Beyond Set Points: Rhythm-Based Detection of Change in Honey Bee Colony State from Hive Sensor Data

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Abstract
Disruption of daily patterns of activity, physiology, or social interaction is associated with stress and reduced fitness across species. In social insects such as honey bees (Apis mellifera), circadian organisation extends to the colony level, where rhythms emerge from interactions among individual clocks, hive conditions, and environmental cues. Precision apiculture offers a mature sensor toolkit for measuring colony-level variables, and several data streams carry early-warning information about colony condition. Almost all alarms, however, are triggered against set points rather than against the daily rhythm of the signal. We review each sensor technology to establish whether its data have been, or could be, analysed with a chronobiological lens, describing the measurement principle, the achievable temporal resolution and record continuity, the rhythmic signature expected on biological grounds, and any evidence that such a signature has been reported. We then use a synthetic dataset to illustrate the workflow: in this simulated example, rhythm metrics flagged a gradually developing decline approximately three weeks before a conventional threshold alert on the same data. This lead time is a property of the simulation and awaits validation on real colonies. Wherever continuous behavioural monitoring is deployed, rhythm-based metrics may offer a route to earlier, more interpretable detection of change than set point comparisons.
Funding Information
  • Royal Society Te Apārangi (24-UOA-241)
  • Ministry of Business, Innovation and Employment (23-UOA-039-CSG)
  • University of Auckland

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