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Prediction of Understory Tree Height Growth in Northern Hardwood Stands

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Abstract:

Stand table projection methodology was used to describe the growth of under-story reproduction trees by height class and species in uneven-aged northern hardwood stands in Wisconsin. The movement of stems to larger height classes was based on potential height growth modified by a competition index. Potential height growth was based on site index curves. The most sensitive reproduction competition index developed was a simple unt of overstory competitors weighted by relative tree heights and distance. Inclusion of measures of understory density did not improve growth predictions. Results further indicate that the height growth of a representative tree, with a height equal to the height-class midpoint, can adequately represent the growth of individuals in that class located elsewhere on the understory quadrat. The simplicity of the reproduction competition index and the evident need for only five understory height classes should also allow efficient growth simulation while retaining sensitivity to the overstory tree spatial pattern. FOREST SCI. 23:391-400.

Keywords: Competition index; regression; reproduction model; simulation model; stand table projection

Document Type: Journal Article

Affiliations: Associate Professor, College of Forestry, University of Minnesota, St. Paul.

Publication date: September 1, 1977

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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