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    姜立春, 潘莹, 李耀翔. 兴安落叶松枝条特征联立方程组模型及树冠形状模拟[J]. 北京林业大学学报, 2016, 38(6): 1-7. DOI: 10.13332/j.1000-1522.20150339
    引用本文: 姜立春, 潘莹, 李耀翔. 兴安落叶松枝条特征联立方程组模型及树冠形状模拟[J]. 北京林业大学学报, 2016, 38(6): 1-7. DOI: 10.13332/j.1000-1522.20150339
    JIANG Li-chun, PAN Ying, LI Yao-xiang. Model systems of branch characteristics and crown profile simulation for Larix gmelinii[J]. Journal of Beijing Forestry University, 2016, 38(6): 1-7. DOI: 10.13332/j.1000-1522.20150339
    Citation: JIANG Li-chun, PAN Ying, LI Yao-xiang. Model systems of branch characteristics and crown profile simulation for Larix gmelinii[J]. Journal of Beijing Forestry University, 2016, 38(6): 1-7. DOI: 10.13332/j.1000-1522.20150339

    兴安落叶松枝条特征联立方程组模型及树冠形状模拟

    Model systems of branch characteristics and crown profile simulation for Larix gmelinii

    • 摘要: 以大兴安岭松岭林业局36株天然兴安落叶松2306个枝条数据为研究对象,采用误差变量联立方程组方法,构建兴安落叶松枝条基径、枝长和角度联立方程组模型系统,同时对比了4种参数估计方法。结果表明, 似乎不相关回归过程SUR(Seemingly Unrelated Regression)法能够解释模型间误差相关性和降低参数估计值的标准误。该系统拟合和检验精度都表现较好,本文所建立的枝条特征联立方程组模型系统能较好地描述兴安落叶松枝条特征和冠形的变化规律。此外,利用非线性混合模型技术构建了含有林分密度变量的枝条基径、枝长和角度联立方程组模型系统。基于参数估计值的显著性以及精度的提高都表明林分密度对枝条基径、长度、角度和树冠形状变化有显著影响。

       

      Abstract: The objectives of this study were to develop the equation systems of branch diameter, branch length and branch angle for natural Dahurian larch (Larix gmelinii) using the error-in-variable simultaneous equation approach, and to compare four parameter estimation approaches. The data were collected from 2306 branch samples of 36 trees in Songling Forest Bureau in Daxing'anling.The results showed that the Seemingly Unrelated Regression (SUR) approach could explain the correlation of error terms across the equations and decrease standard error of parameter estimation. Equation systems of branch characteristics established in our study show better precision and can better describe variation of branch characteristics and crown profile. In addition, our study also developed equation systems of branch diameter, branch length and branch angle with stand density variables using nonlinear mixed-effects modeling techniques. Stand density has a significant impact on branch diameter, branch length, branch angle and crown profile based on significant parameter estimates and better precision.

       

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