@article{HE2026, 
author = {Xingyi HE and Enlin LIU and Yong LYU and Xiongqing ZHANG and Guangyu ZHU},
title = {A diameter at breast height growth model for dominant Chinese fir trees incorporating site and climatic effects},
year = {2026},
journal = {Journal of Central South University of Forestry & Technology},
volume = {46},
number = {6},
pages = {91-102},
keywords = {Chinese fir plantations, nonlinear mixed-effects, site type groups, climate type groups, DBH growth model of dominant trees},
url = {https://www.sciopen.com/article/10.14067/j.cnki.1673-923x.2026.06.009},
doi = {10.14067/j.cnki.1673-923x.2026.06.009},
abstract = {【Objective】To accurately predict the growth dynamics of Chinese fir and construct a dominant tree diameter at breast height (DBH) growth model that integrates site and climatic conditions, and to provide guidance for sustainable management and carbon sequestration assessment of Chinese fir plantations.【Method】Utilizing 1 121 DBH-age datasets from 129 Chinese fir plantation plots, topographic, edaphic and climatic factors were incorporated. Significant environmental drivers affecting DBH growth were identified through Quantification Theory I. The optimal theoretical growth equation was selected from six candidate models. Site types and climate types were clustered into site type groups and climate type groups using the k-means algorithm. Nonlinear mixed-effects regression models were developed by incorporating site type, climate type, and their clustered groups as random effects, either individually or in combination.【Result】Seven leading factors influencing DBH growth of dominant trees, including altitude, aspect, Climatic moisture deficit and extreme minimum temperature, were screened. Among the six basic models, the Korf model had the best fitting effect, with a determination coefficient R2 of 0.782 0, 75 site types and 173 climate types clustered into 5 site type groups and 7 climate type groups, respectively, and the random effect model R2 with site factor groups and climate factor groups only was 0.822 9 and 0.839 1, respectively, and the random effect model with site and climate factors was R2= 0.854 3 which was significantly better than the other models.【Conclusion】The nonlinear mixed-effects model developed in this study, which integrates site- and climate-effects, comprehensively incorporates environmental factors influencing the DBH growth of dominant Chinese fir trees. This model not only provides scientific guidance for predicting the DBH growth of dominant Chinese fir trees, but also establishes a generalizable modeling framework for analyzing and forecasting environmental impacts on the growth of subtropical Chinese fir plantations.}
}