Manganese and iron as structuring parameters of microbial communities in Arctic marine sediments from the Baffin Bay
Bibliographic record
Abstract
The Arctic Baffin Bay between Canada and Greenland is sea ice-covered during the majority of the year, restricting primary production to the summer months. Sediments receive low amounts of mostly terrestrial- and less marine-derived organic matter. To study microbial communities constrained by physicochemical conditions changing with distance from land and ocean depth, we applied high-throughput 16S rRNA gene sequencing and compared sequence diversity with biogeochemical parameters in 40 different sediment samples. Samples originated from seven cores down to 470 cm below seafloor along a shelf-to-basin transect. Bacterial diversity decreased faster with depth in basin than in shelf sediments, suggesting higher organic matter content sustained diversity into greater depths. All samples were dominated by Betaproteobacteria (mostly order Burkholderiales), which were especially abundant in basin sediments with low organic carbon and high Mn and Fe pore water concentrations. Strong statistical correlations between concentrations of reduced Mn and/or Fe and the relative abundances of Betaproteobacteria suggest that this group is involved in metal reduction in Baffin Bay sediments. Dehalococcoidia (phylum Chloroflexi) were abundant in all samples, especially in shelf sediments with high organic content. This study indicates that Mn and/or Fe play important roles structuring microbial communities in Arctic sediments poor in organic matter.
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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 | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".