LAUSR

Tracking the movement of all individual group members in their natural environment remains a challenging task. Using advances in computer vision and Deep Learning, we developed and tested a semi‐automated in situ tracking system to reconstruct simultaneous three‐dimensional trajectories of marked individuals in social groups of a coral‐reef fish. Our system has a temporal resolution of 10s of milliseconds, allowing for multiple 30‐min tracking sessions that have been repeated over weeks to months. We present the technique and illustrate its application for Dascyllus marginatus, a planktivorous damselfish that lives in social groups associated with branching corals. Our technique identified all individuals 85–100% of the time, with a mean spatial error of ~ 1.3 cm. It provides a cost‐effective semi‐automated tool for in situ research on movements and foraging of individuals within small site‐attached groups of animals in their natural environment.