基于混合效应和分位数回归的温带针阔混交林树高与胸径关系研究  

Research on the relationship between tree height and DBH of temperate coniferous and broadleaved mixed forests based on mixed effects and quantile regression

作　　者：程雯 武晓昱 叶尔江·拜克吐尔汉 王娟[4] 赵秀海[1] 张春雨[1] Cheng Wen;Wu Xiaoyu;Yeerjiang Baiketuerhan;Wang Juan;Zhao Xiuhai;Zhang Chunyu(Research Center of Forest Management Engineering of National Forestry and Grassland Administration,Beijing Forestry University,Beijing 100083,China;School of Science,Beijing Forestry University,Beijing 100083,China;College of Forestry and Landscape Architecture,Xinjiang Agricultural University,Key Laboratory of Xinjiang Uygur Autonomous Region for Forest Ecology and Industrial Technology in Arid Zone,Urumqi 830052,Xinjiang,China;School of Ecology and Nature Conservation,Beijing Forestry University,Beijing 100083,China)

机构地区：[1]北京林业大学国家林业和草原局森林经营工程技术研究中心,北京100083 [2]北京林业大学理学院,北京100083 [3]新疆农业大学林学与风景园林学院,新疆干旱区林业生态与产业技术重点实验室,新疆乌鲁木齐830052 [4]北京林业大学生态与自然保护学院,北京100083

出　　处：《北京林业大学学报》2024年第2期28-39,共12页Journal of Beijing Forestry University

基　　金：国家重点研发计划重点专项(2022YFD2201004-4)。

摘　　要：【目的】基于非线性回归和广义模型构建不同分位数回归和混合效应的树高预测方程,并对比分析非线性模型、不同分位点(τ=0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9)模型、广义模型及非线性混合效应模型的拟合效果和预测精度,为研究林分生长和收获提供理论依据。【方法】本研究以吉林蛟河地区针阔混交林的主要树种(红松、色木槭、紫椴和水曲柳)为研究对象,基于21.12 hm2样地数据,首先在11个广泛使用的树高方程基础模型中选定基础模型;其次探究林分变量对树高的影响并构建含林分变量的广义模型;最后在基础模型和广义模型的基础上,构建分位数模型,同时考虑样方效应对树高的影响,构建混合效应模型。【结果】(1)各树种均以Richards模型拟合精度更高,且具有生物学意义,选定为基础模型;考虑林分变量与树高的相关性以及模型收敛性,加入优势木高建立的广义模型能显著提高拟合效果。(2)各树种均为中位数τ=0.5时模型拟合效果最佳,且与非线性回归预测精度相近,红松、色木槭、紫椴和水曲柳最高R^(2)值分别为0.811、0.809、0.724和0.617,广义中位数回归预测能力得到进一步提高,R^(2)值分别为0.891、0.874、0.858和0.627。(3)混合效应模型相对其他模型能显著提高预测精度,其中基础混合模型略优于广义混合模型,4个树种R^(2)值达到0.937、0.919、0.906和0.643,表明包含样方效应的混合模型能得到更准确更稳定的预测结果。【结论】与传统方法建立的基础模型和广义模型以及两者的中位数回归模型相较,基于非线性混合效应构建的树高-胸径模型预测精度更高,其中基于基础混合效应构建的吉林蛟河地区混交林树高-胸径模型更具优越性和稳定性。[Objective]The aim of this study was to construct tree height equation for quantile regression and mixed-effects based on nonlinear regression and generalized models.And fitting effect and prediction accuracy of nonlinear models,different quntile models(τ=0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9),generalized models and nonlinear mixed-effects models were compared and analyzed,so as to provide theoretical basis for further study of stand growth and harvest.[Method]Based on 21.12 ha sample plot data,taking the main tree species(Pinus koraiensis,Acer mono,Tilia amurensis and Fraxinus mandshurica)from coniferous and broadleaved mixed forest of Jiaohe,Jilin Province of northeastern China as the research object.And the base model was first selected from 11 widely-used tree height equations,then we explored the influence of stand variables on tree height and constructed generalized model containing stand variables.Finally,on the basis of basic model and the generalized model,the quantile model was constructed,and the mixed-effect model was established considering the impact of sample effect on tree height.[Result](1)Richards was selected as base model for all tree species because of its higher fitting accuracy and biological significance.And considering the correlation between stand variables and tree height and the convergence of models,the generalized model established by adding dominant tree height can significantly improve the fitting effect.(2)All models based on the median(τ=0.5)performed best,and the prediction accuracy was close to the nonlinear regression.The highest R^(2) values of Pinus koraiensis,Acer mono,Tilia amurensis and Fraxinus mandshurica were 0.811,0.809,0.724 and 0.617,respectively.The generalized median regression prediction ability was further improved,and R^(2) values were 0.891,0.874,0.858 and 0.627,respectively.(3)Mixed-effect models can significantly improve the prediction accuracy compared with other models,among which base mixed model was slightly better than generalized mixed model,and the R^

关 键 词：分位数回归 树高-胸径模型 混合效应模型 广义模型 针阔混交林 

分 类 号：S757[农业科学—森林经理学]