In this study, we utilized the BEEHAVE simulation model to identify early warning indicators of stress in honey bee colonies. This research is crucial for understanding how various stressors impact bee health and for developing effective management strategies to minimize colony losses.
Why Early Warning Signals Matter
Honey bees are essential for pollination and the overall health of our ecosystems. However, they face numerous challenges, including resource stress, Varroa mites, and environmental changes. Detecting stress early in the year is vital for timely interventions that can save colonies from severe impacts later on. Our study aimed to determine which colony-level indicators could reliably signal stress before it leads to significant problems, such as increased winter mortality.
The Six Indicators We Tested
In our simulation experiments using BEEHAVE, we examined six potential indicators of colony stress:
- Number of adult bees
- Number of capped brood cells (pupae)
- Flight activity
- Number of Varroa mites
- Honey reserves
- Brood-bee ratio
These indicators were chosen to cover various aspects of colony health, from population dynamics to resource availability and parasite load.
Key Findings: Brood Cells and Brood-Bee Ratio
Our results indicate that the number of capped brood cells (pupae) and the brood-bee ratio are the most reliable early warning signals of resource stress in the landscape. These indicators provide crucial information about the colony’s reproductive potential and resource balance. Monitoring the number of pupae can be relatively straightforward and offers a clear picture of the colony’s developmental status.
Interestingly, our study found that these indicators are more sensitive to early-year stress compared to other indicators like honey reserves, which are more informative at the end of the season.
Varroa Mites: An Essential Focus
For biotic stress caused by Varroa mites, continuous monitoring remains indispensable. Effective Varroa mite control is critical to prevent the cascading effects of mite infestations over time. Despite the complexity, integrating mite monitoring with other indicators provides a comprehensive view of colony health.
The Power of Simulation Models
The BEEHAVE model has proven invaluable in simulating different stress scenarios and their impacts on bee colonies. By replicating various environmental and management conditions, we can better understand how different factors interact and influence colony health. This approach allows us to identify robust indicators that can be used in real-world monitoring and management.
Looking Forward: Combining Empirical and Simulation Studies
Our findings underscore the importance of combining empirical studies with simulation models. This integrated approach can accelerate the development of reliable health indicators and improve the assessment of environmental risks to honey bees. Future research should aim at refining these indicators and developing practical monitoring protocols that beekeepers can easily implement.
Conclusion
The VIBEE project is dedicated to advancing our understanding of honey bee health and developing tools to protect these vital pollinators. Our latest research highlights the number of brood cells and the brood-bee ratio as critical early warning signals of colony stress. By focusing on these indicators, we can enhance bee management practices and safeguard bee populations for future generations.
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Groeneveld, Jürgen; Odemer, Richard; Requier, Fabrice
Brood indicators are an early warning signal of honey bee colony loss—a simulation-based study Journal Article
In: PLOS ONE, 2024.
@article{nokey,
title = {Brood indicators are an early warning signal of honey bee colony loss—a simulation-based study},
author = {Jürgen Groeneveld and Richard Odemer and Fabrice Requier},
url = {http://vibee-project.net/wp-content/uploads/2024/05/Groeneveld_et_al_2024.pdf},
doi = {10.1371/journal.pone.0302907},
year = {2024},
date = {2024-05-16},
journal = {PLOS ONE},
abstract = {Honey bees (Apis mellifera) are exposed to multiple stressors such as pesticides, lack of forage and diseases. It is therefore a long-standing aim to develop robust and meaningful indicators of bee vitality to support beekeeping. While established indicators often focus on expected colony winter mortality based on adult bee abundance and honey stores at the beginning of the winter, it would be useful to have early warning indicators that allow detection of stress effects earlier in the year to allow for adaptive management. We used the established honey bee simulation model BEEHAVE to explore the potential of different indicators such as population size, number of capped brood cells, flight activity, abundance of varroa mites, honey stores and a brood-bee ratio. We implemented two stressor types in our simulations: 1) parasite pressure, i.e. sub-optimal Varroa treatment by the beekeeper (hereafter referred as Biotic stress) and 2) temporal forage gaps in spring and autumn (hereafter referred as Environmental stress). Neither stressor type could be detected by bee abundance or honey stores at the end of the first year. However, all response variables used in this study (population size, number of capped brood cells, flight activity, abundance of Varroa mites, honey stores, brood-bee ratio) did reveal early warning signals during the course of the year. The most reliable and useful measures seem to be related to brood and the abundance of Varroa mites at the end of the year. However, while in the model we have full access to time series of variables from stressed and unstressed colonies, knowledge of these variables in the field is challenging. We discuss how our findings can nevertheless be used to develop practical early warning indicators. As a next step in the interactive development of such indicators we suggest empirical studies on the importance of the number of capped brood cells at certain times of the year on bee population vitality. },
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Honey bees (Apis mellifera) are exposed to multiple stressors such as pesticides, lack of forage and diseases. It is therefore a long-standing aim to develop robust and meaningful indicators of bee vitality to support beekeeping. While established indicators often focus on expected colony winter mortality based on adult bee abundance and honey stores at the beginning of the winter, it would be useful to have early warning indicators that allow detection of stress effects earlier in the year to allow for adaptive management. We used the established honey bee simulation model BEEHAVE to explore the potential of different indicators such as population size, number of capped brood cells, flight activity, abundance of varroa mites, honey stores and a brood-bee ratio. We implemented two stressor types in our simulations: 1) parasite pressure, i.e. sub-optimal Varroa treatment by the beekeeper (hereafter referred as Biotic stress) and 2) temporal forage gaps in spring and autumn (hereafter referred as Environmental stress). Neither stressor type could be detected by bee abundance or honey stores at the end of the first year. However, all response variables used in this study (population size, number of capped brood cells, flight activity, abundance of Varroa mites, honey stores, brood-bee ratio) did reveal early warning signals during the course of the year. The most reliable and useful measures seem to be related to brood and the abundance of Varroa mites at the end of the year. However, while in the model we have full access to time series of variables from stressed and unstressed colonies, knowledge of these variables in the field is challenging. We discuss how our findings can nevertheless be used to develop practical early warning indicators. As a next step in the interactive development of such indicators we suggest empirical studies on the importance of the number of capped brood cells at certain times of the year on bee population vitality.
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