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Predicting Regeneration in the Grand Fir-Cedar-Hemlock Ecosystem of the Northern Rocky Mountains

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Conifer establishment following regeneration treatments can be predicted in the grand fir-cedar-hemlock ecosystem of the northern Rocky Mountains. Alternative treatments can be evaluated by a model that represents regeneration establishment and early development. This model is designed to be used with the Intermountain Forest and Range Experiment Station's Prognosis Model (Stage 1973). Mathematical equations representing most harvest and site preparation methods common in the northern Rocky Mountains predict the probability of stocking, trees per acre, species composition, and tree heights between 3 to 20 years following treatment. These relations were derived from a stratified random sample of areas managed by conventional harvest and site preparation treatments. However, the analysis and modeling methods are structured to permit combinations of treatments within a stand that might differ from past practices.

Keywords: Succession; conifer establishment; modeling; reproduction; stand simulation

Document Type: Journal Article

Affiliations: Silviculturist, Intermountain Forest and Range Experiment Station, Forest Service, U.S. Department of Agriculture, Moscow, ID 83843

Publication date: March 1, 1986

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

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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