生物多样性 ›› 2004, Vol. 12 ›› Issue (3): 354-360.doi: 10.17520/biods.2004043

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森林群落复杂性分析: 以广东黑石顶森林为例

覃林, 余世孝*   

  1. (中山大学生命科学学院,广州 510275)
  • 收稿日期:2003-11-04 修回日期:2004-02-28 出版日期:2004-05-20
  • 通讯作者: 余世孝

Complexity of forest communities:a case study of three different forest types in Heishiding Nature Reserve, Guangdong

QIN Lin, YU Shi-Xiao*   

  1. School of Life Sciences,Sun Yat-sen University,Guangzhou 510275
  • Received:2003-11-04 Revised:2004-02-28 Online:2004-05-20
  • Contact: YU Shi-Xiao

本文将森林群落复杂性定义为消除群落中任意一个树木个体的种名及层次不确定性所需的平均信息量,提出用联合熵H(X,Y)测度群落复杂性。H(X,Y)=H(X)+H(Y|X),其中H(X)=-∑[DD(]S[]i=1[DD)][SX(]ni[]N[SX)]log2([SX(]ni[]N[SX)]),H(Y|X)=-∑[DD(]S[]i=1[DD)][SX(]ni[]N[SX)]∑[DD(]4[]j=1[DD)][SX(]nij[]ni[SX)]log2([SX(]nij []ni[SX)]),分别为树种组成复杂性和树种结构复杂性。式中S为森林群落树种数,N为森林群落的树木总株数,ni(i=1,2,…,S)为第i个树种的株数,nij(j=1,2,3,4)为第i个树种在第j层次的株数。用联合熵分析了广东省封开县黑石顶自然保护区针叶林、针阔混交林和常绿阔叶林等3种典型森林类型的复杂性。结果表明,群落复杂性的顺序为:常绿阔叶林>针阔混交林>针叶林。同时,各森林类型的群落复杂性H(X,Y)与取样尺度之间具有较好的分形关系。

The complexity of a forest community is defined as having the average amount of its information by eliminating the uncertainties of species and layers of a tree individual randomly selected from all trees in the forest community. The joint entropy H(X,Y) is proposed to measure the complexity of a forest community H(X,Y)=H(X)+H(Y|X), in which H(X)=-∑[DD(]S[]i=1[DD)][SX(]ni[]N[SX)]log2([SX(]ni[]N[SX)]) and H(Y|X)=-∑[DD(]S[]i=1[DD)][SX(]ni[]N[SX)]∑[DD(]4[]j=1[DD)][SX(]nij[]ni[SX)]log2([SX(]nij[]ni[SX)]), where S stands for the number of tree species (X), N for the total number of individuals in the forest community, ni for the number of the ith tree species, and nij ?for the number of the ith tree species in the jth layer. H(X) is defined as the compositional complexity of tree species and H(Y|X) as the structural complexity of tree species. The higher the H(X,Y) value, the greater the complexity in the forest community. A case study is presented based on the survey data from three types of forest communities in Heishiding Nature Reserve, Guangdong Province. Three sampling plots were established, each with a size of 60 m×60 m, representing coniferous forest, mixed coniferous broadleaved forest and evergreen broadleaved forest. Each plot was divided into 36 quadrats with a size of 10 m×10 m. The data for all trees with DBH1 cm were gathered, including their coordinates in the sampling plots. Tree sizes were divided into four categories based on their DBH: DBH1, 5, 10, and 30 cm. Using computer simulation, 13 types of quadrat sizes (12 m×12 m, 16 m×16 m, …, 60 m×60 m) within a plot were objectively selected based on the method of nested quadrat sampling. The results show that the order of H(X,Y) of three typical forest types is as follows: evergreen broadleaved forest > mixed coniferous broadleaved forest > coniferous forest. At the same time, the fractal relationships between H(X,Y) and sampling size among the three forest types reveal that H(X,Y) has a statistical selfsimilarity feature.

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