Species distribution modelling of the endangered Mahogany Glider (Petaurus gracilis) reveals key areas for targeted survey and conservation

Abstract

The Mahogany Glider (Petaurus gracilis) is one of the most endangered marsupials in Australia. Its known distribution is an approximately 120 km strip of fragmented coastal woodland in north-east Queensland, from north of Townsville to the Tully area. Records are clustered in a number of well-surveyed areas, with significant areas of lowland habitat unsurveyed. Around 30% of historic records fall in areas that were subsequently cleared for farmland, and ongoing clearing and fragmentation of lowland sclerophyll forest continues within the potential distribution. Resolving the distribution is an urgent requirement to guide conservation but Mahogany Gliders are difficult to detect in the field. Species distribution modelling offers a technique for estimating the fine-scale distribution and for targeting further field survey and conservation efforts. We used known occurrence records (N = 481) to predict the distribution of Mahogany Gliders across the Wet Tropics bioregion. We used climatic, topographic and other environmental predictors to generate distribution models using Maxent and Random Forest algorithms, each with two bias correction methods. The predictions revealed that many unknown populations may exist within the currently defined distribution and in important areas beyond this (e.g. Hinchinbrook Island). There was reasonable congruence between models, and we include syntheses of the models to present the most likely current distribution. The most important predictor variables across the models were precipitation seasonality (high seasonality), elevation (generally <100 m), soil type (hydrosols) and vegetation type (including Eucalyptus and Melaleuca woodlands). Our results identify core habitat and reveal key areas that require targeted field surveys. Importantly, the predicted suitable habitat is highly fragmented and ongoing conservation efforts need to improve habitat connectivity and limit further fragmentation.