Earthworm lipid content and size help account for differences in pesticide bioconcentration between species

The uptake and elimination kinetics of pesticides from soil to earthworms are important in characterising the risk of pesticides to soil organisms and the risk from secondary poisoning. However, the understanding of the relative importance of chemical, soil, and species differences in determining pesticide bioconcentration into earthworms is limited. Furthermore, there is insufficient independent data in the literature to fully evaluate existing predictive bioconcentration models. We conducted kinetic uptake and elimination experiments for three contrasting earthworm species (Lumbricus terrestris, Aporrectodea caliginosa, Eisenia fetida) in five soils using a mixture of five pesticides (log Kow 1.69 - 6.63). Bioconcentration increased with pesticide hydrophobicity and decreased with soil organic matter. Bioconcentration factors were comparable between earthworm species for hydrophilic pesticides due to the similar water content of earthworm species. Inter-species variations in bioconcentration of hydrophobic pesticides were primarily accounted for by earthworm lipid content and specific surface area (SSA). Existing bioconcentration models either failed to perform well across earthworm species and for more hydrophilic compounds (log Kow < 2) or were not parameterised for a wide range of compounds and earthworm species. Refined models should incorporate earthworm properties (lipid content and SSA) to account for inter-species differences in pesticide uptake from soil.

Evaluation of models to estimate the bioaccumulation of organic chemicals in earthworms

Modelling approaches to estimate the bioaccumulation of organic chemicals by earthworms are important for improving the realism in risk assessment of chemicals. However, the applicability of existing models is uncertain, partly due to the lack of independent datasets to test them. This study therefore conducted a comprehensive literature review on existing empirical and kinetic models that estimate the bioaccumulation of organic chemicals in earthworms and gathered two independent datasets from published literature to evaluate the predictive performance of these models. The Belfroid et al. (1995a) model is the best-performing empirical model, with 91.2% of earthworm body residue simulations within an order of magnitude of observation. However, this model is limited to the more hydrophobic pesticides and to the earthworm species Eisenia fetida or Eisenia andrei. The kinetic model proposed by Jager et al. (2003b) which out-performs that of Armitage and Gobas (2007), predicted uptake of PCB 153 in the earthworm E. andrei to within a factor of 10. However, the applicability of Jager et al.'s model to other organic compounds and other earthworm species is unknown due to the limited evaluation dataset. The model needs to be parameterised for different chemical, soil, and species types prior to use, which restricts its applicability to risk assessment on a broad scale. Both the empirical and kinetic models leave room for improvement in their ability to reliably predict bioaccumulation in earthworms. Whether they are fit for purpose in environmental risk assessment needs careful consideration on a case by case basis.

Characterization of patterns and variability in the dynamics of outdoor aquatic mesocosms: exploring the capabilities and challenges in data supporting aquatic system models

Aquatic mesocosms are complex test systems used within regulatory risk assessment of plant protection products. These model ecosystems allow researchers to capture interactions of multiple species under realistic environmental conditions. They enable assessment of direct and indirect effects of stressors at all trophic levels (i.e., from primary producers to secondary consumers) and impacts on ecosystem functions. Due to the limited ability to test the multitude of potential exposure scenarios, cross-linking aquatic mesocosm studies with virtual mesocosms, i.e., aquatic system models (ASMs), can serve to meet the demand for more environmental realism and ecological relevance in risk assessment. In this study, full control data sets from seven aquatic mesocosm studies conducted at a single test facility under GLP were analysed graphically and using descriptive statistics. Thereby, not only a comprehensive data base but also an insight into the species present, their dynamics over time, and variability in unchallenged mesocosms was observed. While consistency in dynamics could be discerned for physical and chemical parameters, variability was evident for several biological endpoints. This variability points to amplification of small differences over time as well as to stochastic processes. The outline of existing gaps and uncertainties in data leads to the estimation of what can be expected to be captured and predicted by ASMs.

A framework for algae modelling in regulatory risk assessment

The use of toxicokinetic-toxicodynamic (TKTD) modelling in regulatory risk assessment of plant protection products is increasingly popular, especially since the 2018 EFSA opinion on TKTD modelling announced that several established models are ready for use in risk assessment. With careful adherence to the guidelines laid out by EFSA we present a stepwise approach to validation and use of the SAM-X algae model for regulatory submission in Tier 2C. We demonstrate how the use of moving time windows across time-variable exposure profiles can generate thousands of virtual laboratory mimic simulations that seamlessly predict the effects of time variable exposures across a full exposure profile while maintaining the laboratory conditions of the standard OECD growth inhibition test. Thus, every virtual laboratory test has a duration of 72 hours, with OECD medium and constant light and temperature conditions. The only deviation from the standard test setup is the replacement of constant exposure conditions for time variable concentrations. The present work demonstrates that for simulation of 72h toxicity tests, the nutrient dynamics in the SAM-X model are not required, and we propose the alternative use of a simplified model version. For risk assessment, in accordance with the EFSA guidelines we use a EP₅₀ of 10 as a threshold, meaning that if a time window within the exposure profile causes 50% growth inhibition when magnified by a factor of 10, the threshold will have been exceeded. We here present a simplified example for chlorotoluron and isoproturon. This case study brings to life our proposed framework for TKTD modelling of algae to establish whether a given exposure can be considered low risk.

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

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

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.

How to analyse and account for interactions in mixture toxicity with toxicokinetic-toxicodynamic models

The assessment of chemical mixture toxicity is one of the major challenges in ecotoxicology. Chemicals can interact, leading to more or less effects than expected, commonly named synergism and antagonism respectively. The classic ad hoc approach for the assessment of mixture effects is based on dose-response curves at a single time point, and is limited to identifying a mixture interaction but cannot provide predictions for untested exposure durations, nor for scenarios where exposure varies in time. We here propose a new approach using toxicokinetic-toxicodynamic modelling: The General Unified Threshold model of Survival (GUTS) framework, recently extended for mixture toxicity assessment. We designed a dedicated mechanistic interaction module coupled with the GUTS mixture model to i) identify interactions, ii) test hypotheses to identify which chemical is likely responsible for the interaction, and finally iii) simulate and predict the effect of synergistic and antagonistic mixtures. We tested the modelling approach experimentally with two species (Enchytraeus crypticus and Mamestra brassicae) exposed to different potentially synergistic mixtures (composed of: prochloraz, imidacloprid, cypermethrin, azoxystrobin, chlorothalonil, and chlorpyrifos). Furthermore, we also tested the model with previously published experimental data on two other species (Bombus terrestris and Daphnia magna) exposed to pesticide mixtures (clothianidin, propiconazole, dimethoate, imidacloprid and thiacloprid) found to be synergistic or antagonistic with the classic approach. The results showed an accurate simulation of synergistic and antagonistic effects for the different tested species and mixtures. This modelling approach can identify interactions accounting for the entire time of exposure, and not only at one time point as in the classic approach, and provides predictions of the mixture effect for untested mixture exposure scenarios, including those with time-variable mixture composition.

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.

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process-based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer-resource) for a two-stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta-analyses of multiple stressor experimental results have struggled to identify predictors of consistently non-additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management.

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.

Modelling the effects of variability in feeding rate on growth - a vital step for DEB-TKTD modelling

A major limitation of dietary toxicity studies on rodents is that food consumption often differs between treatments. The control treatment serves as a reference of how animals would have grown if not for the toxicant in their diet, but this comparison unavoidably conflates the effects of toxicity and feeding rate on body weight over time. A key advantage of toxicity models based on dynamic energy budget theory (DEB) is that chemical stress and food consumption are separate model inputs, so their effects on growth rate can be separated. To reduce data requirements, DEB convention is to derive a simplified feeding input, f, from food availability; its value ranges from zero (starvation) to one (food available ad libitum). Observed food consumption in dietary toxicity studies shows that, even in the control treatment, rats limit their food consumption, contradicting DEB assumptions regarding feeding rate. Relatively little work has focused on addressing this mismatch, but accurately modelling the effects of food intake on growth rate is essential for the effects of toxicity to be isolated. This can provide greater insight into the results of chronic toxicity studies and allows accurate extrapolation of toxic effects from laboratory data. Here we trial a new method for calculating f, based on the observed relationships between food consumption and body size in laboratory rats. We compare model results with those of the conventional DEB method and a previous effort to calculate f using observed food consumption data. Our results showed that the new method improved model accuracy while modelled reserve dynamics closely followed observed body fat percentage over time. The new method assumes that digestive efficiency increases with body size_. Verifying this relationship through data collection would strengthen the basis of DEB theory and support the case for its use in ecological risk assessment.

Considerations for using reproduction data in toxicokinetic-toxicodynamic modeling

Toxicokinetic-toxicodynamic (TKTD) modeling is essential to make sense of the time dependence of toxic effects, and to interpret and predict consequences of time-varying exposure. These advantages have been recognized in the regulatory arena, especially for environmental risk assessment of pesticides, where time-varying exposure is the norm. We critically evaluate the link between the modeled variables in TKTD models and the observations from laboratory ecotoxicity tests. For the endpoint reproduction, this link is far from trivial. The relevant TKTD models for sublethal effects are based on dynamic energy budget (DEB) theory, which specifies a continuous investment flux into reproduction. In contrast, experimental tests score egg or offspring release by the mother. The link between model and data is particularly troublesome when a species reproduces in discrete clutches and, even more so, when eggs are incubated in the mother's brood pouch (and release of neonates is scored in the test). This situation is quite common among aquatic invertebrates (e.g., cladocerans, amphipods, mysids), including many popular test species. In this discussion paper, we treat these and other issues with reproduction data, reflect on their potential impact on DEB-TKTD analysis, and provide preliminary recommendations to correct them. Both modelers and users of model results need to be aware of these complications, as ignoring them could easily lead to unnecessary failure of DEB-TKTD models during calibration, or when validating them against independent data for other exposure scenarios. Integr Environ Assess Manag 2022;18:479-487. © 2021 SETAC.

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.

Predicting Mixture Effects over Time with Toxicokinetic-Toxicodynamic Models (GUTS): Assumptions, Experimental Testing, and Predictive Power

Current methods to assess the impact of chemical mixtures on organisms ignore the temporal dimension. The General Unified Threshold model for Survival (GUTS) provides a framework for deriving toxicokinetic-toxicodynamic (TKTD) models, which account for effects of toxicant exposure on survival in time. Starting from the classic assumptions of independent action and concentration addition, we derive equations for the GUTS reduced (GUTS-RED) model corresponding to these mixture toxicity concepts and go on to demonstrate their application. Using experimental binary mixture studies with Enchytraeus crypticus and previously published data for Daphnia magna and Apis mellifera, we assessed the predictive power of the extended GUTS-RED framework for mixture assessment. The extended models accurately predicted the mixture effect. The GUTS parameters on single exposure data, mixture model calibration, and predictive power analyses on mixture exposure data offer novel diagnostic tools to inform on the chemical mode of action, specifically whether a similar or dissimilar form of damage is caused by mixture components. Finally, observed deviations from model predictions can identify interactions, e.g., synergism or antagonism, between chemicals in the mixture, which are not accounted for by the models. TKTD models, such as GUTS-RED, thus offer a framework to implement new mechanistic knowledge in mixture hazard assessments.

Bioenergetics modelling to analyse and predict the joint effects of multiple stressors: Meta-analysis and model corroboration

Understanding the consequences of the combined effects of multiple stressors-including stress from man-made chemicals-is important for conservation management, the ecological risk assessment of chemicals, and many other ecological applications. Our current ability to predict and analyse the joint effects of multiple stressors is insufficient to make the prospective risk assessment of chemicals more ecologically relevant because we lack a full understanding of how organisms respond to stress factors alone and in combination. Here, we describe a Dynamic Energy Budget (DEB) based bioenergetics model that predicts the potential effects of single or multiple natural and chemical stressors on life history traits. We demonstrate the plausibility of the model using a meta-analysis of 128 existing studies on freshwater invertebrates. We then validate our model by comparing its predictions for a combination of three stressors (i.e. chemical, temperature, and food availability) with new, independent experimental data on life history traits in the daphnid Ceriodaphnia dubia. We found that the model predictions are in agreement with observed growth curves and reproductive traits. To the best of our knowledge, this is the first time that the combined effects of three stress factors on life history traits observed in laboratory studies have been predicted successfully in invertebrates. We suggest that a re-analysis of existing studies on multiple stressors within the modelling framework outlined here will provide a robust null model for identifying stressor interactions, and expect that a better understanding of the underlying mechanisms will arise from these new analyses. Bioenergetics modelling could be applied more broadly to support environmental management decision making.

Sublethal effect modelling for environmental risk assessment of chemicals: Problem definition, model variants, application and challenges

Bioenergetic models, and specifically dynamic energy budget (DEB) theory, are gathering a great deal of interest as a tool to predict the effects of realistically variable exposure to toxicants over time on an individual animal. Here we use aquatic ecological risk assessment (ERA) as the context for a review of the different model variants within DEB and the closely related DEBkiss theory (incl. reserves, ageing, size & maturity, starvation). We propose a coherent and unifying naming scheme for all current major DEB variants, explore the implications of each model's underlying assumptions in terms of its capability and complexity and analyse differences between the models (endpoints, mathematical differences, physiological modes of action). The results imply a hierarchy of model complexity which could be used to guide the implementation of simplified model variants. We provide a decision tree to support matching the simplest suitable model to a given research or regulatory question. We detail which new insights can be gained by using DEB in toxicokinetic-toxicodynamic modelling, both generally and for the specific example of ERA, and highlight open questions. Specifically, we outline a moving time window approach to assess time-variable exposure concentrations and discuss how to account for cross-generational exposure. Where possible, we suggest valuable topics for experimental and theoretical research.

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.

A knowledge-based approach to designing control strategies for agricultural pests

Chemical control of insect pests remains vital to agricultural productivity, but limited mechanistic understanding of the interactions between crop, pest and chemical control agent have restricted our capacity to respond to challenges such as the emergence of resistance and demands for tighter environmental regulation. Formulating effective control strategies that integrate chemical and non-chemical management for soil-dwelling pests is particularly problematic owing to the complexity of the soil-root-pest system and the variability that occurs between sites and between seasons. Here, we present a new concept, termed COMPASS, that integrates ecological knowledge on pest development and behaviour together with crop physiology and mechanistic understanding of chemical distribution and toxic action within the rhizosphere. The concept is tested using a two-dimensional systems model (COMPASS-Rootworm) that simulates root damage in maize from the corn rootworm Diabrotica spp. We evaluate COMPASS-Rootworm using 119 field trials that investigated the efficacy of insecticidal products and placement strategies at four sites in the USA over a period of ten years. Simulated root damage is consistent with measurements for 109 field trials. Moreover, we disentangle factors influencing root damage and pest control, including pest pressure, weather, insecticide distribution, and temporality between the emergence of crop roots and pests. The model can inform integrated pest management, optimize pest control strategies to reduce environmental burdens from pesticides, and improve the efficiency of insecticide development.

Toxicokinetic-Toxicodynamic Modeling of the Effects of Pesticides on Growth of Rattus norvegicus

Ecological risk assessment is carried out for chemicals such as pesticides before they are released into the environment. Such risk assessment currently relies on summary statistics gathered in standardized laboratory studies. However, these statistics extract only limited information and depend on duration of exposure. Their extrapolation to realistic ecological scenarios is inherently limited. Mechanistic effect models simulate the processes underlying toxicity and so have the potential to overcome these issues. Toxicokinetic-toxicodynamic (TK-TD) models operate at the individual level, predicting the internal concentration of a chemical over time and the stress it places on an organism. TK-TD models are particularly suited to addressing the difference in exposure patterns between laboratory (constant) and field (variable) scenarios. So far, few studies have sought to predict sublethal effects of pesticide exposure to wild mammals in the field, even though such effects are of particular interest with respect to longer term exposure. We developed a TK-TD model based on the dynamic energy budget (DEB) theory, which can be parametrized and tested solely using standard regulatory studies. We demonstrate that this approach can be used effectively to predict toxic effects on the body weight of rats over time. Model predictions separate the impacts of feeding avoidance and toxic action, highlighting which was the primary driver of effects on growth. Such information is relevant to the ecological risk posed by a compound because in the environment alternative food sources may or may not be available to focal species. While this study focused on a single end point, growth, this approach could be expanded to include reproductive output. The framework developed is simple to use and could be of great utility for ecological and toxicological research as well as to risk assessors in industry and regulatory agencies.

Building and Applying Quantitative Adverse Outcome Pathway Models for Chemical Hazard and Risk Assessment

An important goal in toxicology is the development of new ways to increase the speed, accuracy, and applicability of chemical hazard and risk assessment approaches. A promising route is the integration of in vitro assays with biological pathway information. We examined how the adverse outcome pathway (AOP) framework can be used to develop pathway-based quantitative models useful for regulatory chemical safety assessment. By using AOPs as initial conceptual models and the AOP knowledge base as a source of data on key event relationships, different methods can be applied to develop computational quantitative AOP models (qAOPs) relevant for decision making. A qAOP model may not necessarily have the same structure as the AOP it is based on. Useful AOP modeling methods range from statistical, Bayesian networks, regression, and ordinary differential equations to individual-based models and should be chosen according to the questions being asked and the data available. We discuss the need for toxicokinetic models to provide linkages between exposure and qAOPs, to extrapolate from in vitro to in vivo, and to extrapolate across species. Finally, we identify best practices for modeling and model building and the necessity for transparent and comprehensive documentation to gain confidence in the use of qAOP models and ultimately their use in regulatory applications. Environ Toxicol Chem 2019;38:1850-1865. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Factors Affecting the Growth of Pseudokirchneriella subcapitata in Single-Species Tests: Lessons for the Experimental Design and the Reproducibility of a Multitrophic Laboratory Microcosm

The need for an integrated risk assessment at an ecologically relevant scale (e.g., at the population/community levels) has been acknowledged. Multispecies systems with increased ecological complexity, however, are difficult if not impossible to reproduce. The laboratory-scale microcosm TriCosm (Pseudokirchneriella subcapitata, Ceriodaphnia dubia, Hydra viridissima) of intermediate complexity was developed for the reproducible assessment of chemical effects at the population/community levels. The system dynamics were repeatable in the short term, but interexperimental variation of algal dynamics in the long term triggered knock-on effects on grazer and predator populations. We present 20 experiments to assess the effects of 12 factors (test medium, vessel type/condition, shaking speed, light intensity/regime, inoculation density, medium preparation components, metal concentration/composition, buffering salt type/concentration) on algal growth in the TriCosm enclosure. Growth rates varied between ≤ 0 and 1.40 (± 0.21) and generally were greatest with increased shaking speed, light exposure, medium buffer, or aeration time. Treatments conducted in dishes with aseptically prepared, lightly buffered, and/or hardly aerated medium resulted in low growth rates. We found that inter-experimental variation of algal dynamics in the TriCosm was caused by a modification of medium preparation (omission of medium aeration) with the aim of reducing microbial contamination. Our findings highlight the facts that consistency in experimental procedures and in-depth understanding of system components are indispensable to achieve repeatability. Environ Toxicol Chem 2019;00:1-13. © 2019 SETAC.

Automated, high-throughput measurement of size and growth curves of small organisms in well plates

Organism size and growth curves are important biological characteristics. Current methods to measure organism size, and in particular growth curves, are often resource intensive because they involve many manual steps. Here we demonstrate a method for automated, high-throughput measurements of size and growth in individual aquatic invertebrates kept in microtiter well-plates. We use a spheroid counter (Cell³iMager, cc-5000) to automatically measure size of seven different freshwater invertebrate species. Further, we generated calibration curves (linear regressions, all p < 0.0001, r² >=0.9 for Ceriodaphnoa dubia, Asellus aquaticus, Daphnia magna, Daphnia pulex; r² >=0.8 for Hyalella azteca, Chironomus spec. larvae and Culex spec. larvae) to convert size measured on the spheroid counter to traditional, microscope based, length measurements, which follow the longest orientation of the body. Finally, we demonstrate semi-automated measurement of growth curves of individual daphnids (C. dubia and D. magna) over time and find that the quality of individual growth curves varies, partly due to methodological reasons. Nevertheless, this novel method could be adopted to other species and represents a step change in experimental throughput for measuring organisms’ shape, size and growth curves. It is also a significant qualitative improvement by enabling high-throughput assessment of inter-individual variation of growth.

Quantifying pesticide deposits and spray patterns at micro-scales on apple (Malus domesticus) leaves with a view to arthropod exposure

BACKGROUND

Pesticides used in commercial crop systems can adversely affect non-target arthropod populations. The spatial distribution of pesticide residues is rarely studied at scales relevant to these populations. Here, we combine two methods for assessing pesticide spray deposits at spatial scales relevant to non-target arthropods found in apple orchards. Pesticide residues were determined on individual apple leaves through conventional residue analysis; water-sensitive paper was used to investigate spatial distributions in deposits at the micro-scale. We also evaluated how accurately a digital image analysis program estimated pesticide residues.

RESULTS

We found that mean pesticide spray coverage on water-sensitive paper varied by up to 6.1% (95% CI 9.4%, 2.7%) within an apple orchard, and leaf residues varied by up to 0.95 (95% CI 0.54, 1.36) mg kg^-1 within a tree. Leaf residues based on analytical chemistry were six times lower than pesticide deposition estimated through image analysis of water-sensitive paper, although these correlated strongly. This correlation allowed estimation of actual residues by application of a correction factor.

CONCLUSION

Our method demonstrates accurate estimation of pesticide deposits at the individual leaf scale through digital analysis of water-sensitive paper and is a low-cost, rapid alternative to conventional residue analysis techniques. © 2018 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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.

A standardized tritrophic small-scale system (TriCosm) for the assessment of stressor-induced effects on aquatic community dynamics

Chemical impacts on the environment are routinely assessed in single-species tests. They are employed to measure direct effects on nontarget organisms, but indirect effects on ecological interactions can only be detected in multispecies tests. Micro- and mesocosms are more complex and environmentally realistic, yet they are less frequently used for environmental risk assessment because resource demand is high, whereas repeatability and statistical power are often low. Test systems fulfilling regulatory needs (i.e., standardization, repeatability, and replication) and the assessment of impacts on species interactions and indirect effects are lacking. In the present study we describe the development of the TriCosm, a repeatable aquatic multispecies test with 3 trophic levels and increased statistical power. High repeatability of community dynamics of 3 interacting aquatic populations (algae, Ceriodaphnia, and Hydra) was found with an average coefficient of variation of 19.5% and the ability to determine small effect sizes. The TriCosm combines benefits of both single-species tests (fulfillment of regulatory requirements) and complex multispecies tests (ecological relevance) and can be used, for instance, at an intermediate tier in environmental risk assessment. Furthermore, comparatively quickly generated population and community toxicity data can be useful for the development and testing of mechanistic effect models. Environ Toxicol Chem 2018;37:1051-1060. © 2017 SETAC.

Physiological modes of action across species and toxicants: the key to predictive ecotoxicology

As ecotoxicologists we strive for a better understanding of how chemicals affect our environment. Humanity needs tools to identify those combinations of man-made chemicals and organisms most likely to cause problems. In other words: which of the millions of species are at risk from pollution? And which of the tens of thousands of chemicals contribute most to the risk? We identified our poor knowledge on physiological modes of action (how a chemical affects the energy allocation in an organism), and how they vary across species and toxicants, as a major knowledge gap. We also find that the key to predictive ecotoxicology is the systematic, rigorous characterization of physiological modes of action because that will enable more powerful in vitro to in vivo toxicity extrapolation and in silico ecotoxicology. In the near future, we expect a step change in our ability to study physiological modes of action by improved, and partially automated, experimental methods. Once we have populated the matrix of species and toxicants with sufficient physiological mode of action data we can look for patterns, and from those patterns infer general rules, theory and models.

Toxic Mixtures in Time-The Sequence Makes the Poison

"The dose makes the poison". This principle assumes that once a chemical is cleared out of the organism (toxicokinetic recovery), it no longer has any effect. However, it overlooks the other process of re-establishing homeostasis, toxicodynamic recovery, which can be fast or slow depending on the chemical. Therefore, when organisms are exposed to two toxicants in sequence, the toxicity can differ if their order is reversed. We test this hypothesis with the freshwater crustacean Gammarus pulex and four toxicants that act on different targets (diazinon, propiconazole, 4,6-dinitro-o-cresol, 4-nitrobenzyl chloride). We found clearly different toxicity when the exposure order of two toxicants was reversed, while maintaining the same dose. Slow toxicodynamic recovery caused carry-over toxicity in subsequent exposures, thereby resulting in a sequence effect-but only when toxicodynamic recovery was slow relative to the interval between exposures. This suggests that carry-over toxicity is a useful proxy for organism fitness and that risk assessment methods should be revised as they currently could underestimate risk. We provide the first evidence that carry-over toxicity occurs among chemicals acting on different targets and when exposure is several days apart. It is therefore not only the dose that makes the poison but also the exposure sequence.

Toward refined environmental scenarios for ecological risk assessment of down-the-drain chemicals in freshwater environments

Current regulatory practice for chemical risk assessment suffers from the lack of realism in conventional frameworks. Despite significant advances in exposure and ecological effect modeling, the implementation of novel approaches as high-tier options for prospective regulatory risk assessment remains limited, particularly among general chemicals such as down-the-drain ingredients. While reviewing the current state of the art in environmental exposure and ecological effect modeling, we propose a scenario-based framework that enables a better integration of exposure and effect assessments in a tiered approach. Global- to catchment-scale spatially explicit exposure models can be used to identify areas of higher exposure and to generate ecologically relevant exposure information for input into effect models. Numerous examples of mechanistic ecological effect models demonstrate that it is technically feasible to extrapolate from individual-level effects to effects at higher levels of biological organization and from laboratory to environmental conditions. However, the data required to parameterize effect models that can embrace the complexity of ecosystems are large and require a targeted approach. Experimental efforts should, therefore, focus on vulnerable species and/or traits and ecological conditions of relevance. We outline key research needs to address the challenges that currently hinder the practical application of advanced model-based approaches to risk assessment of down-the-drain chemicals. Integr Environ Assess Manag 2017;13:233-248. © 2016 SETAC.

Integrated presentation of ecological risk from multiple stressors

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Reintroducing Environmental Change Drivers in Biodiversity-Ecosystem Functioning Research

For the past 20 years, research on biodiversity and ecosystem functioning (B-EF) has only implicitly considered the underlying role of environmental change. We illustrate that explicitly reintroducing environmental change drivers in B-EF research is needed to predict the functioning of ecosystems facing changes in biodiversity. Next we show how this reintroduction improves experimental control over community composition and structure, which helps to provide mechanistic insight on how multiple aspects of biodiversity relate to function and how biodiversity and function relate in food webs. We also highlight challenges for the proposed reintroduction and suggest analyses and experiments to better understand how random biodiversity changes, as studied by classic approaches in B-EF research, contribute to the shifts in function that follow environmental change.

Modelling survival: exposure pattern, species sensitivity and uncertainty

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Computationally Efficient Implementation of a Novel Algorithm for the General Unified Threshold Model of Survival (GUTS)

The General Unified Threshold model of Survival (GUTS) provides a consistent mathematical framework for survival analysis. However, the calibration of GUTS models is computationally challenging. We present a novel algorithm and its fast implementation in our R package, GUTS, that help to overcome these challenges. We show a step-by-step application example consisting of model calibration and uncertainty estimation as well as making probabilistic predictions and validating the model with new data. Using self-defined wrapper functions, we show how to produce informative text printouts and plots without effort, for the inexperienced as well as the advanced user. The complete ready-to-run script is available as supplemental material. We expect that our software facilitates novel re-analysis of existing survival data as well as asking new research questions in a wide range of sciences. In particular the ability to quickly quantify stressor thresholds in conjunction with dynamic compensating processes, and their uncertainty, is an improvement that complements current survival analysis methods.

Prediction of pest pressure on corn root nodes: the POPP-Corn model

A model for the corn rootworm Diabrotica spp. combined with a temporally explicit model for development of corn roots across the soil profile was developed to link pest ecology, root damage and yield loss. Development of the model focused on simulating root damage from rootworm feeding in accordance with observations in the field to allow the virtual testing of efficacy from management interventions in the future. We present the model and demonstrate its applicability for simulating root damage by comparison between observed and simulated pest development and root damage (assessed according to the node injury scale from 0 to 3) for field studies from the literature conducted in Urbana, Illinois (US), between 1991 and 2014. The model simulated the first appearance of larvae and adults to within a week of that observed in 88 and 71 % of all years, respectively, and in all cases to within 2 weeks of the first sightings recorded for central Illinois. Furthermore, in 73 % of all years simulated root damage differed by <0.5 node injury scale points compared to the observations made in the field between 2005 and 2014 even though accurate information for initial pest pressure (i.e. number of eggs in the soil) was not measured at the sites or available from nearby locations. This is, to our knowledge, the first time that pest ecology, root damage and yield loss have been successfully interlinked to produce a virtual field. There are potential applications in investigating efficacy of different pest control measures and strategies.

Using toxicokinetic-toxicodynamic modeling as an acute risk assessment refinement approach in vertebrate ecological risk assessment

Recent guidance identified toxicokinetic-toxicodynamic (TK-TD) modeling as a relevant approach for risk assessment refinement. Yet, its added value compared to other refinement options is not detailed, and how to conduct the modeling appropriately is not explained. This case study addresses these issues through 2 examples of individual-level risk assessment for 2 hypothetical plant protection products: 1) evaluating the risk for small granivorous birds and small omnivorous mammals of a single application, as a seed treatment in winter cereals, and 2) evaluating the risk for fish after a pulsed treatment in the edge-of-field zone. Using acute test data, we conducted the first tier risk assessment as defined in the European Food Safety Authority (EFSA) guidance. When first tier risk assessment highlighted a concern, refinement options were discussed. Cases where the use of models should be preferred over other existing refinement approaches were highlighted. We then practically conducted the risk assessment refinement by using 2 different models as examples. In example 1, a TK model accounting for toxicokinetics and relevant feeding patterns in the skylark and in the wood mouse was used to predict internal doses of the hypothetical active ingredient in individuals, based on relevant feeding patterns in an in-crop situation, and identify the residue levels leading to mortality. In example 2, a TK-TD model accounting for toxicokinetics, toxicodynamics, and relevant exposure patterns in the fathead minnow was used to predict the time-course of fish survival for relevant FOCUS SW exposure scenarios and identify which scenarios might lead to mortality. Models were calibrated using available standard data and implemented to simulate the time-course of internal dose of active ingredient or survival for different exposure scenarios. Simulation results were discussed and used to derive the risk assessment refinement endpoints used for decision. Finally, we compared the "classical" risk assessment approach with the model-based approach. These comparisons showed that TK and TK-TD models can bring more realism to the risk assessment through the possibility to study realistic exposure scenarios and to simulate relevant mechanisms of effects (including delayed toxicity and recovery). Noticeably, using TK-TD models is currently the most relevant way to directly connect realistic exposure patterns to effects. We conclude with recommendations on how to properly use TK and TK-TD model in acute risk assessment for vertebrates.

Post-ozonation in a municipal wastewater treatment plant improves water quality in the receiving stream

BACKGROUND

Removal of organic micropollutants from wastewater by post-ozonation has been investigated in a municipal wastewater treatment plant (WWTP) temporarily upgraded with full-scale ozonation, followed by sand filtration, as an additional treatment step of the secondary effluent. Here, the SPEAR (species at risk) indicator was used to analyse macroinvertebrate abundance data that were collected in the receiving stream before, during and after ozonation to investigate whether ozonation improved the water quality.

RESULTS

The SPEAR values indicate a better water quality downstream the WWTP during ozonation. With ozonation the relative abundance of vulnerable macroinvertebrates in the stream receiving the treated wastewater increases from 18 % (CI 15-21 %) to 30 % (CI 28-32 %). This increase of 12 % (CI 8-16 %) indicates improved ecological quality of the stream and shifts classification according to the Water Framework Directive from poor to moderate.

CONCLUSIONS

The SPEAR concept, originally developed to indicate pesticide stress, also appears to indicate toxic stress by a mixture of various micropollutants including pharmaceuticals, personal care products and pesticides. The responsiveness of the SPEAR indicator means that those macroinvertebrates that are vulnerable to pesticide pollution are also vulnerable to micropollutants from WWTPs. The change in the macroinvertebrate community downstream the WWTP indicates that toxicity by pollutants decreased by more than one order of magnitude during ozonation. Ozonation followed by sand filtration has favourable impacts on the composition of the macroinvertebrate community and can improve the water quality in the receiving stream.

Death Dilemma and Organism Recovery in Ecotoxicology

Why do some individuals survive after exposure to chemicals while others die? Either, the tolerance threshold is distributed among the individuals in a population, and its exceedance leads to certain death, or all individuals share the same threshold above which death occurs stochastically. The previously published General Unified Threshold model of Survival (GUTS) established a mathematical relationship between the two assumptions. According to this model stochastic death would result in systematically faster compensation and damage repair mechanisms than individual tolerance. Thus, we face a circular conclusion dilemma because inference about the death mechanism is inherently linked to the speed of damage recovery. We provide empirical evidence that the stochastic death model consistently infers much faster toxicodynamic recovery than the individual tolerance model. Survival data can be explained by either, slower damage recovery and a wider individual tolerance distribution, or faster damage recovery paired with a narrow tolerance distribution. The toxicodynamic model parameters exhibited meaningful patterns in chemical space, which is why we suggest toxicodynamic model parameters as novel phenotypic anchors for in vitro to in vivo toxicity extrapolation. GUTS appears to be a promising refinement of traditional survival curve analysis and dose response models.

Toxicology across scales: Cell population growth in vitro predicts reduced fish growth

Environmental risk assessment of chemicals is essential but often relies on ethically controversial and expensive methods. We show that tests using cell cultures, combined with modeling of toxicological effects, can replace tests with juvenile fish. Hundreds of thousands of fish at this developmental stage are annually used to assess the influence of chemicals on growth. Juveniles are more sensitive than adult fish, and their growth can affect their chances to survive and reproduce. Thus, to reduce the number of fish used for such tests, we propose a method that can quantitatively predict chemical impact on fish growth based on in vitro data. Our model predicts reduced fish growth in two fish species in excellent agreement with measured in vivo data of two pesticides. This promising step toward alternatives to fish toxicity testing is simple, inexpensive, and fast and only requires in vitro data for model calibration.

Minimised bioconcentration tests: a useful tool for assessing chemical uptake into terrestrial and aquatic invertebrates?

Current guidelines for determining bioconcentration factors (BCF) and uptake and depuration rate constants require labor intensive studies with large numbers of organisms. A minimized approach has recently been proposed for fish BCF studies but its applicability to other taxonomic groups is unknown. In this study, we therefore evaluate the use of the minimized approach for estimating BCF and uptake and depuration rate constants for chemicals in aquatic and terrestrial invertebrates. Data from a range of previous BCF studies were resampled to calculate BCFs and rate constants using the minimized method. The resulting values were then compared to values obtained using full study designs. Results demonstrated a good correlation for uptake rate constants, a poor correlation for depuration rate constants and a very good correlation between the BCFs obtained using the traditional and minimized approach for a variety of organic compounds. The minimized approach therefore has merit in deriving bioconcentration factors and uptake rate constants but may not be appropriate for deriving depuration rate constants for use in, for example, toxico-kinetic toxico-dynamic modeling. The approach uses up to 70% fewer organisms, requires less labor and has lower analytical costs. The minimized design therefore could be a valuable approach for running large multifactorial studies to assess bioconcentration of the plethora of chemicals that occur in the environment into the many taxonomic groups that occur in the environment. The approach should therefore help in accelerating the development of our understanding of factors and processes affecting uptake of chemicals into organisms in the environment.

Modeling the contribution of toxicokinetic and toxicodynamic processes to the recovery of Gammarus pulex populations after exposure to pesticides

Because aquatic macroinvertebrates may be exposed regularly to pesticides in edge-of-the-field water bodies, an accurate assessment of potential adverse effects and subsequent population recovery is essential. Standard effect risk assessment tools are not able to fully address the complexities arising from multiple exposure patterns, nor can they properly address the population recovery process. In the present study, we developed an individual-based model of the freshwater amphipod Gammarus pulex to evaluate the consequences of exposure to 4 compounds with different modes of action on individual survival and population recovery. Effects on survival were calculated using concentration-effect relationships and the threshold damage model (TDM), which accounts for detailed processes of toxicokinetics and toxicodynamics. Delayed effects as calculated by the TDM had a significant impact on individual survival and population recovery. We also evaluated the standard assessment of effects after short-term exposures using the 96-h concentration-effect model and the TDM, which was conservative for very short-term exposure. An integration of a TKTD submodel with a population model can be used to explore the ecological relevance of ecotoxicity endpoints in different exposure environments.

Importance of toxicokinetics for interspecies variation in sensitivity to chemicals

Interspecies variation in sensitivity to synthetic chemicals can be orders of magnitude large. Species traits causing the variation can be related to toxicokinetics (uptake, distribution, biotransformation, elimination) or toxicodynamics (interaction with biological target sites). We present an approach to systematically measure and model the contribution of uptake, biotransformation, internal distribution, and elimination kinetics toward species sensitivity differences. The aim is to express sensitivity as target tissue specific, internal lethal concentrations. A case study with the pesticides diazinon, imidacloprid, and propiconazole and the aquatic invertebrates Gammarus pulex, Gammarus fossarum, and Lymnaea stagnalis illustrates the approach. L. stagnalis accumulates more pesticides than Gammaridae when measured in whole organisms but less in target tissues such as the nervous system. Toxicokinetics, i.e. biotransformation and distribution, explain the higher tolerance of L. stagnalis to the insecticide diazinon when compared to Gammaridae. L. stagnalis was again more tolerant to the other neurotoxicant imidacloprid; however, the difference in sensitivity could not be explained by toxicokinetics alone, indicating the importance of toxicodynamic differences. Sensitivity to propiconazole was comparable among all species and, when expressed as internal lethal concentrations, falls in the range of baseline toxicity.

Nanopesticides: guiding principles for regulatory evaluation of environmental risks

Nanopesticides or nano plant protection products represent an emerging technological development that, in relation to pesticide use, could offer a range of benefits including increased efficacy, durability, and a reduction in the amounts of active ingredients that need to be used. A number of formulation types have been suggested including emulsions (e.g., nanoemulsions), nanocapsules (e.g., with polymers), and products containing pristine engineered nanoparticles, such as metals, metal oxides, and nanoclays. The increasing interest in the use of nanopesticides raises questions as to how to assess the environmental risk of these materials for regulatory purposes. Here, the current approaches for environmental risk assessment of pesticides are reviewed and the question of whether these approaches are fit for purpose for use on nanopesticides is addressed. Potential adaptations to existing environmental risk assessment tests and procedures for use with nanopesticides are discussed, addressing aspects such as analysis and characterization, environmental fate and exposure assessment, uptake by biota, ecotoxicity, and risk assessment of nanopesticides in aquatic and terrestrial ecosystems. Throughout, the main focus is on assessing whether the presence of the nanoformulation introduces potential differences relative to the conventional active ingredients. The proposed changes in the test methodology, research priorities, and recommendations would facilitate the development of regulatory approaches and a regulatory framework for nanopesticides.

Measured and modeled toxicokinetics in cultured fish cells and application to in vitro-in vivo toxicity extrapolation

Effect concentrations in the toxicity assessment of chemicals with fish and fish cells are generally based on external exposure concentrations. External concentrations as dose metrics, may, however, hamper interpretation and extrapolation of toxicological effects because it is the internal concentration that gives rise to the biological effective dose. Thus, we need to understand the relationship between the external and internal concentrations of chemicals. The objectives of this study were to: (i) elucidate the time-course of the concentration of chemicals with a wide range of physicochemical properties in the compartments of an in vitro test system, (ii) derive a predictive model for toxicokinetics in the in vitro test system, (iii) test the hypothesis that internal effect concentrations in fish (in vivo) and fish cell lines (in vitro) correlate, and (iv) develop a quantitative in vitro to in vivo toxicity extrapolation method for fish acute toxicity. To achieve these goals, time-dependent amounts of organic chemicals were measured in medium, cells (RTgill-W1) and the plastic of exposure wells. Then, the relation between uptake, elimination rate constants, and log KOW was investigated for cells in order to develop a toxicokinetic model. This model was used to predict internal effect concentrations in cells, which were compared with internal effect concentrations in fish gills predicted by a Physiologically Based Toxicokinetic model. Our model could predict concentrations of non-volatile organic chemicals with log KOW between 0.5 and 7 in cells. The correlation of the log ratio of internal effect concentrations in fish gills and the fish gill cell line with the log KOW was significant (r>0.85, p = 0.0008, F-test). This ratio can be predicted from the log KOW of the chemical (77% of variance explained), comprising a promising model to predict lethal effects on fish based on in vitro data.

Imidacloprid perturbs feeding of Gammarus pulex at environmentally relevant concentrations

Changes in food uptake by detritivorous macroinvertebrates could disrupt the ecosystem service of leaf litter breakdown, necessitating the study of shredding under anthropogenic influences. The impact of the neonicotinoid insecticide imidacloprid on the feeding rate of individual Gammarus pulex was measured at a daily resolution both during and after a 4-d exposure period. The authors found that imidacloprid inhibits feeding of G. pulex during exposure at concentrations ≥ 30 µg/L and that there was no recovery in feeding on transfer into clean media for 3 d. Exposure to imidacloprid at concentrations ≥ 0.81 µg/L and ≤ 9.0 µg/L resulted in increased feeding after exposure even though there was no significant effect on feeding during the exposure itself. Comparison with the literature shows that concentrations found to influence feeding lie within the range of estimated and measured environmental concentrations. Additionally, effects on feeding rate were observed at concentrations 2 orders of magnitude lower than those causing mortality. The lethal concentration for 50% of test organisms after 4 d of exposure (270 µg/L, literature data) and the effect concentration for a reduction in feeding by 50% (5.34 µg/L) were used for this comparison. The present study discusses the potential that effects on feeding may evoke effects at the population level or disturb leaf litter breakdown in the environment.

Bioconcentration of organic contaminants in Daphnia resting eggs

Organic contaminants detected in sediments from Lake Greifensee and other compounds falling in the log Dow range from 1 to 7 were selected to study the bioconcentration of organic contaminants in sediments in Daphnia resting eggs (ephippia). Our results show that octocrylene, tonalide, triclocarban, and other personal care products, along with pesticides and biocides can accumulate in ephippia with log BCF values up to 3. Data on the uptake and depuration kinetics show a better fit toward a two compartment organism model over a single compartment model due to the differences in ephippial egg content in the environment. The obtained BCFs correlate with hydrophobicity for neutral compounds. Independence between BCF and hydrophobicity was observed for partially ionized compounds with log Dow values around 1. Internal concentrations in ephippia in the environment were predicted based on sediment concentrations using the equilibrium partitioning model and calculated BCFs. Estimated internal concentration values ranged between 1 and 68,000 μg/kglip with triclocarban having the highest internal concentrations followed by tonalide and triclosan. The outcomes indicate that contaminants can be taken up by ephippia from the water column or the pore water in the sediment and might influence fitness and sexual reproduction in the aquatic key species of the genus Daphnia.

Comparative toxicokinetics of organic micropollutants in freshwater crustaceans

Exposure and depuration experiments for Gammarus pulex and Daphnia magna were conducted to quantitatively analyze biotransformation products (BTPs) of organic micropollutants (tramadol, irgarol, and terbutryn). Quantification for BTPs without available standards was performed using an estimation method based on physicochemical properties. Time-series of internal concentrations of micropollutants and BTPs were used to estimate the toxicokinetic rates describing uptake, elimination, and biotransformation processes. Bioaccumulation factors (BAF) for the parents and retention potential factors (RPF), representing the ratio of the internal amount of BTPs to the parent at steady state, were calculated. Nonlinear correlation of excretion rates with hydrophobicity indicates that BTPs with lower hydrophobicity are not always excreted faster than the parent compound. For irgarol, G.pulex showed comparable elimination, but greater uptake and BAF/RPF values than D.magna. Further, G. pulex had a whole set of secondary transformations that D. magna lacked. Tramadol was transformed more and faster than irgarol and there were large differences in toxicokinetic rates for the structurally similar compounds irgarol and terbutryn. Thus, predictability of toxicokinetics across species and compounds needs to consider biotransformation and may be more challenging than previously thought because we found large differences in closely related species and similar chemical structures.

Highly time-variable exposure to chemicals--toward an assessment strategy

Organisms in the environment experience fluctuating, pulsed, or intermittent exposure to pollutants. Accounting for effects of such exposures is an important challenge for environmental risk assessment, particularly given the simplified design of standard ecotoxicity tests. Dynamic simulation using toxicokinetic-toxicodynamic (TK-TD) models describes the processes that link exposure with effects in an organism and provides a basis for extrapolation to a range of exposure scenarios. In so doing, TK-TD modeling makes the risk assessment more robust and aids use and interpretation of experimental data. Toxicokinetic-toxicodynamic models are well-developed for predicting survival of individual organisms and are increasingly applied to sublethal endpoints. In the latter case particularly, linkage to individual-based models (IBMs) allows extrapolation to population level as well as accounting for differences in effects of toxicant exposure at different stages in the life cycle. Extrapolation between species remains an important constraint because there is currently no systematic understanding of species traits that cause differences in the relevant processes. Toxicokinetic-toxicodynamic models allow interrogation of exposure profiles to determine intrinsic toxicity potential rather than using absolute maximum concentrations or time-weighted averages as surrogates. A decision scheme is proposed to guide selection of risk assessment approaches using dose extrapolation based on Haber's Law, TK-TD models, and/or IBMs depending on the nature of toxic effect and timing in relation to life history.

The insecticide imidacloprid causes mortality of the freshwater amphipod Gammarus pulex by interfering with feeding behavior

If an organism does not feed, it dies of starvation. Even though some insecticides which are used to control pests in agriculture can interfere with feeding behavior of insects and other invertebrates, the link from chemical exposure via affected feeding activity to impaired life history traits, such as survival, has not received much attention in ecotoxicology. One of these insecticides is the neonicotinoid imidacloprid, a neurotoxic substance acting specifically on the insect nervous system. We show that imidacloprid has the potential to indirectly cause lethality in aquatic invertebrate populations at low, sublethal concentrations by impairing movements and thus feeding. We investigated feeding activity, lipid content, immobility, and survival of the aquatic arthropod Gammarus pulex under exposure to imidacloprid. We performed experiments with 14 and 21 days duration, both including two treatments with two high, one day pulses of imidacloprid and one treatment with a low, constant concentration. Feeding of G. pulex as well as lipid content were significantly reduced under exposure to the low, constant imidacloprid concentration (15 µg/L). Organisms were not able to move and feed--and this caused high mortality after 14 days of constant exposure. In contrast, feeding and lipid content were not affected by repeated imidacloprid pulses. In these treatments, animals were mostly immobilized during the chemical pulses but did recover relatively fast after transfer to clean water. We also performed a starvation experiment without exposure to imidacloprid which showed that starvation alone does not explain the mortality in the constant imidacloprid exposure. Using a multiple stressor toxicokinetic-toxicodynamic modeling approach, we showed that both starvation and other toxic effects of imidacloprid play a role for determining mortality in constant exposure to the insecticide.

A method to predict and understand fish survival under dynamic chemical stress using standard ecotoxicity data

The authors present a method to predict fish survival under exposure to fluctuating concentrations and repeated pulses of a chemical stressor. The method is based on toxicokinetic-toxicodynamic modeling using the general unified threshold model of survival (GUTS) and calibrated using raw data from standard fish acute toxicity tests. The model was validated by predicting fry survival in a fish early life stage test. Application of the model was demonstrated by using Forum for Co-ordination of Pesticide Fate Models and Their Use surface water (FOCUS-SW) exposure patterns as model input and predicting the survival of fish over 485 d. Exposure patterns were also multiplied by factors of five and 10 to achieve higher exposure concentrations for fish survival predictions. Furthermore, the authors quantified how far the exposure profiles were below the onset of mortality by finding the corresponding exposure multiplication factor for each scenario. The authors calculated organism recovery times as additional characteristic of toxicity as well as number of peaks, interval length between peaks, and mean duration as additional characteristics of the exposure pattern. The authors also calculated which of the exposure patterns had the smallest and largest inherent potential toxicity. Sensitivity of the model to parameter changes depends on the exposure pattern and differs between GUTS individual tolerance and GUTS stochastic death. Possible uses of the additional information gained from modeling to inform risk assessment are discussed.

Effects of repeated pulsed herbicide exposures on the growth of aquatic macrophytes

Many contaminants are released into aquatic systems intermittently in a series of pulses. Pulse timing and magnitude can vary according to usage, compound-specific physicochemical properties, and use area characteristics. Standard laboratory ecotoxicity tests typically employ continuous exposure concentrations over defined durations and thus may not accurately and realistically reflect the effects of certain compounds on aquatic organisms, resulting in potential over- or underestimation. Consequently, the relative effects of pulsed (2 and 4 d) and continuous exposures of the duckweed Lemna minor to isoproturon, metsulfuron-methyl, and pentachlorophenol over a period of 42 d were explored in the present study. At the highest test concentrations, exposure of L. minor to pulses of metsulfuron-methyl resulted in effects on growth similar to those of an equivalent continuous exposure. For isoproturon, pulsed exposures had a lower impact than a corresponding continuous exposure, whereas the effect of pentachlorophenol delivered in pulses was greater. These differences may be explained by compound-specific uptake and degradation or dissipation rates in plants and the recovery potential that occurs following pulses for different pesticides. Given these results, use of a simple time-weighted average approach to estimate effects of intermittent exposures from short-term standard toxicity studies may not provide an accurate prediction that reflects realistic exposure scenarios. Development of mechanistic modeling approaches may facilitate better estimates of effects from intermittent exposures.