Soil moisture dataset for typical vegetation types in the Ailao Mountains from 2006 to 2024

Soil moisture content is a key component of long-term forest ecosystem monitoring, essential for revealing forest water cycling processes, assessing water conservation functions, and understanding their effects on ecosystem structure and function. Subtropical forests, the most widely distributed forest type in China, play a critical role in global climate regulation and biodiversity conservation. The Ailao Mountains in Yunnan, as a typical subtropical evergreen broad-leaved forest region, are characterized by rich biodiversity and notable water conservation capacity. Based on long-term monitoring within the Chinese Ecosystem Research Network (CERN), this dataset compiles soil quality moisture content data from 2006 to 2024 across three vegetation types in the Ailao Mountains: summit mossy dwarf forest, Populus forest, and evergreen broad-leaved forest. Measurements were conducted manually at a frequency of once per month, in accordance with CERN protocols. The dataset reflects soil moisture content dynamics under different vegetation types in response to seasonal variations and extreme climate conditions, providing essential data to support hydrological model optimization, water conservation assessments, forest ecosystem climate change response predictions, and the development of forest management and ecological protection strategies.