A field spray drift study to determine the downwind effects of isoxaflutole herbicide to nontarget plants.

Spray drift buffers are often required on herbicide labels to prevent potential drift effects to nontarget plants. Buffers are typically derived by determining the distance at which predicted exposure from spray drift equals the ecotoxicology threshold for sensitive plant species determined in greenhouse tests. Field studies performed under realistic conditions have demonstrated, however, that this approach is far more conservative than necessary. In 2016, the US Environmental Protection Agency estimated that isoxaflutole (IFT), a herbicide used to control grass and broadleaf weeds, could adversely affect downwind nontarget dicot plants at distances of ≥304 m from the edge of the treated field due to spray drift. This prediction implies that a buffer of at least 304 m is required to protect nontarget plants. To refine the predicted buffer distance for IFT, we conducted a field study in which sensitive nontarget plants (lettuce and navy bean, two to four leaf stage) were placed at various distances downwind from previously harvested soybean fields sprayed with Balance® Flexx Herbicide. The test plants were then transported to a greenhouse for grow out following the standard vegetative vigor test protocol. There were three trials. One had vegetation in the downwind deposition area (i.e., test plants placed in mowed grass; typical exposure scenario) and two had bare ground deposition areas (worst-case exposure scenario). For both plant species in bare ground deposition areas, effects on shoot height and weight were observed at 1.52 m but not at downwind distances of ≥9.14 m from the edge of the treated area. No effects were observed at any distance for plants placed in the vegetated deposition area. The field study demonstrated that a buffer of 9.14 m protects nontarget terrestrial plants exposed to IFT via spray drift even under worst-case conditions. Integr Environ Assess Manag 2022;18:757-769. © 2021 Bayer. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Integrating Exposure and Effect Distributions with the Ecotoxicity Risk Calculator: Case Studies with Crop Protection Products.

Risk curves describe the relationship between cumulative probability and magnitude of effect and thus express far more information than risk quotients. However, their adoption has remained limited in ecological risk assessment. Therefore, we developed the Ecotoxicity Risk Calculator (ERC) to simplify the derivation of risk curves, which can be used to inform risk management decisions. Case studies are presented with crop protection products, highlighting the utility of the ERC at incorporating various data sources, including surface water modeling estimates, monitoring observations, and species sensitivity distributions. Integr Environ Assess Manag 2021;17:321-330. © 2020 Syngenta Crop Protection, LLC. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Correcting for Phylogenetic Autocorrelation in Species Sensitivity Distributions.

A species sensitivity distribution (SSD) is a cumulative distribution function of toxicity endpoints for a receptor group. A key assumption when deriving an SSD is that the toxicity data points are independent and identically distributed (iid). This assumption is tenuous, however, because closely related species are more likely to have similar sensitivities than are distantly related species. When the response of 1 species can be partially predicted by the response of another species, there is a dependency or autocorrelation in the data set. To date, phylogenetic relationships and the resulting dependencies in input data sets have been ignored in deriving SSDs. In this paper, we explore the importance of the phylogenetic signal in deriving SSDs using a case studies approach. The case studies involved toxicity data sets for aquatic autotrophs exposed to atrazine and aquatic and avian species exposed to chlorpyrifos. Full and partial data sets were included to explore the influences of differing phylogenetic signal strength and sample size. The phylogenetic signal was significant for some toxicity data sets (i.e., most chlorpyrifos data sets) but not for others (i.e., the atrazine data sets, the chlorpyrifos data sets for all insects, crustaceans, and birds). When a significant phylogenetic signal did occur, effective sample size was reduced. The reduction was large when the signal was strong. In spite of the reduced effective sample sizes, significant phylogenetic signals had little impact on fitted SSDs, even in the tails (e.g., hazardous concentration for 5th percentile species [HC5]). The lack of a phylogenetic signal impact occurred even when we artificially reduced original sample size and increased strength of the phylogenetic signal. We conclude that it is good statistical practice to account for the phylogenetic signal when deriving SSDs because most toxicity data sets do not meet the independence assumption. That said, SSDs and HC5s are robust to deviations from the independence assumption. Integr Environ Assess Manag 2019;00:1-13. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

A refined ecological risk assessment for California red-legged frog, Delta smelt, and California tiger salamander exposed to malathion.

The California red-legged frog (CRLF), Delta smelt (DS), and California tiger salamander (CTS) are 3 species listed under the United States Federal Endangered Species Act (ESA), all of which inhabit aquatic ecosystems in California. The US Environmental Protection Agency (USEPA) has conducted deterministic screening-level risk assessments for these species potentially exposed to malathion, an organophosphorus insecticide and acaricide. Results from our screening-level analyses identified potential risk of direct effects to DS as well as indirect effects to all 3 species via reduction in prey. Accordingly, for those species and scenarios in which risk was identified at the screening level, we conducted a refined probabilistic risk assessment for CRLF, DS, and CTS. The refined ecological risk assessment (ERA) was conducted using best available data and approaches, as recommended by the 2013 National Research Council (NRC) report "Assessing Risks to Endangered and Threatened Species from Pesticides." Refined aquatic exposure models including the Pesticide Root Zone Model (PRZM), the Vegetative Filter Strip Modeling System (VFSMOD), the Variable Volume Water Model (VVWM), the Exposure Analysis Modeling System (EXAMS), and the Soil and Water Assessment Tool (SWAT) were used to generate estimated exposure concentrations (EECs) for malathion based on worst-case scenarios in California. Refined effects analyses involved developing concentration-response curves for fish and species sensitivity distributions (SSDs) for fish and aquatic invertebrates. Quantitative risk curves, field and mesocosm studies, surface-water monitoring data, and incident reports were considered in a weight-of-evidence approach. Currently, labeled uses of malathion are not expected to result in direct effects to CRLF, DS or CTS, or indirect effects due to effects on fish and invertebrate prey. Integr Environ Assess Manag 2018;14:224-239. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Risk assessment considerations with regard to the potential impacts of pesticides on endangered species.

Simple, deterministic screening-level assessments that are highly conservative by design facilitate a rapid initial screening to determine whether a pesticide active ingredient has the potential to adversely affect threatened or endangered species. If a worst-case estimate of pesticide exposure is below a very conservative effects metric (e.g., the no observed effects concentration of the most sensitive tested surrogate species) then the potential risks are considered de minimis and unlikely to jeopardize the existence of a threatened or endangered species. Thus by design, such compounded layers of conservatism are intended to minimize potential Type II errors (failure to reject a false null hypothesis of de minimus risk), but correspondingly increase Type I errors (falsely reject a null hypothesis of de minimus risk). Because of the conservatism inherent in screening-level risk assessments, higher-tier scientific information and analyses that provide additional environmental realism can be applied in cases where a potential risk has been identified. This information includes community-level effects data, environmental fate and exposure data, monitoring data, geospatial location and proximity data, species biology data, and probabilistic exposure and population models. Given that the definition of "risk" includes likelihood and magnitude of effect, higher-tier risk assessments should use probabilistic techniques that more accurately and realistically characterize risk. Moreover, where possible and appropriate, risk assessments should focus on effects at the population and community levels of organization rather than the more traditional focus on the organism level. This document provides a review of some types of higher-tier data and assessment refinements available to more accurately and realistically evaluate potential risks of pesticide use to threatened and endangered species.

Refined avian risk assessment for aldicarb in the United States.

Aldicarb was recently reviewed by the US Environmental Protection Agency (USEPA) for re-registration eligibility. In this paper, we describe a refined avian risk assessment for aldicarb that was conducted to build upon the screening-level methods used by USEPA. The goal of the refined ERA was to characterize and understand better the risks posed by aldicarb to birds in areas where the pesticide is applied. Aldicarb is a systemic insecticide sold in granular form under the trade name Temik. It is applied directly to soil and is used to control mites, nematodes, and aphids on a variety of crops (e.g., cotton, potatoes, peanuts). Consumption of grit is necessary for proper digestion in many bird species, particularly for granivores and insectivores. Thus, aldicarb granules may be mistaken for grit by birds. The Granular Pesticide Avian Risk Assessment Model (GranPARAM) is described in a companion paper and was used to estimate the probability and magnitude of effects to flocks of birds that frequent aldicarb-treated fields. One hundred thirty-five exposure scenarios were modeled that together include a range of bird species, crops, application methods and rates, and regions in the United States. The results indicated that, even for the most sensitive bird species, the risks associated with the agricultural use of granular aldicarb are negligible to low. There are several reasons for the limited risk: 1) the Temik formulation includes a gypsum core and a graphite coating and is black in color, all of which have been shown to be unattractive to birds, and 2) the pesticide is applied subsurface and rapidly dissolves following contact with water. The fact that no bird kill incidents involving appropriate label uses of aldicarb have been conclusively documented in the United States over its 38 years of use supports the results of this refined risk assessment.

Refined aquatic risk assessment for aldicarb in the United States.

Aldicarb is a systemic insecticide applied directly to soil and to control mites, nematodes, and aphids on a variety of crops (e.g., cotton, potatoes, peanuts). It is highly soluble in water (6,000 mg/L) and mobile in soils (K(oc) = 100). As a result, aldicarb has the potential to be transported to aquatic systems close to treated fields. The US Environmental Protection Agency (USEPA) recently conducted an aquatic screening-level ERA for aldicarb as part of the re-registration review process. We conducted a refined risk assessment for aldicarb to characterize better the risks posed by aldicarb to fish and invertebrates inhabiting small freshwater ponds near agricultural areas. For the exposure assessment, tier II PRZM/EXAMS (Predicted Root Zone Model [PRZM] and Exposure Analysis Modelling System [EXAMS]) modelling was conducted to estimate 30-y distributions of peak concentrations of aldicarb and the carbamate metabolites (aldicarb sulfoxide, aldicarb sulfone) in surface waters of a standard pond arising from different uses of aldicarb. The effects assessment was performed using a species sensitivity distribution (SSD) approach. The resulting risk curves as well as available incident reports suggest that risks to freshwater fish and invertebrates from exposure to aldicarb are minor. The available monitoring data did not provide conclusive evidence about risks to aquatic biota.

Probabilistic risk-assessment model for birds exposed to granular pesticides.

For granular formulations of pesticides, direct consumption by birds is generally the most important route of exposure. A probabilistic exposure model was developed that estimates how many pesticide granules a bird ingests and, from that, the quantity of pesticide ingested. This model, referred to as the "granular pesticide avian risk assessment model" (GranPARAM), has input variables not included in current screening-level assessments for granular pesticides, such as proportion of time for which birds forage in the field, grit ingestion rates, attractiveness of pesticide granules compared with natural grit, and proportions of soil particles and pesticide granules in the size range consumed by birds. For input variables that are uncertain, variable, or both, distributions are used rather than point estimates. Monte Carlo analysis is then performed to propagate input variable uncertainties through the exposure model for granular pesticides. The outputs from the exposure portion of GranPARAM are estimated pesticide doses for each of 20 birds of a selected species on each of 1000 fields. The dose for each bird is compared with a randomly chosen dose from the dose-response curve for that species or an appropriate surrogate. If the exposure dose for a bird exceeds the randomly chosen effects dose, the bird is considered dead; otherwise, the bird is assumed to be alive. Thus, the risk output from GranPARAM is a bar chart showing the percentages of fields with 0/20 dead birds, 1/20 dead birds, 2/20 dead birds, and so forth.