Honey bees are crucial pollinators for agricultural crops but are threatened by a multitude of stressors including exposure to pesticides. Linking our understanding of how pesticides affect individual bees to colony-level responses is challenging because colonies show emergent properties based on complex internal processes and interactions among individual bees. Agent-based models that simulate honey bee colony dynamics may be a tool for scaling between individual and colony effects of a pesticide. The U.S. Environmental Protection Agency (USEPA) and U.S. Department of Agriculture (USDA) are developing the VarroaPop + Pesticide model, which simulates the dynamics of honey bee colonies and how they respond to multiple stressors, including weather, Varroa mites, and pesticides. To evaluate this model, we used Approximate Bayesian Computation to fit field data from an empirical study where honey bee colonies were fed the insecticide clothianidin. This allowed us to reproduce colony feeding study data by simulating colony demography and mortality from ingestion of contaminated food. We found that VarroaPop + Pesticide was able to fit general trends in colony population size and structure and reproduce colony declines from increasing clothianidin exposure. The model underestimated adverse effects at low exposure (36 µg/kg), however, and overestimated recovery at the highest exposure level (140 µg/kg), for the adult and pupa endpoints, suggesting that mechanisms besides oral toxicity-induced mortality may have played a role in colony declines. The VarroaPop + Pesticide model estimates an adult oral LD₅₀ of 18.9 ng/bee (95% CI 10.1–32.6) based on the simulated feeding study data, which falls just above the 95% confidence intervals of values observed in laboratory toxicology studies on individual bees. Overall, our results demonstrate a novel method for analyzing colony-level data on pesticide effects on bees and making inferences on pesticide toxicity to individual bees.

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使用菌落模型和贝叶斯推理从基于田间的喂养研究推断杀虫剂对蜜蜂的毒性

蜜蜂是农作物的重要传粉者，但受到包括接触杀虫剂在内的多种压力源的威胁。将我们对农药如何影响个体蜜蜂的理解与蜂群水平的反应联系起来具有挑战性，因为蜂群基于复杂的内部过程和个体蜜蜂之间的相互作用显示出紧急特性。模拟蜜蜂群动态的基于代理的模型可能是一种在农药的个体效应和群效应之间进行缩放的工具。美国环境保护署 (USEPA) 和美国农业部 (USDA) 正在开发 VarroaPop + Pesticide 模型，该模型模拟蜜蜂群落的动态以及它们如何应对多种压力源，包括天气、Varroa螨虫和杀虫剂。为了评估这个模型，我们使用近似贝叶斯计算来拟合来自经验研究的现场数据，其中蜜蜂群落被喂食杀虫剂噻虫胺。这使我们能够通过模拟菌落人口统计和摄入受污染食物的死亡率来重现菌落喂养研究数据。我们发现 VarroaPop + Pesticide 能够适应菌落种群规模和结构的总体趋势，并重现由于噻虫胺暴露量增加而导致的菌落下降。然而，该模型低估了在低暴露水平（36 µg/kg）下的不良反应，并高估了成年和蛹终点在最高暴露水平（140 µg/kg）下的恢复，这表明除了口服毒性引起的死亡率之外的机制可能具有在殖民地下降中发挥了作用。VarroaPop + Pesticide 模型估计成人口服 LD_{18.9 ng/蜜蜂中的50}只（95% CI 10.1-32.6）基于模拟喂养研究数据，略高于在实验室毒理学研究中观察到的单个蜜蜂值的 95% 置信区间。总体而言，我们的研究结果证明了一种新方法，用于分析农药对蜜蜂的影响的菌落水平数据，并推断农药对个体蜜蜂的毒性。