A microbial perspective on the local influence of Arctic rivers and estuaries on Hudson Bay (Canada)
Bibliographic record
Abstract
A clear divide typically exists between freshwater and marine microbial communities, with transitional communities found in estuarine zones. The estuarine communities can derive from inflowing rivers and the sea via tidal mixing and incursions or be comprised of unique brackish species, depending on flow regimes and retention time within an estuary. Only a few studies have been carried out in the Arctic, where moderate salinities associated with the influence of seasonal ice melt could potentially favor marine microbes adapted to lower salinities in fresh-to-saltwater transition zones irrespective of river flows and tidal mixing. To test this idea, we examined early summer microbial communities in 2 western Hudson Bay (Canada) river-to-sea systems: the Churchill and Nelson river systems. Both rivers originate from the same headwaters, suggesting similar catchment conditions, but differ in geomorphology and hydroelectric diversions that induce very different flow and stratification regimes. Using amplicons of the V4 region of the 16S rRNA gene, we identified distinct riverine bacterial communities that were significantly different from the 2 associated estuaries and offshore communities. In the much smaller Churchill Estuary, the microbial community showed a marked influence of freshwater microbial species, along with marine influences. In contrast, in the larger high-flow Nelson River Estuary, riverine bacterioplankton were less evident in the estuary, where the marine signal was much stronger. The marine samples in both systems differed somewhat consistently with the phenology of the phytoplankton bloom in the Bay and tended to harbor distinct attached and free-living bacterial communities. Our results highlight the relevance of river flow and estuarine circulation on selection of bacterial species in estuaries, with ecological implications for food web functionality and biogeochemical cycles in the Anthropocene, where flow regimes would be affected by larger climatic variability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".