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The assessment of pesticide risks to bees in North America currently relies in part on Tier 1 honey bee laboratory toxicity studies to support the registration and registration review processes for crop protection chemicals. For immature stages, the studies follow two standardized test designs recommended by the Organization for Economic Cooperation (OECD), evaluating acute (seven-day single-dose, TG OECD 237) and chronic (22-day repeated-dose, GD OECD 239) toxicity in bee larvae. In this article, we aim to evaluate the current approach for generating and interpreting honey bee larval toxicity data, enhancing pesticide risk assessment for pollinators. First, by considering that the repeated-dose larval study covers all stages of honey bee brood development up to adult emergence, we compared endpoints (larval LD/ED50 and LC/EC50 values) from seven-day acute exposure studies with the 22-day chronic exposure studies. Our goal was to identify the study design offering greater sensitivity in assessing pesticide toxicity to immature bees. Our second objective involved analyzing available weight data from emerged adults and comparing it to survival endpoints (e.g., NOEL and LD50) to determine if the weight after adult emergence would accurately represent a sensitive indicator of pesticide effects on developing honey bees. Our analysis determined that the use of a single 22-day chronic exposure study adequately covers all immature stages and that the toxicity values based on cumulative dose are more accurate and representative measures of exposure for immature bees than using endpoints based on estimated daily doses. Furthermore, our analysis suggests that measuring the weight of emerged adults was a more sensitive indicator than mortality of treatment-related effects in 22% of the compounds included in our analysis. Here we also discuss the importance of standardized protocols for proper collection of weight after emergence and the need for further discussion on the relevance of this parameter at risk assessment scheme. Integr Environ Assess Manag 2024;00:1-11. © 2024 SETAC.

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Section 7 of the Endangered Species Act requires the US Environmental Protection Agency (US EPA) to consult with the Services (US Fish and Wildlife Service and National Marine Fisheries Service) over potential pesticide impacts on federally listed species. Consultation is complicated by the large number of pesticide products and listed species, as well as by lack of consensus on best practices for conducting co-occurrence analyses. Previous work demonstrates that probabilistic estimates of species' ranges and pesticide use patterns improve these analyses. Here we demonstrate that such estimates can be made for suites of sympatric listed species. Focusing on two watersheds, one in Iowa and the other in Mississippi, we obtained distribution records for 13 species of terrestrial and aquatic listed plants and animals occurring therein. We used maximum entropy modeling and bioclimatic, topographic, hydrographic, and land cover variables to predict species' ranges at high spatial resolution. We constructed probabilistic spatial models of use areas for two pesticides based on the US Department of Agriculture Cropland Data Layer and reduced classification errors by incorporating information on the relationships between individual pixels and their neighbors using object-based images analysis. We then combined species distribution and crop footprint models to derive overall probability of co-occurrence of listed species and pesticide use. For aquatic species, we also integrated an estimate of downstream residue transport. We report each separate species-by-use-area co-occurrence estimate and also combine these modeled co-occurrence probabilities across species within watersheds to produce an overall metric of potential pesticide exposure risk for these listed species at the watershed level. We propose that the consultation process between US EPA and the Services be based on such batched estimation of probabilistic co-occurrence for multiple listed species at a regional scale. Integr Environ Assess Manag 2022;18:1088-1100. © 2021 SETAC.

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In many countries, the western honey bee is used as surrogate in pesticide risk assessments for bees. However, uncertainty remains in the estimation of pesticide risk to non-Apis bees because their potential routes of exposure to pesticides, life histories, and ecologies differ from those of honey bees. We applied the vulnerability concept in pesticide risk assessment to 10 bee species including the honey bee, 2 bumble bee species, and 7 solitary bee species with different nesting strategies. Trait-based vulnerability considers the evaluation of a species at the level of both the organism (exposure and effect) and the population (recovery), which goes beyond the sensitivity of individuals to a toxicant assessed in standard laboratory toxicity studies by including effects on populations in the field. Based on expert judgment, each trait was classified by its relationship to the vulnerability to pesticide exposure, effects (intrinsic sensitivity), and population recovery. The results suggested that the non-Apis bees included in our approach are potentially more vulnerable to pesticides than the honey bee due to traits governing exposure and population recovery potential. Our analysis highlights many uncertainties related to the interaction between bee ecology and the potential exposures and population-level effects of pesticides, emphasizing the need for more research to identify suitable surrogate species for higher tier bee risk assessments. Environ Toxicol Chem 2021;40:2640-2651. © 2021 SETAC.

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Characterizing potential spatial overlap between federally threatened and endangered ("listed") species distributions and registered pesticide use patterns is important for accurate risk assessment of threatened and endangered species. Because accurate range information for such rare species is often limited and agricultural pesticide use patterns are dynamic, simple spatial co-occurrence methods may overestimate or underestimate overlap and result in decisions that benefit neither listed species nor the regulatory process. Here, we demonstrate a new method of co-occurrence analysis that employs probability theory to estimate spatial distribution of rare species populations and areas of pesticide use to determine the likelihood of potential exposure. Specifically, we 1) describe a probabilistic method to estimate pesticide use based on crop production patterns; 2) construct species distribution models for 2 listed insect species whose ranges were previously incompletely described, the rusty-patched bumble bee (Bombus affinis) and the Poweshiek skipperling (Oarisma poweshiek); and 3) develop a probabilistic co-occurrence methodology and assessment framework. Using the principles of the Bayes' theorem, we constructed probabilistic spatial models of pesticide use areas by integrating information from land-cover spatial data, agriculture statistics, and remote-sensing data. We used maximum entropy methods to build species distribution models for 2 listed insects based on species collection and observation records and predictor variables relevant to the species' biogeography and natural history. We further developed novel methods for refinement of these models at spatial scales relevant to US Fish and Wildlife Service (FWS) regulatory priorities (e.g., critical habitat areas). Integrating both probabilistic assessments and focusing on USFWS priority management areas, we demonstrate that spatial overlap (i.e., potential for exposure) is not deterministic but instead a function of both species distribution and land use patterns. Our work serves as a framework to enhance the accuracy and efficiency of threatened and endangered species assessments using a data-driven likelihood analysis of species co-occurrence. Integr Environ Assess Manag 2019;00:1-12. © 2019 SETAC.

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Neonicotinoid insecticides have been used in a wide range of crops through seed treatment, soil and foliar applications and a large database exists on both their lethal and sub-lethal effects on honey bees under controlled laboratory conditions. However, colony-level studies on the effects of neonicotinoids in field studies are limited, primarily due to their complexity and the resources required. This paper reports the combined results of two large-scale colony-feeding studies, each with 6 weeks of continuous dosing of 12 colonies per treatment (24 control) to 12.5, 25, 37.5, 50 or 100 ng thiamethoxam/g sucrose solution. Exposure continued beyond dosing with residues present in stored nectar and bee-bread. The studies were conducted in an area with limited alternative forage and colonies were required to forage for pollen and additional nectar The studies provide colony-level endpoints: significant effects (reductions in bees, brood) were observed after exposure to the two highest dose rates, colony loss occurred at the highest dose rate, but colonies were able to recover (2-3 brood cycles after the end of dosing) after dosing with 50 ng thiamethoxam/g sucrose. No significant colony-level effects were observed at lower dose rates. The data reported here support the conclusions of previous colony-level crop-based field studies with thiamethoxam, in which residues in pollen and nectar were an order of magnitude below the colony-level NOEC of 37.5 ng thiamethoxam/g sucrose. The feeding study data are also compared to the outcomes of regulatory Tier 1 risk assessments conducted using guidance provided by the USA, Canada, Brazil and the EU regulatory authorities. We propose an adaptation of the European chronic adult bee risk assessment that takes into account the full dataset generated in laboratory studies while still providing an order of magnitude of safety compared with the colony feeding study NOEC.

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Neonicotinoid insecticides have been used globally on a wide range of crops through seed treatment as well as soil and foliar applications and have been increasingly studied in relation to the potential risk to bees because of their detection in pollen and nectar of bee-attractive crops. The present article reports the results of laboratory studies (10-d adult and 22-d larval toxicity studies assessing the chronic toxicity of thiamethoxam to adult honey bees and larvae, respectively) and a colony feeding study, with 6 wk of exposure in an area with limited alternative forage, to provide a prewintering colony-level endpoint. The endpoints following exposure of individuals in the laboratory (10-d adult chronic no-observed-effect concentration [NOEC] for mortality 117 µg thiamethoxam/kg sucrose solution, 141 µg thiamethoxam/L sucrose solution; 22-d larval chronic NOEC 102 µg thiamethoxam/kg diet) are compared with those generated at the colony level, which incorporates sublethal effects (no-observed-adverse-effect concentration [NOAEC] 50 µg thiamethoxam/L sucrose solution, 43 µg thiamethoxam/kg sucrose solution). The data for sucrose-fed honey bee colonies support the lack of effects identified in previous colony-level field studies with thiamethoxam. However, unlike these field studies demonstrating no effects, colony feeding study data also provide a threshold level of exposure likely to result in adverse effects on the colony in the absence of alternative forage, and a basis by which to evaluate the potential risk of thiamethoxam residues detected in pollen, nectar, or water following treatment of bee-attractive crops. Environ Toxicol Chem 2018;37:816-828. © 2017 SETAC.

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