Diversity and distribution characteristics of myxobacteria in the rhizosphere and nonrhizosphere soils of the halophyte <i>Haloxylon ammodendron</i> in the high saline-alkaline Ebinur Lake Wetland
Bibliographic record
Abstract
This study employed Illumina HiSeq high-throughput sequencing technology to analyze the V4–V5 regions of myxobacterial 16S rRNA in rhizosphere and nonrhizosphere soils of Haloxylon ammodendron in the saline-alkaline wetland of Ebinur Lake, with the aim of investigating the community structure and diversity of myxobacteria. Results indicated that myxobacterial communities in rhizosphere soils exhibited greater diversity and richness compared to nonrhizosphere soils. Soil physicochemical properties, particularly moisture content, were identified as key environmental factors influencing myxobacterial diversity. The halotolerant genus Haliangium was found to be predominant under saline-alkaline conditions. Additionally, myxobacteria demonstrated distinct ecological specificity and environmental adaptability between rhizosphere and nonrhizosphere soils. For example, the genus Enhygromyxa exhibited a negative correlation with soil moisture content in rhizosphere soils but a positive correlation with soil electrical conductivity in nonrhizosphere soils. Co-occurrence network analysis revealed complex interaction patterns among myxobacterial genera and other bacterial genera, with closer interactions observed in rhizosphere soils. This study highlights the importance of environmental factors in regulating microbial community structure and function in saline-alkaline wetlands, providing new insights into the ecological roles and interaction mechanisms of myxobacteria within the ecosystem.
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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 | 0.000 | 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".