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Modeling Species’ Distributions to Improve Conservation in Semiurban Landscapes: Koala Case Study

Rhodes, JR, Wiegand, T, McAlpine, CA, Callaghan, J, Lunney, D, Bowen, M & Possingham, HP 2006, Conservation Biology, vol. 20, no. 2, pp. 449-459.

Logistic regression models can be used to show the distribution of koalas in response to the quality of natural habitat and anthropogenic impacts, and consequently to predict changes in populations in response to these variables over time. Here, this modelling approach in combination with distribution mapping techniques showed that natural habitat availability was the most important factor determining koala presence; however, anthropogenic impacts are an increasing threat to the existence of koalas in some areas, particularly at a local scale. 

  To model koala distributions, this study used koala faecal pellets collected from survey sites around semi-urban areas of Port Stephens. Environmental variables categorised as either natural or anthropogenic were then mapped, including habitat type, fire history, road density, traffic, human population density and domestic dog density. A mixed-effects logistic regression technique was then applied to model the probability of koala presence against each individual explanatory variable. The results show that on average across the study sites, natural habitat availability was the most important factor determining koala presence, closely followed by road density.

  Although anthropogenic impacts such as road density are understood to increase the mortality of koalas and therefore decrease their population numbers in a specific area, it is less understood how the quality of natural habitat affects the demographic rates of koalas. At some study sites, koalas seemed to demonstrate a strong selection for good quality natural habitat; however, some of these sites were also subject to high anthropogenic impacts. These human-induced impacts negatively impacted the koala population, despite the natural habitat being of good quality. When reviewing this spatial data, it is therefore crucial to understand how natural and anthropogenic explanatory variables interact at different spatial scales to affect koala distribution, as human-induced impacts may become more important at the local-scale.

  Understanding natural and anthropogenic impacts on koala presence is necessary for planning effective conservation management actions. The authors suggest that protecting or reconstructing natural habitat and reducing anthropogenic effects around habitats will benefit koala populations. It should be noted that these management strategies must be applied at the appropriate spatial scales, which can be determined using the modelling approach developed in this study.

 

Summarised by Robyn Boldy

 

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