Predictive models in ecotoxicology: Bridging the gap between scientific progress and regulatory applicability-Remarks and research needs

Mortality Pattern of Poecilus cupreus Beetles after Repeated Topical Exposure to Insecticide─Stochastic Death or Individual Tolerance?

The mortality of organisms exposed to toxicants has been attributed to either stochastic processes or individual tolerance (IT), leading to the stochastic death (SD) and IT models. While the IT model follows the principles of natural selection, the relevance of the SD model has been debated. To clarify why the idea of stochastic mortality has found its way into ecotoxicology, we investigated the mortality of Poecilus cupreus (Linnaeus, 1758) beetles from pesticide-treated oilseed rape (OSR) fields and unsprayed meadows, subjected to repeated insecticide treatments. We analyzed the mortality with the Kaplan-Meier estimator and general unified threshold model for survival (GUTS), which integrates SD and IT assumptions. The beetles were exposed three times, ca. monthly, to the same dose of Proteus 110 OD insecticide containing thiacloprid and deltamethrin, commonly used in the OSR fields. Kaplan-Meier analysis showed that the mortality of beetles from meadows was much higher after the first treatment than after the next two, indicating the IT model. Beetles from the OSR displayed approximately constant mortality after the first and second treatments, consistent with the SD model. GUTS analysis did not conclusively identify the better model, with the IT being marginally better for beetles from meadows and the SD better for beetles from OSR fields.

Multi- and Trans-Generational Effects on Daphnia Magna of Chlorpyrifos Exposures

Chlorpyrifos, a broad-spectrum neurotoxic organophosphate insecticide, is subject to atmospheric and hydrolytic transport from application sites to aquatic ecosystems. Across the landscape, concentrations in surface water can vary spatially and temporally according to seasonal use practices. Standardized bioassays can provide a screening-level understanding of aquatic receptor acute and chronic toxicity. However, these bioassays do not address ecologically relevant exposure patterns that may impact fitness and survival within and across generations. The aim of the present study was to evaluate the utility of a second-tier, screening-level methodology employing Daphnia magna multi- and transgenerational bioassays spanning four generations to investigate the effect of variable chronic chlorpyrifos exposure. The multigenerational assay consisted of continuous chlorpyrifos exposure across four consecutive 21-day bioassays using progeny from the previous assay for each successive generation. In the transgenerational assay, only the parent (F0) generation was exposed. For both assays, survival and reproduction were assessed across treatments and generations. Results indicated that (1) following continuous chlorpyrifos exposure at ecologically relevant concentrations to four generations of D. magna, the highest treatment showed an apparent tolerance response for both survival and reproductive success in the F3 generation, and (2) chlorpyrifos exposure to the F0 generation did not result in treatment effects in the unexposed F1, F2, and F3 generations in the apical endpoints of survival and reproduction. Employing a suite of acute and chronic bioassays, including chronic exposures spanning multiple generations, allows for a more robust screening-level evaluation of the potential impact of chlorpyrifos on aquatic receptors for variable periods of exposure. Environ Toxicol Chem 2022;41:1054-1065. © 2021 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.

Consensus versus Individual QSARs in Classification: Comparison on a Large-Scale Case Study

Consensus strategies have been widely applied in many different scientific fields, based on the assumption that the fusion of several sources of information increases the outcome reliability. Despite the widespread application of consensus approaches, their advantages in quantitative structure–activity relationship (QSAR) modeling have not been thoroughly evaluated, mainly due to the lack of appropriate large-scale data sets. In this study, we evaluated the advantages and drawbacks of consensus approaches compared to single classification QSAR models. To this end, we used a data set of three properties (androgen receptor binding, agonism, and antagonism) for approximately 4000 molecules with predictions performed by more than 20 QSAR models, made available in a large-scale collaborative project. The individual QSAR models were compared with two consensus approaches, majority voting and the Bayes consensus with discrete probability distributions, in both protective and nonprotective forms. Consensus strategies proved to be more accurate and to better cover the analyzed chemical space than individual QSARs on average, thus motivating their widespread application for property prediction. Scripts and data to reproduce the results of this study are available for download.