北京松山自然保护区森林群落物种多样性及其神经网络预测

Abstract

物种多样性是群落结构和功能复杂性的一种度量,物种多样性的空间分布格局受许多环境因子的影响。运用多样性指数,多层感知器网络,分析了松山保护区森林群落物种多样性与群落类型、结构和生境之间的关系。结果表明:(1)大果榆+山杨混交林、油松+青杨混交林物种丰富度、多样性和均匀度均较高,而大果榆林、华北落叶松林的各项指数值均较低。Patrick指数和Shannon-Weiner指数在森林群落中均表现为草本层>灌木层>乔木层;Pielou指数在榆林中表现为草本层>乔木层>灌木层,而在其他森林群落中表现为灌木层>草本层>乔木层。(2)功能层物种多样性在海拔梯度上的变化趋势不同,在乔木层,丰富度、多样性和均匀度随海拔的升高逐渐降低;在灌木层,丰富度、多样性和均匀度均呈比较明显的单峰曲线变化趋势;在草本层,丰富度和多样性随海拔的升高都呈下降趋势,而在草本层,均匀度变化不大。(3)用多层感知器网络预测功能层多样性效果很好,结果发现坡向对乔木层和灌木层物种多样性的影响最大,而海拔高度对草本层物种多样性的影响最大。;Species diversity is a measure of the complexity of community structure and function, and the spatial distribution pattern of species diversity is affected by many environmental factors. In this paper, the relationships between species diversity and community type, habitat and community structure of forests in the Songshan National Nature Reserve were analyzed by diversity indices and multi-layer perceptron network. The dataset included 68 quadrats, 291 species, and 6 environmental variables (elevation, slope, aspect, litter layer thickness, soil depth, and soil solidity). The results showed that species richness, species diversity and evenness values of <em>Ulmus macrocarpa </em>+ <em>Populus davidiana</em> mixed forest and <em>Pinus tabulaeformis</em>+<em> Populus cathayana</em> mixed forest were higher, but these values of<em> Ulmus macrocarpa</em> forest and <em>Larix principis-rupprechtii</em> forest were lower. The Patrick and Shannon-Weiner indices varied in order of herb layer > shrub layer > tree layer; the Pielou value of <em>Ulmus pumila</em> forest varied in order of herb layer > tree layer >shrub layer, and other community types varied in order of shrub layer >herb layer > tree layer.<br>Species diversity of functional layers changed differently along elevational gradient. In tree layer, the species richness, diversity and evenness decreased with increasing elevation. In shrub layer, the species richness, diversity and evenness were significantly peaked at the intermediate elevation. In herb layer, the species richness and diversity decreased with increasing elevation, but the evenness value changed little.<br>Applying multi-perceptron network to predict the diversity of functional layers, we found that aspect affected species diversity of tree and shrub layers greatly, but elevation affected species diversity greatly in herb layer.