The influence of phytoplankton biomass on the spatial distribution of carbon dioxide in surface sea water of a coastal area of the Gulf of Cádiz (southwestern Spain)
Bibliographic record
Abstract
The spatial variability in carbon dioxide in surface waters of a coastal area of the Gulf of Cádiz (southwestern Spain) was examined in situ under spring bloom conditions. The influence of phytoplankton biomass and physicochemical variables on the CO2 concentration was studied. According to the relationship observed between chlorophyll a and pCO2, phytoplankton biomass was the main factor responsible for variations in carbon dioxide. The distribution of organic matter in the form of dissolved organic carbon and transparent exopolymer particles also reflected changes in phytoplankton abundance, since high levels of both variables were associated with high chlorophyll concentrations and low levels of free CO2. The involvement of the enzyme carbonic anhydrase in the process of inorganic carbon uptake by the phytoplankton community was also investigated through the effect of the inhibitors dextran-bound sulfonamide and ethoxyzolamide on primary production rates. Ethoxyzolamide substantially inhibited carbon fixation, causing decreases of 40%60% in the maximum photosynthetic rates; whereas the membrane impermeable inhibitor dextran-bound sulfonamide affected primary production, depending on the diversity of the phytoplankton species composition. Calculations of CO2 fluxes indicated that the sampled coastal sector of the Gulf of Cádiz behaved as a net sink for atmospheric CO2 at the time of analysis, with an average CO2 absorption of 0.41 mmol·m2·d1.Key words: airsea exchange of CO2, carbonic anhydrase, flow cytometry, Gulf of Cádiz, phytoplankton, transparent exopolymer particles.
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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".