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Record W2172249191 · doi:10.1093/plankt/fbv050

Testing the potential ballast role for dimethylsulfoniopropionate in marine phytoplankton: a modeling study

2015· article· en· W2172249191 on OpenAlexaff
Michel Lavoie, Maurice Levasseur, Marcel Babin

Bibliographic record

VenueJournal of Plankton Research · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsThalassiosira pseudonanaEmiliania huxleyiDimethylsulfoniopropionateCoccolithophorePhytoplanktonDiatomBallastAlgaeEnvironmental chemistryOceanographyNutrientBiologyPhotic zoneBotanyEcologyChemistryGeology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.107
GPT teacher head0.318
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2015
Admission routes1
Has abstractyes

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