Optimum Selection of Clustered Conservation Areas Within Military Installations

Abstract

Suitable habitat areas for many rare, threatened, or endangered species in the United States are found inside the boundaries of military installations. Because these same lands are also needed for conventional and emerging training requirements, there is growing need to manage military landscapes in a balanced way that can satisfy competing goals. This study introduces linear integer programming formulations that can be used as a decision-support tool for relocating multiple populations of a species at risk to clustered conservation areas inside a military installation. The authors present a basic clustered relocation model and extend it to minimize the distances of relocation and to produce meta-clustering of separate conservation areas. Two meta-clustering methods are introduced, the first using a constraint and the second using a multi-objective function. The models are applied to a dataset related to the Gopher Tortoise (GT), a keystone species determined to be at risk at Fort Benning, GA. Analysis of the results is presented. The results illustrate that, using integer programming, it is possible to optimally design habitat areas that incorporate spatial and ecological consideration for species relocation where competing land uses must be supported.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2011
Accession Number
ADA553526

Entities

People

  • Harold E. Balbach
  • Hayri Önal
  • James D. Westervelt
  • Sahan T. Dissanayake

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Birds
  • Clustering
  • Computer Programming
  • Data Sets
  • Department Of Defense
  • Endangered Species
  • Engineering
  • Geometric Forms
  • Integer Programming
  • Mathematical Models
  • Military Training
  • Models
  • Relocation
  • Site Selection
  • Training
  • United States

Fields of Study

  • Environmental science

Readers

  • Aquatic Ecology
  • Distributed Systems and Data Platform Development
  • Operations Research