As an important ground cover of forest ecosystems, the litter layer plays a significant role in hydrological cycle of these systems. Different vegetation types exhibit varying water-holding capacities in their litter layers, and the water content of litter layer is crucial for the fulfillment of its ecological functions. The water content of the litter layer is a key indicator in the long-term monitoring of water environments in terrestrial ecosystem of Chinese Ecosystem Research Network (CERN). This dataset presents the water content of the litter layer of four typical forest types in Xishuangbanna from 2017 to 2023, which contains tropical seasonal rain forest, tropical secondary forest, limestone monsoon forest, and secondary evergreen broad-leaf forest. The dataset comprises a total of 2,220 entries, with measurements taken using the drying method and an observation frequency of once per month. The observation protocol follows the requirements for litter layer moisture content observation in forest ecosystems as specified in the Chinese Ecosystem Research Network (CERN) Long-term Observation Specifications. After data collection and entry, the completeness, accuracy, and consistency of the data were verified before use. This dataset provides foundational data support for evaluating the eco-hydrological effects and service functions of typical tropical forest vegetation.
LUO et al. (Sun,) studied this question.