生物多样性 ›› 2016, Vol. 24 ›› Issue (3): 280-286.DOI: 10.17520/biods.2015237

• • 上一篇    下一篇

林木分布格局多样性测度方法: 以阔叶红松林为例

惠刚盈*(), 张弓乔, 赵中华, 胡艳波, 白超   

  1. 中国林业科学研究院林业研究所, 国家林业局林木重点培育实验室, 北京 100091
  • 收稿日期:2015-09-17 接受日期:2015-11-02 出版日期:2016-03-20 发布日期:2016-04-05
  • 通讯作者: 惠刚盈
  • 基金资助:
    “十二五”国家科技支撑课题“西北华北森林可持续经营技术研究与示范” (2012BAD22B03)

Measuring diversity of tree distribution patterns in natural forests

Gangying Hui*(), Gongqiao Zhang, Zhonghua Zhao, Yanbo Hu, Chao Bai   

  1. Key Laboratory of Tree Breeding and Cultivation of the State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091
  • Received:2015-09-17 Accepted:2015-11-02 Online:2016-03-20 Published:2016-04-05
  • Contact: Hui Gangying

摘要:

林木分布格局是森林结构的重要组成部分, 直接影响森林生态系统的健康与稳定, 维持森林结构多样性被认为是保护生物多样性的最佳途径。本研究探讨了林木分布格局多样性的测度方法, 以期为揭示森林结构多样性提供理论依据。格局多样性研究的关键在于选择合适的生物多样性测度方法和具有分布属性的格局指数。本研究通过统计角尺度分布频率和Voronoi多边形边数分布频率, 运用Simpson指数分别计算角尺度多样性和Voronoi多边形边数分布多样性, 作为表达林木分布格局多样性指数的方法, 并以我国东北吉林蛟河的3个100 m × 100 m的阔叶红松(Pinus koreansis)林长期定位监测标准地为例, 分析了林木分布格局的多样性。结果表明: 无论是角尺度分布还是Voronoi多边形的边数分布都接近正态分布, 角尺度分布中随机分布林木的频数最多, 占55%以上; Voronoi多边形的类型多达10个以上, 50%以上的林木有5-6株最近相邻木。利用Simpson指数衡量林木格局多样性, 角尺度分布与Voronoi多边形的边数分布都显示出聚集分布的林分比随机分布林分的格局多样性高。研究还发现, 两种格局判定方法得出的Simpson指数值有所不同, 角尺度分布的多样性数值明显低于Voronoi多边形的边数分布的多样性数值, 主要原因是二者的等级数量不同。可见, 林木分布格局多样性研究应选择具有分布属性的格局指数, 但由于各指数反映的角度不同, 所以在分析比较不同林分格局多样性时应采用相同的分析方法。

关键词: 分布格局多样性, 角尺度分布, Voronoi多边形边数分布, Simpson指数

Abstract

Patterns of tree distribution are an important part of forest structure and directly affect the health and stability of forest ecosystems. Maintaining and preserving forest structural diversity has often been considered the best way to protect biodiversity. One method measuring the diversity of tree distribution patterns was discussed in this paper in order to provide a theoretical basis for the expression of forest structure diversity. The key to the study of distribution pattern diversity is to select the appropriate biodiversity measuring method and index which has a distributed attribute. In this paper, we put forward a method to express tree distribution pattern diversity which counted the distributions frequency of uniform angle index and Voronoi polygon side, and calculate uniform angle index diversity and Voronoi polygon side distribution diversity by the Simpson index, respectively. The distribution pattern diversity of three long-term monitoring Pinus koreansis broad-leaved forest plots (area = 100 m × 100 m) in northeastern China was analyzed by this method. The results showed that both of the distribution of uniform angle index and the Voronoi polygon side were close to the normal distribution. The frequency of randomly distributed trees was the maximum and more than 55% in the uniform angle index distribution; the type of Voronoi polygon side was great than 10 and over 50% of the trees had 5-6 closest neighboring trees. The result of using the Simpson index to analyze tree distribution pattern diversity showed that the tree distribution pattern diversity was higher in the cluster distribution stand than the random distribution stand. We also found that Simpson index values were different when different distribution pattern diversity methods were used, and the uniform angle distribution diversity was significantly lower than that of the Voronoi polygon side distribution diversity, which mainly due to the different quantity grade of each index. Therefore, study on the diversity of forest distribution pattern should choose distribution pattern indices with distribution attribute. The uniform angle index distribution and Voronoi polygon side distribution used in this paper had this attribute, however, different indices reflected different aspects of distribution pattern, so the same pattern analysis method should be used in the analysis and comparison of distribution pattern diversity of different forest stands.

Key words: distribution pattern diversity, uniform angle index distribution, Voronoi polygon side distribution, Simpson index