Decline of pesticide residue on treated crop seeds: An analysis of comprehensive industry data and implications of the current risk assessment scheme for plant protection products.

For plant protection products applied as seed treatments, the risk to birds and mammals possibly feeding on treated seeds must be addressed in the EU to register products for commercial use. One assumption of the Tier 1 long-term risk assessment of the European Food Safety Authority (EFSA) is that residues of pesticides on treated seeds do not decline over time after seeding. Consequently, a time-weighted average factor (fTWA ) of 1 (i.e., no dissipation) is used to calculate residue concentrations on seeds. In contrast, for spray applications, a default dissipation half-life (DT50 ) of 10 days is considered corresponding to an fTWA of 0.53. The aim of this study was to establish a default fTWA for treated seeds based on 29 industry-conducted seed dissipation studies, providing 240 datasets covering different active substances, crops, and regions. For fTWA calculation, two approaches were used: (i) kinetic fitting and (ii) using measured data without kinetic fitting. From kinetic fitting, 145 reliable DT50 values were obtained. Because there were no significant differences in DT50 values between crops and between the central and southern EU, the DT50 data from all studies were pooled. The geometric mean DT50 was 3.8 days and the 90th percentile was 13.0 days, corresponding to 21-day fTWA values of 0.27 and 0.59, respectively. Twenty-one-day fTWA values could be calculated directly from measured residues for 204 datasets. The resulting 21-day fTWA values were comparable with those from kinetic fitting (geometric mean: 0.29, 90th percentile: 0.59). The results demonstrate that residue decline on seeds is comparable with foliar dissipation after spray applications. Therefore, the risk assessment scheme by EFSA should implement a default fTWA < 1.0 in the Tier 1 risk assessment for treated seeds (e.g., either 0.53 as for foliage or 0.59, the 90th percentile fTWA in seeds reported in this study). Integr Environ Assess Manag 2024;20:239-247. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Availability of pesticide-treated seeds on the soil surface in different crops and countries: A comprehensive data set reflecting modern agronomic practice.

For plant protection products applied as seed treatments, the risk to birds and mammals possibly feeding on such treated seeds needs to be addressed in the EU, in order to register these products for commercial use. For this purpose, the European Food Safety Food Authority (EFSA) has provided guidance on how to execute such a risk assessment. The risk assessment follows a tiered approach. In the Tier 1 risk assessment of the EFSA guidance (2023), it is assumed that birds or mammals have ad libitum access to treated seeds and exclusively feed on treated seeds. Due to this conservative assumption, the Tier I risk assessment typically indicates an unacceptable risk to birds and mammals and higher-tier refinements are required. One option for refinement is to use data on the availability of treated seeds on the soil surface directly after drilling. Published data on seed counts are, however, limited to a few countries and crops, and often these data are not contemporary, that is, do not reflect advances in sowing technology and current agronomic practice. To address this data gap, we provide recently generated data from industry field trials (the studies were conducted from 2000 to 2022, >70% between 2019 and 2022), covering 270 fields from seven countries (Austria, France, Germany, Hungary, Poland, Spain, UK) for spring and winter cereals, winter oilseed rape, and sunflower. This comprehensive data set realistically reflects modern agronomic practice and is thus suitable for consideration in a regulatory context for refining the risk assessment for birds and mammals. Integr Environ Assess Manag 2024;20:1706-1714. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

A spatiotemporally explicit modeling approach for more realistic exposure and risk assessment of off-field soil organisms.

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).

Making the right conclusions based on wrong results and small sample sizes: interpretation of statistical tests in ecotoxicology.

In environmental risk assessments statistical tests are a standard tool to evaluate the significance of effects by pesticides. While it has rarely been assessed how likely it is to detect effects given a specific sample size, it was never analysed how reliable results are if the test preconditions, particularly of parametric tests, are not fulfilled or how likely it is to detect deviations from these preconditions. Therefore, we analyse the performance of a parametric and a non-parametric test using Monte Carlo simulation, focussing on typical data used in ecotoxicological risk assessments. We show that none of the data distributions are normal and that for typical sample sizes of N<20 it is very unlikely to detect deviations from normality. Non-parametric tests performed markedly better than parametric tests, except when data were in fact normally distributed. We finally discuss the impact of using different tests on pesticide risk assessments.

Reduction of variability for the assessment of side effects of toxicants on honeybees and understanding drivers for colony development.

The statistical power of studies for the assessment of side effects of toxicants on honeybees conducted according to current guidelines is often limited. A new test design and modified field methods have therefore been developed to decrease uncertainty and variability and to be able to detect small effects. The new test design comprises a monitoring phase (before the tunnel phase) for the selection of honeybee colonies and modified methods, which include assessments of colony strength, an evaluation of the cell content of all cells of hives using photos and digital analysis, and the use of video recordings for the assessment of foraging activity and forager mortality. With the proposed new study design and the modified field methods variability between hives was considerably reduced, which resulted in a marked reduction of the minimum detectable difference (MDD). This makes it possible to address the Specific Protection Goals defined by the European Food Safety Authority and to gain unprecedented insight into the development of hives and driving factors.

A simple probabilistic estimation of spray drift--factors determining spray drift and development of a model.

Spray drift represents a major mode of exposure in off-crop habitats or surface waters after pesticide spray application. Currently, the estimation of exposure by spray drift is based on a deterministic estimation of the amount of drifting residues, either with the use of default drift values or deterministic models, which, however, do not reproduce the entire range of spray drift observed in reality. However, because a series of data from extensive field trials are available, probabilistic methods based on Monte Carlo simulation can reveal realistic estimates of the entire range of exposures. For the development of a probabilistic spray drift model, previously published data from a series of field trials was analyzed to reveal how these data could be used for the parameterization of a probabilistic model. This analysis showed that wind speed, agricultural equipment (nozzle type, spray pressure), and relative humidity showed the strongest effect on spray drift. But remarkably, the effect differed for different distances from sprayed fields. For example, higher wind speed increased spray drift only at larger distances while it even reduced spray drift very close to field borders. Also spray pressure influenced spray drift predominantly close to fields. After identifying the parameters with the strongest effects, a probabilistic model for the estimation of the exposure by spray drift in off-crop habitats was developed. Spray drift can be simulated for any given distance from fields. It is demonstrated how the exposure and the amount of effects can be estimated when applying this model in real landscapes. Results are compared with a deterministic risk assessment.

Dissipation of plant protection products from foliage.

In the environmental risk assessment for plant protection products in the European Union a default foliar dissipation half-life (DT50) of 10 d is used for the risk assessment of herbivorous birds and mammals feeding on sprayed foliage. This generic DT50 of 10 d is based on a compilation of residue trials conducted over 30 yr ago, in which many compounds and formulations were considered that are not used anymore. We therefore reassessed foliar dissipation based on a data set of 396 residue trials covering 30 compounds. Foliar DT50s were calculated, and potential factors determining dissipation were analyzed, such as crop group, residue zone, and rainfall. The strongest source of variability was found between individual trials. Other factors, including the residue zone and crop group, did not have a significant impact on dissipation. Only heavy rainfall (>6.5 mm/d, i.e., the 95th percentile of rainfall) had a statistically significant influence, although rainfall explained only approximately 5% of the overall variability. Moderate rainfall (≤6.5 mm/d) did not significantly correlate with dissipation and explained only 0.1% of the overall variability. Most importantly, the differences in DT50s between crops and residue zones were neither marked nor statistically significant; hence, trials from different residue zones and crops could be pooled to obtain more robust half-lives. Over all compounds, trials, zones, and crops the geometric mean DT50 was 3.2 d (90th percentile 7.9 d). Environ Toxicol Chem 2018;37:1926-1932. © 2018 SETAC.

Modeling individual movement decisions of brown hare (Lepus europaeus) as a key concept for realistic spatial behavior and exposure: A population model for landscape-level risk assessment.

Spatial behavior is of crucial importance for the risk assessment of pesticides and for the assessment of effects of agricultural practice or multiple stressors, because it determines field use, exposition, and recovery. Recently, population models have increasingly been used to understand the mechanisms driving risk and recovery or to conduct landscape-level risk assessments. To include spatial behavior appropriately in population models for use in risk assessments, a new method, "probabilistic walk," was developed, which simulates the detailed daily movement of individuals by taking into account food resources, vegetation cover, and the presence of conspecifics. At each movement step, animals decide where to move next based on probabilities being determined from this information. The model was parameterized to simulate populations of brown hares (Lepus europaeus). A detailed validation of the model demonstrated that it can realistically reproduce various natural patterns of brown hare ecology and behavior. Simulated proportions of time animals spent in fields (PT values) were also comparable to field observations. It is shown that these important parameters for the risk assessment may, however, vary in different landscapes. The results demonstrate the value of using population models to reduce uncertainties in risk assessment and to better understand which factors determine risk in a landscape context. Environ Toxicol Chem 2017;36:2299-2307. © 2017 SETAC.

Characterization and prediction of alternative splice sites.

Human alternative isoform, cryptic, skipped, and constitutive splice sites from the ALTEXTRON database were analysed regarding splice site strength, composition, GC content, position and binding site strength of polypyrimidine tract and branch site. Several features were identified which distinguish alternative isoform and cryptic splice sites, but not skipped splice sites from constitutive ones. These include splice site strength, introns GC content, U2AF35 binding site score, and oligonucleotide frequencies. For the predictive classification of splice sites, pattern recognition models for different splicing factor binding sites and oligonucleotide frequency models (OFMs) were combined using backpropagation networks. 67.45% of acceptor sites and 71.23% of donor sites are correctly classified by networks trained for classification of constitutive and alternative isoform/cryptic splice sites. A web-application for the prediction of alternative splice sites is available at http://es.embnet.org/~mwang/assp.html .

An example of population-level risk assessments for small mammals using individual-based population models.

This article presents a case study demonstrating the application of 3 individual-based, spatially explicit population models (IBMs, also known as agent-based models) in ecological risk assessments to predict long-term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of FungicideX was defined so that the deterministic long-term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e., higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all 3 cases low population sensitivity unless FungicideX was applied at very high (×10) rates. Recovery from local population impacts was generally fast. Only when patch extinctions occured in simulations of intentionally high acute toxic effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios.

Short-range compositional correlation in the yeast genome depends on transcriptional orientation.

This article reports an analysis of composition of about 5000 intergenic regions and neighboring ORFs in the nuclear genome of Saccharomyces cerevisiae, and their correlation. Intergenic regions flanked by divergently transcribed ORFs are GC richer (36%) than those separating convergent ORFs (29%). This difference in GC content cannot be fully attributed to its location upstream or downstream the ORFs, since no such strong compositional bias is found within 3' and 5' segments of intergenic regions between ORFs transcribed in the same direction. We have also found that the GC content of intergenic regions is positively correlated to that of its flanking ORFs in tandem and divergent orientations, but not in convergent orientations, and that the correlation coefficient between the GC content of nearby ORFs is higher for divergent pairs. Our observations are discussed in the light of recent work stressing the relationships between base composition, chromatin structure and meiotic recombination.

From home range dynamics to population cycles: validation and realism of a common vole population model for pesticide risk assessment.

Despite various attempts to establish population models as standard tools in pesticide risk assessment, population models still receive limited acceptance by risk assessors and authorities in Europe. A main criticism of risk assessors is that population models are often not, or not sufficiently, validated. Hence the realism of population-level risk assessments conducted with such models remains uncertain. We therefore developed an individual-based population model for the common vole, Microtus arvalis, and demonstrate how population models can be validated in great detail based on published data. The model is developed for application in pesticide risk assessment, therefore, the validation covers all areas of the biology of the common vole that are relevant for the analysis of potential effects and recovery after application of pesticides. Our results indicate that reproduction, survival, age structure, spatial behavior, and population dynamics reproduced from the model are comparable to field observations. Also interannual population cycles, which are frequently observed in field studies of small mammals, emerge from the population model. These cycles were shown to be caused by the home range behavior and dispersal. As observed previously in the field, population cycles in the model were also stronger for longer breeding season length. Our results show how validation can help to evaluate the realism of population models, and we discuss the importance of taking field methodology and resulting bias into account. Our results also demonstrate how population models can help to test or understand biological mechanisms in population ecology.

Regulation (EC) No. 1107/2009 and upcoming challenges for exposure assessment of plant protection products--Harmonisation or national modelling approaches?

In the new European Pesticide Regulation (EC) No. 1107/2009, the harmonisation of approaches for estimation of the environmental exposure of pesticides is considered a major goal. Several member states currently require their own models for the calculation of predicted environmental concentrations (PEC) in surface water. The variety of methods makes risk evaluations rather time-consuming for both notifiers and evaluating authorities. In the present study we compare surface water concentrations of 19 compounds using EU and country-specific models and risk assessment approaches to evaluate to which extent the resulting estimated exposure concentrations differ. Our results show that EU and country specific approaches and the resulting surface water concentrations differ considerably regarding basic model assumptions and assessment methods. The results indicate that the aimed harmonisation of risk assessment approaches within the EU will be difficult based on current models. New scenarios may help to achieve a harmonisation taking country-specific features into account.

Adverse outcome pathways and ecological risk assessment: bridging to population-level effects.

Maintaining the viability of populations of plants and animals is a key focus for environmental regulation. Population-level responses integrate the cumulative effects of chemical stressors on individuals as those individuals interact with and are affected by their conspecifics, competitors, predators, prey, habitat, and other biotic and abiotic factors. Models of population-level effects of contaminants can integrate information from lower levels of biological organization and feed that information into higher-level community and ecosystem models. As individual-level endpoints are used to predict population responses, this requires that biological responses at lower levels of organization be translated into a form that is usable by the population modeler. In the current study, we describe how mechanistic data, as captured in adverse outcome pathways (AOPs), can be translated into modeling focused on population-level risk assessments. First, we describe the regulatory context surrounding population modeling, risk assessment and the emerging role of AOPs. Then we present a succinct overview of different approaches to population modeling and discuss the types of data needed for these models. We describe how different key biological processes measured at the level of the individual serve as the linkage, or bridge, between AOPs and predictions of population status, including consideration of community-level interactions and genetic adaptation. Several case examples illustrate the potential for use of AOPs in population modeling and predictive ecotoxicology. Finally, we make recommendations for focusing toxicity studies to produce the quantitative data needed to define AOPs and to facilitate their incorporation into population modeling.

Population models in pesticide risk assessment: lessons for assessing population-level effects, recovery, and alternative exposure scenarios from modeling a small mammal.

In the last few years, the interest in using ecological population models as a tool for pesticide risk assessment has increased rapidly. Practical guidance, however, on how to perform a risk assessment with a population model is still lacking. It is still unclear which endpoint (population density, population growth, etc.) is the most sensitive indicator of population-level effects and how risk can be evaluated at the population level. Moreover, a main added value of model-based risk assessments, which is an understanding of the mechanisms involved in alternative exposure scenarios, so far has received little attention. We therefore used an example model to compare commonly used endpoints and alternative exposure scenarios. The model is a structurally realistic, but relatively simple, individual-based, spatially explicit model for the common shrew (Sorex araneus), which was selected because it has been tested and validated extensively. We show that population density is more sensitive for detecting population-level effects in the short term (months) than population growth rate. Population viability measured by extinction risk can also be a relevant endpoint, because it is especially sensitive for small populations. We show that landscape structure and the timing of pesticide application (population structure at the time of application) can have a great impact on population recovery, and we analyze statistical tests for use in population-level risk assessments. Our results demonstrate which factors and insights should be taken into account in population-level risk assessments.