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Title: Linking linear programming and spatial simulation models to predict landscape effects of forest management alternatives
Author: Gustafson, Eric J.; Roberts, L. Jay; Leefers, Larry A.
Source: Journal of Environmental Management. 81: 339?350.
Description: Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (Spectrum) to optimize timber harvest schedules, then a simulation model (HARVEST) to project those schedules in a spatially explicit way and produce maps from which the spatial pattern of habitat could be calculated. We demonstrated the power of this approach by evaluating alternative plans developed for a national forest plan revision in Wisconsin, USA. The amount of forest interior habitat was inversely related to the amount of timber cut, and increased under the alternatives compared to the current plan. The amount of edge habitat was positively related to the amount of timber cut, and increased under all alternatives. The amount of mature northern hardwood interior and edge habitat increased for all alternatives, but mature pine habitat area varied. Mature age classes of all forest types increased, and young classes decreased under all alternatives. The average size of patches (defined by age class) generally decreased. These results are consistent with the design goals of each of the alternatives, but reveal that the spatial differences among the alternatives are modest. These complementary models are valuable for quantifying and comparing the spatial effects of alternative management strategies.
Keywords: forest management planning, landscape pattern, models, decision support
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Gustafson, Eric J.; Roberts, L. Jay; Leefers, Larry A. 2006. Linking linear programming and spatial simulation models to predict landscape effects of forest management alternatives. Journal of Environmental Management. 81: 339?350.
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