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与年龄无关的马尾松优势高生长模型研究

Age-independent Dominant Height Growth Model for Pinus massoniana Plantation

  • 摘要:
    目的 通过构建与年龄无关的理论生长方程,用于预测在年龄未知或不是有效影响因子时的马尾松人工林优势高。
    方法 基于常用的Hossfeld IV、Lundqvist-Kolf、Richards、Schumacher等4个理论生长方程,推导其不含年龄因子的差分形式,构建与地位指数相关的可变参数、与年龄无关的马尾松优势高模型。
    结果 在4种基础理论生长模型中,以Richards模型建立的与年龄有关的马尾松人工林优势高生长模型效果最优。与年龄无关模型的拟合精度均高于与年龄有关模型的拟合精度,Richards模型和Korf模型差分形式建立的与年龄无关的马尾松人工林优势高生长模型效果最优。在引入地位指数时,Hossfeld模型的拟合精度提高效果最明显,且以设定k为可变参数时,建立与年龄无关的马尾松人工林优势高生长模型效果最优。
    结论 在异龄林或年龄难以获得时,与年龄无关的理论生长模型能够预测优势高的生长,将地位指数与可变参数建立函数关系代入模型拟合后,模型精度提高,可以更好地应用于预测林分生长。

     

    Abstract:
    Objective An age-independent theoretical growth equation was constructed to predict the dominant height of Pinus massoniana plantation when the age was unknown or not an effective influence factor.
    MethodsBased on the four theoretical growth equations of Hossfeld IV, Lundqvist-Kolf, Richards and Schumacher, an age-independent dominant height model of Pinus massoniana was constructed by using the difference form of hidden age factors, and the free parameters were expressed as a function of site index.
    ResultsAmong the four basic theoretical growth models, the age-related dominant growth model of Pinus massoniana plantation established by Richards model performed the best. The fitting accuracy of age-independent models was higher than that of age-related models, and the age-independent dominant growth model of Pinus massoniana plantation established by Richards model and Korf model performed the best. When the site index was introduced to the model, the fitting accuracy of Hossfeld model improved most obviously, and when k was set as a variable parameter, the age-independent dominant high growth model was the best.
    Conclusion When the forest of different age or age is difficult to obtain, the theoretical growth model independent of age can predict the growth of dominant height. After the functional relationship between site index and free parameters is replaced in the model, the accuracy of the model is improved and the model can be better applied to predict stand growth.

     

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