Exposure pattern-specific species sensitivity distributions for the ecological risk assessments of insecticides

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).

Ecological risk assessment for difenoconazole in aquatic ecosystems using a web-based interspecies correlation estimation (ICE)-species sensitivity distribution (SSD) model

Difenoconazole is a typical triazole fungicide that can inhibit demethylation during ergosterol synthesis. Due to its wide use, difenoconazole is frequently detected in surface water, paddy water, agricultural water, and other aquatic environments. Presently, an assessment of the ecological risk posed by difenoconazole in aquatic ecosystems is lacking. Here, a web-based interspecies correlation estimation (ICE)-species sensitivity distribution (SSD) model was first applied to assess the ecological risk of difenoconazole in aquatic environments. Meanwhile, maximum acceptable concentration (MAC), maximum risk-free concentration (MRFC), and risk quotient (RQ) values were used to evaluate the potential risk of difenoconazole to aquatic organisms. Our results showed that an aquatic MAC value of 0.31 μg/L was acceptable for difenoconazole in aquatic environments. Further, the detected concentration of difenoconazole was lower than the MRFC value of 0.09 μg/L indicating no risk to aquatic organisms. Assessment data suggested that difenoconazole exhibited potential risks to eight studied aquatic ecosystems (including surface water, paddy water, and agricultural water) in different countries (RQ > 1), indicating that difenoconazole overuse could cause adverse effects to aquatic organisms in these aquatic ecosystems. Thus, restricted use and rational use of difenoconazole are recommended.

Fiproles as a proxy for ecological risk assessment of mixture of fipronil and its degradates in effluent-dominated surface waters

Environmental risk assessment of complex chemical mixtures has increasingly been prioritized as a management goal, especially in the regulatory sector. Although fipronil and its three degradates (-sulfone, -sulfide and -desulfinyl) have been frequently quantified in waterways, little information is available about the likelihood and magnitude of ecological risk posed by these chemical mixtures - collectively known as fiproles - in surface water. In the present study, a probabilistic risk assessment of mixtures of fipronil and its three degradates was conducted for three effluent-dominated southern California rivers: Los Angeles River (LAR), San Gabriel River (SGR) and Santa Clara River (SCR), California, USA. The assessments, which used fiproles as an integrated proxy, were based on three levels of toxicity endpoints: median lethal concentration (LC50), half-maximal effective concentration (EC50), and lowest observed effect concentration (LOEC), to gain comprehensive assessment information. Probabilistic approaches based on species sensitivity distribution (SSD) and exposure concentration distribution (ECD) were developed with the log-logistic model by pooling the toxicity and occurrence data, respectively. The 5th percentile hazardous concentrations (HC5s) were calculated to be at low parts per billion levels, enabling these values to be used to estimate the chemical-specific benchmarks for components that lack ecotoxicity data. The single substance potentially affected fraction (ssPAF) of fiproles revealed risk levels for the three rivers in descending order: LAR ≥ SGR > SCR. The overall risk probability estimated from the joint probability curve (JPC) by Monte Carlo simulation was 1.13 ± 0.20% (LC50), 9.31 ± 1.46% (EC50), and 6.58 ± 1.43% (LOEC) for the three rivers collectively. These results derived from the fiproles indicates that fipronil and its degradates pose risks to the aquatic organisms in the surface water of the three rivers. The present study provides a methodology for the use of a proxy in the risk assessment of chemical mixtures.

A 3D ecotoxi-topological profile: Using concentration-time-response surfaces to show peroxidase activity in Zea mays (L.) exposed to aluminium or arsenic in hydroponic conditions

This study sought to use concentration-time-response surfaces to show the effects of exposure to toxic (semi-)metals on peroxidase activity in higher plants as a function of exposure-concentration and exposure-time. Maize (Zea mays L.) seedlings (i.e., leaves and roots) were exposed to arsenic (as As³⁺) or aluminium (as Al³⁺) under hydroponic conditions, and their biomass and peroxidase enzyme responses were assessed at different concentration-time-exposures. The 3D ecotoxi-profile generated with these data showed two distinct regions: the first region is formed by exposures (i.e., points for time-concentration pairings) that were not statistically different from the results of the control points (i.e., zero toxicant concentration and all exposure-times), whereas the second region is formed by exposure pairings with results that were statistically different to those obtained from control pairings. Overall, the data show that enzyme activity increased over a shorter exposure-time when there was an increase in the exposure-concentration of the toxicant, which can be seen on a 3-D toxicity profile. We propose that quantitative relationship ratios from different assessed endpoints (e.g., biomass and enzyme activity) and enzymatic concentration-time-response surfaces could be helpful in the field of environmental-policy management.

Application of General Unified Threshold Models of Survival Models for Regulatory Aquatic Pesticide Risk Assessment Illustrated with an Example for the Insecticide Chlorpyrifos

Mathematical models within the General Unified Threshold models of Survival (GUTS) framework translate time-variable chemical exposure information into expected survival of animals. The GUTS models are species and compound specific and explicitly describe the internal exposure dynamics in an organism (toxicokinetics) and the related damage and effect dynamics (toxicodynamics), thereby connecting the external exposure concentration dynamics with the simulated mortality or immobility over time. In a recent scientific opinion on toxicokinetic-toxicodynamic (TKTD) models published by the European Food Safety Authority (EFSA), the GUTS modeling framework was considered ready for use in the aquatic risk assessment for pesticides and aquatic fauna. The GUTS models are suggested for use in risk assessment, if they are sufficiently validated for a specific substance-species combination. This paper aims to illustrate how they can be used in the regulatory environmental risk assessment for pesticides for a specific type of refinement, that is, when risks are triggered by lower tiers in acute as well as in chronic risk assessment and mortality or immobility is the critical endpoint. This approach involves the evaluation of time-variable exposure regimes in a so-called "Tier-2C" assessment. The insecticide chlorpyrifos was selected as an example compound because a large data set was available. The GUTS models for 13 different freshwater arthropods and 8 different theoretical aquatic exposure profiles were used to calculate a series of GUTS-based risk estimates, including exposure profile-specific multiplication factors leading to 50% mortality or immobility at the end of the tested profile (LP50/EP50) as "margins of safety." To put the use of GUTS models within the tiered aquatic risk assessment into perspective, GUTS models for the 13 aquatic arthropods were also used to predict the environmental risks of a measured chlorpyrifos exposure profile from an experimental ditch study (Tier-3 approach), and the results are discussed in the context of calibration of the tiered approach. Integr Environ Assess Manag 2021;17:243-258. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Effect Modeling Quantifies the Difference Between the Toxicity of Average Pesticide Concentrations and Time-Variable Exposures from Water Quality Monitoring

Synthetic chemicals are frequently detected in water bodies, and their concentrations vary over time. Water monitoring programs typically employ either a sequence of grab samples or continuous sampling, followed by chemical analysis. Continuous time-proportional sampling yields the time-weighted average concentration, which is taken as proxy for the real, time-variable exposure. However, we do not know how much the toxicity of the average concentration differs from the toxicity of the corresponding fluctuating exposure profile. We used toxicokinetic-toxicodynamic models (invertebrates, fish) and population growth models (algae, duckweed) to calculate the margin of safety in moving time windows across measured aquatic concentration time series (7 pesticides) in 5 streams. A longer sampling period (14 d) for time-proportional sampling leads to more deviations from the real chemical stress than shorter sampling durations (3 d). The associated error is a factor of 4 or less in the margin of safety value toward underestimating and an error of factor 9 toward overestimating chemical stress in the most toxic time windows. Under- and overestimations occur with approximate equal frequency and are very small compared with the overall variation, which ranged from 0.027 to 2.4 × 10¹⁰ (margin of safety values). We conclude that continuous, time-proportional sampling for a period of 3 and 14 d for acute and chronic assessment, respectively, yields sufficiently accurate average concentrations to assess ecotoxicological effects. Environ Toxicol Chem 2020;39:2158-2168. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Improving Risk Assessment by Predicting the Survival of Field Gammarids Exposed to Dynamic Pesticide Mixtures

Exposure assessment of pesticides has substantially improved over time, with methods that now include a combination of advanced analytical techniques and fate/transport models to evaluate their spatiotemporal distribution. However, the current regulatory environmental risk assessment considers thresholds from laboratory studies completed under standardized conditions that do not reflect environmental dynamics. Using the General Unified Threshold model for Survival (GUTS) model framework, we predicted the impact of time-varying pesticide exposures on the survival of gammarids in a small agricultural stream. The LP₅₀ values were used as an additional metric for assessing risks (defined in GUTS as a multiplication factor applied to the concentration time series to induce 50% mortality by the end of exposure). Although real-case exposures to individual pesticides were predicted to produce little to no impact on survival, the LP₅₀ values indicate acute (LP₅₀ ≤ 100) and/or chronic (LP₅₀ ≤ 10) toxicities for azoxystrobin, chlorpyrifos, diazinon, and imidacloprid, while risk to propiconazole exposure was considered very low (LP₅₀ ≫ 100). Finally, the model was extended to reflect mixture toxicity via concentration addition. It predicted risks under acute and chronic exposures to organophosphates and neonicotinoids. Given that gammarids are simultaneously exposed to multiple chemicals and other stressors throughout their lifetime, a decline in survival probabilities due to chemical stress can likely influence their overall fitness. We recognize that some assumptions require validation, but our work included a level of realism that can assist risk managers when evaluating the cumulative consequences of chemical exposure.