Risk evaluations for agricultural chemicals are necessary to preserve healthy populations of honey bee colonies. Field studies on whole colonies are limited in behavioural research, while results from lab studies allow only restricted conclusions on whole colony impacts. Methods for automated long-term investigations of behaviours within comb cells, such as brood care, were hitherto missing. In the present study, we demonstrate an innovative video method that enables within-cell analysis in honey bee (Apis mellifera) observation hives to detect chronic sublethal neonicotinoid effects of clothianidin (1 and 10 ppb) and thiacloprid (200 ppb) on worker behaviour and development. In May and June, colonies which were fed 10 ppb clothianidin and 200 ppb thiacloprid in syrup over three weeks showed reduced feeding visits and duration throughout various larval development days (LDDs). On LDD 6 (capping day) total feeding duration did not differ between treatments. Behavioural adaptation was exhibited by nurses in the treatment groups in response to retarded larval development by increasing the overall feeding timespan. Using our machine learning algorithm, we demonstrate a novel method for detecting behaviours in an intact hive that can be applied in a versatile manner to conduct impact analyses of chemicals, pests and other stressors.

为了保护健康的蜜蜂群体，必须对农业化学品进行风险评估。对整个菌落的实地研究在行为研究中是有限的，而实验室研究的结果只能对整个菌落的影响做出有限的结论。迄今为止，缺乏对梳状细胞内行为的自动长期调查方法，例如育雏护理。在本研究中，我们演示了一种创新的视频方法，该方法可以对蜜蜂（Apis mellifera）进行细胞内分析）观察蜂巢，以检测噻虫胺（1和10 ppb）和噻虫啉（200 ppb）对工人行为和发展的慢性致死性新烟碱作用。在5月和6月，在三周内以糖浆饲喂10 ppb的可比丁和200 ppb的噻虫啉的菌落显示，在各个幼虫发育日（LDDs）期间的觅食次数和持续时间均减少。在LDD 6（封顶日）之间，各处理的总喂食时间没有差异。在治疗组中，护士表现出行为适应性，以响应于通过增加总体进食时间而延缓幼虫发育。使用我们的机器学习算法，我们演示了一种用于检测完整蜂巢中行为的新颖方法，该方法可以以多种方式应用于化学物质，有害生物和其他胁迫因素的影响分析。