Distribution and metabolism of dimethylsulfoniopropionate (DMSP) and phylogenetic affiliation of DMSP‐assimilating bacteria in northern Baffin Bay/Lancaster Sound
Bibliographic record
Abstract
We determined the distribution and bacterial metabolism of dimethylsulfoniopropionate (DMSP) and dimethylsulfide (DMS) in the two dominant surface water masses in northern Baffin Bay/Lancaster Sound during September 2008. Concentrations of particulate DMSP (DMSPp; 5–70 nmol L−1) and the DMSPp:Chl a ratios (15–229 nmol μg−1) were relatively high, suggesting the presence of DMSP‐rich phytoplankton taxa. Photosynthetic picoeukaryotes and total prokaryotes were tenfold and threefold more abundant in Baffin Bay surface water (BBS) than in Arctic surface water (AS), respectively. Heterotrophic bacterial production (0.07–2.5μC L−1 d−1) and bacterial turnover rate constants for dissolved DMSP (DMSPd) were low (0.03–0.11 h−1) compared with the values previously reported in warmer and more productive environments. Nonetheless, a relatively large proportion (12%–31%) of the DMSP metabolized by the bacteria was converted into DMS. Additionally, between 40% and 65% of the total bacterial cells incorporated sulfur from DMSPd, with Gammaproteobacteriaand non‐Roseobacter Alphaproteobacteria (AlfR‐) contributing proportionally more to total DMSP‐incorporating cells. The contribution of AlfR‐ to the total prokaryotic community was 50% higher in BBS than in AS, while the bacterial rate constants for DMSPd turnover were 78% higher in BBS than in AS. These results show that the two different Arctic water masses host specific microbial assemblages that result in distinct affinity for DMSP.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".