摘要
以我国南方地区的最重要针叶树种——杉木为研究对象,采用误差变量联立方程组和哑变量模型方法,建立适合不同杉木生长区域(总体)应用的相容性立木材积方程、地上生物量方程及生物量转换因子函数。结果表明:二元立木材积方程和地上生物量方程均优于其相应的一元模型;不同总体的模型之间存在显著差异,总体A的模型估计值要大于总体B;一元和二元地上生物量方程的平均预估误差均在3%以内,可应用于不同区域的杉木林生物量估计。
Taking the most important coniferous species of southern China,Chinese fir( Cunninghamia lanceolata),as the study object,the compatible tree volume equations,aboveground biomass equations and biomass conversion factor functions suitable for two regions( population areas) were constructed using the error-in-variable simultaneous equation and dummy variable model approach. The results showed that two-variable models are better than one-variable models whether tree volume equation or aboveground biomass equation; the models for two populations are significantly different and the projected estimates for population A are larger than those for population B; the mean prediction errors( MPE's) of one- and two-variable aboveground biomass equations are both less than 3%,which means the aboveground biomass equations could be applied for estimation of Chinese fir forest biomass in the regions.
出处
《林业科学》
EI
CAS
CSCD
北大核心
2013年第10期74-79,共6页
Scientia Silvae Sinicae
关键词
材积方程
生物量方程
生物量转换因子
误差变量联立方程组
哑变量
杉木
volume equation
biomass equation
biomass conversion factor
error-in-variable simultaneous equation
dummy variable
Cunninghamia lanceolata