Comparison of Microbial Community Compositions of Two Subglacial Environments Reveals a Possible Role for Microbes in Chemical Weathering Processes
Bibliographic record
Abstract
Viable microbes have been detected beneath several geographically distant glaciers underlain by different lithologies, but comparisons of their microbial communities have not previously been made. This study compared the microbial community compositions of samples from two glaciers overlying differing bedrock. Bulk meltwater chemistry indicates that sulfide oxidation and carbonate dissolution account for 90% of the solute flux from Bench Glacier, Alaska, whereas gypsum/anhydrite and carbonate dissolution accounts for the majority of the flux from John Evans Glacier, Ellesmere Island, Nunavut, Canada. The microbial communities were examined using two techniques: clone libraries and dot blot hybridization of 16S rRNA genes. Two hundred twenty-seven clones containing amplified 16S rRNA genes were prepared from subglacial samples, and the gene sequences were analyzed phylogenetically. Although some phylogenetic groups, including the Betaproteobacteria, were abundant in clone libraries from both glaciers, other well-represented groups were found at only one glacier. Group-specific oligonucleotide probes were developed for two phylogenetic clusters that were of particular interest because of their abundance or inferred biochemical capabilities. These probes were used in quantitative dot blot hybridization assays with a range of samples from the two glaciers. In addition to shared phyla at both glaciers, each glacier also harbored a subglacial microbial population that correlated with the observed aqueous geochemistry. These results are consistent with the hypothesis that microbial activity is an important contributor to the solute flux from glaciers.
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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 | 0.001 | 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".