Testing the potential ballast role for dimethylsulfoniopropionate in marine phytoplankton: a modeling study
Bibliographic record
Abstract
The increase in dimethylsulfoniopropionate (DMSP) biosynthesis measured in several nitrogen-limited marine algae may partially replace other less dense organic solutes such as glycine betaine (GBT). This raises the possibility that phytoplankton could synthesize the denser organic solute DMSP in low nutrient oceanic surface waters facilitating sinking into zones of the euphotic zone richer in nutrients and maximizing their growth, hereafter referred to the “DMSP-ballast” hypothesis. The objective of this study was to test the DMSP-ballast hypothesis by modeling the sinking rates of the diatom Thalassiosira pseudonana and two strains of the coccolithophore Emiliania huxleyi as a function of DMSP synthesis in nitrogen-limited conditions. We also explored the potential ballast effect of DMSP in the positively buoyant non-motile algal species Ethmodiscus rex and Pyrocystis noctiluca. The model results suggest that replacement of trimethylammonium and GBT by DMSP in the naked E. huxleyi strain and T. pseudonana grown under nitrogen limitation could increase the sinking rate by 1–22%; while a putative increase in DMSP synthesis (in the millimolar range) in E. rex and P. noctiluca could decrease the rising rate by 43% to several orders of magnitude. The present study suggests a potential ballast role for DMSP in phytoplankton.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".