HARNESSING MODELLING FOR ASSESSING THE POPULATION RELEVANCE OF EXPOSURE TO ENDOCRINE ACTIVE CHEMICALS

The presence of endocrine active chemicals (EACs) in the environment continues to cause concern for wildlife given their potential for adverse effects on organisms. However, there is a significant lack of understanding on the potential effects of EACs on populations. This has real-world limitations for EAC management and regulation, where the aim in environmental risk assessment is to protect populations. Here we propose a methodological approach for the application of modelling in addressing the population relevance of EAC exposure in fish. We provide a case study with the fungicide prochloraz to illustrate how this approach could be applied. Two population models, one for brown trout (Salmo trutta, inSTREAM) and the other for three-spined stickleback (Gasterosteus aculeatus) that met regulatory requirements for development and validation were used in this study. Effects data extracted from the literature were combined with environmentally realistic exposure profiles generated with the FOCUS SW software. Population-level effects for prochloraz were observed in some modelling scenarios (hazard-threshold) but not others (dose-response), demonstrating the repercussions of making different decisions on implementation of exposure and effects. The population responses, defined through changes in abundance and biomass, of both trout and stickleback exposed to prochloraz were similar, indicating that the use of conservative effects/exposure decisions in model parameterisation may be of greater significance in determining population-level adverse effects to EAC exposure than life-history characteristics. Our study supports the use of models as an effective approach to evaluate the adverse effects of EACs on fish populations. In particular, our hazard-threshold parameterisation is proposed for the use of population modelling in a regulatory context in accordance with Commission Regulation (EU) 2018/605.

Heterogeneity in biological assemblages and exposure in chemical risk assessment: Exploring capabilities and challenges in methodology with two landscape-scale case studies

Chemical exposure concentrations and the composition of ecological receptors (e.g., species) vary in space and time, resulting in landscape-scale (e.g. catchment) heterogeneity. Current regulatory, prospective chemical risk assessment frameworks do not directly address this heterogeneity because they assume that reasonably worst-case chemical exposure concentrations co-occur (spatially and temporally) with biological species that are the most sensitive to the chemical's toxicity. Whilst current approaches may parameterise fate models with site-specific data and aim to be protective, a more precise understanding of when and where chemical exposure and species sensitivity co-occur enables risk assessments to be better tailored and applied mitigation more efficient. We use two aquatic case studies covering different spatial and temporal resolution to explore how geo-referenced data and spatial tools might be used to account for landscape heterogeneity of chemical exposure and ecological assemblages in prospective risk assessment. Each case study followed a stepwise approach: i) estimate and establish spatial chemical exposure distributions using local environmental information and environmental fate models; ii) derive toxicity thresholds for different taxonomic groups and determine geo-referenced distributions of exposure-toxicity ratios (i.e., potential risk); iii) overlay risk data with the ecological status of biomonitoring sites to determine if relationships exist. We focus on demonstrating whether the integration of relevant data and potential approaches is feasible rather than making comprehensive and refined risk assessments of specific chemicals. The case studies indicate that geo-referenced predicted environmental concentration estimations can be achieved with available data, models and tools but establishing the distribution of species assemblages is reliant on the availability of a few sources of biomonitoring data and tools. Linking large sets of geo-referenced exposure and biomonitoring data is feasible but assessment of risk will often be limited by the availability of ecotoxicity data. The studies highlight the important influence that choices for aggregating data and for the selection of statistical metrics have on assessing and interpreting risk at different spatial scales and patterns of distribution within the landscape. Finally, we discuss approaches and development needs that could help to address environmental heterogeneity in chemical risk assessment.

The BEEHAVEecotox Model-Integrating a Mechanistic Effect Module into the Honeybee Colony Model

Mechanistic effect models are powerful tools for extrapolating from laboratory studies to field conditions. For bees, several good models are available that can simulate colony dynamics. Controlled and reliable experimental systems are also available to estimate the inherent toxicity of pesticides to individuals. However, there is currently no systematic and mechanistic way of linking the output of experimental ecotoxicological testing to bee models for bee risk assessment. We introduce an ecotoxicological module that mechanistically links exposure with the hazard profile of a pesticide for individual honeybees so that colony effects emerge. This mechanistic link allows the translation of results from standard laboratory studies to relevant parameters and processes for simulating bee colony dynamics. The module was integrated into the state-of-the-art honeybee model BEEHAVE. For the integration, BEEHAVE was adapted to mechanistically link the exposure and effects on different cohorts to colony dynamics. The BEEHAVEecotox model was tested against semifield (tunnel) studies, which were deemed the best study type to test whether BEEHAVEecotox predicted realistic effect sizes under controlled conditions. Two pesticides used as toxic standards were chosen for this validation to represent two different modes of action: acute mortality of foragers and chronic brood effects. The ecotoxicological module was able to predict effect sizes in the tunnel studies based on information from standard laboratory tests. In conclusion, the BEEHAVEecotox model is an excellent tool to be used for honeybee risk assessment, interpretation of field and semifield studies, and exploring the efficiency of different mitigation measures. The principles for exposure and effect modules are portable and could be used for any well-constructed honeybee model. Environ Toxicol Chem 2022;41:2870-2882. © 2022 Bayer AG & Sygenta, et al. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The use of ecological models to assess the effects of a plant protection product on ecosystem services provided by an orchard

The objective of this case study was to explore the feasibility of using ecological models for applying an ecosystem services-based approach to environmental risk assessment using currently available data and methodologies. For this we used a 5 step approach: 1) selection of environmental scenario, 2) ecosystem service selection, 3) development of logic chains, 4) selection and application of ecological models and 5) detailed ecosystem service assessment. The study system is a European apple orchard managed according to integrated pest management principles. An organophosphate insecticide was used as the case study chemical. Four ecosystem services are included in this case study: soil quality regulation, pest control, pollination and recreation. Logic chains were developed for each ecosystem service and describe the link between toxicant effects on service providing units and ecosystem services delivery. For the soil quality regulation ecosystem service, springtails and earthworms were the service providing units, for the pest control ecosystem service it was ladybirds, for the pollination ecosystem service it was honeybees and for the recreation ecosystem service it was the meadow brown butterfly. All the ecological models addressed the spatio-temporal magnitude of the direct effects of the insecticide on the service providing units and ecological production functions were used to extrapolate these outcomes to the delivery of ecosystem services. For all ecosystem services a decision on the acceptability of the modelled and extrapolated effects on the service providing units could be made using the protection goals as set by the European Food Safety Authority (EFSA). Developing quantitative ecological production functions for extrapolation of ecosystem services delivery from population endpoints remains one of the major challenges. We feel that the use of ecological models can greatly add to this development, although the further development of existing ecological models, and of new models, is needed for this.

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.

Three questions to ask before using model outputs for decision support

Decision makers must have sufficient confidence in models if they are to influence their decisions. We propose three screening questions to critically evaluate models with respect to their purpose, organization, and evidence. They enable a more transparent, robust, and secure use of model outputs.

Applying a mechanistic model to predict interacting effects of chemical exposure and food availability on fish populations

The potential environmental impacts of chemical exposures on wildlife are of growing concern. Freshwater ecosystems are vulnerable to chemical effects and wildlife populations, including fish, can be exposed to concentrations known to cause adverse effects at the individual level. Wild fish populations are also often subjected to numerous other stressors simultaneously which in temperate climates often include sustained periods of food limitation. The potential interactive effects of chemical exposures and food limitation on fish populations are however difficult to establish in the field. Mechanistic modelling approaches can be employed to help predict how the physiological effects of chemicals and food limitation on individuals may translate to population-level effects. Here an energy budget-individual-based model was developed and the control (no chemical) model was validated for the three-spined stickleback. Findings from two endocrine active chemical (EAC) case studies, (ethinyloestradiol and trenbolone) were then used to investigate how effects on individual fecundity translated into predicted population-level effects for environmentally relevant exposures. The cumulative effects of chemical exposure and food limitation were included in these analyses. Results show that effects of each EAC on the population were dependent on energy availability, and effects on population abundance were exacerbated by food limitation. Findings suggest that chemical effects and density dependent food competition interact to determine population responses to chemical exposures. Our study illustrates how mechanistic modelling approaches might usefully be applied to account for specific chemical effects, energy budgets and density-dependent competition, to provide a more integrated evaluation of population outcomes in chemical risk assessments.

Behavior underpins the predictive power of a trait-based model of butterfly movement

Dispersal ability is key to species persistence in times of environmental change. Assessing a species' vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or an index of mobility derived from expert opinion, or a mechanistic modeling approach that extrapolates displacement rates from empirical data on short-term movements.Here, we compare and evaluate the success of the correlative and mechanistic approaches using a mechanistic random-walk model of butterfly movement that incorporates relationships between wingspan and sex-specific movement behaviors.The model was parameterized with new data collected on four species of butterfly in the south of England, and we observe how wingspan relates to flight speeds, turning angles, flight durations, and displacement rates.We show that flight speeds and turning angles correlate with wingspan but that to achieve good prediction of displacement even over 10 min the model must also include details of sex- and species-specific movement behaviors.We discuss what factors are likely to differentially motivate the sexes and how these could be included in mechanistic models of dispersal to improve their use in ecological forecasting.

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.

Data on the movement behaviour of four species of grassland butterfly

This Data in Brief article describes data on the movement behaviour of four species of grassland butterflies collected over three years and at four sites in southern England. The datasets consist of the movement tracks of Maniola jurtina, Aricia agestis, Pyronia tithonus, and Melanargia galathea, recorded using standard methods and presented as steps distances and turning angles. Sites consisted of nectar-rich field margins, meadows, and mown short turf grasslands with minimal flowers. In total, 783 unique movement tracks were collected. The data were used for analysing the movement behaviour of the species and for parameterising individual-based movement models.

Predicting impacts of chemicals from organisms to ecosystem service delivery: A case study of insecticide impacts on a freshwater lake

Assessing and managing risks of anthropogenic activities to ecological systems is necessary to ensure sustained delivery of ecosystem services for future generations. Ecological models provide a means of quantitatively linking measured risk assessment endpoints with protection goals, by integrating potential chemical effects with species life history, ecological interactions, environmental drivers and other potential stressors. Here we demonstrate how an ecosystem modeling approach can be used to quantify insecticide-induced impacts on ecosystem services provided by a lake from toxicity data for organism-level endpoints. We used a publicly available aquatic ecosystem model AQUATOX that integrates environmental fate of chemicals and their impacts on food webs in aquatic environments. By simulating a range of exposure patterns, we illustrated how exposure to a hypothetical insecticide could affect aquatic species populations (e.g., recreational fish abundance) and environmental properties (e.g., water clarity) that would in turn affect delivery of ecosystem services. Different results were observed for different species of fish, thus the decision to manage the use of the insecticide for ecosystem services derived by anglers depends upon the favored species of fish. In our hypothetical shallow reservoir, water clarity was mostly driven by changes in food web dynamics, specifically the presence of zooplankton. In contrast to the complex response by fishing value, water clarity increased with reduced insecticide use, which produced a monotonic increase in value by waders and swimmers. Our study clearly showed the importance of considering nonlinear ecosystem feedbacks where the presence of insecticide changed the modeled food-web dynamics in unexpected ways. Our study highlights one of the main advantages of using ecological models for risk assessment, namely the ability to generalize to meaningful levels of organization and to facilitate quantitative comparisons among alternative scenarios and associated trade-offs among them while explicitly accounting for different groups of beneficiaries.

Integrating the influence of weather into mechanistic models of butterfly movement

BACKGROUND

Understanding the factors influencing movement is essential to forecasting species persistence in a changing environment. Movement is often studied using mechanistic models, extrapolating short-term observations of individuals to longer-term predictions, but the role of weather variables such as air temperature and solar radiation, key determinants of ectotherm activity, are generally neglected. We aim to show how the effects of weather can be incorporated into individual-based models of butterfly movement thus allowing analysis of their effects.

METHODS

We constructed a mechanistic movement model and calibrated it with high precision movement data on a widely studied species of butterfly, the meadow brown (Maniola jurtina), collected over a 21-week period at four sites in southern England. Day time temperatures during the study ranged from 14.5 to 31.5 °C and solar radiation from heavy cloud to bright sunshine. The effects of weather are integrated into the individual-based model through weather-dependent scaling of parametric distributions representing key behaviours: the durations of flight and periods of inactivity.

RESULTS

Flight speed was unaffected by weather, time between successive flights increased as solar radiation decreased, and flight duration showed a unimodal response to air temperature that peaked between approximately 23 °C and 26 °C. After validation, the model demonstrated that weather alone can produce a more than two-fold difference in predicted weekly displacement.

CONCLUSIONS

Individual Based models provide a useful framework for integrating the effect of weather into movement models. By including weather effects we are able to explain a two-fold difference in movement rate of M. jurtina consistent with inter-annual variation in dispersal measured in population studies. Climate change for the studied populations is expected to decrease activity and dispersal rates since these butterflies already operate close to their thermal optimum.

Assessing the population relevance of endocrine-disrupting effects for nontarget vertebrates exposed to plant protection products

The European Commission intends to protect vertebrate wildlife populations by regulating plant protection product (PPP) active substances that have endocrine-disrupting properties with a hazard-based approach. In this paper we consider how the Commission's hazard-based regulation and accompanying guidance can be operationalized to ensure that a technically robust process is used to distinguish between substances with adverse population-level effects and those for which it can be demonstrated that adverse effects observed (typically in the laboratory) do not translate into adverse effects at the population level. Our approach is to use population models within the adverse outcome pathway framework to link the nonlinear relationship between adverse effects at the individual and population levels in the following way: (1) use specific protection goals for focal wildlife populations within an ecosystem services framework; (2) model the effects of changes in population-related inputs on focal species populations with individual-based population models to determine thresholds between negligible and nonnegligible (i.e., adverse) population-level effects; (3) compare these thresholds with the relevant endpoints from laboratory toxicity tests to determine whether they are likely to be exceeded at hazard-based limits or the maximum tolerated dose/concentration from the experimental studies. If the population threshold is not exceeded, then the substance should not be classified as an endocrine disruptor with population-relevant adversity unless there are other lines of evidence within a weight-of-evidence approach to challenge this. We believe this approach is scientifically robust and still addresses the political and legal requirement for a hazard-based assessment. Integr Environ Assess Manag 2019;15:278-291. © 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Predicting impacts of chemicals from organisms to ecosystem service delivery: A case study of endocrine disruptor effects on trout

We demonstrate how mechanistic modeling can be used to predict whether and how biological responses to chemicals at (sub)organismal levels in model species (i.e., what we typically measure) translate into impacts on ecosystem service delivery (i.e., what we care about). We consider a hypothetical case study of two species of trout, brown trout (Salmo trutta; BT) and greenback cutthroat trout (Oncorhynchus clarkii stomias; GCT). These hypothetical populations live in a high-altitude river system and are exposed to human-derived estrogen (17α‑ethinyl estradiol, EE2), which is the bioactive estrogen in many contraceptives. We use the individual-based model inSTREAM to explore how seasonally varying concentrations of EE2 could influence male spawning and sperm quality. Resulting impacts on trout recruitment and the consequences of such for anglers and for the continued viability of populations of GCT (the state fish of Colorado) are explored. inSTREAM incorporates seasonally varying river flow and temperature, fishing pressure, the influence of EE2 on species-specific demography, and inter-specific competition. The model facilitates quantitative exploration of the relative importance of endocrine disruption and inter-species competition on trout population dynamics. Simulations predicted constant EE2 loading to have more impacts on GCT than BT. However, increasing removal of BT by anglers can enhance the persistence of GCT and offset some of the negative effects of EE2. We demonstrate how models that quantitatively link impacts of chemicals and other stressors on individual survival, growth, and reproduction to consequences for populations and ecosystem service delivery, can be coupled with ecosystem service valuation. The approach facilitates interpretation of toxicity data in an ecological context and gives beneficiaries of ecosystem services a more explicit role in management decisions. Although challenges remain, this type of approach may be particularly helpful for site-specific risk assessments and those in which tradeoffs and synergies among ecosystem services need to be considered.

Assessing and mitigating simulated population-level effects of 3 herbicides to a threatened plant: Application of a species-specific population model of Boltonia decurrens

Extrapolating from organism-level endpoints, as generated from standard pesticide toxicity tests, to populations is an important step in threatened and endangered species risk assessments. We apply a population model for a threatened herbaceous plant species, Boltonia decurrens, to estimate the potential population-level impacts of 3 herbicides. We combine conservative exposure scenarios with dose-response relationships for growth and survival of standard test species and apply those in the species-specific model. Exposure profiles applied in the B. decurrens model were estimated using exposure modeling approaches. Spray buffer zones were simulated by using corresponding exposure profiles, and their effectiveness at mitigating simulated effects on the plant populations was assessed with the model. From simulated exposure effects scenarios that affect plant populations, the present results suggest that B. decurrens populations may be more sensitive to exposures from herbicide spray drift affecting vegetative stages than from runoff affecting early seedling survival and growth. Spray application buffer zones were shown to be effective at reducing effects on simulated populations. Our case study demonstrates how species-specific population models can be applied in pesticide risk assessment to bring organism-level endpoints, exposure assumptions, and species characteristics together in an ecologically relevant context. Environ Toxicol Chem 2018;37:1545-1555. © 2018 SETAC.

Developing population models: A systematic approach for pesticide risk assessment using herbaceous plants as an example

Population models are used as tools in species management and conservation and are increasingly recognized as important tools in pesticide risk assessments. A wide variety of population model applications and resources on modeling techniques, evaluation and documentation can be found in the literature. In this paper, we add to these resources by introducing a systematic, transparent approach to developing population models. The decision guide that we propose is intended to help model developers systematically address data availability for their purpose and the steps that need to be taken in any model development. The resulting conceptual model includes the necessary complexity to address the model purpose on the basis of current understanding and available data. We provide specific guidance for the development of population models for herbaceous plant species in pesticide risk assessment and demonstrate the approach with an example of a conceptual model developed following the decision guide for herbicide risk assessment of Mead's milkweed (Asclepias meadii), a species listed as threatened under the US Endangered Species Act. The decision guide specific to herbaceous plants demonstrates the details, but the general approach can be adapted for other species groups and management objectives. Population models provide a tool to link population-level dynamics, species and habitat characteristics as well as information about stressors in a single approach. Developing such models in a systematic, transparent way will increase their applicability and credibility, reduce development efforts, and result in models that are readily available for use in species management and risk assessments.

Capturing ecology in modeling approaches applied to environmental risk assessment of endocrine active chemicals in fish

Endocrine active chemicals (EACs) are widespread in freshwater environments and both laboratory and field based studies have shown reproductive effects in fish at environmentally relevant exposures. Environmental risk assessment (ERA) seeks to protect wildlife populations and prospective assessments rely on extrapolation from individual-level effects established for laboratory fish species to populations of wild fish using arbitrary safety factors. Population susceptibility to chemical effects, however, depends on exposure risk, physiological susceptibility, and population resilience, each of which can differ widely between fish species. Population models have significant potential to address these shortfalls and to include individual variability relating to life-history traits, demographic and density-dependent vital rates, and behaviors which arise from inter-organism and organism-environment interactions. Confidence in population models has recently resulted in the EU Commission stating that results derived from reliable models may be considered when assessing the relevance of adverse effects of EACs at the population level. This review critically assesses the potential risks posed by EACs for fish populations, considers the ecological factors influencing these risks and explores the benefits and challenges of applying population modeling (including individual-based modeling) in ERA for EACs in fish. We conclude that population modeling offers a way forward for incorporating greater environmental relevance in assessing the risks of EACs for fishes and for identifying key risk factors through sensitivity analysis. Individual-based models (IBMs) allow for the incorporation of physiological and behavioral endpoints relevant to EAC exposure effects, thus capturing both direct and indirect population-level effects.

Modeling Effects of Honeybee Behaviors on the Distribution of Pesticide in Nectar within a Hive and Resultant in-Hive Exposure

Recently, the causes of honeybee colony losses have been intensely studied, showing that there are multiple stressors implicated in colony declines, one stressor being the exposure to pesticides. Measuring exposure of individual bees within a hive to pesticide is at least as difficult as assessing the potential exposure of foraging bees to pesticide. We present a model to explore how heterogeneity of pesticide distribution on a comb in the hive can be driven by worker behaviors. The model contains simplified behaviors to capture the extremes of possible heterogeneity of pesticide location/deposition within the hive to compare with exposure levels estimated by averaging values across the comb. When adults feed on nectar containing the average concentration of all pesticide brought into the hive on that particular day, it is likely representative of the worst-case exposure scenario. However, for larvae, clustering of pesticide in the comb can lead to higher exposure levels than taking an average concentration in some circumstances. The potential for extrapolating the model to risk assessment is discussed.

A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals

Protection of ecosystem services is increasingly emphasized as a risk-assessment goal, but there are wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various types of biological interactions and feedbacks. For illustration, the authors introduce 2 case studies that employ well-developed and validated mechanistic effects models: the inSTREAM individual-based model for fish populations and the AQUATOX ecosystem model. They also show how dynamic energy budget theory can provide a common currency for interpreting organism-level toxicity. They suggest that a framework based on mechanistic models that predict impacts on ecosystem services resulting from chemical exposure, combined with economic valuation, can provide a useful approach for informing environmental management. The authors highlight the potential benefits of using this framework as well as the challenges that will need to be addressed in future work. Environ Toxicol Chem 2017;36:845-859. © 2017 SETAC.

Colony impact of pesticide-induced sublethal effects on honeybee workers: A simulation study using BEEHAVE

Research on neonicotinoids and honeybees have changed focus from direct mortality to sublethal effects. In the present study, a published honeybee model, BEEHAVE, is used to compare induced colony level impact of pesticides including direct mortality, poor brood care, disorientation, and increased handling time in oilseed rape and sunflower crops. Actual effects on individual bees will depend on exposure concentrations, but in the present study large effects were enforced. In oilseed rape, poor brood care had the largest colony impact, because it created a bottleneck for spring build-up of the workforce, and colony impact for all effect types peaked 1 mo after exposure ceased. In sunflower, the later exposure changed the response so colony impact peaked during exposure, and the bottleneck was honey store build-up. In all scenarios, good forage mitigated effects substantially. It is concluded that field studies should continue at least 1 mo after exposure to ensure detection of ecologically relevant sublethal effects. The results indicated that even if a sublethal effect is difficult to detect in the field, subsequent ecologically relevant colony level impacts would be clear if studies are continued for 1 mo after exposure. Guidance for regulatory studies recommends extended observation periods, and published field studies already use extended observation periods, so it is concluded that current methods are adequate for detecting ecologically relevant sublethal effects. Although published laboratory and semifield studies conducted under controlled exposure conditions suggest that sublethal effects may occur, published field studies with neonicotinoid seed treatments, naturally foraging bees, and extended observation periods do not report colony-level effects, suggesting that in these studies no ecologically relevant sublethal effects occurred. Environ Toxicol Chem 2017;36:831-840. © 2016 SETAC.

Population modeling for pesticide risk assessment of threatened species-A case study of a terrestrial plant, Boltonia decurrens

Although population models are recognized as necessary tools in the ecological risk assessment of pesticides, particularly for species listed under the Endangered Species Act, their application in this context is currently limited to very few cases. The authors developed a detailed, individual-based population model for a threatened plant species, the decurrent false aster (Boltonia decurrens), for application in pesticide risk assessment. Floods and competition with other plant species are known factors that drive the species' population dynamics and were included in the model approach. The authors use the model to compare the population-level effects of 5 toxicity surrogates applied to B. decurrens under varying environmental conditions. The model results suggest that the environmental conditions under which herbicide applications occur may have a higher impact on populations than organism-level sensitivities to an herbicide within a realistic range. Indirect effects may be as important as the direct effects of herbicide applications by shifting competition strength if competing species have different sensitivities to the herbicide. The model approach provides a case study for population-level risk assessments of listed species. Population-level effects of herbicides can be assessed in a realistic and species-specific context, and uncertainties can be addressed explicitly. The authors discuss how their approach can inform the future development and application of modeling for population-level risk assessments of listed species, and ecological risk assessment in general. Environ Toxicol Chem 2017;36:480-491. © 2016 SETAC.

Using BEEHAVE to explore pesticide protection goals for European honeybee (Apis melifera L.) worker losses at different forage qualities

Losses of honeybee colonies are intensely debated and although honeybees suffer multiple stressors, the main focus has been on pesticides. As a result, the European Food Safety Authority (EFSA) revised the guidance for pesticide risk assessment for honeybees. The European Food Safety Authority reported a protection goal of negligible effect at 7% of colony size and then used the Khoury honeybee colony model to set trigger values for forager losses. However, the Khoury model is very simplistic and simulates colonies in an idealized state. In the present study, the authors demonstrate how a more realistic published honeybee model, BEEHAVE, with a few simple changes, can be used to explore pesticide risks. The results show that forage availability interacts with pesticide-induced worker losses, and colony resilience increases with forage quality. Adding alternative unexposed forage to the landscape also substantially mitigates the effects of pesticide exposure. The results indicate that EFSA's reported protection goal of 7% of colony size and triggers for daily worker losses are overly conservative. The authors conclude that forage availability is critical for colony resilience and that with adequate forage the colonies are resilient to even high levels of worker losses. However, the authors recommend setting protection goals using suboptimal forage conditions to ensure conservatism and for such suboptimal forage, a total of 20% reduction in colony size was safe. Environ Toxicol Chem 2017;36:254-264. © 2016 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Assessing the risks of pesticides to threatened and endangered species using population modeling: A critical review and recommendations for future work

United States legislation requires the US Environmental Protection Agency to ensure that pesticide use does not cause unreasonable adverse effects on the environment, including species listed under the Endangered Species Act (ESA; hereafter referred to as listed species). Despite a long history of population models used in conservation biology and resource management and a 2013 report from the US National Research Council recommending their use, application of population models for pesticide risk assessments under the ESA has been minimal. The pertinent literature published from 2004 to 2014 was reviewed to explore the availability of population models and their frequency of use in listed species risk assessments. The models were categorized in terms of structure, taxonomic coverage, purpose, inputs and outputs, and whether the models included density dependence, stochasticity, or risk estimates, or were spatially explicit. Despite the widespread availability of models and an extensive literature documenting their use in other management contexts, only 2 of the approximately 400 studies reviewed used population models to assess the risks of pesticides to listed species. This result suggests that there is an untapped potential to adapt existing models for pesticide risk assessments under the ESA, but also that there are some challenges to do so for listed species. Key conclusions from the analysis are summarized, and priorities are recommended for future work to increase the usefulness of population models as tools for pesticide risk assessments. Environ Toxicol Chem 2016;35:1904-1913. © 2016 SETAC.

How to use mechanistic effect models in environmental risk assessment of pesticides: Case studies and recommendations from the SETAC workshop MODELINK

Mechanistic effect models (MEMs) are useful tools for ecological risk assessment of chemicals to complement experimentation. However, currently no recommendations exist for how to use them in risk assessments. Therefore, the Society of Environmental Toxicology and Chemistry (SETAC) MODELINK workshop aimed at providing guidance for when and how to apply MEMs in regulatory risk assessments. The workshop focused on risk assessment of plant protection products under Regulation (EC) No 1107/2009 using MEMs at the organism and population levels. Realistic applications of MEMs were demonstrated in 6 case studies covering assessments for plants, invertebrates, and vertebrates in aquatic and terrestrial habitats. From the case studies and their evaluation, 12 recommendations on the future use of MEMs were formulated, addressing the issues of how to translate specific protection goals into workable questions, how to select species and scenarios to be modeled, and where and how to fit MEMs into current and future risk assessment schemes. The most important recommendations are that protection goals should be made more quantitative; the species to be modeled must be vulnerable not only regarding toxic effects but also regarding their life history and dispersal traits; the models should be as realistic as possible for a specific risk assessment question, and the level of conservatism required for a specific risk assessment should be reached by designing appropriately conservative environmental and exposure scenarios; scenarios should include different regions of the European Union (EU) and different crops; in the long run, generic MEMs covering relevant species based on representative scenarios should be developed, which will require EU-level joint initiatives of all stakeholders involved. The main conclusion from the MODELINK workshop is that the considerable effort required for making MEMs an integral part of environmental risk assessment of pesticides is worthwhile, because it will make risk assessments not only more ecologically relevant and less uncertain but also more comprehensive, coherent, and cost effective.

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.

Predicting Honeybee Colony Failure: Using the BEEHAVE Model to Simulate Colony Responses to Pesticides

To simulate effects of pesticides on different honeybee (Apis mellifera L.) life stages, we used the BEEHAVE model to explore how increased mortalities of larvae, in-hive workers, and foragers, as well as reduced egg-laying rate, could impact colony dynamics over multiple years. Stresses were applied for 30 days, both as multiples of the modeled control mortality and as set percentage daily mortalities to assess the sensitivity of the modeled colony both to small fluctuations in mortality and periods of low to very high daily mortality. These stresses simulate stylized exposure of the different life stages to nectar and pollen contaminated with pesticide for 30 days. Increasing adult bee mortality had a much greater impact on colony survival than mortality of bee larvae or reduction in egg laying rate. Importantly, the seasonal timing of the imposed mortality affected the magnitude of the impact at colony level. In line with the LD50, we propose a new index of "lethal imposed stress": the LIS50 which indicates the level of stress on individuals that results in 50% colony mortality. This (or any LISx) is a comparative index for exploring the effects of different stressors at colony level in model simulations. While colony failure is not an acceptable protection goal, this index could be used to inform the setting of future regulatory protection goals.

Assessing pesticide risks to threatened and endangered species using population models: Findings and recommendations from a CropLife America Science Forum

This brief communication reports on the main findings and recommendations from the 2014 Science Forum organized by CropLife America. The aim of the Forum was to gain a better understanding of the current status of population models and how they could be used in ecological risk assessments for threatened and endangered species potentially exposed to pesticides in the United States. The Forum panelists' recommendations are intended to assist the relevant government agencies with implementation of population modeling in future endangered species risk assessments for pesticides. The Forum included keynote presentations that provided an overview of current practices, highlighted the findings of a recent National Academy of Sciences report and its implications, reviewed the main categories of existing population models and the types of risk expressions that can be produced as model outputs, and provided examples of how population models are currently being used in different legislative contexts. The panel concluded that models developed for listed species assessments should provide quantitative risk estimates, incorporate realistic variability in environmental and demographic factors, integrate complex patterns of exposure and effects, and use baseline conditions that include present factors that have caused the species to be listed (e.g., habitat loss, invasive species) or have resulted in positive management action. Furthermore, the panel advocates for the formation of a multipartite advisory committee to provide best available knowledge and guidance related to model implementation and use, to address such needs as more systematic collection, digitization, and dissemination of data for listed species; consideration of the newest developments in good modeling practice; comprehensive review of existing population models and their applicability for listed species assessments; and development of case studies using a few well-tested models for particular species to demonstrate proof of concept. To advance our common goals, the panel recommends the following as important areas for further research and development: quantitative analysis of the causes of species listings to guide model development; systematic assessment of the relative role of toxicity versus other factors in driving pesticide risk; additional study of how interactions between density dependence and pesticides influence risk; and development of pragmatic approaches to assessing indirect effects of pesticides on listed species.

Risk assessment considerations with regard to the potential impacts of pesticides on endangered species

Simple, deterministic screening-level assessments that are highly conservative by design facilitate a rapid initial screening to determine whether a pesticide active ingredient has the potential to adversely affect threatened or endangered species. If a worst-case estimate of pesticide exposure is below a very conservative effects metric (e.g., the no observed effects concentration of the most sensitive tested surrogate species) then the potential risks are considered de minimis and unlikely to jeopardize the existence of a threatened or endangered species. Thus by design, such compounded layers of conservatism are intended to minimize potential Type II errors (failure to reject a false null hypothesis of de minimus risk), but correspondingly increase Type I errors (falsely reject a null hypothesis of de minimus risk). Because of the conservatism inherent in screening-level risk assessments, higher-tier scientific information and analyses that provide additional environmental realism can be applied in cases where a potential risk has been identified. This information includes community-level effects data, environmental fate and exposure data, monitoring data, geospatial location and proximity data, species biology data, and probabilistic exposure and population models. Given that the definition of "risk" includes likelihood and magnitude of effect, higher-tier risk assessments should use probabilistic techniques that more accurately and realistically characterize risk. Moreover, where possible and appropriate, risk assessments should focus on effects at the population and community levels of organization rather than the more traditional focus on the organism level. This document provides a review of some types of higher-tier data and assessment refinements available to more accurately and realistically evaluate potential risks of pesticide use to threatened and endangered species.

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.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

BEEHAVE: a systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure

A notable increase in failure of managed European honeybee Apis mellifera L. colonies has been reported in various regions in recent years. Although the underlying causes remain unclear, it is likely that a combination of stressors act together, particularly varroa mites and other pathogens, forage availability and potentially pesticides. It is experimentally challenging to address causality at the colony scale when multiple factors interact. In silico experiments offer a fast and cost‐effective way to begin to address these challenges and inform experiments. However, none of the published bee models combine colony dynamics with foraging patterns and varroa dynamics.

We have developed a honeybee model, BEEHAVE, which integrates colony dynamics, population dynamics of the varroa mite, epidemiology of varroa‐transmitted viruses and allows foragers in an agent‐based foraging model to collect food from a representation of a spatially explicit landscape.

We describe the model, which is freely available online (www.beehave-model.net). Extensive sensitivity analyses and tests illustrate the model's robustness and realism. Simulation experiments with various combinations of stressors demonstrate, in simplified landscape settings, the model's potential: predicting colony dynamics and potential losses with and without varroa mites under different foraging conditions and under pesticide application. We also show how mitigation measures can be tested.

Synthesis and applications. BEEHAVE offers a valuable tool for researchers to design and focus field experiments, for regulators to explore the relative importance of stressors to devise management and policy advice and for beekeepers to understand and predict varroa dynamics and effects of management interventions. We expect that scientists and stakeholders will find a variety of applications for BEEHAVE, stimulating further model development and the possible inclusion of other stressors of potential importance to honeybee colony dynamics.

BEEHAVE offers a valuable tool for researchers to design and focus field experiments, for regulators to explore the relative importance of stressors to devise management and policy advice and for beekeepers to understand and predict varroa dynamics and effects of management interventions. We expect that scientists and stakeholders will find a variety of applications for BEEHAVE, stimulating further model development and the possible inclusion of other stressors of potential importance to honeybee colony dynamics.

Pairing behavior and reproduction in Hyalella azteca as sensitive endpoints for detecting long-term consequences of pesticide pulses

The aim of the present study was to examine acute and delayed effects of pulse exposure of the pyrethroid pesticide, permethrin, on precopulatory pairs of Hyalella azteca. Pairs of H. azteca were exposed to a single 1h pulse of different nominal concentrations of permethrin: 0, 0.3, 0.9 or 2.7 μg/L. During exposure, pairing behavior was observed, and during a 56 day post-exposure period the treatments were monitored for pairing behavior, survival and reproductive output. All permethrin-exposed pairs separated within minutes during exposure and shortly thereafter became immobile; however they regained mobility after transfer to clean water. The time to re-form pairs was significantly longer in all tested concentrations compared to the control, although all surviving pairs re-formed within the 56 day test period. Nevertheless not all pairs exposed to 0.9 and 2.7 μg/L reproduced. Furthermore the numbers of juveniles produced by pairs exposed to 0.9 and 2.7 μg/L, but not 0.3 μg/L, were lower throughout the entire post-exposure period compared to the control groups, and the total numbers of juveniles produced during 56 days were significantly lower in organisms exposed to 0.9 and 2.7 μg/L, but not 0.3 μg/L, compared to the control groups. The long-term effects of short-term exposure on reproductive behavior of pairs could potentially have consequences for the population dynamics of H. azteca. However, since individual-level responses can both overestimate and underestimate effects at the population level, appropriate population models are needed to reduce the uncertainty in extrapolating between these levels of biological organization.

Risk communication discourse among ecological risk assessment professionals and its implications for communication with nonexperts

Risk communication, especially to the general public and end users of plant protection products, is an important challenge. Currently, much of the risk communication the general public receives is via the popular press, and risk managers face the challenge of presenting their decisions and their scientific basis to the general public in an understandable way. Therefore, we decided to explore the obstacles in risk communication, as done by expert risk assessors and managers. Using the discourse analysis framework and readability tests, we studied perspectives of 3 stakeholder groups-regulators, industry representatives, and academics across Europe. We conducted 30 confidential interviews (10 participants in each group), with part of the interview guide focused on communication of pesticide risk to the general public and the ideas experts in the field of risk assessment and management hold of the public perception of pesticides. We used the key informant approach in recruiting our participants. They were first identified as key stakeholders in ecological risk assessment of pesticides and then sampled by means of a snowball sampling technique. In the analysis, first we identified main motifs (themes) in each group, and then we moved to studying length of the sentences and grammar and to uncovering discourses present in the text data. We also used the Flesch Reading Ease test to determine the comprehension difficulty of transcribed interviews. The test is commonly used as a standard for estimating the readability of technical documents. Our results highlight 3 main obstacles standing in the way of effective communication with wider audiences. First of all, ecological risk assessment as a highly technical procedure uses the specific language of ecological risk assessment, which is also highly specialized and might be difficult to comprehend by nonexperts. Second, the idea of existing "expert-lay discrepancy," a phenomenon described in risk perception studies is visibly present in the experts' opinions. Finally, the communication flow among stakeholders was perceived as flawed, e.g., our participants did not consider themselves fully included in the communication process, despite taking part in many networks. Interestingly, both studies on the role of trust in risk perception, and research on links between daily choices and perceived risk, show that the public is more likely to rely on experts they can trust, than the experts in our study were inclined to think.

Towards a systems approach for understanding honeybee decline: a stocktaking and synthesis of existing models

The health of managed and wild honeybee colonies appears to have declined substantially in Europe and the United States over the last decade. Sustainability of honeybee colonies is important not only for honey production, but also for pollination of crops and wild plants alongside other insect pollinators. A combination of causal factors, including parasites, pathogens, land use changes and pesticide usage, are cited as responsible for the increased colony mortality.However, despite detailed knowledge of the behaviour of honeybees and their colonies, there are no suitable tools to explore the resilience mechanisms of this complex system under stress. Empirically testing all combinations of stressors in a systematic fashion is not feasible. We therefore suggest a cross-level systems approach, based on mechanistic modelling, to investigate the impacts of (and interactions between) colony and land management.We review existing honeybee models that are relevant to examining the effects of different stressors on colony growth and survival. Most of these models describe honeybee colony dynamics, foraging behaviour or honeybee - varroa mite - virus interactions.We found that many, but not all, processes within honeybee colonies, epidemiology and foraging are well understood and described in the models, but there is no model that couples in-hive dynamics and pathology with foraging dynamics in realistic landscapes.Synthesis and applications. We describe how a new integrated model could be built to simulate multifactorial impacts on the honeybee colony system, using building blocks from the reviewed models. The development of such a tool would not only highlight empirical research priorities but also provide an important forecasting tool for policy makers and beekeepers, and we list examples of relevant applications to bee disease and landscape management decisions.

A toxicokinetic model for thiamethoxam in rats: implications for higher-tier risk assessment

Risk assessment for mammals is currently based on external exposure measurements, but effects of toxicants are better correlated with the systemically available dose than with the external administered dose. So for risk assessment of pesticides, toxicokinetics should be interpreted in the context of potential exposure in the field taking account of the timescale of exposure and individual patterns of feeding. Internal concentration is the net result of absorption, distribution, metabolism and excretion (ADME). We present a case study for thiamethoxam to show how data from ADME study on rats can be used to parameterize a body burden model which predicts body residue levels after exposures to LD50 dose either as a bolus or eaten at different feeding rates. Kinetic parameters were determined in male and female rats after an intravenous and oral administration of (14)C labelled by fitting one-compartment models to measured pesticide concentrations in blood for each individual separately. The concentration of thiamethoxam in blood over time correlated closely with concentrations in other tissues and so was considered representative of pesticide concentration in the whole body. Body burden model simulations showed that maximum body weight-normalized doses of thiamethoxam were lower if the same external dose was ingested normally than if it was force fed in a single bolus dose. This indicates lower risk to rats through dietary exposure than would be estimated from the bolus LD50. The importance of key questions that should be answered before using the body burden approach in risk assessment, data requirements and assumptions made in this study are discussed in detail.

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.

Stakeholders' perspective on ecological modeling in environmental risk assessment of pesticides: challenges and opportunities

The article closely examines the role of mechanistic effect models (e.g., population models) in the European environmental risk assessment (ERA) of pesticides. We studied perspectives of three stakeholder groups on population modeling in ERA of pesticides. Forty-three in-depth, semi-structured interviews were conducted with stakeholders from regulatory authorities, industry, and academia all over Europe. The key informant approach was employed in recruiting our participants. They were first identified as key stakeholders in the field and then sampled by means of a purposive sampling, where each stakeholder identified as important by others was interviewed and asked to suggest another potential participant for our study. Our results show that participants, although having different institutional backgrounds often presented similar perspectives and concerns about modeling. Analysis of repeating ideas and keywords revealed that all stakeholders had very high and often contradicting expectations from models. Still, all three groups expected effect models to become integrated in future ERA of pesticides. Main hopes associated with effect models were to reduce the amount of expensive and complex testing and field monitoring, both at the product development stage, and as an aid to develop mitigation measures. Our analysis suggests that, although the needs of stakeholders often overlapped, subtle differences and lack of trust hinder the process of introducing mechanistic effect models into ERA.