Long-term protection in grasslands enhances soil carbon storage via reduced disturbance and community trait diversity-environment adaptations
收藏DataONE2026-01-15 更新2026-01-24 收录
下载链接:
https://search.dataone.org/view/sha256:27f6087368f2aa558b4fcfbfe47b2d11711470bf1c6458a8dbecd582eef49fa4
下载链接
链接失效反馈官方服务:
资源简介:
Understanding how ecological disturbance and plant community traits regulate soil carbon storage is critical for predicting ecosystem feedbacks to global change and designing sustainable land-use strategies. However, the processes by which disturbance regimes mediate the trade-offs between species preservation and soil carbon storage are difficult to predict due to their complexity and remain debated, particularly in comparison to protected systems.
We employed a paired-site design, sampling 30 long-term managed grasslands and their paired nature reserve counterparts across a gradient of three grassland types (wet, mesic, and dry) in Central Europe (Czechia). At each site, we quantified soil carbon stocks, characterized soil chemical properties, measured aboveground biomass production, and assessed plant community composition through species diversity and functional trait analyses.
We found that protected grasslands store significantly more carbon than their conventionally managed count..., , # Long-term protection in grasslands enhances soil carbon storage via reduced disturbance and community trait diversity-environment adaptations
Dataset DOI: [10.5061/dryad.jq2bvq8q7](https://doi.org/10.5061/dryad.jq2bvq8q7)
## Description of the data and file structure
This dataset was generated as part of a study investigating the effects of long-term ecological protection versus conventional management on soil carbon storage, biodiversity, and ecosystem functioning in Central European grasslands.
The research employed a paired-site design across 30 grassland pairs (60 sites total) in the Czech Republic. Each pair consisted of one long-term protected grassland (Nature Reserve) and one neighboring commercially managed grassland, stratified across three moisture-based vegetation types: Dry, Mesic, and Wet. Data collection took place during the 2024 season.
The dataset integrates field measurements of soil properties (carbon stocks, nitrogen, pH, electrical conductivity), aboveground...,
创建时间:
2026-01-16



