Main conclusions and perspectives from the collective scientific assessment of the effects of plant protection products on biodiversity and ecosystem services along the land-sea continuum in France and French overseas territories.

Preservation of biodiversity and ecosystem services is critical for sustainable development and human well-being. However, an unprecedented erosion of biodiversity is observed and the use of plant protection products (PPP) has been identified as one of its main causes. In this context, at the request of the French Ministries responsible for the Environment, for Agriculture and for Research, a panel of 46 scientific experts ran a nearly 2-year-long (2020-2022) collective scientific assessment (CSA) of international scientific knowledge relating to the impacts of PPP on biodiversity and ecosystem services. The scope of this CSA covered the terrestrial, atmospheric, freshwater, and marine environments (with the exception of groundwater) in their continuity from the site of PPP application to the ocean, in France and French overseas territories, based on international knowledge produced on or transposable to this type of context (climate, PPP used, biodiversity present, etc.). Here, we provide a brief summary of the CSA's main conclusions, which were drawn from about 4500 international publications. Our analysis finds that PPP contaminate all environmental matrices, including biota, and cause direct and indirect ecotoxicological effects that unequivocally contribute to the decline of certain biological groups and alter certain ecosystem functions and services. Levers for action to limit PPP-driven pollution and effects on environmental compartments include local measures from plot to landscape scales and regulatory improvements. However, there are still significant gaps in knowledge regarding environmental contamination by PPPs and its effect on biodiversity and ecosystem functions and services. Perspectives and research needs are proposed to address these gaps.

A meta-analysis of ecotoxicological models used for plant protection product risk assessment before their placing on the market.

Before their placing on the market, the safety of plant protection products (PPP) towards both human and animal health, and the environment has to be assessed using experimental and modelling approaches. Models are crucial tools for PPP risk assessment and some even help to avoid animal testing. This review investigated the use of modelling approaches in the ecotoxicology section of PPP active substance assessment reports prepared by the authorities and opened to consultation from 2011 to 2021 in the European Union. Seven categories of models (Structure-Activity, ToxicoKinetic, ToxicoKinetic-ToxicoDynamic, Species Sensitivity Distribution, population, community, and mixture) were searched for into the reports of 317 active substances. At least one model category was found for 44 % of the investigated active substances. The most detected models were Species Sensitivity Distribution, Structure-Activity and ToxicoKinetic for 27, 21 and 15 % of the active substances, respectively. The use of modelling was of particular importance for conventional active substances such as sulfonylurea or carbamates contrary to microorganisms and plant derived substances. This review also highlighted a strong imbalance in model usage among the biological groups considered in the European Regulation (EC) No 1107/2009. For example, models were more often used for aquatic than for terrestrial organisms (e.g., birds, mammals). Finally, a gap between the set of models used in reports and those existing in the literature was observed highlighting the need for the implementation of more sophisticated models into PPP regulation.

A Generalized Physiologically Based Kinetic Model for Fish for Environmental Risk Assessment of Pharmaceuticals.

An increasing number of pharmaceuticals found in the environment potentially impose adverse effects on organisms such as fish. Physiologically based kinetic (PBK) models are essential risk assessment tools, allowing a mechanistic approach to understanding chemical effects within organisms. However, fish PBK models have been restricted to a few species, limiting the overall applicability given the countless species. Moreover, many pharmaceuticals are ionizable, and fish PBK models accounting for ionization are rare. Here, we developed a generalized PBK model, estimating required parameters as functions of fish and chemical properties. We assessed the model performance for five pharmaceuticals (covering neutral and ionic structures). With biotransformation half-lives (HLs) from EPI Suite, 73 and 41% of the time-course estimations were within a 10-fold and a 3-fold difference from measurements, respectively. The performance improved using experimental biotransformation HLs (87 and 59%, respectively). Estimations for ionizable substances were more accurate than any of the existing species-specific PBK models. The present study is the first to develop a generalized fish PBK model focusing on mechanism-based parameterization and explicitly accounting for ionization. Our generalized model facilitates its application across chemicals and species, improving efficiency for environmental risk assessment and supporting an animal-free toxicity testing paradigm.

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).

Water quality of the Meuse watershed: Assessment using a multi-biomarker approach with caged three-spined stickleback (Gasterosteus aculeatus L.).

The use of a multi-biomarker approach with three-spined sticklebacks (Gasterosteus aculeatus) through an active biomonitoring strategy appears to be a promising tool in water quality assessment. The present work proposes to assess the efficiency of these tools in the discrimination of some sites in a large scale on the Meuse basin in Europe. The study was part of an EU program which aims to assess water quality in the Meuse across the French-Belgian border. Sticklebacks were caged 21 days upstream and downstream from the wastewater treatment plants (WWTPs) of Namur (Belgium), Charleville-Mézières (France), Bouillon (Belgium) and Avesnes-sur-Helpe (France). First, the state of a variety of physiological functions was assessed using a battery of biomarkers that represented innate immunity (leucocyte mortality and distribution, phagocytosis activity, respiratory burst), antioxidant system (GPx, CAT, SOD and total GSH content), oxidative damages to the membrane lipids (TBARS), biotransformation enzymes (EROD, GST), synaptic transmission (AChE) and reproduction system (spiggin and vitellogenin concentration). The impacts of the effluents were first analysed for each biomarker using a mixed model ANOVA followed by post-hoc analyses. Secondly, the global river contamination was assessed using a principal component analysis (PCA) followed by a hierarchical agglomerative clustering (HAC). The results highlighted a small number of effects of WWTP effluents on the physiological parameters in caged sticklebacks. Despite a significant effect of the "localisation" factor (upstream/downstream) in the mixed ANOVA for several biomarkers, post-hoc analyses revealed few differences between upstream and downstream of the WWTPs. Only a significant decrease of innate immune responses was observed downstream from the WWTPs of Avesnes-sur-Helpe and Namur. Other biomarker responses were not impacted by WWTP effluents. However, the multivariate analyses (PCA and HAC) of the biomarker responses helped to clearly discriminate the different study sites from the reference but also amongst themselves. Thus, a reduction of general condition (condition index and HSI) was observed in all groups of caged sticklebacks, associated with a weaker AChE activity in comparison with the reference population. A strong oxidative stress was highlighted in fish caged in the Meuse river at Charleville-Mézières whereas sticklebacks caged in the Meuse river at Namur exhibited weaker innate immune responses than others. Conversely, sticklebacks caged in the Helpe-Majeure river at Avesnes-sur-Helpe exhibited higher immune responses. Furthermore, weak defence capacities were recorded in fish caged in the Semois river at Bouillon. This experiment was the first to propose an active biomonitoring approach using three-spined stickleback to assess such varied environments. Low mortality and encouraging results in site discrimination support the use of this tool to assess the quality of a large number of water bodies.

Estimating the cumulative human exposures to pyrethroids by combined multi-route PBPK models: Application to the French population.

Human biomarkers of exposure to pyrethroid insecticides are usually urinary concentrations of metabolites that can be specific to a pyrethroid or common to several compounds. We developed a global toxicokinetic model that links the external exposure to four widely-used pyrethroids and their isomers (deltamethrin and cis and trans isomers of permethrin, cypermethrin, and cyfluthrin) to the urinary concentrations of metabolites (cis- and trans-DCCA, 3-PBA, F-PBA and DBCA). This global model includes physiologically based pharmacokinetic models for each parent compound and one-compartment models for the metabolites. Existing in vivo, in vitro and in silico data were used for model calibration, and human toxicokinetic data for model evaluation. Overall, the global model reproduced the data accurately as about 90% of predictions were inside the 3-fold error interval. A sensitivity analysis showed that the most influent parameter for each urinary metabolite concentration was the fraction of parent compound that is transformed into that metabolite. The global model was then tested with realistic exposures for the French population: the predictions were consistent with biomonitoring data. The global model is a tool that will improve the interpretation of biomonitoring data for pyrethroids.

Regulatory identification of BPA as an endocrine disruptor: Context and methodology.

BPA is one of the most investigated substances for its endocrine disruptor (ED) properties and it is at the same time in the center of many ED-related controversies. The analysis on how BPA fits to the regulatory identification as an ED is a challenge in terms of methodology. It is also a great opportunity to test the regulatory framework with a uniquely data-rich substance and learn valuable lessons for future cases. From this extensive database, it was considered important to engage in a detailed analysis so as to provide specific and strong evidences of ED while reflecting accurately the complexity of the response as well the multiplicity of adverse effects. An appropriate delineation of the scope of the analysis was therefore critical. Four effects namely, alterations of estrous cyclicity, mammary gland development, brain development and memory function, and metabolism, were considered to provide solid evidence of ED-mediated effects of BPA.

Toxicokinetic models and related tools in environmental risk assessment of chemicals.

Environmental risk assessment of chemicals for the protection of ecosystems integrity is a key regulatory and scientific research field which is undergoing constant development in modelling approaches and harmonisation with human risk assessment. This review focuses on state-of-the-art toxicokinetic tools and models that have been applied to terrestrial and aquatic species relevant to environmental risk assessment of chemicals. Both empirical and mechanistic toxicokinetic models are discussed using the results of extensive literature searches together with tools and software for their calibration and an overview of applications in environmental risk assessment. These include simple tools such as one-compartment models, multi-compartment models to physiologically-based toxicokinetic (PBTK) models, mostly available for aquatic species such as fish species and a number of chemical classes including plant protection products, metals, persistent organic pollutants, nanoparticles. Data gaps and further research needs are highlighted.

Individual sensitivity distribution evaluation from survival data using a mechanistic model: implications for ecotoxicological risk assessment.

Two main alternatives are typically used to model mechanistically dose-survival relationship in ecotoxicity tests. Effects are related to a concentration of concern, for instance body concentration, and, to account for their differences relative to time-to-death, individuals have either different concentration thresholds for death ("individual tolerance approach"), or equal probability to die, with death occurring randomly ("stochastic death approach"). A general framework to unify both approaches has recently been proposed. We derived a model from this framework to analyse five datasets (daphnids exposed to selenium, guppies exposed to dieldrin and second, third and fourth instars chironomids exposed to copper), by extending the standard stochastic death approach. We showed the possibility to estimate properly the toxicity parameters together with inter-organisms differences of sensitivity for at least one of these parameters (here the threshold for effect). For the daphnids, there was no improvement of using the extended model, which confirms the expected low variability among genetically identical individuals. For all the other datasets, our model outperformed the standard approach without accounting for differences of sensitivity. We estimated coefficients of variations in the distribution of the logarithm of the threshold from 44% to 4% and showed, for chironomids, a decrease of inter-individual differences of sensitivity with the age of the larvae. All standard threshold estimates were close but above the medium value of the distribution in the new approach, which means that a concentration equal to the standard threshold would ultimately result in the death of more than half of the exposed organisms. A more relevant parameter, such as the concentration protecting 95% of the population, would be 2-4 times inferior to the standard threshold.

Model-based estimation of the link between the daily survival probability and a time-varying covariate, application to mosquitofish survival data.

The survival probability in a group of individuals may evolve in time due to the influence of a time-varying covariate. In this paper we present a model-based approach allowing the estimation of the functional link between the survival probability and a time-varying covariate when data are grouped and time-period censored. The approach is based on an underlying model consisting in non-stationary Markov processes and describing the survival of individuals. The underlying model is aggregated in time and at the group level to handle the group structure of data and the censoring. The aggregation yields a generalized non-linear mixed model. Then, a Bayesian procedure allows the estimation of the model parameters and the description of the link between the survival probability and the time-varying covariate. This approach is applied in order to explore the relationship between the daily survival probability of mosquitofish (Gambusia holbrooki) and their time-varying lengths (small mosquitofish die with a higher rate than large ones because they are more affected by predation, cannibalism and environmental stress).