Effects of Vertical Water Mass Segregation on Bacterial Community Structure in the Beaufort Sea
Bibliographic record
Abstract
The Arctic Ocean is one of the least well-studied marine microbial ecosystems. Its low-temperature and low-salinity conditions are expected to result in distinct bacterial communities, in comparison to lower latitude oceans. However, this is an ocean currently in flux, with climate change exerting pronounced effects on sea-ice coverage and freshwater inputs. How such changes will affect this ecosystem are poorly constrained. In this study, we characterized the bacterial community compositions at different depths in both coastal, freshwater-influenced, and pelagic, sea-ice-covered locations in the Beaufort Sea in the western Canadian Arctic Ocean. The environmental factors controlling the bacterial community composition and diversity were investigated. Alphaproteobacteria dominated the bacterial communities in samples from all depths and stations. The Pelagibacterales and Rhodobacterales groups were the predominant taxonomic representatives within the Alphaproteobacteria. Bacterial communities in coastal and offshore samples differed significantly, and vertical water mass segregation was the controlling factor of community composition among the offshore samples, regardless of the taxonomic level considered. These data provide an important baseline view of the bacterial community in this ocean system that will be of value for future studies investigating possible changes in the Arctic Ocean in response to global change and/or anthropogenic disturbance.
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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 | 0.001 |
| 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 | 0.001 |
| 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".