Vulnerability of Arctic Ocean microbial eukaryotes to sea ice loss
Bibliographic record
Abstract
The Arctic Ocean (AO) is changing at an unprecedented rate, with ongoing sea ice loss, warming and freshening impacting the extent and duration of primary productivity over summer months. Surface microbial eukaryotes are vulnerable to such changes, but basic knowledge of the spatial variability of surface communities is limited. Here, we sampled microbial eukaryotes in surface waters of the Beaufort Sea from four contrasting environments: the Canada Basin (open ocean), the Mackenzie Trough (river-influenced), the Nuvuk region (coastal) and the under-ice system of the Canada Basin. Microbial community structure and composition varied significantly among the systems, with the most phylogenetically diverse communities being found in the more coastal systems. Further analysis of environmental factors showed potential vulnerability to change in the most specialised community, which was found in the samples taken in water immediately beneath the sea ice, and where the community was distinguished by rare species. In the context of ongoing sea ice loss, specialised ice-associated microbial assemblages may transition towards more generalist assemblages, with implications for the eventual loss of biodiversity and associated ecosystem function in the Arctic Ocean.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".