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A Generalized Methodology for Estimating Forest Ingrowth at Multiple Threshold Diameters

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Abstract:

Ingrowth is defined as the number or volume of trees that periodically grow into the smallest measured size class of a forest stand. We present a model to predict the number of ingrowth trees at a variable threshold diameter for 6 forest vegetation types common to the central United States. The model is based on observations on 2,373 remeasured inventory plots from 8 sources in Missouri, Illinois, Indiana, and Ohio. The number of ingrowth trees decreases significantly with increasing threshold diameter. The concept of crown competition factor was used to set a biologically realistic upper limit on the number of ingrowth trees for any given threshold diameter. Number of ingrowth trees · acre-1 · decade-1 was predicted as a function of the maximum possible number of ingrowth trees and the threshold diameter. Fitted models were highly significant for all forest types, and the general shape of the response surface was biologically realistic. Precision of the estimates was low because ingrowth is a highly variable process. For. Sci. 39(4):776-798.

Keywords: Growth; central hardwoods; simulation; yield

Document Type: Journal Article

Affiliations: Associate Professor, Department of Forest Resources, Green Hall, University of Minnesota, St. Paul, MN 55108

Publication date: 1993-11-01

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.

    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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