A NONPARAMETRIC ANALYSIS OF PLOT BASAL AREA GROWTH USING TREE-BASED MODELS - INTRODUCTION

Tree based statistical models can be used to investigate data structur e and predict future observations. We used nonparametric and nonlinear models to reexamine the data sets on tree growth used by Bechtold et al. (1991) and Ruark et al. (1991). The growth data were collected by Forest Inventory and Analysis (FIA) teams from 1962 to 1972 (4th cycle ) and 1972 to 1982 (5th cycle). We used tree based models to group obs ervations into clusters that were specified by covariate values. Next, we performed a permutation test on the grouped data to test for a cha nge in tree growth rates from the 4th cycle to the 5th cycle. Our tech niques differed from those used by Bechtold et al. (1991) and Ruark et al. (1991). The data was not assumed to follow any parametric distrib ution, the relation between response and covariates was not assumed to be linear, and the test for a change in tree growth did not require a ny parametric assumptions. The methodology presented here is general a nd applicable to other situations where the significance of a specific covariate is in question. Despite these relaxed constraints of analys is, our results generally agreed with those of Bechtold et al. and Rua rk et al.