movetrack: An R package to model flight paths from radio-telemetry networks

Georg Rüppel, Thiemo Karwinkel, Vera Brust, Heiko Schmaljohann

Tracking small- to large-scale movements of animals is important for studying their interactions with the environment, including how they adjust and adapt their migration in response to environmental and human-induced changes. Despite the technical progress in tracking devices, a major challenge remains for small animals-such as songbirds, bats, and insects-because GPS transmitters are still too heavy to be carried by these lightweight species. Automated radio-telemetry offers a lightweight, scalable alternative. However, unlike GPS, radio-telemetry does not yield precise location data-only information about receiving antennas and the strength of detected signals. Existing localisation methods either rely solely on receiver locations or offer only small-scale, site-specific estimates, limiting their ability to reconstruct full flight paths. We fill this gap by presenting movetrack, an R package that reconstructs animal trajectories from automated radio-telemetry data-such as that collected by the Motus Wildlife Tracking System-using a hidden Markov model (HMM) framework. Our approach combines coarse geometric position estimates-based on antenna bearing and signal strength-with an HMM that accounts for measurement error, temporal gaps, and movement dynamics. The model distinguishes behavioural states such as migratory flight, local movement, and stopovers by analysing directional persistence and speed of the animal. We validate movetrack using controlled low-altitude aircraft flights, simultaneously recorded with GPS and radiotelemetry, to simulate migratory flights of aerial species. Our results convincingly demonstrate that movetrack produces biologically realistic flight path estimates with quantifiable uncertainty, enhancing localisation in telemetry-based movement research. movetrack provides a straightforward and practical approach, without requiring enhanced mathematical knowledge, to precisely reconstruct flight movements in a high spatiotemporal resolution. The R package enables researchers and conservationists to better study the response of aerial animals to environmental change and, ultimately, to formulate more effective conservation measures, for instance in relation to potential conflicts with anthropogenic stressors, such as artificial light at night, pesticides, and human-made structures.