Unveiling the control of N and P on DOM fate in a Mediterranean coastal environment
Bibliographic record
Abstract
Abstract Dissolved organic matter (DOM) and heterotrophic prokaryotes (HP) are key players in the oceanic carbon cycle. Although several biotic and abiotic factors controlling DOM fates are known, the hierarchy of their respective influences is still debated. Two contrasting Mediterranean coastal sites were sampled: a harbour under strong continental and anthropogenic influence (T) and an open coastal area (G). Interestingly, similar dissolved organic carbon (DOC) concentrations were observed in both samples. However, they showed marked differences in dissolved inorganic nitrogen and organic phosphorus concentrations (60-fold and 80% higher value in T), as well as in DOM optical properties and molecular composition. Incubation experiments were performed to expose the HP communities of each site to dissolved substances from T and G for three weeks. DOC removal was similar (−10 %) regardless HP origin and dissolved substances characteristics. HP growth and their maximal abundance were higher (+ 300 %) with dissolved substances from T, regardless HP origins. This indicates different fates of DOC processed by microbial communities as a function of abiotic determinants. Higher HP growth was associated to elevated initial content and higher consumption of inorganic nitrogen, organic phosphorus, three fluorescent DOM components, nitrogen-containing molecules and carbohydrates. These results provide insights into the main drivers of marine DOM fate: at similar DOC concentrations and low inorganic P concentrations. We evience the preferential consumption of lignin-like compounds where theoretically more labile molecules were available, thus reinforcing the need of in depth molecular studies for a better understanding of DOM-microbes interactions in the ocean.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".