基于枝条木材密度分级的鼎湖山南亚热带常绿阔叶林树高曲线模型

如何便捷准确地测量树高一直是林学及群落生态学所关心的问题。由于木材密度与树木生长密切相关, 因此基于木材密度建立树高曲线模型能够为测量树高提供新的方法。本文以鼎湖山南亚热带常绿阔叶林1.44 ha塔吊样地内119个物种的4,032个个体为研究对象, 利用树高、胸径和木材密度数据来探究基于枝条木材密度分级的树高曲线模型。首先, 对个体进行随机抽样, 将其划分为建模样本(占总样本量的70%)和检验样本(占总样本量的30%), 并通过聚类分析将所有个体的木材密度划分为4级。其次, 基于建模样本利用常见的5种理论生长方程(Richards、Korf、Logistic、Gompertz和Weibull方程)对不同分级建立树高-胸径模型; 基于检验样本检验模型精度, 并确定各分级的最适模型。最后, 构建基于物种分类的树高曲线模型, 并比较其与木材密度分级模型的差异。结果表明: 基于木材密度分级的模型, 各分级小组检验样本的平均绝对误差(MAE)和均方根误差(RMSE)最小值所对应的模型类型与建模样本结果一致, 确定Gompertz模型和Weibull模型为鼎湖山南亚热带常绿阔叶林最适树高模型类型。比较基于木材密度分级的模型与基于物种分类的模型, 发现二者的MAE、RMSE指数差异小。综上, 基于木材密度分级的树高曲线模型对树高估测精度高, 使用方便, 为树高预测提供了新方法, 可以更好服务森林调查等生产实践。

Height-diameter models based on branch wood density classification for the south subtropical evergreen broad-leaved forest of Dinghushan

Aims: Knowing how to measure tree height conveniently and accurately has always been a concern for the fields of forestry and community ecology. Since wood density is closely related with tree growth, building a tree height curve model based on wood density could provide a new method for measuring tree height. This method would provide data support for vegetation investigation of forest dynamics plots and exploration of spatial differences in the radial and vertical distribution of community species resources.