Data · dataset · 2025
Responses of soil properties and bacterial communities to forest stand structure
Listed in Teesside University Research Data Repository
This study selected three ecologically and economically important stand types in northern my country: Robinia pseudoacacia, Pinus tabulaeformis, and mixed Robinia pseudoacacia and Pinus tabulaeformis forests.
Description
Focusing on soil properties and soil bacterial communities, the study measured the structural characteristics (both spatial and non-spatial) of the three stand types, analyzed the corresponding soil physicochemical properties, and elucidated the bacterial community structure using high-throughput sequencing.
Multivariate statistical analysis and structural equation modeling were then used to integrate and analyze the data, revealing the mechanisms by which soil properties and bacterial communities respond to stand structure. This study integrates stand spatial and non-spatial structure into a single framework, systematically exploring their synergistic effects on the belowground soil-microbial ecosystem and providing a more comprehensive understanding.
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Beyond focusing on correlations, the study utilized structural equation modeling (SEM) to reveal the specific driving pathways and cascading effects (particularly indirect effects) of stand structure in influencing soil properties and bacterial communities, further elucidating the underlying mechanisms. The results provide a key scientific basis for forest cultivation practices aimed at multifunctional goals (such as enhancing biodiversity and system stability, accelerating soil fertility improvement, and strengthening ecosystem resilience), particularly through optimizing stand structure configuration and regulation to achieve these goals.
Links
Where it is published
- DOI doi.org/10.17632/v3zp9g9mnz.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science
- Inferred from text
- Sequencing 75%
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/v3zp9g9mnz.1 | 17 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:sequencing | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |