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采用指示种分析方法,研究了会同亚热带森林物种多样性和群落组成对森林管理的响应.从357个林下种中鉴定出显著性指示种94个,并构造新的指示种数据集,检验指示种数据集和源群落数据集之间的关联,评估指示种对林下植被管理效应的预测潜能.结果表明:指示种数据集和源群落数据集之间存在极显著的关联(Mantel r=0.898),指示种数据集很好地预测了生物多样性的变化(回归分析,R2>0.74);指示种很好地预测了群落组成对森林管理的响应(ANOVA,F>16.79);非度量多尺度排序(NMDS)以及K-means聚类分析表明,对于不同森林管理的样地类型,指示种数据集的识别能力和源群落数据集是一致的.从物种多样性、群落组成以及在森林类型的识别上,指示种数据集和源群落数据集有一致性规律,作用几乎相同,因此森林评估可以利用指示种代替源群落预测森林管理效应,以减少森林全面调查的成本.
The indicator species analysis method was used to study the response of species diversity and community composition to forest management in subtropical forests. 94 significant indicator species were identified from 357 understory species, and new indicator species data sets were constructed to test indications (Mantel r = 0.898) between the indicator dataset and the source community dataset, the correlation between the indicator dataset and the source community dataset was evaluated to evaluate the predictive potential of indicator species on the management effect of understory vegetation.The results showed that there was a significant correlation ), Indicating that the data set well predicts the change of biodiversity (regression analysis, R2> 0.74); indicating species well predicted the response of community composition to forest management (ANOVA, F> 16.79); non-metric NMDS and K-means clustering analysis showed that the identification ability of indicator datasets is consistent with that of source community datasets for different types of forest management plots.From the perspective of species diversity, community composition, , The indicator dataset and the source community dataset are consistent and almost the same. Therefore, the forest assessment can use the indicated species instead of the source community to predict the forest management effect to reduce the comprehensive forest survey the cost of.