鲁中山区主要针叶树种树干削度方程研究——以侧柏、赤松、黑松为例

Study on the Tree Trunk Taper Equation of Principal Coiferous Species in Montainous Areas of Middle Shandong Province——Taking Platycladus orientalis,Pinus densiflora and Pinus thunbergii as examples

树干削度方程是描述干形的重要指标,其准确性能够直接决定树干材积的估算结果。本研究以鲁中山区三个主要针叶树种侧柏、赤松和黑松人工林为研究对象,对比常见的树干削度方程,筛选各树种的最优基础方程,并采用连续自回归误差结构(CAR)、设定误差权重值等方法解决同一树干测量数据间自相关性和异方差问题,构建树干削度预估方程。采用决定系数(R^(2))、均方根误差(RMSE)等统计指标评价模型的拟合和检验效果。结果表明,与传统最小二乘方法对比,利用CAR方法能够显著提高模型预测精度,其R^(2)分别为0.9487、0.9476、0.9168,而利用传统方法的R^(2)分别为0.9311、0.9363、0.8911。构建的树干削度方程能够服务于立木材积表和出材率表编制,对精确估计鲁中山区林分蓄积量、生物量和碳储量具有重要意义。

The tree taper equation is an important factor to describe the trunk shape,and its accuracy can directly determine the accuracy of the tree volume estimation.This study was focused on three main coniferous tree species,Platycladus orientalis,Pinus densiflora and Pinus nigra plantations in the middle mountain area of Shandong Province.By comparing the typical taper equations,the optimal basic equation of each tree species was selected,and the auto-correlation and heteroscedasticity between the measured data of the same tree were solved by using the continuous autoregressive error structure(CAR)and setting the error weight value.The taper prediction equations of three tree species were constructed.The fitting and testing effects of the model were evaluated by statistical indicators such as determination coefficient(R^(2))and root mean square error(RMSE).The results showed that compared with the traditional least squares method,the prediction accuracy of the model can be significantly improved by using the CAR method,with the R^(2) of 0.9487,0.9456 and 0.9168 respectively,while the R^(2) of the traditional method is 0.9311,0.9363 and 0.8911 respectively.The constructed taper equation can serve for the compilation of standing timber volume table and timber yield table,and is of great significance for the accurate estimation of forest stock volume,biomass and carbon storage in the middle mountain area of Shandong Province.