This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Haight, R. G. Articles by Snyder, S. A. Search for Related Content

An Integer Optimization Approach to a Probabilistic Reserve Site Selection Problem

U.S.D.A. Forest Service, North Central Research Station, 1992 Folwell Avenue, St. Paul, Minnesota 55108
Johns Hopkins University, Department of Geography and Environmental Engineering, 313 Ames Hall, Baltimore, Maryland 21218
Minnesota Department of Transportation, 108 Cecil Street SE, Minneapolis, MN 55919
rhaight{at}fs.fed.us
revelle{at}jhu.edu
snyder01{at}yahoo.com

Interest in protecting natural areas is increasing as development pressures and conflicting land uses threaten and fragment ecosystems. A variety of quantitative approaches have been developed to help managers select sites for biodiversity protection. The problem is often formulated to select the set of reserve sites that maximizes the number of species or ecological communities that are represented, subject to an upper bound on the number or area of selected sites. Most formulations assume that information about the presence or absence of species in the candidate sites is known with certainty. Because complete information typically is lacking, we developed a reserve selection formulation that incorporates probabilistic presence-absence data. The formulation was a discrete 0/1 optimization model that maximized the number of represented vegetation communities subject to a budget constraint, where a community was considered represented if its probability of occurrence in the set of selected sites exceeded a specified minimum reliability threshold. Although the formulation was nonlinear, a log transformation allowed us to represent the problem in a linear format that could be solved using exact optimization methods. The formulation was tested using a moderately sized reserve selection problem based on data from the Superior National Forest in Minnesota.

Subject classifications: Environment: protected natural reserves on national forests; Programming, integer: discrete 0/1 by exact solution methods; Probability, applications: presence-absence data of species in reserves.
History: Received June 1998; revision received February 1999; revision received June 1999; accepted June 1999.

This article has been cited by other articles:

				H. Onal and R. A. Briers Optimal Selection of a Connected Reserve Network Operations Research, March 1, 2006; 54(2): 379 - 388. [Abstract] [PDF]

				J. D. Camm, S. K. Norman, S. Polasky, and A. R. Solow Nature Reserve Site Selection to Maximize Expected Species Covered Operations Research, November 1, 2002; 50(6): 946 - 955. [Abstract] [PDF]