In the European framework for assessing the ecological effects of plant protection products on aquatic organisms, standard tests usually rely on constant laboratory exposure. This Tier 1 approach may lead to overly conservative assessments for short-term exposures lasting only a few hours under realistic environmental conditions. To address this, the European Food Safety Authority proposed a Tier 2C assessment to incorporate more realistic dynamic exposure profiles through refined tests and toxicokinetic/toxicodynamic (TKTD) modeling. Currently, the only accepted TKTD model for macrophyte growth inhibition relates to the duckweed Lemna sp. We hypothesize that this model can be adapted for other macrophytes including sediment rooted macrophytes. We propose a Modeling Approach for Growth inhibition of MAcrophytes (MAGMA), to simulate both constant and dynamic exposure tests under laboratory conditions. The model was calibrated using experimental data from Myriophyllum spicatum exposed to two herbicides with different modes of action. Validation against single and two-pulse exposure experiments showed good agreement between model predictions and observed data. The modeling approach, MAGMA can therefore serve as a valuable Tier 2C tool for predicting macrophyte growth rates under dynamic exposure conditions.

The inclusion of analytics in soil invertebrate laboratory studies is gaining increasing attention in the European risk assessment of plant protection products (PPPs). Analytics in soil were recently requested for fast-dissipating compounds in the revised Central Zone Working Document. However, the Working Document, as well as the technical Organization for Economic Co-operation and Development (OECD) testing guidelines, lack clarity on (1) how to design the laboratory studies to reliably fulfill this requirement, (2) how to consider the analytically measured values to derive robust ecotoxicological endpoints, and (3) how to use endpoints that consider time-variable exposure in the test, in the risk assessment of PPPs. A hypothetical case study is presented to show the impact on the risk assessment when ecotoxicological endpoints that are expressed as time-weighted average (TWA) concentrations are compared with maximum predicted environmental concentrations (PEC) in soil to calculate a Tier 1 toxicity-exposure-ratio (TER). The persistent compound would pass the critical TER trigger of 5, whereas the fast-dissipating compound fails the risk assessment. However, a fast dissipation of a compound is, from an environmental perspective, a favorable substance property and especially inherent for biological products. This sets the wrong motivation for the development of new PPPs. The suitability of using TWA-PECs in the risk assessment instead of maximum PECs is discussed by comparing temporal exposure scenarios in the test system with scenarios that may occur under realistic field situations. This analysis shows that potential underestimation of the risks may occur only for specific situations where the PEC in soil temporally exceeds the regulatory acceptable concentration over time. In such cases, the use of TWA-PECs in soil may be applicable in the risk assessment, provided the assumption of reciprocity is fulfilled. A reciprocity check can be performed via tailored ecotoxicological testing and/or effect modeling to justify the use of TWA-PECs in the risk assessment.

Linking Dynamic Energy Budget (DEB) models with toxicokinetic-toxicodynamic (TKTD) modules allows for an integrated mechanistic interpretation of lethal and sublethal effects of a species exposed to a toxicant, which has been proposed as a refinement option in the chronic risk assessment of pesticides. Yet, terrestrial non-target arthropods (NTAs) are an underrepresented group when it comes to readily available DEB models in the Add-my-Pet (AmP) portal. One reason for this is that many insect species have complex life cycles, particularly with regard to the acquisition and turnover of reproductive energy, that cannot be adequately represented by existing predefined DEB model variants.In this study we attempted to parametrize DEB models for four regulatory relevant NTAs, the predatory mite Typhlodromus pyri, the parasitic wasp Aphidius rhopalosiphi, the seven-spot ladybird beetle Coccinella septempunctata, and the green lacewing Chrysoperla carnea with data obtained from open literature and additional laboratory experiments. While parametrization of T. pyri was not possible due to a lack of essential calibration data, the other species could be successfully parametrized through appropriate model adaptations. The life cycle of A. rhopalosiphi could be accurately modeled with the hax model variant, a predefined DEB model for holometabolous insects, which assumes that energetic investment in reproduction mainly takes place during the larval phase. A parasitization module was added to this model allowing to simulate the parasitization rate of A. rhopalosiphi depending on several known influencing factors: the initial reproduction buffer size, host density, host type, temperature, and timing during the reproductive phase. For both C. septempunctata and C. carnea, a new model variant was developed which, in contrast to the existing models for holometabolous insects, assumes that the energetic investment in the formation of eggs takes place mainly after the emergence of the imago. We propose this new model variant as a template for other terrestrial insect species with life-history strategies similar to C. septempunctata and C. carnea. Due to the good representation of the calibration data and a well struck balance between model accuracy and model complexity, we consider all three models suitable for use in DEB-TKTD modeling for regulatory purposes.

Honey bees are important pollinators of wild and cultivated plants. They are therefore a key species in the environmental risk assessment of plant protection products in the European Union. As empirical assessments of effects on honey bees on field and landscape level are challenging, mechanistic modelling offers a powerful complement. Such models can predict exposure and effects in the field and are therefore increasingly accepted within the regulatory framework. The BEEHAVEecotox model is a model which links exposure to colony effects in a mechanistic manner. It uses standard regulatory data to derive individual-level dose-response functions and includes larval mortality. However, it requires separate exposure pathways to be represented using pathway-specific dose-response parameters, making parameterization challenging. We developed an alternative based on the general unified threshold model of survival (GUTS), a generic toxicokinetic-toxicodynamic (TKTD) model. It combines exposure pathways into one effect module with one set of parameters. We present BEEHAVEecoGUTS, the integration of GUTS as an optional effect module in the modular design of BEEHAVEecotox. We found that the effect predictions of the original dose-response and the GUTS module are broadly comparable in semi-field tunnel scenarios, while exploratory repeated exposure scenarios revealed stronger divergences between the modules, particularly at higher application rates. GUTS is therefore a viable alternative with simpler and more robust compound specific parameterization and a broader scope for further expansion. It moves from single point estimates of toxicity and exposure to a holistic exposure-effect link.

The normal operating range (NOR) is defined as the natural variability observed in the properties of organisms and their populations and communities, as driven by various biological and environmental factors. Although still in the exploration phase within pesticide environmental risk assessment (ERA) frameworks, NOR concepts present an opportunity to provide ecological context to effect assessments and support the operationalization of specific protection goals. Discussions from an expert workshop explored possibilities for NOR derivation and applicability across organism groups, highlighting potential benefits and key challenges. While recent efforts suggest that NOR-based approaches could enhance decision making in pesticide ERA, key challenges remain, including defining fit-for-purpose effect thresholds, ensuring approach consistency across ecological contexts, and addressing data limitations. Establishing NORs in regulatory practice will require stakeholder collaborations for improved data accessibility, standardized statistical methodologies, and a clear framework for integrating natural variability into decision-making processes. Ecological modeling could support identifying sources of variability, helping contextualize observed effects and inform risk characterization based on regulatory thresholds. A harmonized approach that integrates empirical data and transparent statistical and computational methodologies will be essential for the successful implementation of NOR concepts in pesticide ERA.

Digitalization in agriculture is rapidly progressing. Smart farming technology and usage of farm management information systems implementing detailed geospatial data are used more frequently. The authorization approach of plant protection products in Europe does not currently make use of these advances. A 90th percentile protection goal is currently often established based on a few scenarios representing a realistic worst case of agri-environmental conditions. Within this process, the products receive authorization and mitigation requirements on the product label, which usually cover all fields, no matter whether the field is very vulnerable or not. This is a pragmatic approach that may lead to sufficient protection of most fields while other fields are accepted as being underprotected. To overcome the limitations of the current assessment based on a few worst-case scenarios, a transformation of the current risk assessment scheme towards a digital-driven field-specific risk management is proposed in three phases. The risk assessment procedure on European Union and Member State level would remain in large parts as it is. All three phases make use of the availability of farm management information systems to distribute field-specific restrictions and mitigation requirements. In phase 1, the mitigation requirements, based on standard regulatory scenarios (e.g., FOCUS [Forum for Co-ordination of Pesticide Fate Models and Their Use]), are transferred to the specific fields showing the closest similarities of environmental conditions. In phase 2, field-specific modeling is performed where the standard parameterization can be adapted for local conditions. In phase 3, geospatial data are used to derive field-specific parameterizations for the exposure and effect models. In all phases, each field receives application restrictions and mitigation requirements depending on the local situation, which farmers can provide by combining different mitigation options from a mitigation toolbox. The proposed scheme increases protection of biodiversity without compromising yield production.

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

Population models have long been thought of as a suitable approach for assessing the population relevance of chemical effects observed on individuals in laboratory studies, although they have rarely been applied in a regulatory context. We modeled potential population-level responses of individual-level adverse effects induced by endocrine-disrupting chemicals (EDCs). We imposed three effect durations (10-year, 3 months summer, or winter) for six common EDC endpoints (fecundity, fertilization rate, sex ratio: male and female skew, courtship and nesting behavior) at four magnitudes of effect (10, 20, 50 and 90% reduction) using individual-based population models for three fish species with differing life histories: stickleback (Gasterosteus aculeatus), brown trout (Salmo trutta) and zebrafish (Danio rerio). The suitability of different assessment criteria for determining the significance of population responses was evaluated. For all endpoints tested individually, effect magnitudes of 20% did not result in any population-level responses in each of the three species, except in the stickleback, where a 20% reduction in fecundity or fertilization rate led to population declines (in these cases, effect magnitudes of 10% did not result in population-level responses). Once standardized, our "exposure-agnostic molecule-independent" approach will enhance our understanding of population outcomes within the regulatory hazard-based assessment of EDCs.

Risk assessment for bees is mainly based on data for honey bees; however, risk assessment is intended to protect all bee species. This raises the question of whether data for honey bees are a good proxy for other bee species. This issue is not new and has resulted in several publications in which the sensitivity of bee species is compared based on the values of the 48-h median lethal dose (LD50) from acute test results. When this approach is used, observed differences in sensitivity may result both from differences in kinetics and from inherent differences in species sensitivity. In addition, the physiology of the bee, like its overall size, the size of the honey stomach (for acute oral tests), and the physical appearance (for acute contact tests) also influences the sensitivity of the bee. The recently introduced Toxicokinetic-Toxicodynamic (TKTD) model that was developed for the interpretation of honey bee tests (Bee General Uniform Threshold Model for Survival [BeeGUTS]) could integrate the results of acute oral tests, acute contact tests, and chronic tests within one consistent framework. We show that the BeeGUTS model can be calibrated and validated for other bee species and also that the honey bee is among the more sensitive bee species. In addition, we found that differences in sensitivity between species are smaller than previously published comparisons based on 48-h LD50 values. The time-dependency of the LD50 and the specifics of the bee physiology are the main causes of the wider variation found in the published literature. Environ Toxicol Chem 2024;43:1431-1441. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

In agricultural landscapes, solitary bees occur in a large diversity of species and are important for crop and wildflower pollination. They are distinguished from honey bees and bumble bees by their solitary lifestyle as well as different nesting strategies, phenologies, and floral preferences. Their ecological traits and presence in agricultural landscapes imply potential exposure to pesticides and suggest a need to conduct ecological risk assessments for solitary bees. However, assessing risks to the large diversity of managed and wild bees across landscapes and regions poses a formidable challenge. Population models provide tools to estimate potential population-level effects of pesticide exposures, can support field study design and interpretation, and can be applied to expand study data to untested conditions. We present a population model for solitary bees, SolBeePopecotox, developed for use in the context of ecological risk assessments. The trait-based model extends a previous version with the explicit representation of exposures to pesticides from relevant routes. Effects are implemented in the model using a simplified toxicokinetic-toxicodynamic model, BeeGUTS (GUTS = generalized unified threshold model for survival), adapted specifically for bees. We evaluated the model with data from semifield studies conducted with the red mason bee, Osmia bicornis, in which bees were foraging in tunnels over control and insecticide-treated oilseed rape fields. We extended the simulations to capture hypothetical semifield studies with two soil-nesting species, Nomia melanderi and Eucera pruinosa, which are difficult to test in empirical studies. The model provides a versatile tool for higher-tier risk assessments, for instance, to estimate effects of potential exposures, expanding available study data to untested species, environmental conditions, or exposure scenarios. Environ Toxicol Chem 2024;43:2645-2661. © 2024 SETAC.

The use of toxicokinetic-toxicodynamic (TKTD) modeling in regulatory risk assessment of plant protection products is increasingly popular, especially since the 2018 European Food Safety Authority (EFSA) opinion on TKTD modeling 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 Simple Algae Model Extended (SAM-X) 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 Organisation for Economic Co-operation and Development (OECD) growth inhibition test. Thus, every virtual laboratory test has a duration of 72 h, 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 study demonstrates that for simulation of 72-h 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 median exposure profile 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 present a simplified example for chlorotoluron and isoproturon. The present case study brings to life our proposed framework for TKTD modeling of algae to establish whether a given exposure can be considered to be of low risk. Environ Toxicol Chem 2023;42:1823-1838. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Natural and seminatural habitats of soil living organisms in cultivated landscapes can be subject to unintended exposure by active substances of plant protection products (PPPs) used in adjacent fields. Spray-drift deposition and runoff are considered major exposure routes into such off-field areas. In this work, we develop a model (xOffFieldSoil) and associated scenarios to estimate exposure of off-field soil habitats. The modular model approach consists of components, each addressing a specific aspect of exposure processes, for example, PPP use, drift deposition, runoff generation and filtering, estimation of soil concentrations. The approach is spatiotemporally explicit and operates at scales ranging from local edge-of-field to large landscapes. The outcome can be aggregated and presented to the risk assessor in a way that addresses the dimensions and scales defined in specific protection goals (SPGs). The approach can be used to assess the effect of mitigation options, for example, field margins, in-field buffers, or drift-reducing technology. The presented provisional scenarios start with a schematic edge-of-field situation and extend to real-world landscapes of up to 5 km × 5 km. A case study was conducted for two active substances of different environmental fate characteristics. Results are presented as a collection of percentiles over time and space, as contour plots, and as maps. The results show that exposure patterns of off-field soil organisms are of a complex nature due to spatial and temporal variabilities combined with landscape structure and event-based processes. Our concepts and analysis demonstrate that more realistic exposure data can be meaningfully consolidated to serve in standard-tier risk assessments. The real-world landscape-scale scenarios indicate risk hot-spots that support the identification of efficient risk mitigation. As a next step, the spatiotemporally explicit exposure data can be directly coupled to ecological effect models (e.g., for earthworms or collembola) to conduct risk assessments at biological entity levels as required by SPGs. Integr Environ Assess Manag 2024;20:263-278. © 2023 Applied Analysis Solutions LLC and WSC Scientific GmbH and Bayer AG and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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

ADVERTISEMENT RETURN TO ISSUEViewpointNEXTIncreased Realism in Risk Assessment and Management of Agrochemicals for a Better Balance between Food Production and Environmental ProtectionRobin Sur*Robin SurRegulatory Science − Environmental Safety, Bayer AG Crop Science Division, 40789 Monheim, Germany*Corresponding author: Robin Sur.More by Robin Surhttps://orcid.org/0000-0002-3403-8168, Thomas G. PreussThomas G. PreussRegulatory Science − Environmental Safety, Bayer AG Crop Science Division, 40789 Monheim, GermanyMore by Thomas G. Preuss, and Andrew C. ChappleAndrew C. ChappleRegulatory Science − Environmental Safety, Bayer AG Crop Science Division, 40789 Monheim, GermanyMore by Andrew C. ChappleCite this: ACS Agric. Sci. Technol. 2023, 3, 6, 455–456Publication Date (Web):June 6, 2023Publication History Received14 April 2023Accepted26 May 2023Revised24 May 2023Published online6 June 2023Published inissue 19 June 2023https://pubs.acs.org/doi/10.1021/acsagscitech.3c00106https://doi.org/10.1021/acsagscitech.3c00106article-commentaryACS PublicationsCopyright © 2023 American Chemical SocietyRequest reuse permissionsArticle Views163Altmetric-Citations1LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Environmental modeling,Pest control,Risk assessment,Soils,Testing and assessment Get e-Alerts

To assess the effect of plant protection products on pollinator colonies, the higher tier of environmental risk assessment (ERA), for managed honey bee colonies and other pollinators, is in need of a mechanistic effect model. Such models are seen as a promising solution to the shortcomings, which empirical risk assessment can only overcome to a certain degree. A recent assessment of 40 models conducted by the European Food Safety Authority (EFSA) revealed that BEEHAVE is currently the only publicly available mechanistic honey bee model that has the potential to be accepted for ERA purposes. A concern in the use of this model is a lack of model validation against empirical data, spanning field studies conducted in different regions of Europe and covering the variability in colony and environmental conditions. We filled this gap with a BEEHAVE validation study against 66 control colonies of field studies conducted across Germany, Hungary, and the United Kingdom. Our study implements realistic initial colony size and landscape structure to consider foraging options. Overall, the temporal pattern of colony strength is predicted well. Some discrepancies between experimental data and prediction outcomes are explained by assumptions made for model parameterization. Complementary to the recent EFSA study using BEEHAVE, our validation covers a large variability in colony conditions and environmental impacts representing the Northern and Central European Regulatory Zones. Thus we believe that BEEHAVE can be used to serve the development of specific protection goals as well as the development of simulation scenarios for the European Regulatory Zone. Subsequently, the model can be applied as a standard tool for higher tier ERA of managed honey bees using the mechanistic ecotoxicological module for BEEHAVE, BEEHAVEecotox . Environ Toxicol Chem 2023;42:1839-1850. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Under current European Union regulation, the risks to aquatic organisms must be assessed for uses of plant protection products (PPPs) that may result in exposure to the environment. For herbicidal PPPs, aquatic macrophytes are often the most sensitive taxa. For some herbicidal modes of action, macrophytes may be affected only while they are actively growing. For the risk assessment, it is therefore useful to know whether application timings would result in surface water exposure during periods when aquatic macrophytes are actively growing (therefore potentially resulting in effects). Toxicity endpoints, which are based on studies with active growth, may be overconservative in cases where exposure of PPPs will not co-occur with active macrophyte growth. A comprehensive literature search was performed, using systematic and manual approaches, with the aim of identifying the main active growth period for macrophytes in natural freshwater bodies in climates relevant to the Central and Northern zones of the European Union. The results of the searches were screened initially to identify all potentially relevant references, for which a full evaluation was then performed. Reliability was assessed using the principles of the Klimisch scoring system. As part of the full evaluation, growth periods were identified for each macrophyte species studied. Finally, the extracted growth periods were considered together to determine an overall active growth period for aquatic macrophytes representative of the Central and Northern EU zones. Based on this literature review, the active growth period identified for most aquatic macrophyte species representative of the Central and Northern EU zones is April to September. Relating to the regulatory implication of these results, it may be possible to conclude a low risk for aquatic macrophytes if the predicted surface water exposure period for certain PPPs is demonstrated to be outside the periods of active growth. Integr Environ Assess Manag 2024;20:1125-1139. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Physiologically based kinetic (PBK) models are a promising tool for xenobiotic environmental risk assessment that could reduce animal testing by predicting in vivo exposure. PBK models for birds could further our understanding of species-specific sensitivities to xenobiotics, but would require species-specific parameterization. To this end, we summarize multiple major morphometric and physiological characteristics in chickens, particularly laying hens (Gallus gallus) and mallards (Anas platyrhynchos) in a meta-analysis of published data. Where such data did not exist, data are substituted from domesticated ducks (Anas platyrhynchos) and, in their absence, from chickens. The distribution of water between intracellular, extracellular, and plasma is similar in laying hens and mallards. Similarly, the lengths of the components of the small intestine (duodenum, jejunum, and ileum) are similar in chickens and mallards. Moreover, not only are the gastrointestinal absorptive areas similar in mallard and chickens but also they are similar to those in mammals when expressed on a log basis and compared to log body weight. In contrast, the following are much lower in laying hens than mallards: cardiac output (CO), hematocrit (Hct), and blood hemoglobin. There are shifts in ovary weight (increased), oviduct weight (increased), and plasma/serum concentrations of vitellogenin and triglyceride between laying hens and sexually immature females. In contrast, reproductive state does not affect the relative weights of the liver, kidneys, spleen, and gizzard.

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

Physiologically-based kinetic (PBK) models are effective tools for designing toxicological studies and conducting extrapolations to inform hazard characterization in risk assessment by filling data gaps and defining safe levels of chemicals. In the present work, a generic avian PBK model for male and female birds was developed using PK-Sim and MoBi from the Open Systems Pharmacology Suite (OSPS). The PBK model includes an ovulation model (egg development) to predict concentrations of chemicals in eggs from dietary exposure. The model was parametrized for chicken (Gallus gallus), bobwhite quail (Colinus virginianus) and mallard duck (Anas platyrhynchos) and was tested with nine chemicals for which in vivo studies were available. Time-concentration profiles of chemicals reaching tissues and egg compartment were simulated and compared to in vivo data. The overall accuracy of the PBK model predictions across the analyzed chemicals was good. Model simulations were found to be in the range of 22-79% within a 3-fold and 41-89% were within 10- fold deviation of the in vivo observed data. However, for some compounds scarcity of in-vivo data and inconsistencies between published studies allowed only a limited goodness of fit evaluation. The generic avian PBK model was developed following a "best practice" workflow describing how to build a PBK model for novel species. The credibility and reproducibility of the avian PBK models were scored by evaluation according to the available guidance documents from WHO (2010), and OECD (2021), to increase applicability, confidence and acceptance of these in silico models in chemical risk assessment.

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