Abstract

The fixed sample plot investigation obtains the dynamic characteristics of ecosystem through long-term data accumulation and accurate space-time comparison, which provides a solid basis for long-term ecosystem research. In accordance with the unified monitoring specifications set forth by the Chinese Ecosystem Research Network (CERN), Dongting Lake Wetland Ecosystem Research Station conducts long-term positioning monitoring on the species composition and community characteristics of typical beach vegetation in the wetland ecosystem in response to the changing hydrological conditions of Dongting Lake. We processed the data of long-term monitoring sample plots of three typical wetland plant communities (Carex sp, Miscanthus lutarioriparius and Polygonum hydropiper) in Dongting Lake to obtain the dataset of sample survey of typical plant communities on East Dongting Lake beach from 2011 to 2015. This dataset covers a total of 14 indicators, including species name, Latin name, number of plants (clusters) (plants or clusters/quadrats), average height of leaf layer (cm), average height of reproductive branches (cm), coverage (%), phenological period, dominant species, number of plant species, density (plants or clusters/m2), leaf layer height (cm) of dominant species, reproductive branch height (cm) of dominant species, total coverage (%), and total dry weight of aboveground green parts (g/m2). This dataset comes with detailed background information to ensure its consistency across both spatial and temporal dimensions. Moreover, to ensure data accuracy and reliability, the dataset underwent comprehensive quality control throughout the entire process and is subject to expert review and verification. It can serve as an important source of background data for studying the process and succession trends of the beach wetland ecosystem in response to the hydrological conditions of Dongting Lake, and provide data support for vegetation remote sensing monitoring, biodiversity protection, wetland ecological restoration and adaptive management of Dongting Lake.

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