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林业资源管理 ›› 2017›› Issue (4): 22-29.doi: 10.13466/j.cnki.lyzygl.2017.04.005

• 科学研究 • 上一篇    下一篇

湖南栎类天然混交林优势木树高曲线哑变量模型研究

朱光玉(), 罗小浪   

  1. 中南林业科技大学,长沙 410004
  • 收稿日期:2017-05-18 修回日期:2017-07-19 出版日期:2017-08-28 发布日期:2020-09-24
  • 作者简介:朱光玉(1978-),男,湖南邵阳人,副教授,博士,主要研究方向:森林可持续经营。Email:zgy1111999@163.com
  • 基金资助:
    国家自然科学基金(31570631);国家自然科学基金(31100476);国家林业局项目(1692016-06);湖南省教育厅项目(17C1664)

Dominant Height-Diameter Models for Mixed Quercus Forest Based on Dummy Variable

ZHU Guangyu(), LUO Xiaolang   

  1. Central South University of Forestry and Technology,Changsha 410004,China
  • Received:2017-05-18 Revised:2017-07-19 Online:2017-08-28 Published:2020-09-24

摘要:

使用13种具有代表性的树高-胸径模型对湖南栎类天然混交林优势木树高-胸径关系进行了拟合,从中筛选出拟合度较高的模型作为基础模型,以进一步构建含林分类型、立地类型哑变量的天然混交林优势木树高曲线模型。研究结果表明:平均优势木模型要优于最高优势木模型,利用哑变量模型拟合的效果要明显优于基础模型;林分类型哑变量和立地类型哑变量平均优势木模型结构相同,都是$ H=1.3+\sum_{i=1}^{n} a_{i} \times Z_{i} \times D_{g} /(D_{g}+1)+b \times D_{g}$,其确定系数分别为0.711 9和0.977 5,立地类型哑变量模型要优于林分类型哑变量模型。利用哑变量模型可提高模型精度及适用性,有助于建立区域性通用生物数学模型,并为全国栎类天然混交林立地质量评价的研究提供科学支撑和参考依据。

关键词: 栎类混交林, 优势木, 树高曲线模型, 哑变量

Abstract:

13 representative height-diameter models were used to simulate correlation of dominant height-diameter in natural Quercus mixed forests.Models with high goodness-of-fit were selected as the foundational model for building dominant height-diameter model with stand types and site types dummy variable.Results showed that mean dominant height models fitted better than maximum dominant height model,the dummy-variable-included models had higher goodness of fit than the foundational models.Stand type and site type dummy variable with mean dominant height had the same formula: $ H=1.3+\sum_{i=1}^{n} a_{i} \times Z_{i} \times D_{g} /(D_{g}+1)+b \times D_{g}$ and the site type dummy variable model (R2=0.9775) fitted better than forest type dummy variable model (R2=0.711 9).It was able to improve the applicability and accuracy of dominant height-diameter models for mixed Quercus forest based on dummy variable,which provided support and reference for establishing regional generalized bio-math models and amending site quality assessment of mixed Quercus forests in area coverage.

Key words: mixed Quercus forest, dominant tree, height-diameter models, dummy variable

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