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Maximum Likelihood Estimation for Predicting the Probability of Obtaining Variable Shortleaf Pine Regeneration Densities

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Abstract:



A logistic equation is the basis for a model that predicts the probability of obtaining regeneration at specified densities. The density of regeneration (trees/ha) for which an estimate of probability is desired can be specified by means of independent variables in the model. When estimating parameters, the dependent variable is set to 1 if the regeneration density (trees/ha) on the plot is greater than the specified density (trees/ha), otherwise 0. Since it is desired to estimate parameters for a range of probability densities, traditional estimation techniques for logistic models cannot be used. Multiple regeneration densities require a multinomial distribution, for which maximum likelihood estimates are obtained. Counts of shortleaf pine regeneration taken 9-10 years after thinning on 182 plots established in naturally occurring shortleaf pine forests are used to estimate parameters. FOR. SCI. 49(4):577–584.

Keywords: Natural regeneration; Pinus echinata; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; logistic regresson; natural resource management; natural resources

Document Type: Miscellaneous

Affiliations: 1: Professor Department of Forestry, Oklahoma State University, Room 008C Ag Hall, Stillwater, OK, 74078, Phone: 405-744-5447; Fax: 405-744-3530 tlynch@okstate.edu 2: (Former) OSU Graduate Research Assistant—Phone: 617-405-3625 nkouka@hotmail.com 3: Natural Resource Economist Boise Corp., P.O. Box 50 Boise, ID, 3728-0001, Phone: 208-384-7212 MikeHuebschmann@bc.com 4: Project Leader/Research Forest Ecologist Southern Research Station, USDA Forest Service, P.O. Box 1270 Hot Springs, AR, 71902, Phone: 501-623-1174 jguldin@fs.fed.us

Publication date: 2003-08-01

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

    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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