文献类型：期刊文献

英文题名：Improving the accuracy of tree-level aboveground biomass equations with height classification at a large regional scale

作者：Li, Haikui[1] Zhao, Pengxiang[2]

第一作者：李海奎

通信作者：Li, HK[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resources Informat, Beijing 100091, Peoples R China;[2]Northwest Agr & Forestry Univ, Coll Forestry, Yangling 712100, Shaanxi, Peoples R China

年份：2013

卷号：289

起止页码：153-163

外文期刊名：FOREST ECOLOGY AND MANAGEMENT

收录：;EI(收录号：20130115869672);Scopus(收录号：2-s2.0-84870201313);WOS:【SCI-EXPANDED(收录号:WOS:000315659500018)】；

基金：This research was supported by grants from the National Natural Science Foundation of China (No. 31070485). The authors thank W. Zeng for providing some biomass data and Y. Lei for helpful comments and suggestions which improved this manuscript. We would like to express our appreciation to two anonymous reviewers for their constructive comments on the manuscript.

语种：英文

外文关键词：Additive equations; Biomass; Cunninghamia lanceolata; Height classification; Prediction accuracy

摘要：A nonlinear simultaneous equations system based on diameter at breast height (DBH), used to ensure additivity for biomass of individual tree components, was fitted for Cunninghamia lanceolata. The data consisted of measurements taken from 600 sample trees in southern China. All sample trees were harvested and measured for biomass of stem wood, stem bark, branches and foliage. Tree height was classified into 2-5 levels based on the height-diameter relationship across a large geographical area. The nonlinear extra sum of squares method and the Lakkis-Jones test were used to evaluate significant differences between biomass equations with DBH only and classified equations and to assess whether height classification had a significant effect on improving the accuracy of the biomass equations. Based on the PRESS residuals, several statistical indicators, e.g. prediction determination coefficient and root mean square error, were used to evaluate model performance. The results show the height classification obviously improved model performance of the fitted equation by increasing the prediction determination coefficient, decreasing root mean square error and reducing bias and absolute bias by DBH class, especially for total aboveground biomass, stem wood biomass and stem bark biomass. Three-levels of height classification was the best for the total aboveground biomass, following by 4-levels, 5-levels and 2-levels. Although statistically significant differences between the classified equations and the equations with DBH only were found for measurements of branch biomass and foliage biomass, their proportions of total aboveground biomass was small and had only a small effect on improving the accuracy of total aboveground biomass estimates. Height classification increased the stability of parameters for the estimation of stem wood and stem bark biomass. The classified biomass equations could be applied to estimate individual tree biomass in the Chinese National Forest Inventory and the method of height classification may be used with other tree species. (C) 2012 Elsevier B.V. All rights reserved.