Tracking small animals in complex landscapes: a comparison of localisation workflows for automated radio telemetry systems

Automated radio telemetry systems (ARTS) have the potential to
revolutionise our understanding of animal movement by providing a
near-continuous record of individual locations in the wild. However,
localisation error in ARTS data can be very high, especially in natural
landscapes with complex vegetation structure and topography. This curtails
the research questions that may be addressed with this technology. We set
up an ARTS grid in a valley with heterogeneous vegetation cover in the
Colombian high Andes and applied an analytical pipeline to test the
effectiveness of localisation methods. We performed calibration trials to
simulate animal movement in high- or low-flight, or walking on the ground,
and compared workflows with varying decisions related to signal cleaning,
selection, smoothing, and interpretation, along with four multilateration
approaches. We also quantified the influence of spatial features on the
system’s accuracy. Results showed large variation in localisation error,
ranging between 0.4–43.4 m and 474–1929 m, depending on the localisation
method used. We found that the selection of higher radio signal strengths
and data smoothing based on the temporal autocorrelation are useful tools
to improve accuracy. Moreover, terrain ruggedness, height of movement,
vegetation type, and the location of animals inside or outside the grid
area influence localisation error. In the case of our study system,
thousands of location points were successfully estimated for two
high-altitude hummingbird species that previously lacked movement data.
Our case study on hummingbirds suggests ARTS grids can be used to estimate
small animals’ home ranges, associations with vegetation types, and
seasonality in occurrence. We present a comparative localisation pipeline,
highlighting the variety of possible decisions while processing radio
signal data. Overall, this study provides guidance to improve the
resolution of location estimates, broadening the application of this
tracking technology in the study of the spatial ecology of wild
populations.