Inorganic carbon uptake by Southern Ocean phytoplankton
Bibliographic record
Abstract
We report the results of laboratory and field studies examining inorganic carbon (Ci) utilization by Southern Ocean phytoplankton. Both in monospecific laboratory cultures of diatoms and Phaeocystis antarctica and in natural assemblages in the Ross Sea, Ci uptake by phytoplankton was dominated by direct HCO31 transport. The contribution of HCO31 transport to total Ci uptake ranged from 65% to 95%, with an overall average of ∼80%. There was no significant difference among diatoms and Phaeocystis in the extent of HCO31 transport. Extracellular carbonic anhydrase activity (eCA) was detected in eight of nine laboratory phytoplankton cultures and in all natural assemblages in the Ross Sea. The effective catalytic enhancement of HCO31 : CO2 interconversion ranged from 1.5‐ to 13‐fold (overall mean ∼4‐fold). Diatom‐dominated Ross Sea assemblages had significantly greater eCA levels than did Phaeocystis‐dominated assemblages. We found no strong correlations between Ci uptake parameters and in situ CO2 concentrations or chlorophyll a levels in the Ross Sea assemblages. Incubation experiments with natural assemblages showed that HCO31 uptake and eCA expression did not change significantly over an 8‐fold range in pCO2 (10.1‐81.1 Pa), although total short‐term C fixation rates increased under low CO2 conditions. Carbon‐concentrating mechanisms are widespread among Southern Ocean phytoplankton and constitutively expressed by natural assemblages in the Ross Sea.
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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) | 0.001 | 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".