Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Schmolke A

PROVIDER: S-EPMC6850421 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Schmolke Amelie A Abi-Akar Farah F Hinarejos Silvia S

Environmental toxicology and chemistry 20190107 2

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 colon ...[more]

PMID: 30575066

Similar Datasets

Project description:Social bees are central place foragers collecting floral resources from the surrounding landscape, but little is known about the probability of a scouting bee finding a particular flower patch. We therefore developed a software tool, BEESCOUT, to theoretically examine how bees might explore a landscape and distribute their scouting activities over time and space. An image file can be imported, which is interpreted by the model as a "forage map" with certain colours representing certain crops or habitat types as specified by the user. BEESCOUT calculates the size and location of these potential food sources in that landscape relative to a bee colony. An individual-based model then determines the detection probabilities of the food patches by bees, based on parameter values gathered from the flight patterns of radar-tracked honeybees and bumblebees. Various "search modes" describe hypothetical search strategies for the long-range exploration of scouting bees. The resulting detection probabilities of forage patches can be used as input for the recently developed honeybee model BEEHAVE, to explore realistic scenarios of colony growth and death in response to different stressors. In example simulations, we find that detection probabilities for food sources close to the colony fit empirical data reasonably well. However, for food sources further away no empirical data are available to validate model output. The simulated detection probabilities depend largely on the bees' search mode, and whether they exchange information about food source locations. Nevertheless, we show that landscape structure and connectivity of food sources can have a strong impact on the results. We believe that BEESCOUT is a valuable tool to better understand how landscape configurations and searching behaviour of bees affect detection probabilities of food sources. It can also guide the collection of relevant data and the design of experiments to close knowledge gaps, and provides a useful extension to the BEEHAVE honeybee model, enabling future users to explore how landscape structure and food availability affect the foraging decisions and patch visitation rates of the bees and, in consequence, to predict colony development and survival.

Project description:Honey bee (Apis mellifera) colonies continue to experience high annual losses that remain poorly explained. Numerous interacting factors have been linked to colony declines. Understanding the pathways linking pathophysiology with symptoms is an important step in understanding the mechanisms of disease. In this study we examined the specific pathologies associated with honey bees collected from colonies suffering from Colony Collapse Disorder (CCD) and compared these with bees collected from apparently healthy colonies. We identified a set of pathological physical characteristics that occurred at different rates in CCD diagnosed colonies prior to their collapse: rectum distension, Malpighian tubule iridescence, fecal matter consistency, rectal enteroliths (hard concretions), and venom sac color. The multiple differences in rectum symptomology in bees from CCD apiaries and colonies suggest effected bees had trouble regulating water. To ensure that pathologies we found associated with CCD were indeed pathologies and not due to normal changes in physical appearances that occur as an adult bee ages (CCD colonies are assumed to be composed mostly of young bees), we documented the changes in bees of different ages taken from healthy colonies. We found that young bees had much greater incidences of white nodules than older cohorts. Prevalent in newly-emerged bees, these white nodules or cellular encapsulations indicate an active immune response. Comparing the two sets of characteristics, we determined a subset of pathologies that reliably predict CCD status rather than bee age (fecal matter consistency, rectal distension size, rectal enteroliths and Malpighian tubule iridescence) and that may serve as biomarkers for colony health. In addition, these pathologies suggest that CCD bees are experiencing disrupted excretory physiology. Our identification of these symptoms is an important first step in understanding the physiological pathways that underlie CCD and factors impacting bee health.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure