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林分空间结构参数N元分布及其诠释

张岗岗 刘瑞红 惠刚盈 张弓乔 赵中华 胡艳波

张岗岗, 刘瑞红, 惠刚盈, 张弓乔, 赵中华, 胡艳波. 林分空间结构参数N元分布及其诠释————以小陇山锐齿栎天然混交林为例[J]. 北京林业大学学报, 2019, 41(4): 21-31. doi: 10.13332/j.1000-1522.20180228
引用本文: 张岗岗, 刘瑞红, 惠刚盈, 张弓乔, 赵中华, 胡艳波. 林分空间结构参数N元分布及其诠释————以小陇山锐齿栎天然混交林为例[J]. 北京林业大学学报, 2019, 41(4): 21-31. doi: 10.13332/j.1000-1522.20180228
Zhang Ganggang, Liu Ruihong, Hui Gangying, Zhang Gongqiao, Zhao Zhonghua, Hu Yanbo. N-variate distribution and its annotation on forest spatial structural parameters: a case study of Quercus aliena var. acuteserrata natural mixed forest in Xiaolong Mountains, Gansu Province of northwestern China[J]. Journal of Beijing Forestry University, 2019, 41(4): 21-31. doi: 10.13332/j.1000-1522.20180228
Citation: Zhang Ganggang, Liu Ruihong, Hui Gangying, Zhang Gongqiao, Zhao Zhonghua, Hu Yanbo. N-variate distribution and its annotation on forest spatial structural parameters: a case study of Quercus aliena var. acuteserrata natural mixed forest in Xiaolong Mountains, Gansu Province of northwestern China[J]. Journal of Beijing Forestry University, 2019, 41(4): 21-31. doi: 10.13332/j.1000-1522.20180228

林分空间结构参数N元分布及其诠释

————以小陇山锐齿栎天然混交林为例

doi: 10.13332/j.1000-1522.20180228
基金项目: “十三五”国家重点研发计划项目(2016YFD0600203)
详细信息
    作者简介:

    张岗岗。主要研究方向:森林经营理论与技术。Email:zg201394@163.com 地址:100091北京市海淀区香山路东小府1号中国林业科学研究院林业研究所

    责任作者:

    惠刚盈,研究员,博士生导师。主要研究方向:森林经营。Email:hui@caf.ac.cn 地址:同上

  • 中图分类号: S758.5+3

N-variate distribution and its annotation on forest spatial structural parameters: a case study of Quercus aliena var. acuteserrata natural mixed forest in Xiaolong Mountains, Gansu Province of northwestern China

  • 摘要: 目的以甘肃省小陇山锐齿栎天然混交林为例,采用林分空间结构参数N元分布全面、系统地揭示林分空间结构特征,以实现森林结构信息的精确描述和直观表达,为森林结构精准调控和重建提供基础参考信息。方法对70 m × 70 m标准地内的林木进行每木定位和调查,采用Winkelmass计算每株林木的混交度(M)、角尺度(W)、大小比数(U)和密集度(C),借助Excel透视表统计N元分布相对频率,并采用R 3.4.3、Origin 2015绘制N元分布图。结果锐齿栎天然混交林整体及林分内大多数林木呈随机分布、混交良好、较为密集;林分整体中庸且各大小比数等级林木均接近20%;二元分布、三元分布和四元分布中该林分结构最突出特点表现为:不管结构参数如何组合,林分均表现出不同结构组合下大多数林木呈随机分布或混交良好。结论结构参数N元分布借助分布频率表达优势从不同层次和角度全面系统地描述了林分结构特征信息,且不同分布之间优势互补,实现了林分结构从“点→线→面→体→超体”的精准详尽解译;双X横坐标或双Y纵坐标的3D图满足了多元分布结构信息直观展现需求;N元分布为森林结构精准调控和林分结构重建提供了先决信息。

     

  • 图  1  林木分布

    不同实心圆●●●●●●●分别代表锐齿栎、山榆、华山松、辽东栎、太白槭、山核桃和其他树种,其大小代表林木胸径大小;空心圆代表冠幅大小。Different solid circles ●●●●●●● respectively represent Quercus aliena var. acuteserrata, Ulmus davidiana, Pinus armandii, Quercus wutaishanica, Acer caesium, Carya cathayensis and other species, and their size represents the DBH size. Different hollow circles represent the canopy size.

    Figure  1.  Tree distribution

    图  2  结构参数具体取值和生物学意义

    Figure  2.  Specific meanings of the W, M, U and C

    图  3  一元分布

    Figure  3.  Univariate distribution

    图  4  二元分布

    Figure  4.  Bivariate distribution

    图  5  三元分布

    Figure  5.  Trivariate distribution

    图  6  四元分布

    Figure  6.  Quadrivariate distribution

    表  1  主要树种概况

    Table  1.   General situation of main tree species

    树种 
    Tree species 
    蓄积/(m3·hm− 2)
    Volume/(m3·ha− 1)
    断面积/(m2·hm− 2)
    Basal area/(m2·ha− 1)
    平均胸径
    Mean DBH/cm
    平均树高
    Mean tree height/m
    密度/(tree·hm− 2)
    Density/(tree·ha− 1)
    锐齿栎 Quercus aliena var. acuteserrata120.1013.3928.6118.92208
    山榆 Ulmus davidiana37.234.3426.3618.78 80
    华山松 Pinus armandii14.451.8215.7012.02 94
    辽东栎 Quercus wutaishanica11.671.3630.7018.04 18
    太白槭 Acer caesium6.401.029.9611.13131
    山核桃 Carya cathayensis5.720.6837.6917.53 6
    其他树种 Other species27.954.3012.289.30363
    总计 Total223.5226.9119.5113.15900
    下载: 导出CSV

    表  2  结构参数N元分布比较

    Table  2.   Comparison of different N-variate distributions

    类别
    Type
    零元分布(均值)
    Zero variate distribution (average value)
    一元分布
    Univariate distribution
    二元分布
    Bivariate distribution
    三元分布
    Trivariate distribution
    四元分布
    Quadrivariate distribution
    几何形状
    Geometrical shape
    点 Point线 Line面 Plane体 Cube超体 Supercube
    结构组合
    Structural combination
    $\scriptstyle C_1^1 $ = 1$\scriptstyle C_5^1 $ = 5$\scriptstyle C_5^1 C_5^1 $ = 25$\scriptstyle C_5^1 C_5^1 C_5^1 $ = 125$\scriptstyle C_5^1 C_5^1 C_5^1 C_5^1 $ = 625
    结构信息量
    Quantity of structural information
    $\scriptstyle C_4^1 C_1^1 $ = 4$\scriptstyle C_4^1 C_5^1 $ = 20$\scriptstyle C_4^2 C_5^1 C_5^1 $ = 150$\scriptstyle C_4^3 C_5^1 C_5^1 C_5^1 $ = 500$\scriptstyle C_4^4 C_5^1 C_5^1 C_5^1 C_5^1 $ = 625
    特点
    Characteristics
    描述林分整体结构的平均状态;易于理解且计算简便;非常适于林分总体特征判断。
    Describing the average state of the overall forest structure; being easy to understand and calculate makes it very suitable to evaluate the overall characteristics of stand.
    刻画林分单方面结构特征;计算简易,图表展现非常直观;结果易于解释和应用;适于需要详细了解单方面结构信息的林分。
    Describing the unilateral characteristics of stand structure; its calculation is simple and graphing is intuitional, and its results could be easily explained and applied. It is very powerful for detailedly interpreting unilateral structural information.
    同时表征林分结构2方面结构特征;可推导出对应的两个一元分布及其平均值;图表展现多样,比较直观;适于详细同步分析林分某两方面结构信息,可操作性较强。
    Simultaneously characterize two aspects of stand structure; the corresponding two univariate distributions and their mean values could be derived. The results graphing are diverse and intuitive. It is suitable for simultaneously analyzing two aspects of structural information in detail.
    同时反映林分结构某3方面特征;可推导出3个二元分布、一元分布及其平均值;图表展现比较直观,信息量较大;适于详细同步分析林分结构的3个方面,针对性、实用性和可操作性较强。
    Simultaneously characterize three aspects of stand structure; three bivariate distributions, univariate distributions and their mean values can be derived. The result charts are intuitive and contain more information. It is suitable for detailedly interpreting three aspects of heterogeneous structural information, being highly specific, practical and feasible.
    全面量化林分结构4方面特征,是最详细完整的结构解译;可推导出6个二元分布,4个三元分布、一元分布及其平均值;图表内容详实,信息量最丰富;非常适于复杂林分的结构分析,尤其是适合林分结构全方位精准调整和重建。
    Comprehensively analyze four aspects of stand structure, being the most detailed and complete structural interpretation; six bivariate distributions, four trivariate distributions, univariate distributions and their mean values can be derived. The charts and graphs are detailed and informative. It is very suitable for the structural analysis of complex stands, especially for the adjustment and reconstruction of stand structures in all aspects.
    应用示例
    Application examples
    文献[8, 19-21]
    References
    [8, 19-21]
    文献[8, 19-21]
    References
    [8, 19-21]
    文献[12-13]
    References [12-13]
    文献[17]
    Reference [17]
    本文
    This article
    共同点
    Common
    points
    基于最近相邻木空间关系从林木大小、分布格局、是否异种和密集4个方面量化林分结构;借助UWMC4个结构参数的N元分布对林分结构“分而析之”,也即从不同角度、不同层次和深度精准解析林分结构,利于林分结构潜在问题的精准判定、精确量化、精细调整和采伐木的高效选择。
    Based on the spatial relationships among the nearest neighboring trees, the stand structure is quantified from four aspects: tree size, horizontal pattern, species diversity and crowding degree. N-variate distributions of the four structural parameters (U, W, M and C) can precisely characterize forest structure from different angles, levels and depths, which is conducive to the accurate determination, precise quantification, and fine adjustment of the potential problems of stand structure and the effective selection of cutting wood.
    联系和
    区别
    Connection
    and distinction
    N元分布是N-一元分布的逐步细化;基于垂直投影降维和边际分布函数可对四元分布→三元分布→二元分布→一元分布→零元分布(均值)“合而求之”,但该递推过程不可逆;不同分布之间优势互补,联合效应类似“1 + 1 > 2”。
    N-variate distribution is the stepwise refinement of N-1-variate distribution. Based on the vertical projection dimensionality reduction and marginal probability distribution function, it is possible to realize the stepwise recurrence from the quadrivariate distribution to zero variate distribution (mean value), but the recursive process is not reversible. Different N-variate distributions are complementary to each other, and their combined use has better effects, similar to “1 + 1 > 2”.
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-07-12
  • 修回日期:  2019-03-15
  • 网络出版日期:  2019-04-02
  • 刊出日期:  2019-04-01

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