Minaud Étienne, Rebaudo François, Davidson Padraig, Hatjina Fani, Hotho Andreas, Mainardi Giulia, Steffan-Dewenter Ingolf, Vardakas Philippos, Verrier Elise, Requier Fabrice
Université Paris-Saclay, CNRS, IRD, UMR Évolution, Génomes, Comportement et Écologie, 91198, Gif-sur-Yvette, France.
Data Science Chair, Center for Artificial Intelligence and Data Science (CAIDAS), University of Würzburg, Würzburg, Germany.
Heliyon. 2024 Jul 10;10(14):e34390. doi: 10.1016/j.heliyon.2024.e34390. eCollection 2024 Jul 30.
High winter mortality of honey bees () has been observed in temperate regions over the past 30 years. Several biotic and abiotic stressors associated with winter colony losses have been identified, but the mechanisms and interactions underlying their effects remain unclear. We reviewed the effects of stressors on key overwintering biological traits, distinguishing between individual and colony traits. We found that disturbances at the level of individual traits can be amplified when transmitted to colony traits. By analyzing these cascading effects, we propose a concept of a feedback loop mechanism of winter mortality. We found that population size, social thermoregulation and honey reserve are integrative traits and can predict overwintering failure. Furthermore, we identified social thermoregulation as a good candidate for an early warning indicator. We therefore discuss existing tools for monitoring hive temperature to help mitigate the current high winter mortality of honey bees and support the sustainability of beekeeping.
在过去30年里，温带地区观察到蜜蜂（）冬季死亡率很高。已经确定了一些与冬季蜂群损失相关的生物和非生物应激源，但其影响背后的机制和相互作用仍不清楚。我们回顾了应激源对关键越冬生物学特性的影响，区分了个体和蜂群特性。我们发现，个体特性层面的干扰传递到蜂群特性时会被放大。通过分析这些级联效应，我们提出了冬季死亡率反馈回路机制的概念。我们发现种群规模、社会体温调节和蜂蜜储备是综合特性，能够预测越冬失败。此外，我们确定社会体温调节是一个很好的早期预警指标候选。因此，我们讨论了现有的监测蜂箱温度的工具，以帮助减轻当前蜜蜂冬季的高死亡率，并支持养蜂业的可持续性。
