Individual tree basal area increment models for broadleaved forests in Bhutan

The correct and accurate assessments of growing stock (stem volume) in combination with forest growth predictions from models are essential for sustainable forest management. Currently, no such information exists for the broadleaved forests of Bhutan. This study evaluates the important factors of individual tree growth for broadleaved species in Dagana, Bhutan. Data were collected from 96 inventory plots covering forest stand information, tree and stand parameters along with 5-year tree growth increment information from tree cores. Due to the large number of tree species (87), four species groups were created using principal component and cluster analysis to simplify the calibration of individual tree basal area increment (BAI) models. The main determinants of tree growth were shown to be tree size variables and competition within a forest stand. Distance dependent competition indices showed higher correlation to growth than distance independent competition indices. The resulting increment models provided consistent and unbiased estimates of individual tree BAI predictions. Increasing competition levels reduce the productivity of the individual trees. This emphasises the need for crown release to obtain higher individual tree growth. We demonstrate that the BAI models developed in this study can be used to predict tree growth by species group according to different stand density conditions and, if they are verified on a wider scale, could form the basis of sustainable forest management in Bhutan.