Statistical handling of reproduction data for exposure-response modeling

Deep dive into the chronic toxicity of tyre particle mixtures and their leachates

Particles from the tread of vehicle tyres are a global pollutant, which are emitted into the environment at an approximate rate of 1.4 kg.year-1 for an average passenger-car. In this study, popular tyre brands were used to generate a tyre tread microparticle mixture. The chronic toxicity of both particles and chemical leachates were compared on a planktonic test species (Daphnia magna). Over 21 days of exposure, pristine tyre tread microparticles were more toxic (LC50 60 mg.L-1) than chemical lechates alone (LC50 542 mg.L-1). Microparticles and leachates showed distinct effects on reproduction and morphological development at environmentally relevant concentrations, with dose-dependent uptake of particles visible in the digestive tract. Chemical characterization of leachates revealed a metal predominance of zinc, titanium, and strontium. Of the numerous organic chemicals present, at least 54 were shared across all 5 tyre brands, with many classified to be very toxic. Our results provide a critically needed information on the toxicity of tyre tread particles and the associated chemicals that leach from them to inform future mitigation measures. We conclude that tyre particles are hazardous pollutants of particular concern that are close to or possibly above chronic environmental safety limits in some locations.

Environmental safety of second and third generation bioplastics in the context of the circular economy

Bioplastics derived from organic materials other than crude oil are often suggested as sustainable solutions for tackling end-of-life plastic waste, but little is known of their ecotoxicity to aquatic species. Here, we investigated the ecotoxicity of second and third generation bioplastics toward the freshwater zooplankton Daphnia magna. In acute toxicity tests (48 h), survival was impacted at high concentrations (g.L^-1 range), within the range of salinity-induced toxicity. Macroalgae-derived bioplastic induced hormetic responses under chronic exposure (21 d). Most biological traits were enhanced from 0.06 to 0.25 g.L^-1 (reproduction rate, body length, width, apical spine, protein concentration), while most of these traits returned to controls level at 0.5 g.L^-1. Phenol-oxidase activity, indicative of immune function, was enhanced only at the lowest concentration (0.06 g.L^-1). We hypothesise these suggested health benefits were due to assimilation of carbon derived from the macroalgae-based bioplastic as food. Polymer identity was confirmed by infra-red spectroscopy. Chemical analysis of each bioplastic revealed low metal abundance whilst non target exploration of organic compounds revealed trace amounts of phthalates and flame retardants. The macroalgae-bioplastic disintegrated completely in compost and biodegraded up to 86 % in aqueous medium. All bioplastics acidified the test medium. In conclusion, the tested bioplastics were classified as environmentally safe. Nonetheless, a reasonable end-of-life management of these safer-by-design materials is advised to ensure the absence of harmful effects at high concentrations, depending on the receiving environment.

A critical review of effect modeling for ecological risk assessment of plant protection products

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

Considerations for using reproduction data in toxicokinetic-toxicodynamic modeling

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

In Silico Methods for Environmental Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives

This chapter aims to introduce the reader to the basic principles of environmental risk assessment of chemicals and highlights the usefulness of tiered approaches within weight of evidence approaches in relation to problem formulation i.e., data availability, time and resource availability. In silico models are then introduced and include quantitative structure-activity relationship (QSAR) models, which support filling data gaps when no chemical property or ecotoxicological data are available. In addition, biologically-based models can be applied in more data rich situations and these include generic or species-specific models such as toxicokinetic-toxicodynamic models, dynamic energy budget models, physiologically based models, and models for ecosystem hazard assessment i.e. species sensitivity distributions and ultimately for landscape assessment i.e. landscape-based modeling approaches. Throughout this chapter, particular attention is given to provide practical examples supporting the application of such in silico models in real-world settings. Future perspectives are discussed to address environmental risk assessment in a more holistic manner particularly for relevant complex questions, such as the risk assessment of multiple stressors and the development of harmonized approaches to ultimately quantify the relative contribution and impact of single chemicals, multiple chemicals and multiple stressors on living organisms.

Application of the Closure Principle Computational Approach Test to Assess Ecotoxicological Field Studies: Comparative Analysis Using Earthworm Field Test Abundance Data

Field studies to determine the effects of chemicals on earthworm communities are generally conducted according to International Organization for Standardization standard 11268-3 (and later comments). However, statistical test procedures suggested in the guideline are frequently criticized, mainly for 2 reasons: 1) Earthworm abundances are count data and often do not fulfill requirements for multiple t tests (normal distribution and homogeneity of variance), and 2) the resulting toxicity metrics of multiple testing procedures (no/lowest-observed-effect concentrations [NOEC/LOEC]) fail to adequately detect the actual level of effects. Recently, a new method to overcome these shortcomings was presented by the introduction of the closure principle computational approach test (CPCAT). We applied this statistical method to assess chemical effects on abundance in a large dataset of 26 earthworm field studies (with up to 3 test chemical application rates) and an additional extended study with 6 application rates. A comparative analysis was provided considering results of well-established multiple testing approaches (Dunnett's test) with particular consideration of the degree of overdispersion found in these data. It was shown that the CPCAT detects substantially more effects in earthworm field tests as statistically significant than standard t test approaches. This lowered the LOEC/NOEC for many chemical treatments to control comparisons. As a consequence, the statistically detected NOECs/LOECs were often set at lower percentage deviations between control and chemical treatment. This is the first time the performance of the CPCAT has been assessed within a comprehensive analysis of earthworm field study data. Environ Toxicol Chem 2021;40:1750-1760. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

How to account for the uncertainty from standard toxicity tests in species sensitivity distributions: An example in non-target plants

This research proposes new perspectives accounting for the uncertainty on 50% effective rates (ER₅₀) as interval input for species sensitivity distribution (SSD) analyses and evaluating how to include this uncertainty may influence the 5% Hazard Rate (HR₅) estimation. We explored various endpoints (survival, emergence, shoot-dry-weight) for non-target plants from seven standard greenhouse studies that used different experimental approaches (vegetative vigour vs. seedling emergence) and applied seven herbicides at different growth stages. Firstly, for each endpoint of each study, a three-parameter log-logistic model was fitted to experimental toxicity test data for each species under a Bayesian framework to get a posterior probability distribution for ER₅₀. Then, in order to account for the uncertainty on the ER₅₀, we explored two censoring criteria to automatically censor ER₅₀ taking the ER₅₀ probability distribution and the range of tested rates into account. Secondly, based on dose-response fitting results and censoring criteria, we considered input ER₅₀ values for SSD analyses in three ways (only point estimates chosen as ER₅₀ medians, interval-censored ER₅₀ based on their 95% credible interval and censored ER₅₀ according to one of the two criteria), by fitting a log-normal distribution under a frequentist framework to get the three corresponding HR₅ estimates. We observed that SSD fitted reasonably well when there were at least six distinct intervals for the ER₅₀ values. By comparing the three SSD curves and the three HR₅ estimates, we shed new light on the fact that both propagating the uncertainty from the ER₅₀ estimates and including censored data into SSD analyses often leads to smaller point estimates of HR₅, which is more conservative in a risk assessment context. In addition, we recommend not to focus solely on the point estimate of the HR₅, but also to look at the precision of this estimate as depicted by its 95% confidence interval.

bmd: an R package for benchmark dose estimation

The benchmark dose (BMD) methodology is used to derive a hazard characterization measure for risk assessment in toxicology or ecotoxicology. The present paper's objective is to introduce the R extension package bmd, which facilitates the estimation of BMD and the benchmark dose lower limit for a wide range of dose-response models via the popular package drc. It allows using the most current statistical methods for BMD estimation, including model averaging. The package bmd can be used for BMD estimation for binomial, continuous, and count data in a simple set up or from complex hierarchical designs and is introduced using four examples. While there are other stand-alone software solutions available to estimate BMDs, the package bmd facilitates easy estimation within the established and flexible statistical environment R. It allows the rapid implementation of available, novel, and future statistical methods and the integration of other statistical analyses.

A Review of Recent Advances in Benchmark Dose Methodology

In this review, recent methodological developments for the benchmark dose (BMD) methodology are summarized. Specifically, we introduce the advances for the main steps in BMD derivation: selecting the procedure for defining a BMD from a predefined benchmark response (BMR), setting a BMR, selecting a dose-response model, and estimating the corresponding BMD lower limit (BMDL). Although the last decade has shown major progress in the development of BMD methodology, there is still room for improvement. Remaining challenges are the implementation of new statistical methods in user-friendly software and the lack of consensus about how to derive the BMDL.

The CPCAT as a novel tool to overcome the shortcomings of NOEC/LOEC statistics in ecotoxicology: a simulation study to evaluate the statistical power

Species reproduction is an important determinant of population dynamics. As such, this is an important parameter in environmental risk assessment. The closure principle computational approach test (CPCAT) was recently proposed as a method to derive a NOEC/LOEC for reproduction count data such as the number of juvenile Daphnia. The Poisson distribution used by CPCAT can be too restrictive as a model of the data-generating process. In practice, the generalized Poisson distribution could be more appropriate, as it allows for inequality of the population mean μ and the population variance σ 2 . It is of fundamental interest to explore the statistical power of CPCAT and the probability of determining a regulatory relevant effect correctly. Using a simulation, we varied between Poisson distribution ( μ = σ 2 ) and generalized Poisson distribution allowing for over-dispersion ( μ < σ 2 ) and under-dispersion ( μ > σ 2 ). The results indicated that the probability of detecting the LOEC/NOEC correctly was ≥ 0.8 provided the effect was at least 20% above or below the mean level of the control group and mean reproduction of the control was at least 50 individuals while over-dispersion was missing. Specifically, under-dispersion increased, whereas over-dispersion reduced the statistical power of the CPCAT. Using the well-known Hampel identifier, we propose a simple and straight forward method to assess whether the data-generating process of real data could be over- or under-dispersed.

MOSAIC: a web-interface for statistical analyses in ecotoxicology

In ecotoxicology, bioassays are standardly conducted in order to measure acute or chronic effects of potentially toxic substances on reproduction, growth, and/or survival of living animals. MOSAIC, standing for MOdeling and StAtistical tools for ecotoxICology, is a user-friendly web interface dedicated to the mathematical and statistical modelling of such standard bioassay data. Its simple use makes MOSAIC a turnkey decision-making tool for ecotoxicologists and regulators. Without wasting time on extensive mathematical and statistical technicalities, users are provided with advanced and innovative methods for a valuable quantitative environmental risk assessment. MOSAIC is available at http://pbil.univ-lyon1.fr/software/mosaic/ .

Integrated Modeling of Survival Data from Multiple Stressor Ecotoxicology Experiments

Ecotoxicological assessments often focus on the response of an organism to an individual contaminant under standardized laboratory conditions. Under more ecologically realistic conditions, however, individuals are likely to be exposed to a range of environmental conditions that have the potential to act as additional stressors. Multiple-stressor experiments improve our understanding of an organism's response to a toxicant under ecologically relevant conditions and provide realistic risk assessment data. To date, there is no standardized method for analyzing multiple-stressor data using dose-response regression. We present a reliable technique to assess for the effects of additional stressors on an LCx estimate in a consistent framework, providing interpretable results that meaningfully deal with environmental changes and their possible impacts on sensitivity estimates to a toxicant. The method is applicable to any data set where toxicity tests are conducted at varying levels of one or more additional stressors. We illustrate the method with data from an experiment that investigates the effects of salinity and temperature on the sensitivity of the subantarctic isopod Limnoria stephenseni to copper, where it is shown that the major change in the LC50 can be primarily attributed to a specific temperature increase. This method has been incorporated into an R package available at github.com/ahproctor/LC50.

Optimizing the design of a reproduction toxicity test with the pond snail Lymnaea stagnalis

This paper presents the results from two ring-tests addressing the feasibility, robustness and reproducibility of a reproduction toxicity test with the freshwater gastropod Lymnaea stagnalis (RENILYS strain). Sixteen laboratories (from inexperienced to expert laboratories in mollusc testing) from nine countries participated in these ring-tests. Survival and reproduction were evaluated in L. stagnalis exposed to cadmium, tributyltin, prochloraz and trenbolone according to an OECD draft Test Guideline. In total, 49 datasets were analysed to assess the practicability of the proposed experimental protocol, and to estimate the between-laboratory reproducibility of toxicity endpoint values. The statistical analysis of count data (number of clutches or eggs per individual-day) leading to ECx estimation was specifically developed and automated through a free web-interface. Based on a complementary statistical analysis, the optimal test duration was established and the most sensitive and cost-effective reproduction toxicity endpoint was identified, to be used as the core endpoint. This validation process and the resulting optimized protocol were used to consolidate the OECD Test Guideline for the evaluation of reproductive effects of chemicals in L. stagnalis.

The Effects of Natural and Anthropogenic Microparticles on Individual Fitness in Daphnia magna

Concerns are being raised that microplastic pollution can have detrimental effects on the feeding of aquatic invertebrates, including zooplankton. Both small plastic fragments (microplastics, MPs) produced by degradation of larger plastic waste (secondary MPs; SMPs) and microscopic plastic spheres used in cosmetic products and industry (primary MPs; PMPs) are ubiquitously present in the environment. However, despite the fact that most environmental MPs consist of weathered plastic debris with irregular shape and broad size distribution, experimental studies of organism responses to MP exposure have largely used uniformly sized spherical PMPs. Therefore, effects observed for PMPs in such experiments may not be representative for MP-effects in situ. Moreover, invertebrate filter-feeders are generally well adapted to the presence of refractory material in seston, which questions the potential of MPs at environmentally relevant concentrations to measurably affect digestion in these organisms. Here, we compared responses to MPs (PMPs and SMPs) and naturally occurring particles (kaolin clay) using the cladoceran Daphnia magna as a model organism. We manipulated food levels (0.4 and 9 μg C mL-1) and MP or kaolin contribution to the feeding suspension (<1 to 74%) and evaluated effects of MPs and kaolin on food uptake, growth, reproductive capacity of the daphnids, and maternal effects on offspring survival and feeding. Exposure to SMPs caused elevated mortality, increased inter-brood period and decreased reproduction albeit only at high MP levels in the feeding suspension (74% by particle count). No such effects were observed in either PMP or kaolin treatments. In daphnids exposed to any particle type at the low algal concentration, individual growth decreased by ~15%. By contrast, positive growth response to all particle types was observed at the high algal concentration with 17%, 54% and 40% increase for kaolin, PMP and SMP, respectively. When test particles comprised 22% in the feeding suspension, both MP types decreased food intake by 30%, while kaolin had no effect. Moreover, SMPs were found to homoaggregate in a concentration-dependent manner, which resulted in a 77% decrease of the ingested SMPs compared to PMPs. To better understand MP-processing in the gut, gut passage time (GPT) and evacuation rate of MPs were also assayed. SMPs and PMPs differed in their effects on daphnids; moreover, the particle effects were dependent on the MP: algae ratio in the suspension. When the MP contribution to the particle abundance in the medium changed from 1 to 4%, GPT for daphnids exposed to SMPs increased 2-fold. Our results suggest that MPs and, in particular, SMPs, have a greater capacity to negatively affect feeding in D. magna compared to naturally occurring mineral particles of similar size. Moreover, grazer responses observed in experiments with PMPs cannot be extrapolated to the field where SMPs dominate, because of the greater effects caused by the latter.