Diversity and community structure of ammonia-oxidizing archaea in rhizosphere soil of four plant groups in Ebinur Lake wetland
Bibliographic record
Abstract
The aim of this study was to reveal the differences in the community structure of ammonia-oxidizing archaea (AOA) between rhizosphere and non-rhizosphere soil, to provide a theoretical basis for further study on the relationship between halophyte rhizosphere soil microorganisms and salt tolerance. The results of diversity and community structure showed that the diversity of the AOA community in rhizosphere soil of Reeds was higher than that in non-rhizosphere soil in spring and lower than that in non-rhizosphere soil in summer and autumn. In summer, the diversity of rhizosphere soil of Karelinia caspica was higher than that of non-rhizosphere soil and lower than that of non-rhizosphere soil in spring and autumn. The diversity of rhizosphere soil of Halocnemum strobilaceum in 3 seasons was lower than that in non-rhizosphere soil. The diversity of rhizosphere soil of Salicornia was higher than that in non-rhizosphere soil in 3 seasons. In addition, the relative abundance of AOA in rhizosphere soil of 4 plants was higher than that in non-rhizosphere soil. The AOA community in all soil samples was mainly concentrated in Crenarchaeota and Thaumarchaeota. Redundancy analysis results showed salinity, soil water moisture, pH, and soil organic matter were important factors affecting the differentiation of AOA communities.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".