Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis

Abstract

ABSTRACT The aims of the present study were to test the hypothesis that data stratification by cluster analysis and the use of other variables, in addition to DBH, can improve the precision of the estimates in diametric increment modeling for Mixed Ombrophilous Forest species. The study was carried out in the Irati National Forest. Data from 25 permanent sample plots of 1 ha each were used with all individuals presenting DBH equal to or greater than 10 cm being identified and measured. The increment modeling was performed for the whole forest (non-stratified data), ecological groups and species subgroups (stratified data) defined by cluster analysis. DBH presented a low correlation with the diametric increment and the use of other independent variables had a positive effect on the fitting, reducing the standard error of estimate and increasing the coefficient of determination. The data stratification did not make the models suitable to estimate the diametric increment; however, it provided improvements by reducing the standard error of estimate, suggesting that this technique can be better applied in the search for improvements to diametric modeling in natural forests.

Keywords

• data stratification
• growth
• Mixed Ombrophilous Forest
• multivariate analysis