2026-10-14T15:07:28Z https://www.scidb.cn/oai

10.11922/sciencedb.j00001.00175 2020-11-20T10:12:25Z

2020-11-20 A dataset of water content of litter in typical forest ecosystems of Dinghushan (2012-2018) doi:10.11922/sciencedb.j00001.00175 en Water content of litter is one of the important components in the hydrological cycle of forest ecosystem and plays a key role in the hydrological processes such as soil evaporation, water infiltration and runoff generation at the interface of surface soil. The type, composition and the degree of decomposition of litter are important factors affecting the water content of litter. Water content of litter has been listed as one of the hydrologic factors in the long-term positioning observations of forest ecosystem experimental stations by the Chinese Ecosystem Research Network (CERN), providing a solid foundation for the study of the temporal dynamics of hydrological processes in major types of ecosystems in China. Dinghushan Forest Ecosystem Research Station (hereafter referred to as Dinghushan Station) strictly follows the observation requirements of CERN, standardizing the monitoring of water content of litter and accumulating a large number of data. The Pinus massoniana coniferous forest (PF), mixed Pinus massoniana broad-leaved forest (MF), and monsoon evergreen broad-leaved forest (MEBF) are typical forest types in the south subtropical regions in China. This dataset publicly reported long-term observation data of litter water content of three typical forest types in Dinghushan from 2012 to 2018, aiming to deeply reveal the ecological and hydrological effects of typical forest vegetation in this region, and provide data support for quantitative research and service evaluation of hydrological regulation of different forest ecosystems. water content of litter; eco-hydrology; representative vegetation; Dinghushan Liu peiling Zhang qianmei Liu Xiaodong Liu Shizhong Chu Guowei Zhang Deqiang Mengze PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.11922/csdata.2020.0084.zh Science Data Bank