Using dead-reckoning to track movements and map burrows of fossorial species

Abstract Background Researching the movement patterns of fossorial animals and mapping of burrow systems presents a significant challenge due to the difficulty of direct observation and the limitations of most tracking systems to collect location fixes underground. A potential solution is using archival tags combined with dead-reckoning, a technique employed in nautical navigation to track animal movement underwater and through dense vegetation. However, this method has not yet been applied to the mapping of complex burrow systems in fossorial species. This study aims to test this approach using accelerometers and magnetometers attached to collars on black-tailed prairie dogs ( Cynomys ludovicianus ) The goal was to determine if 2D dead-reckoning, based on vectors derived from speed and heading data, could accurately track prairie dog movements and, by extension, map the structure of their burrows. To evaluate this method, we deployed 12 tags on wild animals and recorded acceleration and magnetometer data at 40 Hz and 16 Hz, respectively. These animals were allowed to move through artificial burrows comprised of plastic tubes of defined shape, before being released into the wild and tracked. The “tube runs” were used to validate 2D dead reckoning trajectory estimation. We compared the accuracy of five techniques for deriving speed: vectorial dynamic body acceleration (VeDBA), vectorial static body acceleration (VeSBA), step count, and constant speed. Results Acceleration signals reliably indicated traveling behavior. Among the methods tested, the Vectorial sum of Dynamic Body Acceleration (VeDBA) proved to be the most accurate proxy for speed, with the smallest mean error (Fig. 5). Speed coefficients for VeDBA varied between runs (0.009 to 0.042) with this variation being the result of individual differences The animals moved at speeds ranging from 0.01 to 1.42 m/s. In addition, the 2D dead-reckoning process documented all turns (100%) in our plastic tunnel system and had a mean error of 15.38 cm over all test tunnel lengths of up to 4 m. This highlighted the potential for representing animal movements and the layout of burrows in free-roaming prairie dogs. We also determined that use of acceleration metrics identified 22 of 24 times (92%) when collared animals exited their burrows but only 4 or 6 times (67%) when they entered them. Conclusions This work highlights the importance of dead-reckoning in studying space use by fossorial animals, essential for understanding how they interact with their environment, including vegetation and topography. Beyond environmental context, analyzing the specifics of animal movement—such as path tortuosity, speed, step lengths, and turn angles—is crucial for insights into species diffusion, foraging strategies, and vigilance.