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林业科学 ›› 2017, Vol. 53 ›› Issue (3): 84-93.doi: 10.11707/j.1001-7488.20170310

• 论文与研究报告 • 上一篇    下一篇

基于混合效应的人工落叶松树冠轮廓模型

高慧淋, 董利虎, 李凤日   

  1. 东北林业大学林学院 哈尔滨 150040
  • 收稿日期:2016-03-21 修回日期:2016-04-19 出版日期:2017-03-25 发布日期:2017-04-25
  • 通讯作者: 李凤日
  • 基金资助:
    国家自然科学基金项目(31570626);中央高校基本科研业务费专项资金资助(2572015AA23)。

Crown Shape Model for Larix olgensis Plantation Based on Mixed Effect

Gao Huilin, Dong Lihu, Li Fengri   

  1. School of Forestry, Northeast Forestry University Harbin 150040
  • Received:2016-03-21 Revised:2016-04-19 Online:2017-03-25 Published:2017-04-25

摘要: [目的] 以林木易测因子为预测变量,构建黑龙江省人工落叶松树冠最大外部轮廓及内部轮廓(未着叶部分)的预估模型,为进一步估计人工落叶松树冠表面积、树冠体积和树冠生物量提供依据。[方法] 基于佳木斯市孟家岗林场49株解析木的枝解析数据,树冠外部轮廓模型采用分段回归技术,构建带有约束条件并满足生物学意义的连续性分段曲线模型,即在梢头处树冠半径为"0",在整个树冠内外部轮廓的拐点的存在是唯一的,且在拐点处树冠半径达到最大值;内部轮廓直接采用线性模型进行模拟。分析模型参数与林木变量之间的相关性,将关系密切的树木变量或变量组合引入到模型中并选出最优模型,以此作为基础模型分别建立单水平的外部轮廓及内部轮廓的混合效应模型,利用混合模型的固定效应部分对外部轮廓及内部轮廓进行模拟。[结果] 以林木因子胸径、高径比、冠长及冠长率构建的分段抛物线模型能准确预估树冠的外部轮廓形状,利用胸径、高径比及冠长能有效预测树冠的内部轮廓形状。基于模型的拟合优度及检验指标,采用单水平(样地)混合模型能够显著提高模型的预测精度,外部轮廓混合效应预估模型的决定系数(R2)、均方误差根(RMSE)和平均偏差(Bias)分别为0.914 2、0.232 7 m和0.001 2 m,内部轮廓混合效应预估模型的R2、RMSE和Bias分别为0.723 5、0.147 0 m和-0.000 034 m。与基础模型相比,混合模型的R2都有所提高,RMSE、Bias都有所降低。在其他变量保持不变的条件下,外部轮廓半径分别随着胸径、冠长率的增大而增大,随着高径比、冠长的增大而减小;内部轮廓半径均随着胸径、高径比及冠长的增大而增大。[结论] 具有生物学意义的分段抛物线模型和线性模型分别能够有效描述人工落叶松树冠外部轮廓及内部轮廓的形状变化特征,加入混合效应后能够提高模型的拟合精度并改善组内的方差异性特征,基于混合效应模型中的固定效应部分,能够合理地对树冠外部轮廓及内部轮廓进行模拟,分段抛物线模型能够灵活地反映拐点在树冠内的移动规律线,简单的线性模型能够对内部轮廓进行准确预估。

关键词: 人工长白落叶松, 外部轮廓, 内部轮廓, 非线性混合模型

Abstract: [Objective] The maximum outer and inner (defoliation part) crown shape predicted models for Larix olgensis plantation were developed based on the easily measurable individual tree variables to provide suitable approach to estimate crown surface area, crown volume and crown biomass for L. olgensis plantation.[Method] Using branch analysis data of 49 trees from Mengjiagang forest farm in Heilongjiang Province, the models of maximum outer crown and inner shape were developed. Outer crown shape predicted model constructed the continuous segmented equation with constraints and biological reasoning by employing the segmented regression technology. The outer crown radius equaled "0" at the tree tip and the inflection point where crown radius got maximum value was unique. Different from outer model, the straight line was used to model the inner crown shape. The relationships between the estimated parameters and tree variables were analyzed and the most intimate variable or variables combination were included in the models. The best models were selected as the basic model to develop the one level mixed effect model for the outer and inner crown shape. Based on the fixed effect of models, the outer and inner crown shapes were simulated.[Result] Diameter at breast height (DBH), tree height to diameter ratio (HD), crown length (CL) combined with crown ratio (CR) would predict the outer crown shape with the high accuracy. While the inner crown shape was modeled as DBH, HD and CL. The predicted accuracy was significantly increased by using 1 level (plot) mixed effect models compared with the basic models based on the goodness-of-fit and validation criteria. The coefficients of determination (R2), RMSE and average bias (Bias) of outer crown shape predicted model were 0.914 2,0.232 7 m,0.001 2 m respectively and 0.723 5,0.147 0 m,-0.000 034 m for the inner crown shape predicted model,respectively. Compared to the basic model, R2 increased,while RMSE and Bias decreased for the mixed effect model. The segmented polynomial can reflect the variation regularity of the inflection point within the entire crown. The radii of the outer crown shape increased with the increase of DBH and CL, and decreased with HD and CL while other variables kept constant. The radii of inner crown shape increased with DBH, HD and CL.[Conclusion] The segmented polynomial equation with biological reasoning and linear model could effectively reflect the outer and inner crown shape. The models which possessed the random effect have improved the prediction accuracy and heteroscedasticity features of the models. Based on the fixed effect, the model could give reasonable simulation to the outer and inner crown shape. The segmented polynomial equation was flexible to describe the movement regularity of inflection points within the entire crown. Singular linear model performed well in modeling inner crown shape.

Key words: larch (Larix olgensis) plantation, outer crown shape, inner crown shape, nonlinear mixed effect model

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