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Scientia Silvae Sinicae ›› 2013, Vol. 49 ›› Issue (6): 74-82.doi: 10.11707/j.1001-7488.20130611

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Modeling and Predicting Bivariate Distributions of Tree Diameter and Height

Jin Xingji1, Li Fengri1, Jia Weiwei1, Zhang Lianjun2   

  1. 1. School of Forestry, Northeast Forestry University Harbin 150040;
    2. College of Environmental Science and Forestry, State University of New York (SUNY-ESF) Syracuse, NY13210,USA
  • Received:2012-08-06 Revised:2012-10-23 Online:2013-06-25 Published:2013-07-16

Abstract:

The horizontal and vertical structures of the spruce-fir stands in the northeast, USA were modeled by the bivariate generalized beta distribution (GBD-2) and Johnson's SBB distribution. The goodness-of-fit tests indicated that GBD-2 performed better than did Johnson's SBB in fitting both marginal and joint distributions of tree diameter and height, and in predicting tree height and volume. Regression models were developed for predicting the parameters of the GBD-2 distributions using ordinary stand variables as predictors, such as stand density, basal area, mean tree diameter, mean tree height, and mean crown length and width. Thus, the future stand horizontal and vertical structures can be predicted when the future values of these stand variables were available. The bivariate distribution models developed in this study will provide useful information on the realistic relationships and dynamics of tree diameter and height.

Key words: bivariate generalized beta distribution(GBD-2), Johnson's SBB, goodness-of-fit, stand horizontal and vertical structures, regression model

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