Assessment of the Vulnerability to Pesticide Exposures Across Bee Species.

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.

Overview of the testing and assessment of effects of microbial pesticides on bees: strengths, challenges and perspectives.

Currently, there is a growing interest in developing biopesticides and increasing their share in the plant protection market as sustainable tools in integrated pest management (IPM). Therefore, it is important that regulatory requirements are consistent and thorough in consideration of biopesticides' unique properties. While microbial pesticides generally have a lower risk profile, they present special challenges in non-target organism testing and risk assessment since, in contrast to chemical pesticides, their modes of action include infectivity and pathogenicity rather than toxicity alone. For this reason, non-target organism testing guidelines designed for conventional chemical pesticides are not necessarily directly applicable to microbial pesticides. Many stakeholders have recognised the need for improvements in the guidance available for testing microbial pesticides with honey bees, particularly given the increasing interest in development and registration of microbial pesticides and concerns over risks to pollinators. This paper provides an overview of the challenges with testing and assessment of the effects of microbial pesticides on honey bees (Apis mellifera), which have served as a surrogate for both Apis and non-Apis bees, and provides a foundation toward developing improved testing methods.

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.

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.

A Comparison of Acute Toxicity Endpoints for Adult Honey Bees with Technical Grade Active Ingredients and Typical End-use Products as Test Substance.

The honey bee, Apis mellifera L. (Hymenoptera: Apidae), is a model organism for pollinators in risk assessment frameworks globally. The acute toxicity tests with adult honey bees for contact and oral exposure are part of the requirements for pesticide registration and are typically conducted with the active ingredient. A question often asked is if the typical end-use product (TEP) is more toxic than the technical grade active ingredient (TGAI) to honey bees. We explored this question by mining publicly available databases from regulatory agencies worldwide, where testing with the TEP is required. The objective of this study was to determine whether TEPs are comparable in toxicity to the TGAI. The dataset was analyzed via a 3 × 3 contingency table with toxicity categories, as the data cannot be computed for regression analysis. Of the 151 active ingredients with reported endpoints for contact exposure, 28 were classified as either moderately or highly toxic, 123 were classified as practically nontoxic, and 3 were inconclusive. Only two (1.3%) were reclassified from nontoxic to moderately toxic as the TEP. Of the 141 active ingredients with reported endpoints for oral exposure, 23 were classified as moderately or highly toxic, 113 were classified as practically nontoxic, and 5 were inconclusive. Only five (3.6%) were reclassified from nontoxic to moderately toxic as the TEP. Fewer than 5% of the total TEPs evaluated (contact and oral) were shown to be more toxic than the TGAI, suggesting that the risk assessments of TGAIs would be sufficiently protective to pollinators at the screening laboratory level.

Pesticide Exposure Assessment Paradigm for Solitary Bees.

Current pesticide risk assessment for bees relies on a single (social) species, the western honey bee, Apis mellifera L. (Hymenoptera: Apidae). However, most of the >20,000 bee species worldwide are solitary. Differences in life history traits between solitary bees (SB) and honey bees (HB) are likely to determine differences in routes and levels of pesticide exposure. The objectives of this review are to: 1) compare SB and HB life history traits relevant for risk assessment; 2) summarize current knowledge about levels of pesticide exposure for SB and HB; 3) identify knowledge gaps and research needs; 4) evaluate whether current HB risk assessment schemes cover routes and levels of exposure of SB; and 5) identify potential SB model species for risk assessment. Most SB exposure routes seem well covered by current HB risk assessment schemes. Exceptions to this are exposure routes related to nesting substrates and nesting materials used by SB. Exposure via soil is of particular concern because most SB species nest underground. Six SB species (Hymenoptera: Megachilidae - Osmia bicornis L., O. cornifrons Radoszkowski, O. cornuta Latreille, O. lignaria Say, Megachile rotundata F., and Halictidae - Nomia melanderi Cockerell) are commercially available and could be used in risk assessment. Of these, only N. melanderi nests underground, and the rest are cavity-nesters. However, the three Osmia species collect soil to build their nests. Life history traits of cavity-nesting species make them particularly suitable for semifield and, to a lesser extent, field tests. Future studies should address basic biology, rearing methods and levels of exposure of ground-nesting SB species.

Workshop on Pesticide Exposure Assessment Paradigm for Non-Apis Bees: Foundation and Summaries.

Current pesticide risk assessment practices use the honey bee, Apis mellifera L., as a surrogate to characterize the likelihood of chemical exposure of a candidate pesticide for all bee species. Bees make up a diverse insect group that provides critical pollination services to both managed and wild ecosystems. Accordingly, they display a diversity of behaviors and vary greatly in their lifestyles and phenologies, such as their timing of emergence, degree of sociality, and foraging and nesting behaviors. Some of these factors may lead to disparate or variable routes of exposure when compared to honey bees. For those that possess life histories that are distinct from A. mellifera, further risk assessments may be warranted. In January 2017, 40 bee researchers, representative of regulatory agencies, academia, and agrochemical industries, gathered to discuss the current state of science on pesticide exposure to non-Apis bees and to determine how well honey bee exposure estimates, implemented by different regulatory agencies, may be protective for non-Apis bees. Workshop participants determined that although current risk assessment procedures for honey bees are largely conservative, several routes of exposure are unique to non-Apis bees and warranted further investigation. In this forum article, we discuss these key routes of exposure relevant to non-Apis bees and identify important research gaps that can help inform future bee risk assessment decisions.

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.

Initial recommendations for higher-tier risk assessment protocols for bumble bees, Bombus spp. (Hymenoptera: Apidae).

Global declines of bumble bees and other pollinator populations are of concern because of their critical role for crop production and maintenance of wild plant biodiversity. Although the consensus among scientists is that the interaction of many factors, including habitat loss, forage scarcity, diseases, parasites, and pesticides, potentially plays a role in causing these declines, pesticides have received considerable attention and scrutiny. In response, regulatory agencies have introduced more stringent pollinator testing requirements for registration and reregistration of pesticides, to ensure that the risks to pollinators are minimized. In this context, guidelines for testing bumble bees (Bombus spp.) in regulatory studies are not yet available, and a pressing need exists to develop suitable protocols for routine higher-tier studies with these non-Apis sp., social bees. To meet this need, Bayer CropScience LP, Syngenta Crop Protection LLC US, and Valent USA. Corporation organized a workshop bringing together a group of global experts on bumble bee behavior, ecology, and ecotoxicology to discuss and develop draft protocols for both semi-field (Tier II) and field (Tier III) studies. The workshop was held May 8-9, 2014, at the Bayer Bee Care Center, North Carolina, USA. The participants represented academic, consulting, and industry scientists from Europe, Canada, the United States, and Brazil. The workshop identified a clear protection goal and generated proposals for basic experimental designs, relevant measurements, and endpoints for both semifield (tunnel) and field tests. These initial recommendations are intended to form the basis of discussions to help advance the development of appropriate protocol guidelines.

Using toxicokinetic-toxicodynamic modeling as an acute risk assessment refinement approach in vertebrate ecological risk assessment.

Recent guidance identified toxicokinetic-toxicodynamic (TK-TD) modeling as a relevant approach for risk assessment refinement. Yet, its added value compared to other refinement options is not detailed, and how to conduct the modeling appropriately is not explained. This case study addresses these issues through 2 examples of individual-level risk assessment for 2 hypothetical plant protection products: 1) evaluating the risk for small granivorous birds and small omnivorous mammals of a single application, as a seed treatment in winter cereals, and 2) evaluating the risk for fish after a pulsed treatment in the edge-of-field zone. Using acute test data, we conducted the first tier risk assessment as defined in the European Food Safety Authority (EFSA) guidance. When first tier risk assessment highlighted a concern, refinement options were discussed. Cases where the use of models should be preferred over other existing refinement approaches were highlighted. We then practically conducted the risk assessment refinement by using 2 different models as examples. In example 1, a TK model accounting for toxicokinetics and relevant feeding patterns in the skylark and in the wood mouse was used to predict internal doses of the hypothetical active ingredient in individuals, based on relevant feeding patterns in an in-crop situation, and identify the residue levels leading to mortality. In example 2, a TK-TD model accounting for toxicokinetics, toxicodynamics, and relevant exposure patterns in the fathead minnow was used to predict the time-course of fish survival for relevant FOCUS SW exposure scenarios and identify which scenarios might lead to mortality. Models were calibrated using available standard data and implemented to simulate the time-course of internal dose of active ingredient or survival for different exposure scenarios. Simulation results were discussed and used to derive the risk assessment refinement endpoints used for decision. Finally, we compared the "classical" risk assessment approach with the model-based approach. These comparisons showed that TK and TK-TD models can bring more realism to the risk assessment through the possibility to study realistic exposure scenarios and to simulate relevant mechanisms of effects (including delayed toxicity and recovery). Noticeably, using TK-TD models is currently the most relevant way to directly connect realistic exposure patterns to effects. We conclude with recommendations on how to properly use TK and TK-TD model in acute risk assessment for vertebrates.