九寨沟水生植物群落β多样性特征研究
STUDIES ON THEβDIVERSITY ANALYSES OF AQUATIC PLANT COMMUNITY IN JIUZHAIGOU
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摘要: 通过典型样地调查,运用β多样性的Wilson-Shmida指数(βT)和Bray-Curtis指数(CN)分别对九寨沟水生植物群落进行测度。结果显示,九寨沟水生维管植物种类共有75种,主要群落类型有11种,以挺水植物群落类型为主,兼有少量的沉水植物群落。β多样性测度表明,样地间种类组成随海拔梯度及其他因子的变化差异比较明显,CN1、CN2和CNN3的数量数据测度结果有差异,以重要值为基础的CN3指数具有较强的综合性和稳定性。海拔梯度和空间聚类分析表明,海拔梯度是影响水生植物群落β多样性变化的主要因子,随着海拔升高和落差的增大,β多样性变化明显,种类组成变化愈显著。同时,β多样性数量数据可以划分成四种类型,Ⅲ型的非海拔梯度因子作用结果说明流域特征和群落类型会对多样性的变化产生一定影响。Abstract: To protect the ecological environment and aquatic plant resources in Jiuzhaigou where is famous for its beautiful water scape and virgin forest, it is very important for us to study on the aquatic plant community diversity and the relationship between the βdiversity change and environment gradients.On the foundation of general quadrats investigation and study, this paper applied the Wilson Shmida Index (βT-(to calculate the binary data-and Bray Curtis Index ( CN-(to calculate the numerical data-to measure the βdiversity of aquatic plant community in Jiuzhaigou.In this paper, we respectively used the species number, relative coverage and important value as the numerical data to calculate CN.The primary statistic results showed that there are 75 species (including 23 families, 41 genera-of aquatic vascular plant and 11 types of aquatic plant communities in Jiuzhaigou.The difference of species composition variety as the altitude alters and other factors happens obviously, and the measurement of CN3 whose CN based on important value had better characteristics of synthesis and stability than others.Through analyzing the altitude alters on βdiversity, we found that altitude gradients are the main factors to affect the βdiversity of aquatic plant community.Along with the altitude rise, the change trend of βdiversity index between the first quadrat and each of others come to be one valley (βT-or one peak ( CN), and the two adjacent quadratspcome to be two valleys (βT-or two peaks ( CN).At the same time, the spatial cluster can be spplied on analyzing the βdiversity variety and its effect factors.Spatial cluster analysis results made it chear that the numerical data of βdiversity ( CN3-can be divided into 4 types.Type Ⅰ, Ⅱand Ⅳall belong to the sensitive clusters whose comparability of communities descends when the altitude height rises, and this conclusion showed the altitude gradientps dominant effect to the βdiversity variety.On the other hand, Type Ⅲwhich resulted fromthe factors of non-altitude gradient revealed that the valley character and community type partial effects to the variety of βdiversity.