Current issue: 54(2)
Diameter at breast height (DBH) and height (H) of trees are two important variables used in forest management plans. However, collecting the measurements of H is time-consuming and costly. Instead, the H-DBH relationship is modeled and used to estimate H. But, ignoring the effects of slope, aspect and tree competition on the H-DBH relationship often impedes the improvement of H predictions. In this study, to improve predictions of Cyclobalanopsis glauca (Thunb.) Oerst. tree H in mixed forests, we compared eleven H-DBH models and examined the influence of slope and aspect on the H-DBH relationship using 426 trees. We then improved Hegyi competition index and explored its effect on the H predictions by including it in the selected models. Results showed 1) There were statistically significant effects of slope and aspect on the H-DBH relationship; 2) The log transformation and exponential model performed best for sunny- and shady-steep, respectively, and the Gompertz’s model was optimal for both sunny- and shady-gentle; 3) Compared with the whole dataset, the division of the data into the slope and aspect sub-datasets significantly reduced the RMSE of H predictions; 4) Compared with the selected models without competition index, adding the original Hegyi and improved Hegyi_I into the models improved the H predictions but only the models containing the improved Hegyi_I significantly increased the prediction accuracy at the significant level of 0.1. This study implied that modeling the H-DBH relationship under different slopes and aspects and including the improved Hegyi_I provided the great potential to improve the H predictions.