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Spatial Autocorrelation of Individual Tree Characteristics in Loblolly Pine Stands

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Mathematical methods of assessing the levels of spatial autocorrelation in forest stands were identified. These methods were used to investigate spatial autocorrelation associated with tree characteristics such as product, defect, species class, and basal area. With the exception of the species classification, significant levels of spatial autocorrelation were not associated with any discrete variable. For individual tree basal area, the levels of spatial autocorrelation tended to be positive for low levels of competition, negative at intermediate levels of competition, and positive again at high levels of competition. Using measures of spatial autocorrelation, characteristics were assigned to individual trees in computer generated stands. These methods, applicable for discrete or continuous characteristics, assign the characteristics to individual trees depending on the spatial location of the individual tree and characteristics of its neighbors. Forest Sci. 31:575-587.
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Keywords: Pinus taeda; competition; simulation; spatial distribution

Document Type: Journal Article

Affiliations: Thomas M. Brooks Professor of Forest Biometrics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061

Publication date: 1985-09-01

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.

    2016 Impact Factor: 1.782 (Rank 17/64 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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