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    基于混合效应模型的人工红松枝下高模型研建

    Construction of the height to crown base mixed model for Korean pine

    • 摘要:
        目的  基于帽儿山红松人工林63块样地2 972株红松数据,利用非线性混合模型构建红松枝下高模型,为进一步研究生长与收获模型提供理论依据。
        方法  本文首先使用8个常用的枝下高模型,选出最优基础模型;其次,研究林分变量或单木变量对枝下高的影响,建立含林分变量的枝下高模型;最终在基础模型和含林分变量模型的基础上,考虑样地效应对红松枝下高的影响,构建红松枝下高基础混合效应模型和广义混合效应模型。模型用4种抽样方式(随机抽取、抽取最大树、抽取最小树、抽取平均树)和8种样本大小(1 ~ 8株树)对基础混合效应模型和广义混合效应模型进行抽样检验。
        结果  Logistic模型拟合精度好,符合生物学意义,且模型形式简单,选为最优基础模型。除树高、胸径以外,大于对象木断面积之和、优势木高和冠幅与枝下高有显著相关性,加入后明显提升模型的拟合精度。枝下高广义混合效应模型的拟合效果要优于其他模型。模型检验结果表明:当应用基础混合效应模型预测时,建议抽取胸径最小的4个样本;当应用广义混合效应模型预测时,建议随机抽取4个样本。
        结论  枝下高广义混合效应模型在拟合效果和预测精度方面优于其他3种模型,建议将此模型作为人工红松枝下高模型。当应用广义混合效应模型预测时,建议随机抽取4个样本。

       

      Abstract:
        Objective  Based on the data of 2 972 Korean pine trees in 63 sample plots of Korean pine plantation in Maor Mountain of northeastern China, a nonlinear mixed model was used to construct the height to crown base model of Korean pine, which provided a theoretical basis for further research on growth and yield model.
        Method  Firstly, the optimal basic model was selected from eight commonly used models of height to crown base. Secondly, the influence of stand variables or individual tree variables on height to crown base was studied, and a generalized model was established. Finally, on the basis of the basic model and the generalized model, considering the effects of sample plot on the height to crown base of Korean pine, the basic mixed effect model and generalized mixed effect model of height to crown base for Korean pine were constructed. Four alternatives of height to crown base (HCB) sampling designs (the randomly selected trees and selecting the maximum, medium-size and minimum trees) and eight sample sizes (1−8 trees) were studied for sampling correction of basic mixed effect model and generalized mixed effect model respectively.
        Result  Logistic model had good fitting accuracy and biological significance, and its form was simple, so it was chosen as the the optimal basic model. In addition to tree height (H) and DBH, there was a significant correlation between the basal area sum larger than subject tree (BAL), dominant height (HD), crown width (CW) and HCB, and the fitting accuracy of the model was improved obviously. The fitting effect of height to crown base generalized mixed effect model was better than that of other models. The model validation showed that when the basic mixed effect model was used to predict, it was recommended to select four samples with the smallest DBH, and when the generalized mixed effect model was used to predict, it was recommended to randomly select four samples.
        Conclusion  The generalized mixed effect model is superior to the other three models in fitting effect and prediction accuracy. It is recommended that this model can be used as the height to crown base model for Korean pine. When applying generalized mixed effect model prediction, it is recommended that four samples can be randomly selected.

       

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