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

Abstract 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, offer only small‐scale, site‐specific estimates or were less user‐friendly though already integrating antenna geometry, signal strength and spatiotemporal uncertainty, limiting their ability either to reconstruct full flight paths or to be easily applied by practitioners. 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.

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Publication Details

Journal
Methods in Ecology and Evolution
Published
2026-03-03
DOI
https://doi.org/10.1111/2041-210x.70273
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
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article

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

Methods in Ecology and Evolution
UAV Applications and Optimization
article

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

article en

Abstract

Abstract 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, offer only small‐scale, site‐specific estimates or were less user‐friendly though already integrating antenna geometry, signal strength and spatiotemporal uncertainty, limiting their ability either to reconstruct full flight paths or to be easily applied by practitioners. 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.

Methods in Ecology and Evolution
Carl von Ossietzky Universität Oldenburg (DE), Institute of Avian Research (DE)
Openalex Percentile: Top 31%
UAV Applications and Optimization
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