AN APPROACH TO GROWTH AND YIELD MODELS FOR INDIVIDUAL CHINA-FIR (CUNNINGHAMIA LANCEOLATA) TREES IN SOUTHEAST CHINA

文献类型： 外文期刊

第一作者： Xu, H.

作者： Xu, H.;Sun, Y. J.;Wu, X. D.;Wang, Z. J.;He, J. L.;Yu, H. Q.

作者机构：

关键词： individual-tree model; autocorrelation; heteroscedasticity; nonlinear mixed-effects models; Cunninghamia lanceolata

期刊名称：APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH （ 影响因子：0.711； 五年影响因子：0.796 ）

ISSN： 1589-1623

年卷期： 2019 年 17 卷 6 期

页码：

收录情况： SCI

摘要： As the most commonly grown afforestation species in southeast China, China-fir (Cunninghamia lanceolata) shows a huge ecological service function. Generalized individual-tree growth models were developed for C. lanceolata. Data was obtained from 61 plantation-grown China-fir trees in 17 single-species plots located in four sites by stem analysis. The best base models were chosen from five theoretical growth equations for modeling increases in diameter at breast high, tree, height and stem volume using ordinary nonlinear least squares regression; selection criteria were the smallest absolute mean residual, root mean square error and the largest adjusted coefficient of determination To account for autocorrelation in the data with repeated measures, we developed a nested multi-level nonlinear mixed-effects (NLME) model, constructed on the selected base model; the NLME models incorporated random effect for tree, plot and site. 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 and autocorrelation was also addressed. For diameter and height growth, the NLME models including the exponential function and ARMA(1,1) performed best, and the NLME models including the power function and ARMA(1,1) performed best for stem growth. The NLME models were considered to be the best approach to analyze the variation of tree growth and yield.

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