文献类型：期刊文献

英文题名：A generalized interregional nonlinear mixed-effects crown width model for Prince Rupprecht larch in northern China

作者：Fu, Liyong[1,2] Sharma, Ram P.[3] Hao, Kaijie[4] Tang, Shouzheng[1]

第一作者：Fu, Liyong;符利勇

通信作者：Tang, SZ[1]

机构：[1]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]Penn State Univ, Ctr Stat Genet, Loc T3436,Mail Code CH69,500 Univ Dr, Hershey, PA 17033 USA;[3]Czech Univ Life Sci, Fac Forestry & Wood Sci, Prague, Czech Republic;[4]Shanxi Acad Forestry Sci, Taiyuan 030012, Shanxi, Peoples R China

年份：2017

卷号：389

起止页码：364-373

外文期刊名：FOREST ECOLOGY AND MANAGEMENT

收录：;EI(收录号：20170303264131);Scopus(收录号：2-s2.0-85009821263);WOS:【SCI-EXPANDED(收录号:WOS:000398868800036)】；

基金：We would like to thank the Forestry Public Welfare Scientific Research Project of China (No. 201404417) and the National Natural Science Foundations of China (Nos. 31570628, 31300534, and 31470641) for the financial support of this study. We also appreciate the valuable comments and constructive suggeations from two anonymous referees and the Associate Editor.

语种：英文

外文关键词：Crown width; Interregional effects; Optimal sample size; Random effects; Two-level mixed-effects model

摘要：Crown width is a tree variable that is commonly used as an important predictor in forest growth and yield models that serve as decision-support tools in forestry. Here, we developed a generalized interregional nonlinear mixed-effects individual tree crown width model using data from 3369 Prince Rupprecht larch (Larix principis-rupprechtii Mayr.) trees on 116 sample plots that were distributed across the two most important regions in northern China. Because measurements from the same sample plot were highly correlated with each other, random effects at the levels of both sample plots and stands with different site conditions (blocks) were used to develop a two-level nonlinear mixed-effects crown width model. To describe the interregional variability of crown width between the regions, a dummy variable, which accounts for region-specific differences, was introduced into the model. The results showed that the two-level interregional nonlinear mixed-effects crown width model accurately described the regional variability of crown width for Prince Rupprecht larch in northern China. Modeling the random effects at the block level alone led to significantly high correlations among the residuals. However, these correlations decreased significantly when the random effects were modeled at both the block and sample plot levels. Measuring the crown width of four randomly selected Prince Rupprecht larch trees per sample plot is recommended for localizing the mixed-effects crown width model and precisely predicting the crown widths of the remaining trees on each plot. (C) 2017 Elsevier B.V. All rights reserved.