Assessing honeybee colony health using temperature time series.

Abstract

Honeybees face an increasing number of stressors that disrupt the natural behaviour of colonies and, in extreme cases, can lead to their collapse. Quantifying the status and resilience of colonies is essential to measure the impact of stressors and to identify colonies at risk. In this article, we present and apply a methodology to efficiently diagnose the status of a honeybee colony based on a metric of its thermoregulatory capacity. This metric is derived from data-informed analysis of time series, specifically the hive's core temperature in relation to environmental temperature. Healthy honeybee colonies have a remarkable ability to control temperature near the brood area. Our method exploits this fact and quantifies the status of a hive by measuring how resilient they are to extreme environmental temperatures, which act as natural stressors. After analysing 22 hives during different times of the year, including three hives that collapsed, we find the statistical signatures of stress that reveal whether honeybee colonies are stable or are at risk of failure. Based on these analyses, we propose a simple scale of hive status (stable, warning and collapse) that, once calibrated, can be used to diagnose hive status from a few temperature measurements. Our approach offers a lower cost and practical bee-monitoring solution, providing a non-invasive way to track hive conditions and trigger interventions to save colonies from collapse.