Soil is a fundamental component of forest ecosystems, providing essential water and nutrients for plant growth and functioning as a crucial medium for various physical, chemical, and biological processes. The Dinghushan National Nature Reserve, located in the South Subtropical Zone of China, is characterized by rich ecosystem diversity and represents a typical region that is highly sensitive to global environmental changes. As such, it has become a hotspot for extensive ecological research. The predominant soil types in the region include lateritic red soil and mountain yellow soil, both developing on sandstone and shale, as well as mountain shrub meadow soil. In recent years, the study of soil chemical element composition in this region has gained increasing attention. To deepen the understanding of soil element dynamics and their responses to global changes in South Subtropical forests, this dataset compiles long-term observational data from the Dinghushan Forest Ecosystem National Field Observation and Research Station, spanning from 2000 to 2020. The sampling sites encompass three vegetation types ascross different successional stages: Pinus massoniana coniferous forest, mixed Pinus massoniana broad-leaved forest, and monsoon evergreen broad-leaved forest. The primary observation indicators include annual measurements of trace elements in surface soils (including available B, Mo, Mn, Zn, Cu, Fe and S), decadal assessments of trace elements (including total B, Mo, Mn, Zn, Cu, Fe and Se) and heavy metal elements (including Co, Cd, Pb, Cr, Ni, Hg and As) in soil profiles. All samples were collected from fixed sampling locations and analyzed in the laboratory using standardized experimental protocols. To ensure the accuracy and reliability of the data, the quality of the dataset was controlled and evaluated in multiple links such as sample collection, experimental analysis and historical data comparison during the research process. The establishment and public sharing of this dataset will provide valuable long-term data to improve regional soil property databases, support monitoring systems for soil quality in subtropical forest ecosystems, enhance forest ecosystem research networks, refine ecological process models, and inform regional environmental management strategies.
DENG et al. (2026) studied this question.