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Spatial Optimization of Wildlife Populations with Probabilistic Habitat Connections

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I consider a land area divided into cells and the problem that consists of determining the cells that must be harvested and the cells that must be left in old-growth to maximize the size of wildlife populations that depend on amounts of young- and old-growth forest. In each old-growth cell, the size of the old-growth-dependent population depends on the spatial arrangement of the old-growth cells, specifically of the probability that the cell is connected to at least one other old-growth cell. This problem suggested by Hof and Bevers can be easily formulated by a difficult nonlinear 0-1 program. These authors proposed a linear approximation of a special case of the pairwise connection probabilities. The aim of this article was to show that the problem can be solved simply and efficiently with any set of connection probabilities by using standard 0-1 linear programming software. The key feature to transform the nonlinear program into a linear program is an approximation of the logarithmic function curve by some of its tangents. Computational results on hypothetical grid forests with up to 900 cells are presented to illustrate potentialities of the approach. Near-optimal solutions guaranteed to be within 0.5% of the optimal solution are obtained in less than 10 minutes of computing time.

Keywords: habitat connectivity; integer linear programming; land allocation modeling; probabilistic optimization; species richness

Document Type: Research Article

Publication date: 2011-08-01

More about this publication?
  • 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

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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