Microbial community structure and diversity within hypersaline Keke Salt Lake environments
Bibliographic record
Abstract
Keke Salt Lake is located in the Qaidamu Basin of China. It is a unique magnesium sulfate-subtype hypersaline lake that exhibits a halite domain ecosystem, yet its microbial diversity has remained unstudied. Here, the microbial community structure and diversity was investigated via high-throughput sequencing of the V3–V5 regions of 16S rRNA genes. A high diversity of operational taxonomic units was detected for Bacteria and Archaea (734 and 747, respectively), comprising 21 phyla, 43 classes, and 201 genera of Bacteria and 4 phyla, 4 classes, and 39 genera of Archaea. Salt-saturated samples were dominated by the bacterial genera Bacillus (51.52%–58.35% relative abundance), Lactococcus (9.52%–10.51%), and Oceanobacillus (8.82%–9.88%) within the Firmicutes phylum (74.81%–80.99%), contrasting with other hypersaline lakes. The dominant Archaea belonged to the Halobacteriaceae family, and in particular, the genera (with an abundance of >10% of communities) Halonotius, Halorubellus, Halapricum, Halorubrum, and Natronomonas. Additionally, we report the presence of Nanohaloarchaeota and Woesearchaeota in Qinghai–Tibet Plateau lakes, which has not been previously documented. Total salinity (especially Mg 2+ , Cl – , Na + , and K + ) mostly correlated with taxonomic distribution across samples. These results expand our understanding of microbial resource utilization within hypersaline lakes and the potential adaptations of dominant microorganisms that allow them to inhabit such environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".