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基于广义非线性混合效应的华北落叶松天然次生林枝下高模型(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2018年02期
Page:
170-176
Column:
专题报道
publishdate:
2018-03-20

Article Info:/Info

Title:
Generalized nonlinear mixed-effects crown base height model of Larix principis-rupprechtii natural secondary forests
Article ID:
1000-2006(2018)02-0170-07
Author(s):
DUAN Guangshuang12LI Xuedong3 FENG Yan4 FU Liyong1*
1. Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China; 2. College of Mathematics and Statistics, Xinyang Normal University, Xinyang 464000, China; 3. Experimental Centre of Forestry in North China, Chinese Academy of Forestry, Beijing 102300, China; 4. Chinese Academy of Forestry, Beijing 100091, China
Keywords:
Keywords:Larix principis-rupprechtii generalized nonlinear mixed model crown base height natural secondary forests
Classification number :
S758
DOI:
10.3969/j.issn.1000-2006.201703103
Document Code:
A
Abstract:
【Objective】As a core tool for forest management, a model of crown base height,which utilizes the method of nonlinear mixed effects, was established in this study for researching the growth and yield of Larix principis-rupprechtii natural secondary forests.【Method】Based on individual tree data of 112 plots of a Larix principis-rupprechtii natural secondary forests, an optimal basic model was selected from seven candidate crown base height models.The influence on crown height base of nine disparate individual tree or stand characteristics and their combinations were analyzed, and these significant factors were regarded as predictor variables for improving the precision of the model. Taking into account the disturbance from block- and plot-level random effects, a nested two-level nonlinear mixed-effects model of crown height base was constructed.【Result】The Logistic model was selected as the basic model on account of its higher prediction accuracy and interpret ability of model parameters. Tree diameter at breast height, total basal area of all trees with diameter larger than that of the target tree, mean crown length and stand density were used as predictor variables because of their significant correlation to crown height base, and not to tree height. Compared with the conventional model, the prediction accuracy of the nested two-level nonlinear mixed-effects model was enhanced distinctly, and its coefficient of determination and root mean square error were increased by 53.26% and reduced by 24.73% respectively.【Conclusion】The disturbance from block and plot level random effects significantly influenced the prediction of the crown height base.However, the prediction accuracy of the crown height base model with these random effects was still improved obviously.

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Last Update: 2018-06-12