Linking chlorophyll-nutrient dynamics to the RedÞeld N:C ratio with a model of optimal phytoplankton growth
Bibliographic record
Abstract
The Redfield N:C ratio is a fundamental quantity in marine biogeochemistry because it is a key determinant of the efficiency of the biological carbon pump, yet no convincing explanations have been put forward for its remarkable constancy over much of the world ocean. Phytoplankton growth models have so far been unable to account for the different relationships between growth rate and N:C ratio under nutrient and light limitation, and have not been able to predict the Redfield N:C ratio. A relatively simple model of coupled chlorophyll and nutrient dynamics is developed from the premise that phytoplankton maximize growth by optimally allocating nutrient and energy resources among competing metabolic requirements for nutrient uptake, light-harvesting, and growth. The model reconciles nutrient and light limitation and appears valid under both balanced and non-balanced growth conditions. The Redfield N:C ratio and its constancy are explained as a result of evolutionary pressure towards maximizing light-limited growth rates in relatively carbon-rich oceanic waters.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".