Reserve selection as a maximal covering location problem

Reserve selection as a maximal covering location problem Many alternative approaches have been proposed for setting conservation priorities from a database of species (or communities) by site. We present a model based on the premise that reserve selection or site prioritization can be structured as a classic covering problem commonly used in many location problems. Specifically, we utilize a form of the maximal covering location model to identify sets of sites which represent the maximum possible representation of specific species. An example application is given for vertebrate data of Southwestern California, which is then compared to an iterative solution process used in previous studies. It is shown that the maximal covering model can quickly meet or exceed iterative models in terms of the coverage objective and automatically satisfies a complementarity objective. Refinements to the basic model are also proposed to address additional objectives such as irreplaceability and flexibility. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biological Conservation Elsevier

Reserve selection as a maximal covering location problem

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Publisher
Elsevier
Copyright
Copyright © 1996 Elsevier Ltd
ISSN
0006-3207
D.O.I.
10.1016/0006-3207(95)00102-6
Publisher site
See Article on Publisher Site

Abstract

Many alternative approaches have been proposed for setting conservation priorities from a database of species (or communities) by site. We present a model based on the premise that reserve selection or site prioritization can be structured as a classic covering problem commonly used in many location problems. Specifically, we utilize a form of the maximal covering location model to identify sets of sites which represent the maximum possible representation of specific species. An example application is given for vertebrate data of Southwestern California, which is then compared to an iterative solution process used in previous studies. It is shown that the maximal covering model can quickly meet or exceed iterative models in terms of the coverage objective and automatically satisfies a complementarity objective. Refinements to the basic model are also proposed to address additional objectives such as irreplaceability and flexibility.

Journal

Biological ConservationElsevier

Published: Jan 1, 1996

References

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