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中国农学通报

中国农学通报 ›› 2011, Vol. 27 ›› Issue (25): 37-44.

• 林学 园艺 园林 • 上一篇    下一篇

利用哑变量研究湘西桤木林分优势平均高与平均高的相关关系

王忠诚 朱光玉 文仕知 何功秀 张江 孙华   

  • 收稿日期:2011-03-31 修回日期:2011-04-25 出版日期:2011-10-05 发布日期:2011-10-05
  • 基金资助:

    国家野外科学观测研究站项目;国家林业局重点项目;湖南省科技攻关计划项目;湖南省自然基金资助项目

The Study on the Correlation of Average Dominant Height and Mean Height of Alnus cremastogyne Stands in Xiangxi by Applying Dummy Variable

  • Received:2011-03-31 Revised:2011-04-25 Online:2011-10-05 Published:2011-10-05

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摘要：

林分优势平均高和林分平均高是立地质量评价的2个重要指标。以78块湘西桤木人工林标准地数据为研究对象，采用数量化方法I分析了地名、林分类型、坡度、坡位、坡向、土壤厚度、土壤类型、自然灾害、公顷株数、海拔、年龄和郁闭度11种因子对高比值（林分平均高与优势平均高之比）的显著性影响程度，选出影响显著的主导因子作为哑变量，确定地名和林分类型（绝对纯林和相对纯林）为显著性影响的主导因子，2个因子对高比值具有显著性影响的可靠性为93.70%和99.96%，选取这2个因子作为哑变量，建立了基于哑变量的林分优势平均高与林分平均高非线性模型和常规的非线性模型，采用确定系数、残差均值、绝对残差均值、相对误差均值和精度5个指标，通过对常规、基于地名哑变量和基于林分类型哑变量的3种非线性模型的建模精度和模型适应性检验结果比较，指出基于哑变量的非线性模型优于常规非线性模型，且基于地名哑变量的模型最优。基于地名哑变量、基于林分类型哑变量和常规非线性模型的建模精度分别为98.65%、97.53%、93.43%，建模确定系数分别为0.9389、0.9266和0.9015，建模残差均值分别为2.16E-09、5.53E-09和2.30E-07，建模绝对残差均值1.0631、1.1323和1.8522，建模相对误差均值分别为0.1197、0.2038和0.2932。研究方法和结果有助于提高建模精度，并为建立区域性通用生物数学模型提供了一种思维方法。

关键词: 酶活性, 酶活性

Abstract:

Stand average dominant height and mean height are important indicators for site index evaluation. Based on 78 plot data of Alnus cremastogyne plantation in Xiangxi, using quantification theory type I, 11 kinds of factors were analyzed whether they had significant effect on height ratio (stand mean height/stand average dominant height), they were place name, stand type, gradient, slope situation, slope orientation, soil thickness, natural disaster, tree number/hm2, elevation, age and crown density. If the factor had most significant effect on height ratio, it would be selected as a dummy variable. The place name and stand type, including absolute pure stand and relative pure stand were selected as dummy variables, because they had most significant effect on height ratio. The dependability of that place name and stand type had most significant effect on height ratio were 93.70% and 99.96%. Based on these dummy variables, these non-linear correlation models of stand average dominant height and mean height had been established, and the general non-linear model had also been established. The establishing model and test precisions had also been analyzed and compared with 5 indicators, they were determination coefficient, residuals mean, absolute residuals mean, relative residuals mean and precision. The precisions of non-linear model based on dummy variable with place name, non-linear model based on dummy variable with stand type and general non-linear model were 98.65%, 97.53% and 93.43%. The determination coefficients of them were 0.9389, 0.9266 and 0.9015, the residuals means of them were 2.16E-09, 5.53E-09 and 2.30E-07, the absolute residuals means of them were 1.0631, 1.1323 and 1.8522, the relative residuals means of them were 0.1197, 0.2038 and 0.2932. It showed that the non-linear model based on dummy variable with place name were more than the others, and the non-linear model with dummy variable were more than the model without dummy variable. These method for establishing model and research results maybe help to improve the model precision and establish a biology mode used in area coverage.