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Creators/Authors contains: "Koenig, Phoebe A."

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  1. Abstract

    Investment in defence may not be uniformly beneficial across an organism's lifespan. Risk, and therefore potential payoff of defence, may change with age and behaviour, but for colony‚Äźliving organisms, it may also change with colony size and reproductive stage.

    The acorn antTemnothorax longispinosususes venom to defend against socially parasitic ants that raid their nests to steal brood. We investigated the idea thatT. longispinosusadjust their venom allocation in accordance with raid risk. We tested the predictions thatT. longispinosusants should produce more venom when raids are most likely to occur and during the parts of the nest reproductive cycle when the potential fitness loss per raid is highest. We also asked whether venom volume varies between nurses and foragers within a colony, which have different potential risk levels, and whether this difference increases with colony size.

    We found that workers had more venom in the summer, both before and during the period when raids occur, than in the fall when pupae were no longer present in nests. Workers engaging in nursing behaviours had more venom as the pupa to worker ratio in the nest increased, indicating that nurses invest more in venom as the relative number of pupae requiring defence increases. In addition, the difference in venom volume between nurses and foragers grew with colony size.

    These results provide observational support for the hypothesis that individuals vary their investment in venom over their colony's development in conjunction with the risk of social parasitism.

     
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  2. Abstract

    Honey bees are vital pollinators and can be used to monitor the landscape. Consequently, interest in mounting technologies onto bees to track foraging behaviors is increasing. The barrier to entry is steep, in part because the methodology for fastening tags to bees, and the success rates, are often missing from publications. We tested six factors suspected to influence the presence and tag retention rates of nurse honey bees after their introduction to hives, and followed bees until foraging age. We also compared reintroducing foragers to their maternal colony using the best method for nurse bees to releasing them in front of their maternal hive and allowing them to fly back unaided. Nurses were most likely to be present in the hive with their tag still attached when introduced using an introduction cage at night. Glue type was important, but may further be influenced by tag material. Foragers were most likely to be present with a tag attached if released in front of their colony. Preparation and introduction techniques influence the likelihood of tagged honey bee survival and of the tags remaining attached, which should be considered when executing honey bee tagging and tracking experiments.

     
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  3. Abstract In digital agriculture, large-scale data acquisition and analysis can improve farm management by allowing growers to constantly monitor the state of a field. Deploying large autonomous robot teams to navigate and monitor cluttered environments, however, is difficult and costly. Here, we present methods that would allow us to leverage managed colonies of honey bees equipped with miniature flight recorders to monitor orchard pollination activity. Tracking honey bee flights can inform estimates of crop pollination, allowing growers to improve yield and resource allocation. Honey bees are adept at maneuvering complex environments and collectively pool information about nectar and pollen sources through thousands of daily flights. Additionally, colonies are present in orchards before and during bloom for many crops, as growers often rent hives to ensure successful pollination. We characterize existing Angle-Sensitive Pixels (ASPs) for use in flight recorders and calculate memory and resolution trade-offs. We further integrate ASP data into a colony foraging simulator and show how large numbers of flights refine system accuracy, using methods from robotic mapping literature. Our results indicate promising potential for such agricultural monitoring, where we leverage the superiority of social insects to sense the physical world, while providing data acquisition on par with explicitly engineered systems. 
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