Showing papers by "Simon Ferrier published in 2002"
TL;DR: Three strategies for making more effective use of available biological data and knowledge to alleviate regional conservation planning problems are proposed, more closely integrating biological and environmental data through predictive modeling, with increased emphasis on modeling collective properties of biodiversity rather than individual entities.
Abstract: Vast gaps in available information on the spatial distribution of biodiversity pose a major challenge for regional conservation planning in many parts of the world. This problem is often ad- dressed bybasing suchplanning on variousbiodiversity surrogates. In some situations, distributional datafor selectedtaxamaybeusedassurrogatesforbiodiversityasawhole.However, thisapproach is less effective in data-poor regions, where there may be little choice but to base conservation planning on someform ofremoteenvironmentalmapping,derived, forexample,frominterpretationof satellite imagery or from numerical classiecation of abiotic environmental layers. Although this alternative approach confers obvious beneets in terms of cost-effectiveness and rapidity of application, problems may arise if congruence is poor between mapped land-classes and actual biological distributions. I propose three strategies for making more effective use of available biological data and knowledge to alleviatesuchproblemsby(1)morecloselyintegratingbiologicalandenvironmentaldatathroughpre- dictive modeling, with increased emphasis on modeling collective properties of biodiversity rather than individual entities; (2) making more rigorous use of remotely mapped surrogates in conser- vation planning by incorporating knowledge of heterogeneity within land-classes, and of varying levels of distinctiveness between classes, into measures of conservation priority and achievement; and (3) using relatively data-rich regions as test-beds for evaluating the performance of surrogates that can be readily applied across data-poor regions. (Biodiversity; regional conservation planning; surrogates.)
677 citations
TL;DR: An overview of approaches to community-level modelling employed in a series of major land-use planning processes in the northeast New South Wales region of Australia is provided, and how well communities and assemblages derived using these techniques function as surrogates in regional conservation planning is evaluated.
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.
529 citations
Journal Article•
21 citations