Co-occurrence of macroplastics, microplastics, and legacy and emerging plasticisers in UK soils.

Despite a theoretical link between plastic and plasticiser occurrence in the terrestrial environment, there are few empirical studies of the relationship between these contaminants in soils. We carried out a field study to assess the co-occurrence of plastic waste, and legacy and emerging plasticisers in UK soils (n = 19) from various land uses (woodlands, urban roadsides, urban parklands, landfill-associated). Surface plastics and soil microplastics were quantified and characterised using ATR-FTIR and µ-FTIR. Eight legacy (phthalate) and three emerging (adipate, citrate, trimellitate) plasticisers were quantified using GC-MS. Surface plastics were found at higher prevalence at landfill-associated and urban roadside sites, with levels significantly (2 orders of magnitude) greater than in woodlands. Microplastics were detected in landfill-associated (mean 12.3 particles g-1 dw), urban roadside (17.3 particles g-1 dw) and urban parkland (15.7 particles g-1 dw) soils, but not in woodland soils. The most commonly detected polymers were polyethene, polypropene and polystyrene. Mean ∑plasticiser concentration in urban roadside soils (3111 ng g-1 dw) was significantly higher than in woodlands (134 ng g-1 dw). No significant difference was found between landfill-associated (318 ng g-1 dw) and urban parkland (193 ng g-1 dw) soils and woodlands. Di-n-butyl phthalate (94.7% detection frequency) and the emerging plasticiser trioctyl trimellitate (89.5%) were the most commonly detected plasticisers, with diethylhexyl phthalate (493 ng g-1 dw) and di-iso-decyl phthalate (96.7 ng g-1 dw) present at the highest concentrations. ∑plasticiser concentrations were significantly correlated with surface plastic (R2 = 0.23), but not with soil microplastic concentrations. Whilst plastic litter seems a fundamental source of plasticisers in soils, mechanisms such as airborne transport from source areas may be as important. Based on the data from this study, phthalates remain the dominant plasticisers in soils, but emerging plasticisers are already widespread, as reflected by their presence in all land uses studied.

A Novel Lepidoptera bioassay analysed using a reduced GUTS model.

Lepidopteran species can be both pests and also beneficial pollinators for agricultural crops. However, despite these important roles, the effects of pesticides on this diverse taxa are relatively understudied. To facilitate the assessment of pesticides and other chemical hazards on this taxa, we present a novel bioassay capable of testing chemical sensitivity to lepidopteran larvae through dietary exposure. We used Mamestra brassicae caterpillars as a model lepidopteran and tested their sensitivity for the organophosphate insecticide chlorpyrifos. We exposed larvae to an artificial diet spiked with chlorpyrifos and monitored survival over time, as well as weight change over a 96-hour exposure period. To test the repeatability and reliability of the developed bioassay, the experiment was repeated three times. The survival in time data collected enabled analysis with the General Unified Threshold of Survival (GUTS) model, recently recognized by EFSA as a ready-to-use tool for regulatory purposes. The GUTS modelling was used to derive a set of relevant toxicokinetic and toxicodynamic parameters relating to the larval response to exposure over time. We found that across the three repeats studies there was no more than a threefold difference in LC50 values (13.1, 18.7 and 8.1 mg/Kg) at 48 h and fourfold difference at 96 h, highlighting the repeatability of the bioassay. We also highlighted the potential of the method to observe sub-lethal effects such as changes in weight. Finally, we discuss the applications of this new bioassay method to chemical risk assessments and its potential for use in other scenarios, such as mixture or pulsed exposure testing.

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

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

The genome sequence of the red compost earthworm, Lumbricus rubellus (Hoffmeister, 1843).

We present a genome assembly from an individual Lumbricus rubellus (the red compost earthworm; Annelida; Clitellata; Haplotaxida; Lumbricidae). The genome sequence is 787.5 megabases in span. Most of the assembly is scaffolded into 18 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 15.81 kilobases in length. Gene annotation of this assembly on Ensembl identified 33,426 protein coding genes.

The genome sequence of the common earthworm, Lumbricus terrestris (Linnaeus, 1758).

We present a genome assembly from an individual Lumbricus terrestris (the common earthworm; Annelida; Clitellata; Haplotaxida; Lumbricidae). The genome sequence is 1,056.5 megabases in span. Most of the assembly is scaffolded into 18 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 15.93 kilobases in length.

Molecular insights into high-altitude adaption and acclimatisation of Aporrectodea caliginosa.

Here, we explore the high-altitude adaptions and acclimatisation of Aporrectodea caliginosa Population diversity is assessed through mitochondrial barcoding, identifying closely related populations across the island of Pico (Azores). We present the first megabase N50 assembly size (1.2 Mbp) genome for A. caliginosa High- and low-altitude populations were exposed experimentally to a range of oxygen and temperature conditions, simulating altitudinal conditions, and the transcriptomic responses explored. SNP densities are assessed to identify signatures of selective pressure and their link to differentially expressed genes. The high-altitude A. caliginosa population had lower differential expression and fewer co-expressed genes between conditions, indicating a more condition-refined epigenetic response. Genes identified as under adaptive pressure through Fst and nucleotide diversity in the high-altitude population clustered around the differentially expressed an upstream environmental response control gene, HMGB1. The high-altitude population of A. caliginosa indicated adaption and acclimatisation to high-altitude conditions and suggested resilience to extreme weather events. This mechanistic understanding could help offer a strategy in further identifying other species capable of maintaining soil fertility in extreme environments.

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

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

Soil Ecotoxicology Needs Robust Biomarkers: A Meta-Analysis Approach to Test the Robustness of Gene Expression-Based Biomarkers for Measuring Chemical Exposure Effects in Soil Invertebrates.

Gene expression-based biomarkers are regularly proposed as rapid, sensitive, and mechanistically informative tools to identify whether soil invertebrates experience adverse effects due to chemical exposure. However, before biomarkers could be deployed within diagnostic studies, systematic evidence of the robustness of such biomarkers to detect effects is needed. In our study, we present an approach for conducting a meta-analysis of the robustness of gene expression-based biomarkers in soil invertebrates. The approach was developed and trialed for two measurements of gene expression commonly proposed as biomarkers in soil ecotoxicology: earthworm metallothionein (MT) gene expression for metals and earthworm heat shock protein 70 (HSP70) gene expression for organic chemicals. We collected 294 unique gene expression data points from the literature and used linear mixed-effect models to assess concentration, exposure duration, and species effects on the quantified response. The meta-analysis showed that the expression of earthworm MT was strongly metal concentration dependent, stable over time and species independent. The metal concentration-dependent response was strongest for cadmium, indicating that this gene is a suitable biomarker for this metal. For copper, no clear concentration-dependent response of MT gene expression in earthworms was found, indicating MT is not a reliable biomarker for this metal. For HSP70, overall marginal up-regulation and lack of a concentration-dependent response indicated that this gene is not suitable as a biomarker for organic pollutant effects in earthworms. The present study demonstrates how meta-analysis can be used to assess the status of biomarkers. We encourage colleagues to apply this open-access approach to other biomarkers, as such quantitative assessment is a prerequisite to ensuring that the suitability and limitations of proposed biomarkers are known and stated. Environ Toxicol Chem 2022;41:2124-2138. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Refinement of the selection of physicochemical properties for grouping and read-across of nanoforms.

Before placing a new nanoform (NF) on the market, its potential adverse effects must be evaluated. This may e.g. be done via hazard and risk assessment. Grouping and read-across of NFs is a possible strategy to reduce resource consumption, maximising the use of existing data for assessment of NFs. The GRACIOUS project provides a framework in which possible grouping and read-across for NFs is mainly based on an evaluation of their similarity. The impact of NFs on human health and the environment depends strongly on the concentration of the NF and its physicochemical properties, such as chemical composition, size distribution, shape, etc. Hence, knowledge of the most relevant physicochemical properties is essential information for comparing similarity. The presented work aims to refine existing proposals for sets of descriptors (descriptor array) that are needed to describe distinct NFs of a material to identify the most relevant ones for grouping and read-across. The selection criteria for refining this descriptor array are explained and demonstrated. Relevant protocols and methods are proposed for each physicochemical property. The required and achievable measurement accuracies of the refined descriptor array are reviewed, as this information is necessary for similarity assessment of NFs based on individual physicochemical properties.

Impacts of Life-Time Exposure of Arsenic, Cadmium and Fluoranthene on the Earthworms' L. rubellus Global DNA Methylation as Detected by msAFLP.

This study reports on the effects of long-term exposure to the metals arsenic (As), cadmium (Cd) and the polycyclic aromatic hydrocarbon fluoranthene on the survival, growth, development and DNA methylation status of the earthworm Lumbricus rubellus. Exposures to the three chemicals were conducted over their whole juvenile developmental period from egg to adult. Significant effects on one or more measured endpoints were found for all three chemicals. Arsenic had no effect on survival, but had a significant effect on growth rates at concentrations of 36 mg/kg or higher and also slowed the rate of maturation. Cadmium significantly reduced juvenile survival at 500 mg/kg, juvenile growth at 148 mg/kg and maturation rates at all tested concentrations. Fluoranthene had no effect on survival or the developmental period, but did significantly reduce growth rates at 800 mg/kg. Effects at these concentrations are consistent with the known effects of these three chemicals on earthworms from previous studies conducted mainly with Eisenia fetida. Both As and Cd had no effect on DNA methylation patterning in earthworms measured at the end of the exposure. Fluoranthene was shown, for the first time. to have an effect on a species' DNA methylation levels. These results suggest that apical phenotypic changes for As and Cd are not necessarily associated with changes in DNA methylation profiles. However, exposure to the organic chemical fluoranthene influenced DNA methylation patterns, suggesting wider remodelling of the epigenome for this chemical.

Proportional contributions to organic chemical mixture effects in groundwater and surface water.

Semi-quantitative GC-MS and LC-MS measurements of organic chemicals in groundwater and surface waters were used to assess the overall magnitude and contribution of the most important substances to calculated mixture hazard. Here we use GC-MS and LC-MS measurements taken from two separate national monitoring programs for groundwater and surface water in England, in combination with chronic species sensitivity distribution (SSD) HC50 values published by Posthuma et al. (2019, Environ. Toxicol. Chem, 38, 905-917) to calculate individual substance hazard quotients and mixture effects using a concentration addition approach. The mixture analysis indicated that, as anticipated, there was an increased hazard from the presence of a cocktail of substances at sites compared to the hazard for any single chemical. The magnitude of the difference between the hazard attributed to the most important chemical and the overall mixture effect, however, was not large. Thus, the most toxic chemical contributed ≥ 20% of the calculated mixture effect in >99% of all measured groundwater and surface water samples. On the basis of this analysis, a 5 fold assessment factor placed on the risk identified for any single chemical would offer a high degree of in cases where implementation of a full mixture analysis was not possible. This finding is consistent with previous work that has assessed chemical mixture effects within field monitoring programs and as such provides essential underpinning for future policy and management decisions on how to effectively and proportionately manage mixture risks.

Worst-case ranking of organic chemicals detected in groundwaters and surface waters in England.

The Environment Agency has been using Gas Chromatography-Mass Spectrometry (GC-MS) and Accurate-mass Quadrupole Time-of-Flight (Q-TOF) / Liquid Chromatography-Mass Spectrometry (LC-MS) target screen analysis to semi-quantitatively measure organic substances in groundwater and surface water since 2009 for GC-MS and 2014 for LC-MS. Here we use this data to generate a worst-case "risk" ranking of the detected substances. Three sets of hazard values relating to effects on aquatic organisms, namely Water Framework Directive EQSs, NORMAN Network PNECs (hereafter NORMAN PNEC) and chronic Species Sensitivity Distribution (SSD) HC50s from Posthuma et al., (2019) were used for the assessment. These hazard values were compared to the highest measured concentration for each chemical to generate a worst-case hazard quotient (HQ). Calculated HQs for each metric were ranked, averaged and multiplied by rank for detection frequency to generate an overall ordering based on HQ and occurrence. This worst-case approach was then used to generate ranking lists for GC-MS and LC-MS detected substances in groundwater and surface water. Pesticides in the top 30 overall ranked list included more legacy pesticides in groundwater and more current use actives in surface water. Specific uses were linked to some high rankings (e.g. rotenone for invasive species control). A number of industrial and plastics associated chemicals were ranked highly in the groundwater dataset, while more personal care products and pharmaceuticals were highly ranked in surface waters. Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) compounds were commonly highly ranked in both environmental compartments. The approach confirmed high rankings for some substance (e.g. selected pesticides) from previous prioritization exercises, but also identified novel substance for consideration (e.g. some PFAS compounds and pharmaceuticals). Overall our approach provided a simple approach using readily accessible data to identify substances for further and more detailed assessment.

Accumulation of nylon microplastics and polybrominated diphenyl ethers and effects on gut microbial community of Chironomus sancticaroli.

Microplastics (MP) are emerging contaminants with the capacity to bind and transport hydrophobic organic compounds of environmental concern, such as polybrominated diphenyl ethers (PBDEs). The aim of this study was to investigate the ingestion of nylon (polyamide) MP alone and when associated with PBDEs and their effects on Chironomus sancticaroli larvae survival and microbiome structure. Survival, PBDE uptake and microbial community composition were measured in fourth instar larvae exposed for 96 h to BDEs- 47, 99, 100 and 153 in the presence and absence of 1% w/w MP in sediment. Microbiome community structures were determined through high throughput sequencing of 16S small subunit ribosomal RNA gene (16S rRNA). Initial experiments showed that larvae ingested MP faster at 0.5% w/w MP, while depuration was more efficient at 1% w/w MP, although retention of MP was seen even after 168 h depuration. No mortality was observed as a result of PBDEs and MP exposure. MP had a negative effect on PBDE concentration within larvae (η2 = 0.94) and a negative effect on sediment concentrations (η2 = 0.48). In all samples, microbial communities were dominated by Alphaproteobacteria, Betaproteobacteria, Actinobacteria and Gammaproteobacteria. Bacterial alpha diversity was not significantly affected by PBDEs or MP exposure. However, the abundance of discrete bacterial taxa was more sensitive to MP (X2 = 45.81, p = 0.02), and PBDE exposure. Our results highlight that C. sancticaroli showed no acute response to MPs and PBDEs, but that MPs influenced bacterial microbiome structure even after only short-term acute exposure.

Long-term cattle grazing shifts the ecological state of forest soils.

Cattle grazing profoundly affects abiotic and biotic characteristics of ecosystems. While most research has been performed on grasslands, the effect of large managed ungulates on forest ecosystems has largely been neglected. Compared to a baseline seminatural state, we investigated how long-term cattle grazing of birch forest patches affected the abiotic state and the ecological community (microbes and invertebrates) of the soil subsystem. Grazing strongly modified the soil abiotic environment by increasing phosphorus content, pH, and bulk density, while reducing the C:N ratio. The reduced C:N ratio was strongly associated with a lower microbial biomass, mainly caused by a reduction of fungal biomass. This was linked to a decrease in fungivorous nematode abundance and the nematode channel index, indicating a relative uplift in the importance of the bacterial energy-channel in the nematode assemblages. Cattle grazing highly modified invertebrate community composition producing distinct assemblages from the seminatural situation. Richness and abundance of microarthropods was consistently reduced by grazing (excepting collembolan richness) and grazing-associated changes in soil pH, Olsen P, and reduced soil pore volume (bulk density) limiting niche space and refuge from physical disturbance. Anecic earthworm species predominated in grazed patches, but were absent from ungrazed forest, and may benefit from manure inputs, while their deep vertical burrowing behavior protects them from physical disturbance. Perturbation of birch forest habitat by long-term ungulate grazing profoundly modified soil biodiversity, either directly through increased physical disturbance and manure input or indirectly by modifying soil abiotic conditions. Comparative analyses revealed the ecosystem engineering potential of large ungulate grazers in forest systems through major shifts in the composition and structure of microbial and invertebrate assemblages, including the potential for reduced energy flow through the fungal decomposition pathway. The precise consequences for species trophic interactions and biodiversity-ecosystem function relationships remain to be established, however.

What Is on the Outside Matters-Surface Charge and Dissolve Organic Matter Association Affect the Toxicity and Physiological Mode of Action of Polystyrene Nanoplastics to C. elegans.

To better understand nanoplastic effects, the potential for surface functionalization and dissolve organic matter eco-corona formation to modify the mechanisms of action and toxicity of different nanoplastics needs to be established. Here, we assess how different surface charges modifying functionalization (postive (+ve) aminated; neutral unfunctionalized; negative (-ve) carboxylated) altered the toxicity of 50 and 60 nm polystyrene nanoplastics to the nematode Caenorhabditis elegans. The potency for effects on survival, growth, and reproduction reduced in the order +ve aminated > neutral unfunctionalized ≫ -ve carboxylated with toxicity >60-fold higher for the +ve than -ve charged forms. Toxicokinetic-toxicodynamic modeling (DEBtox) showed that the charge-related potency was primarily linked to differences in effect thresholds and dose-associated damage parameters, rather than to toxicokinetic parameters. This suggests that surface functionalization may change the nature of nanoplastic interactions with membrane and organelles leading to variations in toxicity. Eco-corona formation reduced the toxicity of all nanoplastics indicating that organic molecule associations may passivate surfaces. Between particles, eco-corona interactions resulting in more equivalent effects; however, even despite these changes, the order of potency of the charged forms was retained. These results have important implications for the development of future grouping approaches.

Off-Target Stoichiometric Binding Identified from Toxicogenomics Explains Why Some Species Are More Sensitive than Others to a Widely Used Neonicotinoid.

Neonicotinoids are currently licensed for use in 120 countries, making accurate nontarget species sensitivity predictions critical. Unfortunately, such predictions are fraught with uncertainty, as sensitivity is extrapolated from only a few test species and neonicotinoid sensitivities can differ greatly between closely related taxa. Combining classical toxicology with de novo toxicogenomics could greatly improve sensitivity predictions and identify unexpectedly susceptible species. We show that there is a >30-fold differential species sensitivity (DSS) for the neonicotinoid imidacloprid between five earthworm species, a critical nontarget taxon. This variation could not be explained by differential toxicokinetics. Furthermore, comparing key motif expression in subunit genes of the classical nicotinic acetylcholine receptor (nAChR) target predicts only minor differences in the ligand binding domains (LBDs). In contrast, predicted dissimilarities in LBDs do occur in the highly expressed but nonclassical targets, acetylcholine binding proteins (AChBPs). Critically, the predicted AChBP divergence is capable of explaining DSS. We propose that high expression levels of putative nonsynaptic AChBPs with high imidacloprid affinities reduce imidacloprid binding to critical nAChRs involved in vital synaptic neurotransmission. This study provides a clear example of how pragmatic interrogation of key motif expression in complex multisubunit receptors can predict observed DSS, thereby informing sensitivity predictions for essential nontarget species.

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

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

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.