Characterization of patterns and variability in the dynamics of outdoor aquatic mesocosms: exploring the capabilities and challenges in data supporting aquatic system models.

Aquatic mesocosms are complex test systems used within regulatory risk assessment of plant protection products. These model ecosystems allow researchers to capture interactions of multiple species under realistic environmental conditions. They enable assessment of direct and indirect effects of stressors at all trophic levels (i.e., from primary producers to secondary consumers) and impacts on ecosystem functions. Due to the limited ability to test the multitude of potential exposure scenarios, cross-linking aquatic mesocosm studies with virtual mesocosms, i.e., aquatic system models (ASMs), can serve to meet the demand for more environmental realism and ecological relevance in risk assessment. In this study, full control data sets from seven aquatic mesocosm studies conducted at a single test facility under GLP were analysed graphically and using descriptive statistics. Thereby, not only a comprehensive data base but also an insight into the species present, their dynamics over time, and variability in unchallenged mesocosms was observed. While consistency in dynamics could be discerned for physical and chemical parameters, variability was evident for several biological endpoints. This variability points to amplification of small differences over time as well as to stochastic processes. The outline of existing gaps and uncertainties in data leads to the estimation of what can be expected to be captured and predicted by ASMs.

Characterization of field-scale spray drift deposition and non-target plant biological sensitivity: a corn herbicide (mesotrione/s-metolochlor) case study.

BACKGROUND: This work reports a combined, field-scale spray drift deposition and plant bioassay study for a pre-mixture of the herbicides mesotrione and s-metolachlor. Wind direction data and field dimensions were used to evaluate the potential for spray drift to bypass downwind sampling devices. Variability in resulting spray drift across downwind distances was assessed alongside wind speed measured at on-site weather stations. Measured wind angles were used to geometrically adjust traveled drift particle distances and enabling isolation of wind direction impact from wind speed. Further, the use of single and multiple in-field monitoring locations was compared to quantify the benefit of higher-resolution meteorological sampling. RESULTS: Generally, increased wind speed resulted in significantly greater herbicide deposition at distances proximal to the edge of the spray zone. According to the drift deposition curves that included wind speed data from single and multiple onsite weather stations, trials with relatively higher wind speeds were associated with greater spray drift deposition at relatively close sampling distances downwind from the application area. Only marginal improvement of linear mixed-effects model fit was observed when including data from three weather stations, compared to the fit from a single weather station or absence of weather data in the model. Using tomato and lettuce plant bioassay species, the overall no-effect distance was 3.0 m (10 ft). CONCLUSION: Results from this study are informative to refine pesticide risk assessment for non-target plants and indicate that a single weather station is sufficient to capture potential influential effects from wind speed and direction on spray drift. © 2022 Society of Chemical Industry.

Simulating Honey Bee Large-Scale Colony Feeding Studies Using the BEEHAVE Model-Part I: Model Validation.

In pesticide risk assessments, semifield studies, such as large-scale colony feeding studies (LSCFSs), are conducted to assess potential risks at the honey bee colony level. However, such studies are very cost and time intensive, and high overwintering losses of untreated control hives have been observed in some studies. Honey bee colony models such as BEEHAVE may provide tools to systematically assess multiple factors influencing colony outcomes, to inform study design, and to estimate pesticide impacts under varying environmental conditions. Before they can be used reliably, models should be validated to demonstrate they can appropriately reproduce patterns observed in the field. Despite the recognized need for validation, methodologies to be used in the context of applied ecological models are not agreed on. For the parameterization, calibration, and validation of BEEHAVE, we used control data from multiple LSCFSs. We conducted detailed visual and quantitative performance analyses as a demonstration of validation methodologies. The BEEHAVE outputs showed good agreement with apiary-specific validation data sets representing the first year of the studies. However, the simulations of colony dynamics in the spring periods following overwintering were identified as less reliable. The comprehensive validation effort applied provides important insights that can inform the usability of BEEHAVE in applications related to higher tier risk assessments. In addition, the validation methodology applied could be used in a wider context of ecological models. Environ Toxicol Chem 2020;39:2269-2285. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Simulating Honey Bee Large-Scale Colony Feeding Studies Using the BEEHAVE Model-Part II: Analysis of Overwintering Outcomes.

Large-scale colony feeding studies (LSCFSs) aim to assess potential pesticide exposure to and effects on honey bees at the colony level. However, these studies are sometimes affected by high losses of control colonies, indicating that other stressors may impact colonies and confound the analysis of potential pesticide impacts. We assessed the study design and environmental conditions experienced by the untreated control colonies across 7 LSCFSs conducted in North Carolina (USA). Overwintering success differed considerably among the studies, as did their initial colony conditions, amount and timing of sugar feeding, landscape composition, and weather. To assess the effects of these drivers on control colonies' overwintering success, we applied the mechanistic colony model BEEHAVE. Sugar feedings and initial status of the simulated colonies were more important for fall colony condition than were landscape and weather. Colonies that had larger colony sizes and honey stores in the fall were those that began with larger honey stores, were provided more sugar, and had supplemental feedings before the fall. This information can be used to inform the standardization of a study design, which can increase the likelihood of overwintering survival of controls and help ensure that LSCFSs are comparable. Our study demonstrates how a mechanistic model can be used to inform study designs for higher tier effects studies. Environ Toxicol Chem 2020;39:2286-2297. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Winds of change, developing a non-target plant bioassay employing field-based pesticide drift exposure: A case study with atrazine.

A field-scale, spray drift study with atrazine was conducted to simultaneously measure spray drift deposition, airborne interception and corresponding biological effects on two sensitive plant species (cucumber and lettuce). Applications of AAtrex 4L (atrazine) were made using ultra-coarse nozzles (TeeJet TTI11004) under worst-case drift potential conditions of bare soil and high wind speeds (i.e. >10 mph; >16 kph). This study was replicated 4 times, each with two parallel spray swaths (92.5 ft or 28 m per swath) perpendicular to wind direction. Within each replicate application, three sampling lines were used to measure drift deposition (using stainless-steel discs) at distances out to 400 ft (122 m), airborne interception (using stainless-steel rods) at distances out to 75 ft (23 m), and potential direct plant effects at 5, 15, 25, 35, and 45 ft (1.5, 4.6, 7.6, 10.7, and 13.7 m) from the downwind edge of the spray swath. Corresponding upwind control discs and plants were also included in each replicate. Each replicate application targeted steady wind speeds between 10 and 15 mph (16 and 24 kph) within a 30-degree angle of the downwind field orientation. On average, each 10% increase in distance from the spray zone resulted in approximately 14% less ground-deposited atrazine. Between 7 and 41× more atrazine mass was collected from vertical rods (airborne drift), compared to horizontally placed stainless-steel discs (ground deposition). Cucumber and lettuce plants exposed to spray drift were monitored for biological effects over 21 days post-application according to standard protocols. Endpoints of survival, weight (biomass), and shoot length were evaluated by comparing distance groups to up-wind controls. Overall, when trials were combined, the aggregate lowest observable effect distance (LOED) was 5-ft (1.5 m) and the aggregate no observable effects distance (NOED) was 15-ft (4.6 m), with cucumbers affected more than lettuce.

Honey bee colony-level exposure and effects in realistic landscapes: An application of BEEHAVE simulating clothianidin residues in corn pollen.

Discerning potential effects of insecticides on honey bee colonies in field studies conducted under realistic conditions can be challenging because of concurrent interactions with other environmental conditions. Honey bee colony models can control exposures and other environmental factors, as well as assess links among pollen and nectar residues in the landscape, their influx into the colony, and the resulting exposures and effects on bees at different developmental stages. We extended the colony model BEEHAVE to represent exposure to the insecticide clothianidin via residues in pollen from treated cornfields set in real agricultural landscapes in the US Midwest. We assessed their potential risks to honey bee colonies over a 1-yr cycle. Clothianidin effects on colony strength were only observed if unrealistically high residue levels in the pollen were simulated. The landscape composition significantly impacted the collection of pollen (residue exposure) from the cornfields, resulting in higher colony-level effects in landscapes with lower proportions of semi-natural land. The application of the extended BEEHAVE model with a pollen exposure-effects module provides a case study for the application of a mechanistic honey bee colony model in pesticide risk assessment integrating the impact of a range of landscape compositions. Environ Toxicol Chem 2019;38:423-435. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.