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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Linking linear programming and spatial simulation models to predict landscape effects of forest management

Eric J Gustafson1, L Jay Roberts, Larry A Leefers

  • 1USDA Forest Service, North Central Research Station, Rhinelander, WI 54501, USA. egustafson@fs.fed.us

Journal of Environmental Management
|March 22, 2006
PubMed
Summary

Forest management models reveal trade-offs between timber harvesting and wildlife habitat. Alternative plans increased forest interior and edge habitats, but spatial differences were modest.

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Area of Science:

  • Forestry Science
  • Wildlife Ecology
  • Spatial Analysis

Background:

  • Forest management requires tools to balance timber production and wildlife habitat.
  • Assessing spatial impacts of management strategies is crucial for effective planning.

Purpose of the Study:

  • To evaluate spatial patterns of alternative forest management strategies.
  • To quantify and compare the effects of different plans on habitat characteristics.

Main Methods:

  • Linked linear programming (Spectrum) for timber harvest optimization with a simulation model (HARVEST) for spatial projection.
  • Used spatially explicit projections to calculate habitat patterns.

Main Results:

  • Forest interior habitat increased as timber harvesting decreased; edge habitat increased with timber harvesting.
  • Mature forest age classes increased, while young classes decreased across all alternatives.
  • Average patch size generally decreased, indicating a shift in spatial configuration.

Conclusions:

  • Complementary modeling approach effectively quantifies spatial effects of forest management alternatives.
  • Results show modest spatial differences among alternatives, despite meeting design goals.
  • The study provides valuable insights for balancing competing forest benefits.