ContextThe development of reliable and cost-efficient survey techniques is key to the monitoring of all wildlife. One group of species that presents particular challenges for monitoring is the arboreal mammals. Traditional techniques for detecting these species often yield low detection probabilities (detectability) and are time-consuming, suggesting the potential for novel methods to enhance our understanding of their distribution, abundance and population trajectories. One technique that has been shown to increase detectability in a range of terrestrial species is thermal imaging, although it has rarely been applied to arboreal species. The true conservation status of Lumholtz’s tree-kangaroo (Dendrolagus lumholtzi) is uncertain because of low detectability under typical survey techniques, and a more suitable method is required to enable effective monitoring of the species, making it an ideal candidate for the present study. AimsWe aimed to compare the success and cost-effectiveness of surveys utilising thermal imaging with two traditional methods, namely, spotlighting and daytime surveys, so as to optimise monitoring of D. lumholtzi. MethodsWe conducted surveys at 10 sites in Queensland (Australia) where D. lumholtzi was known to occur, by using each method, and modelled both the detectability of D. lumholtzi and the cost-effectiveness of each technique. Key resultsDetectability of D. lumholtzi was significantly higher with the use of thermal imaging than it was with the other survey methods, and thermal detection is more cost-effective. In average survey conditions with a trained observer, the single-visit estimated detectability of D. lumholtzi was 0.28 [0.04, 0.79] in a transect through rainforest, by using thermal imaging. Using only spotlights, the detection probability was 0.03 [0, 0.28] under the same conditions. ConclusionsThese results show that incorporating thermal technology into monitoring surveys will greatly increase detection probability for D. lumholtzi, a cryptic arboreal mammal. ImplicationsOur study highlighted the potential utility of thermal detection in monitoring difficult-to-detect species in complex habitats, including species that exist mainly in dense forest canopy.

Fire has shaped ecological communities worldwide for millennia, but impacts of fire on individual species are often poorly understood. We performed a meta‐analysis to predict which traits, habitat, or study variables and fire characteristics affect how mammal species respond to fire. We modeled effect sizes of measures of population abundance or occupancy as a function of various combinations of these traits and variables with phylogenetic least squares regression. Nine of 115 modeled species (7.83%) returned statistically significant effect sizes, suggesting most mammals are resilient to fire. The top‐ranked model predicted a negative impact of fire on species with lower reproductive rates, regardless of fire type (estimate = –0.68), a positive impact of burrowing in prescribed fires (estimate = 1.46) but not wildfires, and a positive impact of average fire return interval for wildfires (estimate = 0.93) but not prescribed fires. If a species’ International Union for Conservation of Nature Red List assessment includes fire as a known or possible threat, the species was predicted to respond negatively to wildfire relative to prescribed fire (estimate = –2.84). These findings provide evidence of experts’ abilities to predict whether fire is a threat to a mammal species and the ability of managers to meet the needs of fire‐threatened species through prescribed fire. Where empirical data are lacking, our methods provide a basis for predicting mammal responses to fire and thus can guide conservation actions or interventions in species or communities.