A method for predicting the spatial distribution of arboreal marsupials

Abstract

A method is described for predicting the spatial distribution of arboreal marsupials. The approach is demonstrated using a statistical habitat association model for the greater glider (Petauroides volans), developed in the mountain ash (Eucalyptus regnans) forests of the central highlands of Victoria. The method is applied to predict the spatial distribution of P. volans in the Ada Forest Block, using forestinventory data on the values of the two significant variables in the statistical model (the age of a stand of forest and the abundance of large trees with hollows in a 3-ha area). The application of the model enabled values for the estimated probability of occurrence of P, volans (with a 95% confidence interval) to be generated for each of approximately 2200 3-ha pixels in the Ada Forest Block. A kernel smoothing procedure was then applied to allow for the spatial dependence implicit in these data. The standard measures of statistical uncertainty employed in our analysis revealed substantial variation in the predicted probability of occurrence of P. volans, even though the terms in the statistical relationship were highly significant. However, whilst the model is unable to reliably predict the occurrence of P. volans at any given 3-ha site, tests of the performance of the model showed that it performed well when the results of field surveys were aggregated over many sites. The results of our analysis emphasise the importance of including measures of uncertainty in spatial predictions generated from statistical models.