Abstract
Sound methods to determine species occurrence and abundance are crucial for successful wildlife management and conservation. When species communities cannot be readily detected using camera traps or acoustic monitoring, ground survey methods such as spotlighting on foot are commonly used. While able to provide precise detection and density estimates, these methods can be laborious and time consuming and are restricted to surveying small areas. Advances in drone technology now allow for the detection of heat signatures of endothermal wildlife using thermal cameras from the sky, which we contrast to traditional ground surveys. We found that drone and ground surveys achieve similar detection probabilities for nocturnal arboreal mammals of southeastern Australia. Drones achieved high detection rates for targeted arboreal wildlife occurrence and consistently recorded more species and individuals than ground-based surveys via spotlighting. Ground surveys often missed specialist species like the endangered southern greater glider (Petauroides volans) when populations had low densities. Drone-derived density estimates for surveyed areas of 100-200 ha were significantly lower than those extrapolated from 10-ha ground survey results. Thermal drone surveys present a promising tool for measuring and monitoring nocturnal arboreal wildlife populations due to their ability to cover larger areas with comparable detection rates to ground surveys. Drone surveys provide comprehensive information on species assemblage, density, and distribution across management compartment-scale survey areas, offering valuable insights into species occurrence and population status. Drones were particularly effective in areas with dense vegetation or that were otherwise inaccessible for ground-based surveys, enhancing the ability to estimate populations, quantify recovery following large-scale disturbances, and to discover previously undocumented populations. Drone-based wildlife survey methods have the potential to reduce uncertainty in compartment-scale population estimates for improved wildlife monitoring and conservation.