[1]彭 娓,李凤日,董利虎.黑龙江省长白落叶松人工林单木生长模型[J].南京林业大学学报(自然科学版),2018,42(03):019-27.[doi:10.3969/j.issn.1000-2006.201711025]
 PENG Wei,LI Fengri,DONG Lihu*.Individual tree diameter growth model for Larix olgensis plantation in Heilongjiang Province, China[J].Journal of Nanjing Forestry University(Natural Science Edition),2018,42(03):019-27.[doi:10.3969/j.issn.1000-2006.201711025]
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黑龙江省长白落叶松人工林单木生长模型
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《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

卷:
42
期数:
2018年03期
页码:
019-27
栏目:
专题报道(Ⅰ)
出版日期:
2018-05-15

文章信息/Info

Title:
Individual tree diameter growth model for Larix olgensis plantation in Heilongjiang Province, China
文章编号:
1000-2006(2018)03-0019-09
作者:
彭 娓李凤日董利虎
东北林业大学林学院,黑龙江 哈尔滨 150040
Author(s):
PENG Wei LI Fengri DONG Lihu*
School of Forestry, Northeast Forestry University, Harbin 150040, China
关键词:
长白落叶松人工林 逐步回归 因变量 哑变量模型 单水平线性混合模型 单木直径生长
Keywords:
Larix olgensis plantation stepwise regression response variables dummy variable model single-level mixed linear model individual-tree increment
分类号:
S758
DOI:
10.3969/j.issn.1000-2006.201711025
文献标志码:
A
摘要:
【目的】利用单水平线性混合模型构建了黑龙江长白落叶松人工林单木直径生长模型,为准确预测黑龙江省落叶松人工林的生长及合理经营提供理论依据。【方法】基于黑龙江省148块固定样地数据,运用逐步回归法,依次引入林木初始大小因子、竞争和立地因子,建立并评估了5种不同因变量(5年间隔期末胸高直径d5,直径增长量d5-d0,5年直径增长量的自然对数ln(d5-d0+1),直径平方增长量的自然对数ln(d25-d20+1),直径平方增长量d25-d20)的黑龙江省长白落叶松人工林传统单木生长模型,同时基于最优传统模型采用哑变量方法构建了与距离无关的单木直径生长模型,并在哑变量模型的基础上把样地作为随机效应因子,运用单水平线性混合模型的方法构建了单木直径生长模型,并利用独立检验样本数据对基础模型、哑变量模型和混合模型进行检验。【结果】对于每一种因变量的单木生长模型,依次加入林木初始大小、竞争因子和立地因子后,模型精度均有显著提高; 因变量为ln(d5-d0+1)的模型为最优单木直径生长模型。影响黑龙江省落叶松人工林单木直径生长的主要因素有林木初始大小(ln d0)、地位指数、林分每公顷断面积和大于对象木断面积和。哑变量模型在保证预估精度的同时体现了两个区域间的差异。混合效应预估模型的R2、均方误差(MSE)和均方根误差(RMSE)分别为0.978 3、0.713 7和0.844 8 cm。与传统模型相比,混合效应模型的相对平均均方误差和均方根误差较传统模型减少了0.300 6和0.162 3 cm,决定系数R2几乎相当。在模型检验中,混合效应模型呈现较好的拟合效果。【结论】基于线性混合效应的黑龙江省长白落叶松人工林的单木直径生长模型较传统模型预测精度更高。
Abstract:
【Objective】The individual tree diameter growth model of a Larix olgensis plantation in Heilongjiang Province was developed by a single level linear mixed model. The model had good prediction accuracy, and it provided a theoretical basis for accurately predicting the growth and reasonable management for Larix olgensis plantations in Heilongjiang Province.【Methods】Based on the data of 148 fixed plots in Heilongjiang Province, this study used a stepwise regression method to introduce the initial size factor, competition, and site factors for trees, and established and evaluated five different independent variables(5-year later diameter(d5), a periodic annual increment model using 5-year diameter increment(d5- d0), the natural logarithm of 5-year diameter increment [ln(d5 - d0 + 1)], the natural logarithm of 5-year squared diameter increment [ln(d25 - d20 + 1)], and 5-year squared diameter increment(d25 - d20)). Additionally, a set of generalized distance-independent individual tree diameter growth models were constructed by using the dummy variable method based on the optimal traditional model. In addition, the individual tree diameter growth model was built based on a single level linear mixed model with a parameter random effect for plot on the basis of the dummy variable model. Each approach was evaluated by using independent validation data.【Results】We could clearly find the progressive improvement in AIC when competition and site were added in a stepwise regression as predictor variables for individual tree diameter growth model with each response variable. The model of ln(d5 - d0 + 1)for response variable was the best model for the individual-tree diameter increment prediction. The natural logarithm of the initial diameter(ln d0), total stand basal area per hectare, basal area of the trees higher than the object tree, and site index were found to be significant predictors. The dummy variable models showed the regional difference while ensuring prediction accuracy. The R2, MSE and RMSE of the mixed effects model were 0.978 3, 0.713 7 and 0.844 8 cm, respectively. Compared with the traditional model, the MSE and RMSE of the mixed model were reduced by 0.300 6 and 0.162 3 cm, respectively, and the R2 values were practically equivalent. The linear mixed model, including fixed and random parameters, provided a better fit among the models tested.【Conclusion】Compared with the traditional model, the individual-tree diameter growth model for the Larix olgensis plantation in Heilongjiang Province based on the linear mixed effect improved the prediction accuracy, which provided a reliable theoretical basis for accurately predicting the growth of Larix olgensis plantations in different regions of Heilongjiang Province.

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备注/Memo

备注/Memo:
基金项目:国家重点研发计划(2017YFD0600402); 国家自然科学基金项目(31600510) 第一作者:彭娓(pengw_2012@126.com),博士生。*通信作者:董利虎(donglihu2006@163.com),讲师。
更新日期/Last Update: 2018-06-06