Nitrogen and sulfur metabolisms encoded in prokaryotic communities associated with sea ice algae
Bibliographic record
Abstract
Abstract Sea ice habitats harbour seasonally abundant microalgal communities, which can be highly productive in the spring when the availability of light increases. An active, bloom-associated prokaryotic community relies on these microalgae for their organic carbon requirements, however an analysis of the encoded metabolic pathways within them is lacking. Hence, our understanding of biogeochemical cycling within sea ice remains incomplete. Here, we generated metagenomic assembled genomes from the bottom of first-year sea ice in northwestern Hudson Bay, during a spring diatom bloom. We show that the prokaryotic community had the metabolic potential to degrade algal derived dimethylsulphoniopropionate and oxidise sulfur. Facultative anaerobic metabolisms, specifically, dissimilatory nitrate reduction and denitrification were also prevalent here, suggesting some sea ice prokaryotes are metabolically capable of adapting to fluctuating oxygen levels during algal bloom conditions. Such denitrification could be an important loss of fixed-N2 in the changing Arctic marine system.
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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 | 0.000 | 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".