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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

Context Monitoring spatial and temporal change in relative abundance using statistically powerful designs is a critical aspect of wildlife management. Many indices of relative abundance are available, but information regarding their influence on statistical power is limited. Aims We compared the statistical power associated with occurrence-based and frequency-based indices derived from faecal pellet counts and camera trapping to detect changes in the activity of five mammalian herbivores. Methods We deployed camera traps and counted faecal pellets in native vegetation subjected to four management treatments in south-eastern Australia. We used simulation coupled with generalised linear mixed models to investigate the statistical power associated with a range of effect sizes for each combination of species, survey method and data type. Key results The index derived from camera frequency data provided the greatest statistical power to detect species’ responses and was the only index capable of detecting small effect sizes with high power. The occurrence index from camera trapping did not provide the same level of statistical power. Indices derived from faecal pellet frequency data also detected spatial and temporal changes in activity levels for some species, but large numbers of plots were required to detect medium to large effect sizes. High power to detect medium to large effects could be achieved using occurrence indices derived from pellet presence–absence data, but required larger sample sizes compared to the camera frequency index. Conclusions Both camera trapping and pellet counts can be applied to simultaneously monitor the activity of multiple mammalian herbivore species with differing activity patterns, behaviour, body size and densities, in open and closed habitat. However, using frequency indices derived from camera trapping may improve management outcomes by maximising the statistical power of monitoring programs to detect changes in abundance and habitat

Context: Habitat loss and fragmentation are key drivers of biodiversity loss worldwide, yet the influence of landscape structure on species distributions is unknown. Globally, reptiles are thought to be especially sensitive to landscape modification due to their limited capacity for dispersal and reliance on native vegetation. New knowledge of how landscape structure influences species distributions is needed to inform conservation strategies. Aims: Our principal aim was to examine the influence of landscape structure on the distributions of 40 terrestrial reptile species in Victoria, southeast Australia. Methods: We obtained species occurrence records from the Victorian Biodiversity Atlas, and used MaxEnt to model the distributions of reptile species within Victoria using biophysical and landscape structure variables. A moving window analysis was applied to a land cover map to derive five landscape structure metrics; two metrics represented landscape cover and three represented landscape configuration. Key results: Climate variables were generally found to be the strongest drivers of species distributions, although 80% of reptile species were also influenced by landscape structure (permutation importance ≥5%). Of the five landscape structure variables, extent of native vegetation had the greatest influence (30 of 40 species), followed by habitat shape. For Lerista bougainvillii and Tiliqua rugosa, native vegetation cover had a greater influence on their distributions than climate variables. Most species responded positively to native vegetation extent, whereas responses to other landscape structure variables were varied. Conclusions: Although most studies of reptile distributions only use biophysical variables in modelling, our research shows that at the scale of our study area, reptile species distributions were also influenced by landscape structure; extent of native vegetation was an important predictor for most species. Integrating landscape structure in modell