Upper Arctic Ocean water masses harbor distinct communities of heterotrophic flagellates
Bibliographic record
Abstract
Abstract. The ubiquity of heterotrophic flagellates (HFL) in marine waters has been recognized for several decades, but the phylogenetic diversity of these small (ca. 0.8–20 μm cell diameter), mostly phagotrophic protists in the upper pelagic zone of the ocean is underappreciated. Community composition of microbes, including HFL, is the result of past and current environmental selection, and different taxa may be indicative of food webs that cycle carbon and energy very differently. While all oceanic water columns can be density stratified due to the temperature and salinity characteristics of different water masses, the Arctic Ocean is particularly well stratified, with nutrients often limiting in surface waters and most photosynthetic biomass confined to a subsurface chlorophyll maximum layer, where light and nutrients are both available. This physically well-characterized system provided an opportunity to explore the community diversity of HFL from different water masses within the water column. We used high-throughput DNA sequencing techniques as a rapid means of surveying the diversity of HFL communities in the southern Beaufort Sea (Canada), targeting the surface, the subsurface chlorophyll maximum layer (SCM) and just below the SCM. In addition to identifying major clades and their distribution, we explored the micro-diversity within the globally significant but uncultivated clade of marine stramenopiles (MAST-1) to examine the possibility of niche differentiation within the stratified water column. Our results strongly suggested that HFL community composition was determined by water mass rather than geographical location across the Beaufort Sea. Future work should focus on the biogeochemical and ecological repercussions of different HFL communities in the face of climate-driven changes to the physical structure of 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 | 0.000 |
| 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) | 0.001 | 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".