Slow carboxylation of <scp>R</scp>ubisco constrains the rate of carbon fixation during <scp>A</scp>ntarctic phytoplankton blooms
Bibliographic record
Abstract
High-latitude oceans are areas of high primary production despite temperatures that are often well below the thermal optima of enzymes, including the key Calvin Cycle enzyme, Ribulose 1,5 bisphosphate carboxylase oxygenase (Rubisco). We measured carbon fixation rates, protein content and Rubisco abundance and catalytic rates during an intense diatom bloom in the Western Antarctic Peninsula (WAP) and in laboratory cultures of a psychrophilic diatom (Fragilariopsis cylindrus). At -1°C, the Rubisco turnover rate, kcat (c) , was 0.4 C s(-1) per site and the half saturation constant for CO2 was 15 μM (vs c. 3 C s(-1) per site and 50 μM at 20°C). To achieve high carboxylation rates, psychrophilic diatoms increased Rubisco abundance to c. 8% of biomass (vs c. 0.6% at 20°C), along with their total protein content, resulting in a low carbon : nitrogen ratio of c. 5. In psychrophilic diatoms, Rubisco must be almost fully active and near CO2 saturation to achieve carbon fixation rates observed in the WAP. Correspondingly, total protein concentrations were close to the highest ever measured in phytoplankton and likely near the maximum possible. We hypothesize that this high protein concentration, like that of Rubisco, is necessitated by slow enzyme rates, and that carbon fixation rates in the WAP are near a theoretical maximum.
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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 | 0.001 | 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".