A new predictor of the irreplaceability of areas for achieving a conservation goal, its application to real-world planning, and a research agenda for further refinement

A new predictor of the irreplaceability of areas for achieving a conservation goal, its... A new statistical approach is described for predicting the irreplaceability of areas (or ‘sites') within a region, defined as the likelihood that a given site will need to be protected to ensure achievement of a set of regional conservation targets. The paper begins by clarifying the relationship between irreplaceability and other conservation planning concepts such as flexibility, rarity, endemism and complementarity. We explain why direct measurement of irreplaceability is currently intractable for most real-world applications, and hence the need for prediction. A new predictive approach is proposed which overcomes a number of major shortcomings of previous approaches to predicting irreplaceability. The new approach employs the central limit theorem to estimate the expected frequency distribution of the area of a feature protected by all possible combinations of a set of sites. This expected distribution is used to estimate the total number of site combinations that would achieve target for the feature. The distribution is then used, for each site in turn, to estimate the number of these combinations for which the site of interest is a critical component. This latter number, expressed as a proportion of the estimated total number of representative combinations, provides a measure of the irreplaceability of a site for a single feature. Two techniques are presented for extending this approach to measure irreplaceability in terms of multiple features. Recent application of the new predictor to regional conservation planning in eastern New South Wales and elsewhere is described, with examples. We then present results of a preliminary evaluation of the accuracy of the predictor. Finally, we outline a future research agenda for further validation and refinement of the new technique. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biological Conservation Elsevier

A new predictor of the irreplaceability of areas for achieving a conservation goal, its application to real-world planning, and a research agenda for further refinement

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Publisher
Elsevier
Copyright
Copyright © 2000 Elsevier Science Ltd
ISSN
0006-3207
DOI
10.1016/S0006-3207(99)00149-4
Publisher site
See Article on Publisher Site

Abstract

A new statistical approach is described for predicting the irreplaceability of areas (or ‘sites') within a region, defined as the likelihood that a given site will need to be protected to ensure achievement of a set of regional conservation targets. The paper begins by clarifying the relationship between irreplaceability and other conservation planning concepts such as flexibility, rarity, endemism and complementarity. We explain why direct measurement of irreplaceability is currently intractable for most real-world applications, and hence the need for prediction. A new predictive approach is proposed which overcomes a number of major shortcomings of previous approaches to predicting irreplaceability. The new approach employs the central limit theorem to estimate the expected frequency distribution of the area of a feature protected by all possible combinations of a set of sites. This expected distribution is used to estimate the total number of site combinations that would achieve target for the feature. The distribution is then used, for each site in turn, to estimate the number of these combinations for which the site of interest is a critical component. This latter number, expressed as a proportion of the estimated total number of representative combinations, provides a measure of the irreplaceability of a site for a single feature. Two techniques are presented for extending this approach to measure irreplaceability in terms of multiple features. Recent application of the new predictor to regional conservation planning in eastern New South Wales and elsewhere is described, with examples. We then present results of a preliminary evaluation of the accuracy of the predictor. Finally, we outline a future research agenda for further validation and refinement of the new technique.

Journal

Biological ConservationElsevier

Published: May 1, 2000

References

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