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.