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Zachariae, A.

Publications and source records attributed to Zachariae, A..

2 recordsLinked to original sources

Collective flow of circadian clock information in honeybee colonies

Honeybee colonies exhibit a collective circadian rhythm reflecting the periodic dynamics of the environment. Thousands of workers, including those engaged in in-hive tasks, must synchronize in various processes that may be rhythmic, such as nectar inflows, or non-rhythmic, such as brood care but it remains unknown how those different rhythms are integrated into a colony-level circadian rhythm. Using an AI-driven automated tracking system, we obtained uninterrupted long-term tracking of all individuals in two honeybee colonies. We demonstrate that circadian rhythmicity is present across all age groups and that this rhythm is entrained into all individuals, however, with peak activity shifting by up to 2 hours in workers furthest from the entrance. Extensive data analysis and an agent-based model suggest that mechanical interactions between individuals facilitate the transfer of movement speed, and hence Zeitgeber information. Finally, we show that this speed transfer leads to a collective slow wave of activity that initiates at the nest entrance, spreading throughout the nest. This simple mechanism, workers bumping into each other, enables colonies to entrain their rhythm to the daily cycle of the external environment and, because of the spatial organization of the nest, activates different groups of workers sequentially. The speed transfer interactions demonstrate a tightly-tuned mechanism that underlines the elegant self-organization of the superorganism.

animal behavior and cognition↗

Social networks predict the life and death of honey bees

In complex societies, individuals roles are reflected by interactions with other conspecifics. Honey bees (Apis mellifera) generally change tasks as they age, but developmental trajectories of individuals can vary drastically due to physiological and environmental factors. We introduce a succinct descriptor of an individuals social network that can be obtained without interfering with the colony. This network age accurately predicts task allocation, survival, activity patterns, and future behavior. We analyze developmental trajectories of multiple cohorts of individuals in a natural setting and identify distinct developmental pathways and critical life changes. Our findings suggest a high stability in task allocation on an individual level. We show that our method is versatile and can extract different properties from social networks, opening up a broad range of future studies. Our approach highlights the relationship of social interactions and individual traits, and provides a scalable technique for understanding how complex social systems function.

animal behavior and cognition↗