Distinct Bacterial Communities Exist beneath a High Arctic Polythermal Glacier
Bibliographic record
Abstract
Bacterial communities reside in basal ice, sediment, and meltwater in the supra-, sub-, and proglacial environments of John Evans Glacier, Nunavut, Canada. We examined whether the subglacial bacterial community shares common members with the pro- and supraglacial communities, and by inference, whether it could be derived from communities in either of these environments (e.g., by ice overriding proglacial sediments or by in-wash of surface meltwaters). Terminal restriction fragment length polymorphism analysis of bacterial 16S rRNA genes amplified from these environments revealed that the subglacial water, basal ice, and sediment communities were distinct from those detected in supraglacial meltwater and proglacial sediments, with 60 of 142 unique terminal restriction fragments (T-RFs) detected exclusively in subglacial samples and only 8 T-RFs detected in all three environments. Supraglacial waters shared some T-RFs with subglacial water and ice, likely reflecting the seasonal flow of surface meltwater into the subglacial drainage system, whereas supraglacial and proglacial communities shared the fewest T-RFs. Thus, the subglacial community at John Evans Glacier appears to be predominantly autochthonous rather than allochthonous, and it may be adapted to subglacial conditions. Chemical analysis of water and melted ice also revealed differences between the supraglacial and proglacial environments, particularly regarding electrical conductivity and nitrate, sulfate, and dissolved organic carbon concentrations. Whereas the potential exists for common bacterial types to be broadly distributed throughout the glacial system, we have observed distinct bacterial communities in physically and chemically different glacial environments.
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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".