Extended statistical approaches to modelling spatial pattern in biodiversity in northeast New South Wales. I. Species-level modelling |
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Authors: | Simon Ferrier Graham Watson Jennie Pearce Michael Drielsma |
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Affiliation: | (1) Wildlife Service, New South Wales National Parks, P.O. Box 402, Armidale, NSW, 2350, Australia;(2) Present address: Department of Land and Water Conservation, University of New England, P.O. Box 245, Armidale, NSW, 2351, Australia;(3) Present address: Canadian Forest Service, 1219 Queens St East, Sault Ste. Marie, Ontario, Canada, P6A 2E5 |
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Abstract: | Statistical modelling of biological survey data in relation to remotely mapped environmental variables is a powerful technique for making more effective use of sparse data in regional conservation planning. Application of such modelling to planning in the northeast New South Wales (NSW) region of Australia represents one of the most extensive and longest running case studies of this approach anywhere in the world. Since the early 1980s, statistical modelling has been used to extrapolate distributions of over 2300 species of plants and animals, and a wide variety of higher-level communities and assemblages. These modelled distributions have played a pivotal role in a series of major land-use planning processes, culminating in extensive additions to the region's protected area system. This paper provides an overview of the analytical methodology used to model distributions of individual species in northeast NSW, including approaches to: (1) developing a basic integrated statistical and geographical information system (GIS) framework to facilitate automated fitting and extrapolation of species models; (2) extending this basic approach to incorporate consideration of spatial autocorrelation, land-cover mapping and expert knowledge; and (3) evaluating the performance of species modelling, both in terms of predictive accuracy and in terms of the effectiveness with which such models function as general surrogates for biodiversity. |
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Keywords: | Biodiversity Northeast New South Wales Regional conservation planning Statistical modelling Surrogates |
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