Automated and repeated aerial observations of GPS‐collared animals using UAVs and open‐source electronics

Abstract

AbstractTelemetry has enabled ecologists to link animal movement trajectories and environmental features at a fine spatiotemporal resolution; however, the effects of social interactions on individual choice within large mobile groups remain largely unknown. Estimating the effect of social interaction in the wild remains challenging because existing long‐term tracking tools such as GPS collars focus on the movements of a single individual and cannot observe the behavior of other individuals within the group. The progression of socially informed movement models requires measuring simultaneous trajectories of many individuals at once, as well as the instantaneous social cues to which individuals may be responding. The availability of low‐flying unmanned aerial vehicles (UAVs) and low‐cost open‐source electronics presents a promising opportunity to collect fine‐scale data on social interactions in order to advance our understanding of collective behavior. Here, we present a tracking system that enables the repeated localization and observation of a collared individual and its near neighbors using nadir video footage collected from a commercial UAV. We make use of open‐source electronics combined with the UAV's in‐built functionality that allows it to follow a stream of GPS locations to create an automated system that can follow a specific individual without user control. We demonstrate the tracking systems' performance by studying the group movements of a herd of Exmoor ponies (Equus ferus caballus), and as a proof of concept, we examine the position of the focal individual (collared animal) in relation to the center of the video frame. We also collect information about the focal individual's nearest neighbors. The automated animal observation tool is effective at consistently keeping the focal individual close to the center of the video frame, offering a new dimension to existing remote telemetry tools. For instance, the repeated observation of the same individual in different physiological states, seasons, and demographic groups potentially opens new avenues in collective movement ecology research. By making our design, software, and firmware freely available, we aim to encourage continuous improvements to collective behavior research and to facilitate replicable approaches across other species and ecosystems.