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<p>Numerous studies have used electronic bee counters to gain a better understanding of the impact of environmental conditions on bee flight activity. In addition to meteorological data, the impact of plant protection products is also of great interest. In this work, we present data from bee counters collected in three semi-field studies, wherein some of the colonies were exposed to well-known chemical treatments, dimethoate or λ-cyhalothrin. We first analyze the bee flight activity of the untreated hives combined with meteorological data: multiple regression models confirm solar radiation and air temperature as the main drivers, while linear mixed models that account for temporal autocorrelation support a richer fixed-effects structure. Furthermore, we investigate the relation between visually assessed foraging activity, flight activity, and meteorological parameters. For our trials, we find weak to moderate Pearson correlations (0.21 to 0.40) between foraging and flight activity. Temperature data can improve the fit, but additional parameters are required to fully explain the foraging activity. We then analyze the signatures of the different chemical treatments in the bee flight data using Bayesian structural time series models. Our approach enables the differentiation between weather and treatment effects and facilitates the analysis of treatment signatures in the data from individual exposed colonies.</p>

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Assessing flight activity and foraging in honey bees: insights from bee counter data and plant protection product exposure in semi-field studies

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月24日

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  • Silke Andree-Labsch,
  • Klaus-Reinhard Thois

摘要

Numerous studies have used electronic bee counters to gain a better understanding of the impact of environmental conditions on bee flight activity. In addition to meteorological data, the impact of plant protection products is also of great interest. In this work, we present data from bee counters collected in three semi-field studies, wherein some of the colonies were exposed to well-known chemical treatments, dimethoate or λ-cyhalothrin. We first analyze the bee flight activity of the untreated hives combined with meteorological data: multiple regression models confirm solar radiation and air temperature as the main drivers, while linear mixed models that account for temporal autocorrelation support a richer fixed-effects structure. Furthermore, we investigate the relation between visually assessed foraging activity, flight activity, and meteorological parameters. For our trials, we find weak to moderate Pearson correlations (0.21 to 0.40) between foraging and flight activity. Temperature data can improve the fit, but additional parameters are required to fully explain the foraging activity. We then analyze the signatures of the different chemical treatments in the bee flight data using Bayesian structural time series models. Our approach enables the differentiation between weather and treatment effects and facilitates the analysis of treatment signatures in the data from individual exposed colonies.