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Nonlinear Mixed-Effects (NLME) Diameter Growth Models for Individual China-Fir (Cunninghamia lanceolata) Trees in Southeast China

Author

Listed:
  • Hao Xu
  • Yujun Sun
  • Xinjie Wang
  • Yao Fu
  • Yunfei Dong
  • Ying Li

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.

Suggested Citation

  • Hao Xu & Yujun Sun & Xinjie Wang & Yao Fu & Yunfei Dong & Ying Li, 2014. "Nonlinear Mixed-Effects (NLME) Diameter Growth Models for Individual China-Fir (Cunninghamia lanceolata) Trees in Southeast China," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
  • Handle: RePEc:plo:pone00:0104012
    DOI: 10.1371/journal.pone.0104012
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    Cited by:

    1. Yan-qiong Li & Xiang-wen Deng & Zhi-hong Huang & Wen-hua Xiang & Wen-de Yan & Pi-feng Lei & Xiao-lu Zhou & Chang-hui Peng, 2015. "Development and Evaluation of Models for the Relationship between Tree Height and Diameter at Breast Height for Chinese-Fir Plantations in Subtropical China," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-21, April.
    2. Manuel Arias-Rodil & Fernando Castedo-Dorado & Asunción Cámara-Obregón & Ulises Diéguez-Aranda, 2015. "Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-20, December.
    3. Ollier, Edouard, 2022. "Fast selection of nonlinear mixed effect models using penalized likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    4. Pires, Sandra Aguiar de Oliveira & de Mendonça, Adriano Ribeiro & da Silva, Gilson Fernandes & d'Oliveira, Marcus Vinícius Neves & de Oliveira, Luís Claudio & Silva, Jeferson Pereira Martins & da Silv, 2021. "Growth modeling of Carapa guianensis and Tetragastris altissima for improved management in native forests in the Amazon," Ecological Modelling, Elsevier, vol. 456(C).

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