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Pests and pathogens are a primary threat to honey bee(Apis mellifera)colonies worldwide. Selective breeding for honey bees resistant to these stressors represents a promising approach for mitigating their impacts on honey bee health. UBeeO is a novel hygiene-eliciting selection tool that has been used to identify honey bee colonies that are resistant to the parasitic miteVarroa destructor, and that are more likely to survive winter without beekeeper intervention. Here, we used three separate case studies to evaluate the effectiveness of the UBeeO assay in identifying colonies resist to disease. In three distinct geographic regions, we measured UBeeO scores along with the prevalence and load of key fungal and viral honey bee pathogens. We show that UBeeO can be used to identify colonies resistant to several other diseases, including the two fungal pathogens chalkbrood (Ascosphaera apis) andVairimorphaspp. (previouslyNosema), and multiple viruses, all critically important to honey bee health and survival. Furthermore, we identify potential UBeeO resistance thresholds for each pathogen, demonstrating an inverse relationship between pathogen virulence and the minimum UBeeO score associated with resistance to that pathogen. These findings suggest that UBeeO-guided selection strategies have the potential to significantly improve honey bee breeding programs by facilitating identification of resilient and pathogen-resistant colonies. The broad geographic range of our study sites underscores the robustness and applicability of UBeeO across varying environmental contexts. Since honey bees provide essential pollination services in both natural and agricultural ecosystems, this work has major implications for environmental health, crop productivity, and food security on a global scale.
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This content will become publicly available on August 7, 2026
Spatiotemporal, environmental, and behavioral predictors of Varroa mite intensity in managed honey bee apiaries
Honey bees contribute substantially to the world economy through pollination services and honey production. In the U.S. alone, honey bee pollination is estimated to contribute at least $11 billion annually, primarily through the pollination of specialty crops. However, beekeepers lose about half of their hives every season due to disease, insecticides, and other environmental factors. Here, we explore and validate a spatiotemporal statistical model ofVarroa destructormite burden (in mites/300 bees) in managed honey bee colonies, exploring the impact of both environmental factors and beekeeper behaviors. We examine risk factors forVarroainfestation using apiary inspection data collected across the state of Illinois over 2018–2019, and we test the models using inspection data from 2020–2021. After accounting for spatial and temporal trends, we find that most environmental factors (e.g., floral quality, insecticide load) are not predictive ofVarroaintensity, while lower numbers of nearby apiaries and several beekeeper behaviors (e.g., supplemental feeding and mite monitoring/treatment) are protective againstVarroa. Interestingly, while monitoringandtreating forVarroais protective, treatingwithoutmonitoring is no more effective than not treating at all. This is an important result supporting Integrated Pest Management (IPM) approaches.
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- Award ID(s):
- 2022049
- PAR ID:
- 10629090
- Editor(s):
- Rueppell, Olav
- Publisher / Repository:
- PLOS
- Date Published:
- Journal Name:
- PLOS One
- Volume:
- 20
- Issue:
- 8
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0325801
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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