Dimethylsulfoniopropionate (DMSP) and dimethyl sulfide (DMS) cycling across contrasting biological hotspots of the New Zealand subtropical front
Bibliographic record
Abstract
Abstract. The oceanic frontal region above the Chatham Rise east of New Zealand was investigated during the late austral summer season in February and March 2012. Despite its potential importance as a source of marine-originating and climate-relevant compounds, such as dimethyl sulfide (DMS) and its algal precursor dimethylsulfoniopropionate (DMSP), little is known of the processes fuelling the reservoirs of these sulfur (S) compounds in the water masses bordering the subtropical front (STF). This study focused on two opposing short-term fates of DMSP-S following its uptake by microbial organisms (either its conversion into DMS or its assimilation into bacterial biomass) and has not considered dissolved non-volatile degradation products. Sampling took place in three phytoplankton blooms (B1, B2, and B3) with B1 and B3 occurring in relatively nitrate-rich, dinoflagellate-dominated subantarctic waters, and B2 occurring in nitrate-poor subtropical waters dominated by coccolithophores. Concentrations of total DMSP (DMSPt) and DMS were high across the region, up to 160 and 14.5 nmol L−1, respectively. Pools of DMSPt showed a strong association with overall phytoplankton biomass proxied by chlorophyll a (rs = 0.83) likely because of the persistent dominance of dinoflagellates and coccolithophores, both DMSP-rich taxa. Heterotrophic microbes displayed low S assimilation from DMSP (less than 5 %) likely because their S requirements were fulfilled by high DMSP availability. Rates of bacterial protein synthesis were significantly correlated with concentrations of dissolved DMSP (DMSPd, rs = 0.86) as well as with the microbial conversion efficiency of DMSPd into DMS (DMS yield, rs = 0.84). Estimates of the potential contribution of microbially mediated rates of DMS production (0.1–27 nmol L−1 day−1) to the near-surface concentrations of DMS suggest that bacteria alone could not have sustained DMS pools at most stations, indicating an important role for phytoplankton-mediated DMS production. The findings from this study provide crucial information on the distribution and cycling of DMS and DMSP in a critically under-sampled area of the global ocean, and they highlight the importance of oceanic fronts as hotspots of the production of marine biogenic S compounds.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".