A dataset of monthly recovery amount of litter fall production in a monsoon evergreen broad-leaved forest at Dinghushan (1999 – 2016)

As a link between plant community and soil, litterfall plays an important role in matter cycling, energy flow and message delivery in forest ecosystems. It is an important structural and functional unit in material cycle and energy flow of forest ecosystems. Therefore, accurate determination of litterfall production in forest ecosystem serves as the basis for related research work. As a core member of Chinese Ecosystem Research Network (CERN) and National Ecosystem Research Network of China (CNERN), Dinghushan Forest Ecosystem Research Station has monitored litter return of main forest types in low subtropical China since its establishment. The gathering work has been done towards the standardization procedure after experiencing a sporadically gathering period in the first years. Among the main forest types, monsoon evergreen broad-leaved forest is a typical zonal forest in this region. According to the unified technical specifications of CERN, 15 litter traps were installed randomly on 15 plots within the permanent site to collect monthly amount of litter fall production. After sorting out and statistically analyzing the data, we obtained the dataset. The dataset presented monthly dynamic measurements of litter components (branches, leaves, flowers, fruits, bark, moss, lichens and debris) return in the monsoon evergreen broad-leaved forest from 1999 to 2016 at Dinghushan. The dataset also included the information on the process of dataset construction. Creating and sharing the dataset can help provide basic data for deep studies on the vegetation structure and ecosystem function responding to the changes of global hydrothermal pattern, supporting forest management and ecosystem function assessment in this region.