Metabolic diversity of heterotrophic bacterioplankton over winter and spring in the coastal Arctic Ocean
Bibliographic record
Abstract
Metabolic diversity of heterotrophic bacterioplankton was tracked from early winter through spring with Biolog Ecoplates under the seasonally ice covered arctic shelf in the Canadian Arctic (Franklin Bay, Beaufort Sea). Samples were taken every 6 days from December 2003 to May 2004 at the surface, the halocline where a temperature inversion occurs, and at 200 m, close to the bottom. Despite the low nutrient levels and low chlorophyll a, suggesting oligotrophy in the winter surface waters, the number of substrates used (NSU) was greater than in spring, when chlorophyll a concentrations increased. Denaturing gradient gel electrophorisis analysis also indicated that the winter and spring bacterial communities were phylogenetically distinct, with several new bands appearing in spring. In spring, the bacterial community would have access to the freshly produced organic carbon from the early phytoplankton bloom and the growth of rapidly growing specialist phenotypes would be favoured. In contrast, in winter bacterioplankton consumed more complex organic matter originated during the previous year's phytoplankton production. At the other depths we tested the NSU was similar to that for the winter surface, with no seasonal pattern. Instead, bacterioplankton metabolism seemed to be influenced by resuspension, advection, and sedimentation events that contributed organic matter that enhanced bacterial metabolism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".