Assessing Honey Bee Colony Health Using Temperature Time Series

TL;DR

This paper introduces a new, practical method to assess honey bee colony health by analyzing temperature time series, enabling early detection of stress and risk of collapse through non-invasive monitoring.

Contribution

The study presents a novel approach that uses temperature resilience metrics to diagnose hive health, offering a low-cost, non-invasive monitoring tool for beekeepers.

Findings

Identified temperature resilience signatures indicating hive stress

Developed a simple scale to classify hive status (stable, warning, collapse)

Validated the method on 22 hives with successful stress detection

Abstract

Honey bees 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 manuscript, we present and apply new methodologies to efficiently diagnose the status of a honey bee colony from widely available time series of hive and environmental temperature. Healthy hives 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. Analysing 22 hives during different times of the year, including 3 hives that collapsed, we find the statistical signatures of stress that reveal whether honeybees are doing well or are at risk of failure. Based on these analyses, we propose a simple scale of hive status (stable, warning, and collapse) that can be determined based on 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 the hives from collapse.