Quantifying individual tree growth of economically high-value timber species is important for the simulation and development of forest management options. Long-term permanent plot data provides crucial information of forest stand dynamics that can be used to predict individual tree growth. In this study, we developed individual tree basal area growth models of three high-value timber species: monarch birch (Betula maximowicziana), castor aralia (Kalopanax septemlobus), and Japanese oak (Quercus crispula) in a cool temperate mixed forest in northern Japan using long-term measurement data (1968–2016) collected in permanent plots. Data included species, diameter at breast height, and survival status, and stand management history. We applied linear mixed-effects modelling to predict the individual tree basal area growth as a function of individual tree size, competition, and forest management. Model prediction followed by leave-one-out cross validation revealed a correlation between predicted and observed basal area increments with r values of 0.62, 0.73, and 0.70 and root mean square errors values of 10.44, 7.91, and 11.62 cm²/year for monarch birch, castor aralia, and Japanese oak, respectively. The individual tree growth models developed in this study will provide valuable information for species-specific forest management of economically high-value timber species.

量化具有经济价值的木材树种的单株生长对于模拟和开发森林管理方案非常重要。长期永久性地块数据提供了林分动态的重要信息，可用于预测单个树木的生长。在这项研究中，我们开发了三种高价值木材物种的个体树根面积生长模型：帝王桦木（Betula maximowicziana），蓖麻阿拉里（Kalopanax septemlobus）和日本栎木（Quercus crispula））在日本北部一个凉爽的温带混交林中，使用在永久性地块中收集的长期测量数据（1968-2016年）。数据包括种类，胸高直径，生存状况以及林分管理史。我们应用了线性混合效应模型来预测个体树的基础面积的增长与个体树的大小，竞争和森林经营的关系。模型预测以及留一法交叉验证揭示了预测的和观察到的基础面积增量之间的相关性，r值为0.62、0.73和0.70，均方根误差值为10.44、7.91和11.62 cm ²/年分别为帝王桦木，蓖麻和日本橡木。本研究中开发的单个树木生长模型将为经济上有价值的木材物种的特定物种森林管理提供有价值的信息。