2018 Fiscal Year Annual Research Report

Using machine vision to understand causes and consequences of collective behavior in a honey bee society(Fostering Joint International Research)

Research Project

Project/Area Number	16KK0175
Research Institution	Okinawa Institute of Science and Technology Graduate University
Principal Investigator	ミケェエヴアレクサンダー沖縄科学技術大学院大学, 生態・進化学ユニット, 准教授 (90601162)
Project Period (FY)	2016 – 2018
Keywords	animal behavior / social insects / machine learning
Outline of Annual Research Achievements	This project aimed to develop a fully-automatic bee-tracking system that would allow quantification of behavior without the need for marking individuals. We achieved this goal, developing a convolutional neural network that can identify the position and orientation of thousands of unmarked bees with an accuracy surpassing that of humans. We applied this system a whole field season of bee foraging, recording five colonies over multiple generations of workers. We are currently analyzing this massive data set, which includes data on foraging activity, weather, and should allow us to reconstruct how individual honey bee colonies allocate their workers in the face of environmental uncertainty. In addition, we are able to follow individual unmarked bees for several minutes at a time, reconstructing ~ 46% of the trajectories in 5-minute recordings and over 71% of the tracks for at least 2 minutes. These advances should enable fully automated behavioral studies of honey bee behavior, including those whose behavior has been altered either pharmacologically or with disease stressors.

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