Trampling to biocrusts declined soil microbial biomass and altered soil microbial communities in desert ecosystems
Bibliographic record
Abstract
Biocrusts occupy soil surface, house key microbes, and further provide other vital ecological functions in oligotrophic drylands. Exploring the impacts of trampled biocrusts on microbial communities can provide important information about ecosystem processes in desert areas. For this, fresh soils from three trampled intensities to biocrusts were sampled in vegetation areas of the Tennger Desert. Soil microbial biomass and microbial communities were studied using chloroform fumigation and Illumina sequencing, respectively. The results collected 393 species of bacterial communities and 135 species of fungal communities. Severe trampling of biocrusts resulted in a reduction in MBC and MBN, and soil microbial abundance and diversity; changed the relative abundance of microbial taxa; altered the soil microbial community structures of cyanobacteria-dominated crusts, and further affected microbial community functions. Reduced soil moisture and nutrients and enhanced pH were the key factors which caused alteration in soil microbial communities after trampled biocrusts. Additionally, there was a negative correlation between trampling intensity with soil nutrient content, microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and microbial abundance. After similar trampling intensity, moss-dominated crusts were significantly higher in soil nutrients, MBC, MBN, soil fungal abundance and diversity, and more distinctive microbial community structures compared to cyanobacteria-dominated crusts. This suggests that there is a positive correlation between biocrust tolerance to trampling and the successional stages of biocrusts. Therefore, severe-trampled biocrusts could modify biocrust fragile structures and functions, alter soil microbial community compositions and structures, discourage their function, and further lead to a degradation process of surface soils in temperate desert ecosystems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".