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    曹梦, 潘萍, 欧阳勋志, 臧颢, 吴自荣, 杨阳, 占常燕. 基于哑变量的闽楠天然次生林单木胸径和树高生长模型研究[J]. 北京林业大学学报, 2019, 41(5): 88-96. DOI: 10.13332/j.1000-1522.20190026
    引用本文: 曹梦, 潘萍, 欧阳勋志, 臧颢, 吴自荣, 杨阳, 占常燕. 基于哑变量的闽楠天然次生林单木胸径和树高生长模型研究[J]. 北京林业大学学报, 2019, 41(5): 88-96. DOI: 10.13332/j.1000-1522.20190026
    Cao Meng, Pan Ping, Ouyang Xunzhi, Zang Hao, Wu Zirong, Yang Yang, Zhan Changyan. Growth model of DBH and tree height for individual tree of natural secondary Phoebe bournei forest based on dummy variable[J]. Journal of Beijing Forestry University, 2019, 41(5): 88-96. DOI: 10.13332/j.1000-1522.20190026
    Citation: Cao Meng, Pan Ping, Ouyang Xunzhi, Zang Hao, Wu Zirong, Yang Yang, Zhan Changyan. Growth model of DBH and tree height for individual tree of natural secondary Phoebe bournei forest based on dummy variable[J]. Journal of Beijing Forestry University, 2019, 41(5): 88-96. DOI: 10.13332/j.1000-1522.20190026

    基于哑变量的闽楠天然次生林单木胸径和树高生长模型研究

    Growth model of DBH and tree height for individual tree of natural secondary Phoebe bournei forest based on dummy variable

    • 摘要:
      目的通过对闽楠天然次生林胸径和树高生长规律及生长模型的研究,为林木生长预估及林分质量提升经营措施的制订提供参考。
      方法以江西省安福县闽楠天然次生林为研究对象,通过标准地调查及树干解析等方法获取基础数据,按林木竞争压力水平从小到大将林木分为类型1、类型2和类型3,分析胸径和树高的生长规律;选取5种具有生物学意义的生长方程,根据模型拟合优度与评价指标选取最优基础生长模型,在最优模型的基础上构建含竞争类型哑变量的生长模型。
      结果(1)利用树干解析数据分析显示,30 ~ 50年为胸径生长速生期,连年生长量最大值达到0.57 cm;35 ~ 45年为树高主要生长速生期,连年生长量最大值为0.37 m。(2)胸径最优基础模型为Gompertz方程,模型R2和预估精度分别为0.756和94.28%,构建的最优哑变量模型的R2和预估精度分别为0.873和95.71%;树高最优基础模型为修正Weibull方程,模型R2和预估精度分别为0.856和96.54%,构建的最优哑变量模型的R2和预估精度分别为0.882和96.96%。(3)由构建的哑变量生长模型拟合的不同竞争类型下的胸径和树高生长曲线得知,胸径和树高总生长量均表现为类型1 > 类型2 > 类型3,类型1胸径最大生长量是类型3的1.6倍。
      结论竞争压力对闽楠胸径、树高生长均产生影响,较大的林木竞争压力不利于闽楠生长;构建含有竞争类型哑变量模型的拟合优度及预估精度均优于基础模型,有利于提高建模的精度和模型的适用性。

       

      Abstract:
      ObjectiveThe growth regularity and growth model of Phoebe bournei natural secondary forest were studied, which will provide the reference basis for its growth prediction and quality improvement management measures.
      MothodTaking natural secondary Phoebe bournei forest in Anfu County of Jiangxi Province, eastern China as research object, the basic data were obtained by means of typical sample investigation and stem analysis. According to the level of competitive pressure, the analysic woods were divided into tree types. From low to high, they were type 1, type 2 and type 3, respectively. Growth regulation of Phoebe bournei was studied in this paper. Five kinds of theoretical growth equations with biological significance were selected, and the optimal basic model was selected according to the model goodness of fit and evaluation indexes. On the basis of the optimal model, the growth model of dummy variables with competition types was constructed.
      Result(1) The stem analysis data showed that 30th−50th year was the main fast growing period of DBH, the maximum current annual growth was 0.57 cm. while that 35th−45th year was the fast growing period of tree height, the maximum current annual growth was 0.37 m. (2) The optimal basic model of DBH was Gompertz equation, the value of R2 was 0.756 and the forecasting accuracy was 94.28%, and the value of R2 and the forecasting accuracy of the optimal dummy variable model were 0.873, 95.71%, respectively. The optimal basic model of tree height was the modified Weibull equation, the value of R2 was 0.856 and the forecasting accuracy was 96.54%, and the value of R2 and the forecasting accuracy of the optimal dummy variable model was 0.882, 96.96%, respectively. (3) According to the growth curves of DBH and tree height under different competition types fitted by the constructed dummy variable growth model, the total increment of DBH and tree height showed that type 1 > type 2 > type 3, and the maximum DBH increment of type 1 was 1.6 times of type 3.
      ConclusionThe competitive pressure has an effect on the growth of DBH and tree height of Phoebe bournei. The goodness of fit and estimation accuracy of dummy variable model with competition type were better than the basic model, which is beneficial to improve the accuracy and applicability of the model.

       

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