The structure of bacterial communities in the western Arctic Ocean as revealed by pyrosequencing of 16S rRNA genes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bacterial communities in the surface layer of the oceans consist of a few abundant phylotypes and many rare ones, most with unknown ecological functions and unclear roles in biogeochemical processes. To test hypotheses about relationships between abundant and rare phylotypes, we examined bacterial communities in the western Arctic Ocean using pyrosequence data of the V6 region of the 16S rRNA gene. Samples were collected from various locations in the Chukchi Sea, the Beaufort Sea and Franklin Bay in summer and winter. We found that bacterial communities differed between summer and winter at a few locations, but overall there was no significant difference between the two seasons in spite of large differences in biogeochemical properties. The sequence data suggested that abundant phylotypes remained abundant while rare phylotypes remained rare between the two seasons and among the Arctic regions examined here, arguing against the 'seed bank' hypothesis. Phylotype richness was calculated for various bacterial groups defined by sequence similarity or by phylogeny (phyla and proteobacterial classes). Abundant bacterial groups had higher within-group diversity than rare groups, suggesting that the ecological success of a bacterial lineage depends on diversity rather than on the dominance of a few phylotypes. In these Arctic waters, in spite of dramatic variation in several biogeochemical properties, bacterial community structure was remarkably stable over time and among regions, and any variation was due to the abundant phylotypes rather than rare ones.
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.
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 | 0.000 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it