Jane Elith and Michael Kearney, University of Melbourne, Australia and Steven Phillips, AT&T, USA talk with Graziella Iossa about their work: 'The art of modelling range-shifting species'. Jane explains that this is a method to predict species distributions, whose range are shifting, like invasive species or species responding to climate change. Mike Kearney then specifies why they used cane toads as a case study for their work. By taking characteristics of the animal and putting this information together they could ask from a physiological point of view, where cane toads could not live. They also asked how to bring together this mechanistic approach with more traditional approaches. This work advances methodology by combining information from physiological models to data in the correlation-based ones; by looking at details of how you can do the modelling; and by looking at tools for understanding models and data, something that a lot of people will find interesting. Then Steven explains about MaxEnt, a programme that models species distributions based on a machine-learning approach, developed with other colleagues and freely available on the web. For example a common use of the programme is predicting how climate change will affect species distributions. Finally, Mike reports that this method should be useful to anybody trying to predict species with unequal distributions. Jane also precises that students, managers, researchers could be potentially interested, especially given that MaxEnt is freely available.
Read the article: http://onlinelibrary.wiley.com/doi/10.1111/j.2041-210X.2010.00036.x/full
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