详细信息
小黑杨树木特征因子与木材生长量的相关性研究 被引量:5
Correlationship between tree characteristics and wood increments of Populus×xiaohei
文献类型:期刊文献
中文题名:小黑杨树木特征因子与木材生长量的相关性研究
英文题名:Correlationship between tree characteristics and wood increments of Populus×xiaohei
作者:刘杏娥[1] 江泽慧[1] 王小青[1] 费本华[1] 任海青[1]
第一作者:刘杏娥
机构:[1]中国林业科学研究院木材工业研究所
年份:2007
卷号:29
期号:3
起止页码:136-141
中文期刊名:北京林业大学学报
外文期刊名:Journal of Beijing Forestry University
收录:CSTPCD;;北大核心:【北大核心2004】;CSCD:【CSCD2011_2012】;
基金:国家自然科学基金重点项目(30230420)
语种:中文
中文关键词:树木特征因子;木材生长量;经验模型;弹性分析
外文关键词:tree characteristic factors, wood increments, empirical models, elasticity analysis
分类号:S781
摘要:为了揭示树木生长特征与木材生长量(幼龄材、成熟材面积及心、边材面积)的关系,该文以山西朔州地区的小黑杨为研究材料,采用相关性分析方法,建立了基于树木特征因子的木材生长量经验模型,并对模型进行了弹性分析.结果表明:冠幅、冠长、胸径与木材生长量呈显著正相关性;以树木胸径、树高、冠幅、尖削度为自变量,采用乘幂函数的方程形式能很好地拟合小黑杨树木特征因子与其木材生长量的关系,其决定系数为0.606-0.932.回归模型的标准回归系数分析表明,胸径对木材生长量的贡献最大.弹性分析进一步表明胸径的影响最大,且模型因子间存在互补又竞争的复杂关系.
To clarify the correlationship between tree characteristics and wood increments (juvenile wood area, mature wood area, sapwood area and heartwood area) of Populus × xiaohei T.S. Hwang et Liang in Shuozhou Region, Shanxi Province, correlation analysis method was applied, and empirical models for prediction of wood increments were established. Elasticity analysis was employed to examine these models. Results indicated that the variables of crown width ( Cw ), crown length ( CL ), as well as diameter at breast height ( DB. ) were all positively related to wood increments. Empirical models, with the form of power functions including DB., height (H), Cw, and stem taper (ST) as explanatory variables, are the best way to describe the relationship between tree characteristics and wood increments. The coefficients of determination of established models ranged from 0.606 to 0.952. Analysis of standardized regression coefficients of regression models shows that DB. contributes most to wood increments. Furthermore, elasticity analysis indicates that DB. has the greatest and most positive influence on wood increments, and both complementary and competitive relationships exist among input variables in these models.
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