Abstract

Context A comprehensive understanding of movements and space use can underpin the effective management of threatened species. GPS dataloggers can collect large amounts of high-quality movement data, and recent advances in statistical approaches allow for robust estimates of home range size to be generated. Until recently, technological and practical constraints have generally restricted the collection of movement data via GPS dataloggers to larger species. However, reductions in the size and weight of GPS dataloggers now allow for this technology to be applied to smaller species. Aims The aim of this study was to describe the home range and movement patterns of a nationally vulnerable, native Australian ground-dwelling mammal, the long-nosed potoroo (Potorous tridactylus), in south-west Victoria, mainland Australia. Methods We attached GPS dataloggers to 40 long-nosed potoroos between 2020 and 2022 and estimated home range size using dynamic Brownian Bridge movement models. We evaluated the influence of physiological factors such as body mass and sex on home range size and described patterns of home range overlap between and within sexes. Key results Mean home range sizes were estimated to be 13.73 ha (95% CI: 10.9–16.6) and 6.67 ha (95% CI: 5.49–7.85) for males and females respectively. Home range size scaled with body mass in males but not females, and ranges were largely overlapping – although there was some evidence of intrasexual spatial partitioning of core range areas in females. Conclusions Ours is the first application of GPS dataloggers to this species, and our home range estimates are over twice as large as other reported estimates for mainland Australia. Long-nosed potoroos may range across larger areas than previously predicted on mainland Australia. Implications This knowledge may be used to optimise the management of long-nosed potoroo populations before and after fire – a key threatening process for this species. Our study highlights the value of integrating GPS dataloggers and robust home range estimators when describing the movement ecology of a population.

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