Contrasting sea ice conditions shape microbial food webs in Hudson Bay (Canadian Arctic)
Bibliographic record
Abstract
The transition from ice-covered to open water is a recurring feature of the Arctic and sub-Arctic, but microbial diversity and cascading effects on the microbial food webs is poorly known. Here, we investigated microbial eukaryote, bacterial and archaeal communities in Hudson Bay (sub-Arctic, Canada) under sea-ice cover and open waters conditions. Co-occurrence networks revealed a <3 µm pico‒phytoplankton-based food web under the ice and a >3 µm nano‒microphytoplankton-based food web in the open waters. The ice-edge communities were characteristic of post-bloom conditions with high proportions of the picophytoplankton Micromonas and Bathycoccus. Nano‒ to micro‒phytoplankton and ice associated diatoms were detected throughout the water column, with the sympagic Melosira arctica exclusive to ice-covered central Hudson Bay and Thalassiosira in open northwestern Hudson Bay. Heterotrophic microbial eukaryotes and prokaryotes also differed by ice-state, suggesting a linkage between microbes at depth and surface phytoplankton bloom state. The findings suggest that a longer open water season may favor the establishment of a large phytoplankton-based food web at the subsurface chlorophyll maxima (SCM), increasing carbon export from pelagic diatoms to deeper waters and affect higher trophic levels in the deep Hudson Bay.
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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 | 0.001 |
| 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".