Short-term variability in bacterial abundance, cell properties, and incorporation of leucine and thymidine in subarctic sea ice
Bibliographic record
Abstract
Sea ice is a biome of immense size and provides a range of habitats for diverse microbial communities, many of which are adapted to living at low temperatures and high salinities in brines. We measured simultaneous incorporation of thymidine (TdR) and leucine (Leu), bacterial cell abundance and cell population properties (by flow cytometry) in subarctic sea ice in SW Greenland. Short-term temporal variability was moderate, and steep environmental gradients, typical for sea ice, were the main drivers of the variability in bacterial cell properties and activity. Low nucleic acid (LNA) bacteria, previously linked to oligotrophic ecotypes in marine habitats, were more abundant in the upper ice layers, whereas high nucleic acid (HNA) bacteria dominated in lower ice, where organic carbon was in high concentrations. Leu incorporation was saturated at micromolar concentrations, as known from freshwater and marine biofilm systems. Leu:TdR ratios were high (up to > 300) in lowermost ice layers, and when compared to published respiration measurements, these results suggest non-specific Leu incorporation. There was evidence of polyhydroxyalkanoate (PHA)-containing bacteria in the sea ice, shown by brightly fluorescing intracellular inclusions after Nile Blue A staining. High Leu saturating concentrations coupled with the occurrence of PHA-producing organisms further highlight the similarity of sea ice internal habitats to biofilm-like systems rather than to open-water systems.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".