title: Nonlinear mixed-effects (NLME) diameter growth models for individual China-Fir (Cunninghamia lanceolata) trees in Southeast China.
abstract: An individual-tree diameter growth model was developed for Cunninghamia lanceolata in Fujian province, southeast China. Data were obtained from 72 plantation-grown China-fir trees in 24 single-species plots. Ordinary non-linear least squares regression was used to choose the best base model from among 5 theoretical growth equations; selection criteria were the smallest absolute mean residual and root mean square error and the largest adjusted coefficient of determination. To account for autocorrelation in the repeated-measures data, we developed one-level and nested two-level nonlinear mixed-effects (NLME) models, constructed on the selected base model; the NLME models incorporated random effects of the tree and plot. The best random-effects combinations for the NLME models were identified by Akaike's information criterion, Bayesian information criterion and -2 logarithm likelihood. Heteroscedasticity was reduced with two residual variance functions, a power function and an exponential function. The autocorrelation was addressed with three residual autocorrelation structures: a first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)] and a compound symmetry structure (CS). The one-level (tree) NLME model performed best. Independent validation data were used to test the performance of the models and to demonstrate the advantage of calibrating the NLME models.
authors.affiliation: The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, PR China.
authors.forename: Hao
authors.initials: H
authors.lastname: Xu
authors.affiliation: The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, PR China.
authors.forename: Yujun
authors.initials: Y
authors.lastname: Sun
authors.affiliation: The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, PR China.
authors.forename: Xinjie
authors.initials: X
authors.lastname: Wang
authors.affiliation: The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, PR China.
authors.forename: Yao
authors.initials: Y
authors.lastname: Fu
authors.affiliation: The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, PR China.
authors.forename: Yunfei
authors.initials: Y
authors.lastname: Dong
authors.affiliation: College of Forestry, Beijing Forestry University, Beijing, PR China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Li
mesh_terms: D002681:China; D032486:Cunninghamia / Q000033:anatomy & histology* / Q000254:growth & development*; D017711:Nonlinear Dynamics; D012044:Regression Analysis; D015203:Reproducibility of Results; D014197:Trees / Q000033:anatomy & histology* / Q000254:growth & development*
references.citation: Biometrics. 1990 Sep;46(3):673-87
references.pmid: 2242409