2008 年 7 巻 p. 39-59
Even in the same even-aged forest stand, trees grow differently due to their own growth capacity, relative spatial conditions, and other environmental factors. In this paper, we use a Gaussian mixture model (GMM) to investigate growth patterns in an even-aged forest to identify groups of trees with the same growth characteristics. Given the Richards growth function for the growth process, the estimated coefficients are used as new response variables in a multivariate GMM to identify growth patterns. The optimal number of grouped growth patterns is searched by minimizing the cross-validation (CV) criterion. We demonstrate our proposed method using growth data from a sugi (Cryptomeria japonica) sample plot in Hoshino Village, Fukuoka Prefecture, Japan. The model identified three separate growth patterns in our sample plot.
