| 摘要: |
| 摘要 文章以湖南省 188 个栎类次生林样地为研究对象，利用 Kolmoglov-Smirnov 检验法对 6 种分布密度函数在直径分布拟合中的适用性进行检验。以林分变量为自变量，采用参数预测法构建 Weibull 函数3 个参数的逐步回归参数模型和以林分类型为哑变量的哑变量参数模型，并对比两类模型的直径分布预测精度。结果表明，Weibull 函数更适合于栎类直径分布的拟合（接受率为 91.7%）；与逐步回归参数模型相比，参数 b、c 的哑变量模型的 R2 分别提高了 0.104 和0.134，且应用于直径分布预测时的精度显著提高（P=0.025）。研究基于林分类型哑变量构建参数模型，并用于栎类次生林的直径分布预测，预测精度较高。 |
| 关键词: 直径分布 哑变量 Weibull 函数 栎类 |
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| Study on Diameter Distribution of Oak Secondary Forest Based on Dummy Variable in Hunan Province |
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LI Shirong, LI Linbing
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Lingnan Integrated Exploration and Design Institute of Guangdong Province
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| Abstract: |
| Abstract Diameter distribution models have been used to predict the dynamical stand structure, and it is an essential tool for forest management and conservation. Based on 188 oak secondary forest plots, the applicability of six density functions were tested using Kolmoglov-Smirnov. The multiple regression model and dummy variable model of Weibull parameters were constructed separately using parameter prediction method with stand variables as independent variables, and the prediction accuracy of diameter distribution of the two models was compared. The results showed that Weibull function was more suitable for fitting oak diameter distribution (acceptance rate 91.7%). Compared with stepwise regression parameter model, the R2 of dummy variable model of parameter b and c increased by 0.104 and 0.134 respectively, and the accuracy of diameter distribution prediction was significantly improved (P = 0.025). In this study, a parameter model was constructed based on dummy variables of stand types, and it was used to predict the diameter distribution of oak secondary forest with high prediction accuracy, which can provide reference for the study of diameter distribution of oaks. |
| Key words: diameter distribution dummy variable Weibull function oak |
