Microbial consortia controlling biogenic gas formation in the Qaidam Basin of western China
Bibliographic record
Abstract
Abstract Knowledge of what controls the activity of subsurface microbial communities is critical for assessing and managing biogenic methane resources. In this study, 19 formation waters and five gas samples were collected at depths of 800 to 1900 m from Quaternary biogenic gas fields of the Qaidam Basin, China. The formation waters were brines with chloride (Cl) concentrations from 1200 to 2700 mM. Bacterial 16S rRNA gene copies ranged from 3.75 × 104 to 2.23 × 106 copies mL−1 of water, and those of archaea ranged from 2.44 × 103 to 4.66 × 107 copies mL−1 of water. Both bacterial and archaea 16 s rRNA gene copies were negatively correlated with Cl concentration. The microbial community structure differed significantly depending on Cl concentrations. At high Cl waters (>1800 mM), the microbial community showed a halophilic signature made up of several abundant taxonomic groups within Firmicules, γ‐Proteobacteria, and methylotrophic Methanosarcinales. At low Cl, Firmicules and hydrogenotrophic methanogens were dominant members. The proportion of inferred hydrogenotrophic methanogens decreased from 89% to 14% of total archaeal reads with increasing Cl concentration; in contrast, methylotrophic species increased from 11% to 85%. Given that the proportion of hydrogenotrophic species was positively correlated with the archaeal gene abundances, we suggest that Cl concentrations primarily constrain the activity of archaea catalyzing H2 reduction of CO2. Our results show that dilution of formation waters is critical in the process of biogenic gas formation, suggesting that an engineered decrease in Cl concentrations may induce methanogenesis as a potential method to increase gas reserves in such areas in the future.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".