Abstract
Honeybees form societies in which thousands of members integrate their behaviours to act as a single functional unit. We have little knowledge on how the collaborative features are regulated by workers’ activities because we lack methods that enable collection of simultaneous and continuous behavioural information for each worker bee. In this study, we introduce the Bee Behavioral Annotation System (BBAS), which enables the automated detection of bees’ behaviours in small observation hives. Continuous information on position and orientation were obtained by marking worker bees with 2D barcodes in a small observation hive. We computed behavioural and social features from the tracking information to train a behaviour classifier for encounter behaviours (interaction of workers via antennation) using a machine learning-based system. The classifier correctly detected 93% of the encounter behaviours in a group of bees, whereas 13% of the falsely classified behaviours were unrelated to encounter behaviours. The possibility of building accurate classifiers for automatically annotating behaviours may allow for the examination of individual behaviours of worker bees in the social environments of small observation hives. We envisage that BBAS will be a powerful tool for detecting the effects of experimental manipulation of social attributes and sub-lethal effects of pesticides on behaviour.
Highlights
Honeybees, like other eusocial insects, form societies in which their members integrate their behaviours to form a single functional unit[1]
Encounter behaviours summarize different worker-worker interaction behaviours that display constant antennal contact and can be further grouped into the following behaviours: (i) antennation behaviour, which is required to initialize and maintain a contact[16], whereby the antennae of two worker bees are in constant contact but no other features of the following behaviours are displayed; (ii) begging behaviour, in which a worker bee begs for food from another nestmate;[16,17] (iii) offering behaviour, in which a worker bee offers food to another nestmate;[17] and, (iv) trophallaxis behaviour, in which nectar from the crop is exchanged between two bees[18,19]
To automatically classify worker behaviours in a small observation hive, we developed the Bee Behavioral Annotation System (BBAS)
Summary
Like other eusocial insects, form societies in which their members integrate their behaviours to form a single functional unit (often described as ‘superorganisms’)[1]. A honeybee may engage in many behavioural tasks, for example, cell cleaning, brood feeding, comb building, pollen and nectar storing, and foraging[3]. Gaining continuous behavioural information on each single worker, their direct contacts (encounters) to other worker bees and their interactions with the local environment would facilitate the further characterization of the underlying mechanisms of colony organization. We currently lack methods that enable the collection of simultaneous and continuous behavioural information for each individual worker bee in the environment of a colony[12]. Behaviours are manually detected by an observer either from video recordings of small observation hives or from direct observations[3,13,14,15]. Encounter behaviours summarize different worker-worker interaction behaviours that display constant antennal contact and can be further grouped into the following behaviours: (i) antennation behaviour, which is required to initialize and maintain a contact[16], whereby the antennae of two worker bees are in constant contact but no other features of the following behaviours are displayed; (ii) begging behaviour, in which a worker bee begs for food from another nestmate;[16,17] (iii) offering behaviour, in which a worker bee offers food to another nestmate;[17] and, (iv) trophallaxis behaviour, in which nectar from the crop is exchanged between two bees[18,19]
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