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[红松人工林树干内节子体积预测模型]

[Prediction models of knot volume inside the stem for Korean pine plantation].

作者信息

Jia Wei-Wei, Hong Yan-Hu, Li Feng-Ri

机构信息

School of Forestry, Northeast Forestry University/Key Laboratory of Sustainable Forest Ecosystem Management of the Ministry of Education, Harbin 150040, China.

出版信息

Ying Yong Sheng Tai Xue Bao. 2020 Sep 15;31(9):2943-2954. doi: 10.13287/j.1001-9332.202009.004.

Abstract

Based on 1207 knots from 49 sample trees of 29 standard plots of Korean pine plantations in Linkou and Dongjingcheng Forest Bureau of Heilongjiang Province, China, we extracted longitudinal sections of knots using the image processing software Digimizer and represented the shape of knots using two-dimensional scatter plots. According to the two-dimensional scatter plots, knots of Korean pine plantation were divided into three types: 1) alive knots (whole knot contained only sound knot portion); 2) non-occluded dead knots (whole knot contained both sound and loose knot portions); 3) occluded dead knots (the sound and loose portion of the knot were partially occluded by the bark). For all the three types of knots, the volume of sound knot was calculated by mathematical integral of the sound knot shape equation. The volume of loose knot was calculated using the volume equation of a cylinder. The total volume of knots was calculated as the sum of sound and loose knot volume. Finally, based on knot variables (diameter, relative height and total length of knots) and tree variable (diameter at breast height), we established the prediction models for sound knot volume, loose knot volume, and total volume of knot using the linear mixed model at plot level and tree level. Compared with fixed-effects model, the mixed effects models of the volume of sound knot, loose knot, and total knots provided more accurate parameter estimation, more uniform residual distribution, and higher model fitting precision. The validation results showed that prediction precision of each fixed-effect model was higher than 90%, while that of the mixed models with plot and tree effect was above 93%, indicating that the established model could well predict the volume of knot for Korean pine plantation.

摘要

基于中国黑龙江省林口和东京城林业局29个标准样地中49棵样木的1207个节子,我们使用图像处理软件Digimizer提取节子的纵向截面,并使用二维散点图表示节子的形状。根据二维散点图,将人工林红松节子分为三种类型:1)活节(整个节子仅包含健全节子部分);2)非闭合死节(整个节子包含健全节子和松散节子部分);3)闭合死节(节子的健全部分和松散部分被树皮部分遮挡)。对于所有三种类型的节子,健全节子的体积通过健全节子形状方程的数学积分计算得出。松散节子的体积使用圆柱体体积公式计算。节子总体积为健全节子体积与松散节子体积之和。最后,基于节子变量(节子直径、相对高度和总长度)和树木变量(胸径),我们在样地水平和树木水平上使用线性混合模型建立了健全节子体积、松散节子体积和节子总体积的预测模型。与固定效应模型相比,健全节子、松散节子和节子总体积的混合效应模型提供了更准确的参数估计、更均匀的残差分布和更高的模型拟合精度。验证结果表明,每个固定效应模型的预测精度均高于90%,而具有样地和树木效应的混合模型的预测精度高于93%,表明所建立的模型能够很好地预测人工林红松节子的体积。

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