A linkage among whole-stand model, individual-tree model and diameter-distribution model.
A linkage among whole-stand model, individual-tree model and diameter-distribution model.
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DOI：
10.17221/102/2009-jfs
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发表时间：
2018-02
影响因子：
1.1
通讯作者：
X. Zhang;Y. Lei
中科院分区：
文献类型：
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作者：
X. Zhang;Y. Lei
林分生长和收获模型包括全林分模型、单木模型和直径分布模型。本研究通过预测组合和参数恢复方法将三个模型依次联系起来。单木模型通过预测组合将联合收割机与全林分模型结合起来。预测组合方法将不同模型的信息进行组合，分散了不同模型产生的误差，从而提高了预测精度。然后通过参数恢复方法将预测组合模型与直径分布模型相连接。在矩估计过程中，采用了算术平均直径和二次平均直径法（A-Q法）和算术平均直径和直径方差法（A-V法）。结果表明：预测组合对林分变量的预测效果分别优于林分水平模型和乔木水平模型; A-V法对Weibull参数的估计效果上级A-Q法;通过预测组合和参数恢复，3种不同的模型可以很好地联系起来。
Stand growth and yield models include whole-stand models, individual-tree models and diameter-distri - bution models. In this study, the three models were linked by forecast combination and parameter recovery methods one after another. Individual-tree models combine with whole-stand models through forecast combination. Forecast combination method combines information from different models, disperses errors generated from different models, and then improves forecast accuracy. And then the forecast combination model was linked to diameter-distribution models via parameter recovery methods. During the moment estimation, two methods were used, arithmetic mean diameter and quadratic mean diameter method (A-Q method), and arithmetic mean diameter and diameter variance method (A-V method). Results showed that the forecast combination for predicting stand variables outperformed over the stand-level and tree-level models respectively; A-V method was superior to A-Q method on estimating Weibull parameters; these three different models could be linked very well via forecast combination and parameter recovery.