Abstract
The honeybee waggle dance communication system is an intriguing example of abstract animal communication and has been investigated thoroughly throughout the last seven decades. Typically, observables such as durations or angles are extracted manually directly from the observation hive or from video recordings to quantify dance properties, particularly to determine where bees have foraged. In recent years, biology has profited from automation, improving measurement precision, removing human bias, and accelerating data collection. As a further step, we have developed technologies to track all individuals of a honeybee colony and detect and decode communication dances automatically. In strong contrast to conventional approaches that focus on a small subset of the hive life, whether this regards time, space, or animal identity, our more inclusive system will help the understanding of the dance comprehensively in its spatial, temporal, and social context. In this contribution, we present full specifications of the recording setup and the software for automatic recognition and decoding of tags and dances, and we discuss potential research directions that may benefit from automation. Lastly, to exemplify the power of the methodology, we show experimental data and respective analyses for a continuous, experimental recording of nine weeks duration.
Highlights
A honeybee colony is a striking example of a complex, dynamical system (Seeley, 1995; Bonabeau et al, 1997)
Besides the mechanisms that regulate individual behavior, the flow of information in the network of individuals is a crucial factor for the emergence of unanimous colony behavior (Hölldobler and Wilson, 2009)
No system is available for the continuous long-term tracking of uniquely identifiable bees and the automatic recognition of the waggle dance, the dance-following behavior and trophallaxis. We propose such a system, in the following called the BeesBook system
Summary
A honeybee colony is a striking example of a complex, dynamical system (Seeley, 1995; Bonabeau et al, 1997). The computer vision software searches and decodes circulatrix tags in these image recordings (see Section Image Analysis) and creates the level of data, the bee detections This data, in turn, serves as input for the tracking software that identifies corresponding detections in time (see Section Tracking and Temporal ID Filter). Identification of dancers, followers, and trophallaxis Due to motion blur and the low sampling frequency, the IDs of waggle dancing bees are hard to determine from the high-res image data. Automatic Waggle Dance Detection and Decoding The waggle motion creates motion blur in the high-resolution recordings but can be detected in high-speed video The dancer swings her body laterally at a frequency of around 13 Hz. A pixel in the image corresponds to a small area on the comb surface. Procedure for this system in Section Dataset 2: Dance Detection and Decoding and report the respective results in Section Dance Detection and Decoding
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