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Jonathan Rhodes

Conservation Planning for the Koala (Phascolarctos cinereus): a Population Modelling Approach

Jonathan Rhodes was PhD Student at the Ecology Centre, University of Queensland, Brisbane, and spends some months at the Marie Curie Training site of our department. Jonathan is currently a postdoctoral fellow at CSIRO Marine and Atmospheric Research in Hobart, Australia, working on monitoring and managing marine ecosystems.

PhD project
Jonathans developed, tested and applied in his  PhD project  spatially explicit population models to koala (Phascolarctos cinereus) populations. Koala populations in eastern Australia are being threatened by continued habitat loss, degradation and fragmentation. Other threats include, growing urbanisation (causing increased dog predation and road deaths), fire, disease and drought. In order to develop appropriate management strategies to conserve koalas we need to understand and quantify these processes, especially with respect to changes in land use through time. The development of the spatially explicit population models allowed a better understanding of the processes of koala population responses to changes in landscape structure and other aspects of their conservation biology. Further, the project enabled us to develop objective methods for choosing between management options for koala conservation. Models were largely be developed using landscape and population data from the Port Stephens area, New South Wales. However, they were also be tested, validated and applied at other study sites in eastern Australia.

Project in Leipzig

An important part of Jonathan’s project was development of a statistical species distribution model that predicts habitat suitability for Koalas (Rhodes et al. 2006). Species distribution models are commonly used to inform landscape and conservation planning. However, in urban and semiurban landscapes the distributions of species are often determined by a combination of natural habitat and anthropogenic impacts. Understanding the spatial influence of these two processes is crucial for making spatially explicit decisions about conservation actions. We used logistic regression model for the distribution of koalas in a semiurban landscape in eastern Australia that explicitly separates the effect of natural habitat quality and anthropogenic impacts on koala distributions. Our approach is novel because it can be applied to landscapes where anthropogenic variables are never close to zero. Our model showed that, averaged across the study area, natural habitat was the main determinant of koala presence. However, at a local scale, anthropogenic impacts could be more important, with consequent implications for conservation planning. We demonstrate that, by using this modeling approach and presenting predictions visually as a map, provides important information for making decisions on how different conservation actions should be spatially allocated. This approach is particularly useful for areas where wildlife and human populations exist in close proximity.