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Forest and Grassland Resources Research >

2019 , Vol. 0 >Issue 4: 46 - 51

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2019.04.007

Developing Models for Tree Height Curves of Main Conifer Species in Yunnan Province

  • Yangping QIN ,
  • Hua LI ,
  • Yongliang LI ,
  • Chengcheng ZHANG ,
  • Meng WANG
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  • 1. Kunming Survey & Design Institute of National Forestry and Grassland Administration,Kunming,Yunnan 650216,China
    2. Research Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,China

Received date: 2019-05-13

  Revised date: 2019-07-28

  Online published: 2020-10-20

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Abstract

Tree height curve plays an important role in the forest management and yield regulation,the tree height curve model for main conifer species in Yunnan Province was established to provide reference for its forest management.Based on two periods of national forest inventory data in Yunnan Province,this paper takes Abies fabri,Pinus kesiya var.langbianensis,Pinus yunnanensis,Pinus armandii,Cunninghamia lanceolata as research objects,Richards etc.fifteen tree height curve models were selected as alternative models,the coefficient of determination,root mean square error,mean absolute error,total relative error and mean predict error were used as the evaluation indicators of the pros and cons of the model.The results show that Hossfeld can better describe the tree height curve of Abies fabri and Cunninghamia lanceolata,hyperbola can better describe the tree height curve of Pinus yunnanensis and Pinus armandii,Wykoff can better describe the tree height curve of Pinus kesiya var.langbianensis.The coefficient of determination of the optimal tree height curve model of Pinus yunnanensis is 0.676,and the coefficient of determination of other conifer tree specieses are greater than 0.710,the independent sample data test shows that the optimal tree height curve model of each tree species has good applicability,and has a good prediction effect on the tree height of the main conifer tree species in Yunnan Province.

Key words： Yunnan Province; tree height curve; conifer species

Cite this article

Yangping QIN , Hua LI , Yongliang LI , Chengcheng ZHANG , Meng WANG . Developing Models for Tree Height Curves of Main Conifer Species in Yunnan Province[J]. Forest and Grassland Resources Research, 2019 , 0(4) : 46 -51 . DOI: 10.13466/j.cnki.lyzygl.2019.04.007

References

[1] Temesgen H, Hann D,J, Monleon D,J . Regional Height-Diameter Equations for Major Tree Species of Southwest Oregon[J]. 2008,22:213-219.
[2] 张鹏, 王新杰, 许昊 . 将乐地区马尾松标准树高曲线的研究[J]. 中南林业科技大学学报, 2015,35(3):69-73.
[3] 赵俊卉, 亢新刚, 刘燕 . 长白山主要针叶树种最优树高曲线研究[J]. 北京林业大学学报, 2009,31(4):13-18.
[4] 孟宪宇 . 测树学[M]. 3版. 北京: 中国林业出版社, 2006.
[5] Larjavaara H C, Muller-Landau M . Measuring tree height:A quantitative comparison of two common field methods in a moist tropical forest[J]. Methods in Ecology and Evolution, 2013,21(5):9.
[6] Adame P, Del RíO M, Ca?ellas I . A mixed nonlinear height-diameter model for pyrenean oak(Quercus pyrenaica Willd.)[J]. Forest Ecology and Management, 2008,256(1):88-98.
[7] 代忠迪, 姜立春 . 大兴安岭不同生态区域兴安落叶松树高曲线的研究[J]. 植物研究, 2015,35(4):583-589.
[8] 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(2):163-169
[9] 刘鑫, 王海燕, 雷相东 , 等. 基于BP神经网络的天然云冷杉针阔混交林标准树高-胸径模型[J]. 林业科学研究, 2017,30(3):368-375.
[10] 赵俊卉, 亢新刚, 张慧东 , 等. 长白山3个主要针叶树种的标准树高曲线[J]. 林业科学, 2010,46(10):191-194.
[11] 陈飞, 王健敏, 孙宝刚 , 等. 云南松的地理分布与气候关系[J]. 林业科学研究, 2012,25(2):163-168.
[12] 孙雪莲, 舒清态, 欧光龙 , 等. 基于随机森林回归模型的思茅松人工林生物量遥感估测[J]. 林业资源管理, 2015(1):71-76.
[13] 汪家社 . 杉木生态系统生物量与固碳能力的分析与评价[J]. 福建林业科技, 2008(2):1-4.
[14] 李元玖, 陈奇伯, 熊好琴 , 等. 滇中高原华山松人工林碳储量及固碳释氧效益[J]. 中南林业科技大学学报, 2015,35(2):79-84.
[15] 李艳丽, 杨华, 亢新刚 , 等. 长白山云冷杉种群结构和动态分析[J]. 北京林业大学学报, 2014,36(3):18-25.
[16] 王明亮, 唐守正 . 标准树高曲线的研制[J]. 林业科学研究, 1997(3):36-41.
[17] 胥辉, 全宏波, 王斌 . 思茅松标准树高曲线的研究[J]. 西南林学院学报, 2000(2):74-77.
[18] 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.
[19] 樊伟, 许崇华, 崔珺 , 等. 基于混合效应的大别山地区杉木树高-胸径模型比较[J]. 应用生态学报, 2017,28(9):2831-2839.
[20] 张懋功 . 云南年鉴[M]. 昆明: 云南年鉴社, 2017.
[21] 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.
[22] 马武, 雷相东, 徐光 , 等. 蒙古栎天然林单木生长模型的研究——Ⅱ.树高-胸径模型[J]. 西北农林科技大学学报:自然科学版, 2015,43(3):83-90.
[23] 曾伟生, 唐守正 . 立木生物量方程的优度评价和精度分析[J]. 林业科学, 2011,47(11):106-113.
[24] 董云飞, 孙玉军, 王轶夫 , 等. 基于BP神经网络的杉木标准树高曲线[J]. 东北林业大学学报, 2014,42(7):154-156.
[25] 董云飞, 孙玉军, 许昊 , 等. 基于非线性混合模型的杉木标准树高曲线[J]. 东北林业大学学报, 2014,42(11):72-76.
[26] 杜志, 甘世书 . 基于BP神经网络的杉木和马尾松树高曲线模型研究[J]. 中南林业调查规划, 2017,36(4):36-39.
[27] 高东启, 邓华锋, 程志楚 , 等. 基于度量误差模型方法建立的林分相容性树高曲线方程组[J]. 西北农林科技大学学报:自然科学版, 2015,43(5):65-70.
[28] 丁贵杰 . 马尾松人工林标准树高曲线模型的研究[J]. 浙江林学院学报, 1997(3):15-20.
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