中国生态系统研究网络(Chinese Ecosystem Research Network,CERN)生物长期样地背景和植被分类特征本底数据集是22个CERN自然生态系统生态站95个长期样地的本底数据的综合集成。基于对CERN生态站长期样地地理位置、建立时间、面积、样地代表性等背景信息的梳理,依据样地建立之初的植物群落调查数据,参照最新的中国植被分类系统,对每个样地植物群落所属的植被型组、植被型、植被亚型进行了明确划分,并依据每个样地的优势种名单,对样地植被所属群系和群丛进行了鉴定和命名。本数据集构建通过了多轮的专家审核-台站核查-专家复审-台站接受等过程,包含生态站代码、生态站名称、样地代码、样地名称、样地类别、样地代表性、地理位置、海拔高度、样地面积及形状、样地建立时间和设计使用年数、植被型组、植被型、植被亚型、群系、群丛、优势种等信息。本数据集可以为植物区系、植被资源分布、生物多样性保护等方面的研究提供基础数据支持。
Types and structure of plant communities in the Yellow River Delta were investigated by using detrended canonical correspondence analyses （DCCAs） and a two-way indicator species analysis （TWINSPAN）. The distribution pattern and influential factors of the plant communities were also analyzed by testing elevation, slope, soil characteristics, longitude and latitude of 134 vegetation samples collected by representative plot sampling methods. Results showed that all the 134 vegetation samples could be divided into seven vegetation groups, separately dominated by Robinia pseucdoacacia, Imperata cylindrical, Miscanthus saccharifleus, Suaeda salsa, Aeluropus sinensis, Phragmites australis and Tamarix chinensis. The vegetation distribution pattern was mainly related to elevation, ground water depth and soil characteristics such as salinity and soluble potassium. Among the factors affecting distribution pattern of the plant communities, the species matrix explained by non-spatial environmental variation accounts for 45.2% of total variation. Spatial variation and spatial-structured environmental variation explain 11.8%, and 2.2%, respectively. Remained 40.8% of undetermined variation is attributed to biological and stochastic factors.
