Distinct bacterial assemblages reside at different depths in Arctic multiyear sea ice
Bibliographic record
Abstract
Bacterial communities in Arctic sea ice play an important role in the regulation of nutrient and energy dynamics in the Arctic Ocean. Sea ice has vertical gradients in temperature, brine salinity and volume, and light and UV levels. Multiyear ice (MYI) has at least two distinct ice layers: old fresh ice with limited permeability, and new saline ice, and may also include a surface melt pond layer. Here, we determine whether bacterial communities (1) differ with ice depth due to strong physical and chemical gradients, (2) are relatively homogenous within a layer, but differ between layers, or (3) do not vary with ice depth. Cores of MYI off northern Ellesmere Island, NU, Canada, were subsectioned in 30-cm intervals, and the bacterial assemblage structure was characterized using 16S rRNA gene pyrotag sequencing. Assemblages clustered into three distinct groups: top (0–30 cm); middle (30–150 cm); and bottom (150–236 cm). These layers correspond to the occurrence of refrozen melt pond ice, at least 2-year-old ice, and newly grown first-year ice at the bottom of the ice sheet, respectively. Thus, MYI houses multiple distinct bacterial assemblages, and in situ conditions appear to play a less important role in structuring microbial assemblages than the age or conditions of the ice at the time of formation. Arctic sea ice that has survived at least one summer has several different bacterial communities, corresponding to the age or origin of the ice. Arctic sea ice that has survived at least one summer has several different bacterial communities, corresponding to the age or origin of the ice.
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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 | 0.000 |
| 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".