华北落叶松天然次生林树高曲线的混合效应模型

doi:10.3969/j.issn.1000-2006.201703014

国家林草科技领军期刊
中国精品科技期刊
中国高校百佳科技期刊
江苏省新闻出版政府奖期刊奖
RCCSE林学权威期刊（A+）
CSCD核心期刊
Scopus数据库收录期刊
中文核心期刊
SCD核心期刊

作者加群：102861116

微信公众号：南京林业大学学报

高级检索

南京林业大学学报（自然科学版） ›› 2018, Vol. 42 ›› Issue (02): 163-169.doi: 10.3969/j.issn.1000-2006.201703014

华北落叶松天然次生林树高曲线的混合效应模型

段光爽^1,2,李学东³,冯岩⁴,符利勇^1*

1.中国林业科学研究院资源信息研究所,北京 100091; 2.信阳师范学院数学与统计学院,河南信阳 464000; 3.中国林业科学研究院华北林业实验中心,北京 102300; 4.中国林业科学研究院,北京 100091

出版日期:2018-04-12 发布日期:2018-04-12
基金资助:
基金项目:国家林业公益性行业科研专项项目(201404417); 国家自然科学基金项目(31570628,31470641); 河南省科技开放合作项目(172106000071) 第一作者:段光爽(oliverdgs@163.com),博士。*通信作者:符利勇(fuly@caf.ac.cn),副研究员。

Developing a height-diameter relationship model with mixed random effects for Larix principis-rupprechtii natural secondary forests

DUAN Guangshuang^1,2,LI Xuedong³, FENG Yan⁴, FU Liyong^1*

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

Online:2018-04-12 Published:2018-04-12

摘要/Abstract

摘要： 【目的】建立华北落叶松天然次生林树高曲线,为森林可持续经营提供技术支撑。【方法】基于116块华北落叶松天然次生林样地单木数据,从11个具有生物学意义的备选模型中选出一个最优基础模型。考虑地域和样地对树高曲线的干扰,基于94块样地利用带哑变量的非线性混合效应模型构建了树高曲线,并对22块样地数据进行验证。【结果】利用全部数据拟合11个备选模型,其中最优模型是Logistic方程,决定系数为0.765 3,均方根误差为3.279 4。引入哑变量和随机效应后,所建模型决定系数为0.915 2,均方根误差为1.892 2,与基础模型相比拟合精度显著提高。验证数据结果表明,带哑变量的非线性混合模型对树高的预测效果良好。【结论】样地随机效应对华北落叶松树高曲线干扰较大,当模型考虑这些随机效应对树高曲线的影响时能显著提高模型预测精度。该模型可用于华北落叶松天然次生林其他样地树高的预测。

Abstract: 【Objective】This study aimed to develop a height-diameter relationship model of Larix principis-rupprechtii natural secondary forests as technical support for sustainable forest management.【Method】Based on individual tree data for 116 plots of Larix principis-rupprechtii natural secondary forests, an optimal basic model was selected from 11 candidate models with biological significance. Taking into account the disturbance from regions and sample plots, a nonlinear mixed-effects model with dummy variables for height-diameter relationships based on 94 plots was constructed, and validation was implemented on 22 surplus plots.【Result】The optimal model of 11 alternative models was fitted to the total data with alogistic equation, and the coefficient of determination and root mean square error were 0.765 3, 3.279 4, respectively. After adjusting the precision of the mixed-effects model with dummy variables and random effects, established with the modeling data, the coefficient of determination and root mean square error were 0.915 2, 1.892 2, respectively, which is a distinctly improvment compared with the basic model. The prediction effects of this model were perfect with the use of the validation data.【Conclusion】The disturbance from plot level random effects significantly influenced the height-diameter relationship.The prediction accuracy of the height-diameter relationship model with these random effects was improved obviously. The prediction of tree height of other plots in Larix principis-rupprechtii natural secondary forests can be implemented with this nonlinear mixed-effects model with dummy variables.

中图分类号:

S758

段光爽,李学东,冯岩,等. 华北落叶松天然次生林树高曲线的混合效应模型[J]. 南京林业大学学报（自然科学版）, 2018, 42(02): 163-169.

DUAN Guangshuang,LI Xuedong, FENG Yan, FU Liyong. Developing a height-diameter relationship model with mixed random effects for Larix principis-rupprechtii natural secondary forests [J].Journal of Nanjing Forestry University (Natural Science Edition), 2018, 42(02): 163-169.DOI: 10.3969/j.issn.1000-2006.201703014.

参考文献

[1] VARGASLARRETA B, CASTEDODORADO F, ÁLVAREZGONZÁLEZ J G, et al. A generalized height-diameter model with random coefficients for uneven-aged stands in El Salto, Durango(Mexico)[J]. Forestry, 2009, 84(4): 445-462.DOI:10.1093/forestry/cpp016.
[2] PENG C, ZHANG L, LIU J. Developing and validating nonlinear height-diameter models for major tree species of Ontario's boreal forests[J]. Northern Journal of Applied Forestry, 2001, 18(3): 87-94.
[3] TEMESGEN H, GADOW K V. Generalized height-diameter models: an application for major tree species in complex stands of interior British Columbia[J]. European Journal of Forest Research, 2004, 123(1): 45-51.DOI:10.1007/s10342-004-0020-z.
[4] ARABATZIS A A, BURKHART H E. An evaluation of sampling methods and model forms for estimating height-diameter relationships in loblolly pine plantations[J]. Forest Science, 1992, 38(1): 192-198.
[5] HUANG S, PRICE D S J T. Development of ecoregion-based height-diameter models for white spruce in boreal forests[J]. Forest Ecology & Management, 2000, 129(1): 125-141.DOI:10.1016/S0378-1127(99)00151-6.
[6] 马小欣,姜鹏,马娇娇,等.沿坝地区华北落叶松胸径-树高生长模型的研究[J].林业资源管理,2015(1):44-48.DOI:10.13466/j.cnki.lyzygl.2015.01.008. MA X X, JIANG P, MA J J, et al. Study on DBH-tree height growth model of Larix principis-rupprechtii along the DAM ecotone[J]. Forest Resources Management, 2015(1): 44-48.
[7] 王冬至,张冬燕,王方,等.塞罕坝主要立地类型针阔混交林树高曲线构建[J].北京林业大学学报,2016, 38(10):7-14.DOI:10.13332/j.1000--1522.20150359. WANG D Z, ZHANG D Y, WANG F, et al. Height curve construction of needle and broadleaved mixed forest under main site types in Saihanba,Hebei of northern China[J]. Journal of Beijing Forestry University, 2016, 38(10): 7-14.
[8] 王冬至,张冬燕,张志东,等.基于非线性混合模型的针阔混交林树高与胸径关系[J].林业科学,2016, 52(1):30-36.DOI:10.11707/j.1001-7488.20160104. WANG D Z, ZHANG D Y, ZHANG Z D, et al. Height-diameter relationship for conifer mixed forest based on nonlinear mixed-effects model[J]. Scientia Silvae Sinicae, 2016, 52(1): 30-36.
[9] 符利勇,何铮,刘应安.关帝山天然次生针叶林林隙大小模型研究[J].南京林业大学学报(自然科学版),2010, 34(5):51-54.DOI:10.3969/j.issn.1000-2006.2010.05.011. FU L Y, HE Z, LIU Y A. Study of the gap size model in a secondary coniferous forest of Guandi Mountain[J]. Journal of Nanjing Forestry University(Natural Sciences Edition), 2010, 34(5): 51-54.
[10] 菇文明,张峰.山西五台山种子植物区系分析[J].植物研究,2000, 20(1):36-47.DOI: 10.3969/j.issn.1673-5102.2000.01.007. GU W M, ZHANG F. Analysis on the flora of seed plants of Wutai Mountains, Shanxi[J]. Bulletin of Botanical Research, 2000, 20(1): 36-47.
[11] MEHTÄTALO L, DEMIGUEL S, GREGOIRE T G. Modeling height-diameter curves for prediction[J]. Canadian Journal of Forest Research, 2015, 45: 826-837.DOI:10.1139/cjfr-2015-0054.
[12] DANIEL L, JEFFERY G. A height-diameter curve for longleaf pine plantations in the GULF coastal plain[J]. Southern Journal of Applied Forestry, 2009, 33(4): 164-170. DOI:10.1007/s11258-009-9605-4.
[13] 李春明,唐守正.基于非线性混合模型的落叶松云冷杉林分断面积模型[J].林业科学,2010, 46(7):106-113.DOI:10.11707/j.1001-7488.20100716. LI C M, TANG S Z. The basal area model of mixed stands of Larix olgensis, Abies nephrolepis and Picea jezoensis based on nonlinear mixed model[J]. Scientia Silvae Sinicae, 2010, 46(7): 106-113.
[14] FANG Z, BAILEY R L. Nonlinear mixed effects modeling for slash pine dominant height growth following intensive silvicultural treatments[J]. Forest Science, 2001, 47(3): 287-300.DOI:10.1046/j.1439-0329.2001.00240.x.
[15] HALL D B, BAILEY R L. Modeling and prediction of forest growth variables based on multilevel nonlinear mixed models[J]. Forest Science, 2001, 47(3): 311-321.DOI:10.1046/j.1439-0329.2001.00240.x.
[16] FU L, SUN H, SHARMA R P, et al. Nonlinear mixed-effects crown width models for individual trees of Chinese fir(Cunninghamia lanceolata)in south-central China[J]. Forest Ecology & Management, 2013, 302(6): 210-220.DOI:10.1016/j.foreco.2013.03.036.
[17] MENG S, HUANG S. Improved calibration of nonlinear mixed-effects models demonstrated on a height growth function[J]. Forest Science, 2009, 55(3):238-248.
[18] FU L, ZHANG H, SHARMA R P, et al. A generalized nonlinear mixed-effects height to crown base model for Mongolian oak in northeast China[J]. Forest Ecology & Management, 2017,384(1):34-43.DOI:10.1016/j.foreco.2016.09.012.
[19] PINHEIRO J C, BATES D M. Mixed-effects models in S and S-PLUS[M]. New York: Springer, 2000.
[20] GREGOIRE T G. Generalized error structure for forestry yield models[J]. Forest Science, 1987, 33(2): 423-444.
[21] PINHEIRO J C, BATES D M. Approximations to the Log-Likelihood function in the nonlinear mixed-effects model[J]. Journal of Computational & Graphical Statistics, 1995, 4(1): 12-35.DOI:10.1080/10618600.1995.10474663.
[22] WOLFINGER R D. An example of using mixed models and PROC MIXED for longitudinal data[J]. Journal of Biopharmaceutical Statistics, 1997, 7(4): 481.DOI:10.1080/10543409708835203.
[23] 符利勇,张会儒,唐守正.基于非线性混合模型的杉木优势木平均高[J].林业科学,2012, 48(7):66-71.DOI:10.11707/j.1001-7488.20120711. FU L Y, ZHANG H R, TANG S Z. Dominant height for Chinese fir plantation using nonlinear mixed effects model based on linearization algorithm[J]. Scientia Silvae Sinicae, 2012, 48(7): 66-71.
[24] CALAMA R, MONTERO G. Interregional nonlinear height-diameter model with random coefficients for stone pine in Spain[J]. Canadian Journal of Forest Research, 2004, 34(1): 150-163.DOI:10.1139/x03-199.

华北落叶松天然次生林树高曲线的混合效应模型

Developing a height-diameter relationship model with mixed random effects for Larix principis-rupprechtii natural secondary forests

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

作者

读者

审稿

[1]	牛弘健, 刘文萍, 陈日强, 宗世祥, 骆有庆. 基于Resnet的林地无人机图像去雾改进算法[J]. 南京林业大学学报（自然科学版）, 2024, 48(2): 175-18.
[2]	高谢雨, 董利虎, 郝元朔. 基于TLS的抚育间伐对长白落叶松干形的影响[J]. 南京林业大学学报（自然科学版）, 2023, 47(6): 85-94.
[3]	李双娴, 陆鑫, 多杰才仁, 张怀清, 薛联凤, 云挺. 一种新的地面激光点云中树木叶面积计算方法[J]. 南京林业大学学报（自然科学版）, 2023, 47(5): 28-38.
[4]	张华聪, 谭新建, 喻龙华, 厉月桥, 陈永富, 刘仁, 张怀清. 基于增强Frost局部滤波及单木距离图重构标记的CHM树冠分割[J]. 南京林业大学学报（自然科学版）, 2023, 47(5): 9-18.
[5]	孙宇, 李凤日, 谢龙飞, 董利虎. 基于林分及地形因子的落叶松人工林林分生物量模型构建[J]. 南京林业大学学报（自然科学版）, 2023, 47(3): 129-136.
[6]	唐依人, 贾炜玮, 王帆, 孙毓蔓, 张颖. 基于TLS辅助的长白落叶松一级枝条生物量模型构建[J]. 南京林业大学学报（自然科学版）, 2023, 47(2): 130-140.
[7]	欧建德. 杈干现象对南方红豆杉树冠形态、生长和形质的影响[J]. 南京林业大学学报（自然科学版）, 2023, 47(2): 87-94.
[8]	王帆, 贾炜玮, 唐依人, 李丹丹. 基于TLS的红松树冠半径提取及其外轮廓模型构建[J]. 南京林业大学学报（自然科学版）, 2023, 47(1): 13-22.
[9]	程晓菲, 武刚. 基于高分辨率卫星影像的CV模型单木定位法[J]. 南京林业大学学报（自然科学版）, 2022, 46(5): 143-151.
[10]	聂璐毅, 董利虎, 李凤日, 苗铮, 谢龙飞. 基于两水平非线性混合效应模型的长白落叶松削度方程构建[J]. 南京林业大学学报（自然科学版）, 2022, 46(3): 194-202.
[11]	赵青, 黄菲, 陈晓辉, 林玉英, 邱荣祖, 巫志龙, 胡喜生. 乔木林丧失的时空变化及驱动力分析[J]. 南京林业大学学报（自然科学版）, 2022, 46(2): 227-235.
[12]	辛士冬, 姜立春, 穆林. 黑龙江省红松人工林林分乔木层可加性碳储量模型[J]. 南京林业大学学报（自然科学版）, 2022, 46(1): 115-121.
[13]	崔泽宇, 张怀清, 左袁青, 杨廷栋, 刘洋, 张京, 王林龙. 杉木三维模型各方向枝下高分布研究[J]. 南京林业大学学报（自然科学版）, 2022, 46(1): 81-87.
[14]	单凯丽, 臧颢, 潘萍, 宁金魁, 欧阳勋志. 赣中天然闽楠单木冠幅预测模型的研究[J]. 南京林业大学学报（自然科学版）, 2022, 46(1): 88-96.
[15]	卢军, 刘宪钊, 孟维亮, 李红军. 基于地面激光点云数据的单木三维重建方法[J]. 南京林业大学学报（自然科学版）, 2021, 45(6): 193-199.