文献类型：期刊文献

英文题名：Variable-Exponent Taper Equation Based on Multilevel Nonlinear Mixed Effect for Chinese Fir in China

作者：Zhang, Sensen[1] Sun, Jianjun[2] Duan, Aiguo[1,3] Zhang, Jianguo[1,3]

第一作者：Zhang, Sensen

通信作者：Duan, AG[1];Duan, AG[2]

机构：[1]Chinese Acad Forestry, Res Inst Forestry, State Key Lab Tree Genet & Breeding, Key Lab Forest Silviculture,State Forestry Adm, Beijing 100091, Peoples R China;[2]Chinese Acad Forestry, Expt Ctr Subtrop Forestry, Fenyi 336600, Peoples R China;[3]Nanjing Forestry Univ, Collaborat Innovat Ctr Sustainable Forestry South, Nanjing 210037, Peoples R China

年份：2021

卷号：12

期号：2

起止页码：1-13

外文期刊名：FORESTS

收录：;EI(收录号：20210609899795);Scopus(收录号：2-s2.0-85100488643);WOS:【SCI-EXPANDED(收录号:WOS:000622503000001)】；

基金：This work was supported by the National Scientific and Technological Task in China (No. 2016YFD0600302), and the special science and technology innovation in Jiangxi Province (No. 201702).

语种：英文

外文关键词：taper function; Chinese fir; mixed-effects models; autocorrelation; tree-level effect

摘要：A variable-exponent taper equation was developed for Chinese fir (Cunninghamia lanceolate (Lamb.) Hook.) trees grown in southern China. Thirty taper equations from different groups of models (single, segmented, or variable-exponent taper equation) were compared to find the excellent basic model with S-plus software. The lowest Akaike information criteria (AIC), Bayesian information criteria (BIC), and -2loglikelihood (-2LL) was chosen to determine the best combination of random parameters. Single taper models were found having the lowest precision, and the variable-exponent taper equations had higher precision than the segmented taper equations. Four variable-exponent taper models that developed by Zeng and Liao, Bi, Kozak, Sharma, and Zhang respectively, were selected as basic model and had no difference in fit statistics between them. Compared with the model without seldom parameter, the nonlinear mixed-effects (NLME) model improves the fitting performance. The plot-level NLME model was found not to remove the residual autocorrelation. The tree-level and two-level NLME model had better simulation accuracy than the plot-level NLME model, and there were no significant differences between the tree-level and two-level NLME model. Variable-exponent taper model developed by Kozak showed the best performance while considering two-level or tree-level NLME model, and produced better predictions for medium stems compared to lower and upper stems.