A Mixed Integer Linear Programming Approach for Spatially Optimizing Wildlife and Timber in Managed Forest Ecosystems
Abstract:This paper presents mixed integer linear programming formulations for land allocation that optimize spatial layout for a single time period and that have the property that the number of integer variables is a linear function of the level of spatial resolution. The formulations focus on timber, edge-dependent wildlife, and area-dependent wildlife. They account for the amount of edge, the fragmentation of habitat area, and a habitat area threshold for minimum viable population size. Habitat area connectivity is modeled as a probabilistic condition. A case example demonstrates the approaches and includes landscape characteristics such as terrain, hiking trails, campgrounds, and rivers, which result in different productivities over the landscape and obstacles to wildlife habitat area connectivity. For. Sci. 39(4):816-834.
Document Type: Journal Article
Affiliations: Principal Range Scientist, Rocky Mountain Forest and Range Experiment Station, USDA Forest Service, Fort Collins, CO
Publication date: November 1, 1993
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- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
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