摘要
地位指数法是当前立地质量评价中广泛采用的一种评定方法。在同一立地上,实现不同树种地位指数之间的转换,建立地位指数互导模型有助于立地质量的评定.譬如,在某一立地上现时生长着马尾松,欲知在马尾松被采伐后营造杉木林的生长潜力,这时就可利用上层木树种间地位指数的关系进行立地质量评定。以雪峰山杉木与马尾松地位指数配对样地数据为基础,建立了杉木与马尾松地位指数的常规线性模型、对偶回归模型和度量误差线性模型,从建模精度和模型适用性检验两方面,对3种模型进行了比较分析。结果表明3种模型的精度均比较高,模型效果差异不明显,其中,常规线性模型、度量误差模型和对偶回归模型的相对误差分别为5.39%、5.39%和5.54%。由于杉木地位指数和马尾松地位指数均存在度量误差,因此,线性度量误差模型和对偶回归模型比常规线性模型更适宜,这是因为,前两种模型的自变量和因变量是可以存在度量误差的,而后者的因变量是没有度量误差的。此外,线性度量误差模型的相对误差比对偶回归模型的要小,所以,3种线性模型中,线性度量误差模型最优。研究结果实现了相同立地条件下杉木地位指数和马尾松地位指数的互导,为不同树种间的立地质量评价提供了可行的方法。
Site index is an effective method that has been widely used to evaluate site quality at present. The study of the correlation among site indexes of different tree species stands and establishment of correlation model of different site indexes in the same site for several tree species could be useful for predicting one site index （ dependent variable） on condition that the other site index （ independent variable） is known,and is propitious to evaluate site quality. For example,when a Pinus massioniana stand would be harvested for some reasons and replanted by Cunninghamia lanceolata,we should predict the growth potential of Cunninghamia lanceolata stand. The correlation model of site indexes of Cunninghamia lanceolata and Pinus massioniana provides a helpful routine to solve this issue. Firstly,the correlation model of site indexes of Cunninghamia lanceolata and Pinus massioniana should be established,and then the site index of Pinus massioniana site based on the investigation appraoch should be obtained. Finally,the site index of Cunninghamia lanceolata could be predicted. In this study,we used the site index data of Cunninghamia lanceolata and Pinus massoniana collected at the same plots in Xuefeng mountain to establish three linear models （ i. e. general linear model,dual regression model and measurement error model,respectively）. The precision and accuracy tests of three model were performed and the efficiency of these models was compared. The results show that the precision of three models is high. The relative error was 5. 39% for general linear model,5. 45% for dual regression model and 5. 39% for measurement error model,respectively. Both the Cunninghamia lanceolata Site-index and Pinus massoniana Site index yielded measurement error. The linear measurement error model and dual regression linear model are more appropriate than general linear model,because that both independent variable and dependent variable had the measurement error in measurement error and dual regression models,no measurement error was found for the dependent variable of the general linear model. Furthermore,the relative error of dual regression model was higher than that of measurement error model,suggesting that linear measurement error model is more appropriate than the other models. This result showed that when Cunninghamia lanceolata site index （ or the Pinus massoniana site index） is known in one site,site index of another tree species could be predicted by using the linear measurement error model. Correspondingly,when the growth ability of Cunninghamia lanceolata stand （ or Pinus massoniana） is known,the growth potential of another tree species stand could be estimated. The method for evaluating the site quality of Cunninghamia lanceolata stand and Pinus massoniana stand would be also effective for other trees species as well.
出处
《生态学报》
CAS
CSCD
北大核心
2010年第21期5862-5867,共6页
Acta Ecologica Sinica
基金
国家自然科学基金资助项目(30871962)
湖南省自然科学基金资助项目(09JJ6058)
中南林业科技大学森林经理学湖南省重点学科资助
关键词
杉木地位指数
马尾松地位指数
对偶回归
度量误差
线性模型
Cunninghamia lanceolata site-index
Pinus massoniana site-index
dual regression
measurement error
linear model
