four of five tested species in the multiple species data set. For compounds such as neonicotinoids, which are known to have the potential to show increased toxicity under prolonged exposure, the calibration and validation of TKTD models for survival needs to be performed ideally by considering calibration data from both acute and chronic tests.

Fit Reduced GUTS Models Online: From Theory to Practice

Mechanistic modeling approaches, such as the toxicokinetic-toxicodynamic (TKTD) framework, are promoted by international institutions such as the European Food Safety Authority and the Organization for Economic Cooperation and Development to assess the environmental risk of chemical products generated by human activities. TKTD models can encompass a large set of mechanisms describing the kinetics of compounds inside organisms (e.g., uptake and elimination) and their effect at the level of individuals (e.g., damage accrual, recovery, and death mechanism). Compared to classical dose-response models, TKTD approaches have many advantages, including accounting for temporal aspects of exposure and toxicity, considering data points all along the experiment and not only at the end, and making predictions for untested situations as realistic exposure scenarios. Among TKTD models, the general unified threshold model of survival (GUTS) is within the most recent and innovative framework but is still underused in practice, especially by risk assessors, because specialist programming and statistical skills are necessary to run it. Making GUTS models easier to use through a new module freely available from the web platform MOSAIC (standing for MOdeling and StAtistical tools for ecotoxIClogy) should promote GUTS operability in support of the daily work of environmental risk assessors. This paper presents the main features of MOSAIC_GUTS: uploading of the experimental data, GUTS fitting analysis, and LCx estimates with their uncertainty. These features will be exemplified from literature data. Integr Environ Assess Manag 2018;14:625-630. © 2018 SETAC.

How to Evaluate the Quality of Toxicokinetic-Toxicodynamic Models in the Context of Environmental Risk Assessment

Environmental risk assessment (ERA) of chemicals relies on the combination of exposure and effects assessment. Exposure concentrations are commonly estimated using mechanistic fate models, but the effects side is restricted to descriptive statistical treatment of toxicity data. Mechanistic effect models are gaining interest in a regulatory context, which has also sparked discussions on model quality and good modeling practice. Proposals for good modeling practice of effect models currently focus very much on population and community models, whereas effects models also exist at the individual level, falling into the category of toxicokinetic-toxicodynamic (TKTD) models. In contrast to the higher-level models, TKTD models are usually completely parameterized by fitting them to experimental data. In fact, one of their explicit aims is to replace descriptive methods for data analysis. Furthermore, the construction of these models does not fit into an orderly modeling cycle, given that most TKTD models have been under continuous development for decades and are being applied by many different research groups, for many different purposes. These aspects have considerable consequences for the application of frameworks for model evaluation. For example, classical sensitivity analysis becomes rather meaningless when all model parameters are fitted to a data set. We illustrate these issues with the General Unified Threshold model for Survival (GUTS), relate them to the quality issues for currently used models in ERA, and provide recommendations for the evaluation of TKTD models and their analyses. Integr Environ Assess Manag 2018;14:604-614. ©2018 SETAC.

Scientific Opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) effect models for regulatory risk assessment of pesticides for aquatic organisms

Following a request from EFSA, the Panel on Plant Protection Products and their Residues (PPR) developed an opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) models and their use in prospective environmental risk assessment (ERA) for pesticides and aquatic organisms. TKTD models are species- and compound-specific and can be used to predict (sub)lethal effects of pesticides under untested (time-variable) exposure conditions. Three different types of TKTD models are described, viz., (i) the 'General Unified Threshold models of Survival' (GUTS), (ii) those based on the Dynamic Energy Budget theory (DEBtox models), and (iii) models for primary producers. All these TKTD models follow the principle that the processes influencing internal exposure of an organism, (TK), are separated from the processes that lead to damage and effects/mortality (TD). GUTS models can be used to predict survival rate under untested exposure conditions. DEBtox models explore the effects on growth and reproduction of toxicants over time, even over the entire life cycle. TKTD model for primary producers and pesticides have been developed for algae, Lemna and Myriophyllum. For all TKTD model calibration, both toxicity data on standard test species and/or additional species can be used. For validation, substance and species-specific data sets from independent refined-exposure experiments are required. Based on the current state of the art (e.g. lack of documented and evaluated examples), the DEBtox modelling approach is currently limited to research applications. However, its great potential for future use in prospective ERA for pesticides is recognised. The GUTS model and the Lemna model are considered ready to be used in risk assessment.

Dynamic energy budget models in ecological risk assessment: From principles to applications

In ecological risk assessment of chemicals, hazard identification and hazard characterisation are most often based on ecotoxicological tests and expressed as summary statistics such as No Observed Effect Concentrations or Lethal Concentration values and No Effect Concentrations. Considerable research is currently ongoing to further improve methodologies to take into account toxico kinetic aspects in toxicological assessments, extrapolations of toxic effects observed on individuals to population effects and combined effects of multiple chemicals effects. In this context, the principles of the Dynamic Energy Budget (DEB), namely the conserved allocation of energy to different life-supporting processes in a wide variety of different species, have been applied successfully to the development of a number of DEB models. DEB models allow the incorporation of effects on growth, reproduction and survival within one consistent framework. This review aims to discuss the principles of the DEB theory together with available DEB models, databases available and applications in ecological risk assessment of chemicals for a wide range of species and taxa. Future perspectives are also discussed with particular emphasis on ongoing research efforts to develop DEB models as open source tools to further support the research and regulatory community to integrate quantitative biology in ecotoxicological risk assessment.

New Insights to Compare and Choose TKTD Models for Survival Based on an Interlaboratory Study for Lymnaea stagnalis Exposed to Cd

Toxicokinetic-toxicodynamic (TKTD) models, as the General Unified Threshold model of Survival (GUTS), provide a consistent process-based framework compared to classical dose-response models to analyze both time and concentration-dependent data sets. However, the extent to which GUTS models (Stochastic Death (SD) and Individual Tolerance (IT)) lead to a better fitting than classical dose-response model at a given target time (TT) has poorly been investigated. Our paper highlights that GUTS estimates are generally more conservative and have a reduced uncertainty through smaller credible intervals for the studied data sets than classical TT approaches. Also, GUTS models enable estimating any x% lethal concentration at any time (LC_x,t), and provide biological information on the internal processes occurring during the experiments. While both GUTS-SD and GUTS-IT models outcompete classical TT approaches, choosing one preferentially to the other is still challenging. Indeed, the estimates of survival rate over time and LC_x,t are very close between both models, but our study also points out that the joint posterior distributions of SD model parameters are sometimes bimodal, while two parameters of the IT model seems strongly correlated. Therefore, the selection between these two models has to be supported by the experimental design and the biological objectives, and this paper provides some insights to drive this choice.

Sequential exposure to low levels of pesticides and temperature stress increase toxicological sensitivity of crustaceans

Frequent pesticide-related impacts on ecosystems at concentrations considered environmentally safe indicate that the current risk assessment framework for registration of pesticides is not protective enough. Causes may include difficulties in assessing the effects of sequential pesticide pulses and their interaction with environmental stressors. By contrast to such realistic scenarios, risk assessment for registration of pesticides is typically based on tests of a single exposure period under benign laboratory conditions. Here, we investigated the toxicological sensitivity of Gammarus pulex, an ecologically relevant crustacean, from uncontaminated control streams and pesticide-contaminated agricultural streams by exposing them to pesticide contamination in the laboratory. Individuals from contaminated streams were 2.7-fold more sensitive to pesticide exposure than individuals from the reference streams. We revealed that this increase in sensitivity was the result of a synergistic interaction of sequential pesticide exposure and temperature stress. Such multiple stressor scenarios are typical for agricultural streams. We conclude that the interactive effects of sequential toxicant exposure and additional environmental stressors need to be considered in a realistic risk assessment framework.

Can Toxicokinetic and Toxicodynamic Modeling Be Used to Understand and Predict Synergistic Interactions between Chemicals?

Some chemicals are known to enhance the effect of other chemicals beyond what can be predicted with standard mixture models, such as concentration addition and independent action. These chemicals are called synergists. Up until now, no models exist that can predict the joint effect of mixtures including synergists. The aim of the present study is to develop a mechanistic toxicokinetic (TK) and toxicodynamic (TD) model for the synergistic mixture of the azole fungicide, propiconazole (the synergist), and the insecticide, α-cypermethrin, on the mortality of the crustacean Daphnia magna. The study tests the hypothesis that the mechanism of synergy is the azole decreasing the biotransformation rate of α-cypermethrin and validates the predictive ability of the model on another azole with a different potency: prochloraz. The study showed that the synergistic potential of azoles could be explained by their effect on the biotransformation rate but that this effect could only partly be explained by the effect of the two azoles on cytochrome P450 activity, measured on D. magna in vivo. TKTD models of interacting mixtures seem to be a promising tool to test mechanisms of interactions between chemicals. Their predictive ability is, however, still uncertain.

The relative sensitivity of freshwater species to antimony(III): Implications for water quality guidelines and ecological risk assessments

Antimony (Sb) is a pollutant in many jurisdictions, yet its threat to aquatic biota is unclear. Water quality guidelines (WQGs) for Sb are not well established and large uncertainty factors are commonly applied in derivation. We constructed freshwater species sensitivity distributions (SSDs) for Sb(III) using available acute toxicity data sourced from temperate and tropical regional studies. A tiered ecological risk assessment (ERA) approach using risk quotients (RQs) was applied for characterisation of risks presented by Sb(III) concentrations measured in the freshwater environment. Multiple parametric models were fitted for each SSD, with the optimal model used to derive the 5% hazardous concentration (HC5), defined as protective of 95% of species, and the corresponding predicted no effect concentration (PNEC). The HC5 values for whole and temperate SSDs were estimated at 781 and 976 μg L^-1 Sb(III), respectively, while the PNECs for both datasets were 156 and 195 μg L^-1 Sb(III), respectively. Due to limited tropical data, a temperate-to-tropic extrapolation factor of 10 was used to estimate an interim PNEC for tropical regions of 20 μg L^-1 Sb(III). Based on published freshwater Sb(III) concentration values across a range of locations, potential ecological risks posed by Sb(III) in some freshwater systems studied would be classified as medium to high risk, but the majority of locations sampled would fall into the low ecological risk category. Our results facilitate the understanding of toxic effects of Sb(III) to freshwater species but also demonstrate that data for Sb ERA are extremely limited.