Inferred influence of nutrient availability on the relationship between Sun‐induced chlorophyll fluorescence and incident irradiance in the Bering Sea
Bibliographic record
Abstract
This study examines variability in the relationship between Sun‐induced chlorophyll fluorescence and incident solar irradiance as a potential diagnostic of the nutritional status of phytoplankton. The study site is the Bering Sea, where two optical drifters were caught for more than 100 days in an anticyclonic eddy, while two others provided data from adjacent waters. Estimates of fluorescence emission normalized to the absorption of light by pigments were analyzed as a function of irradiance to describe variability of the quantum yield of fluorescence. Yields in bright sunlight and under lower light varied by a factor of 5 or more on the scale of days to weeks. For the one drifter that remained in the high‐velocity region of the eddy, there was a lagged correlation between the eddy rotation period and fluorescence parameters, with higher fluorescence yields in both low and high irradiance associated with slower rotation. Since nutrient input to the photic zone may increase with increasing shear of the eddy flow, this is consistent with the established suggestion that Sun‐induced fluorescence increases with nutrient stress in phytoplankton. Independent measurements of variable fluorescence (Fv/Fm, an indicator of photosynthetic efficiency) further support this interpretation. However, modeling shows that the established hypothesis of competition between photosynthesis and fluorescence for absorbed photons (i.e., photochemical quenching), with high fluorescence yields reflecting photosynthetic debility, does not apply near the sea surface, where photosynthesis is saturated, and dissipation of excess absorbed radiation by nonphotochemical quenching is the dominant influence on fluorescence yield.
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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 | 0.000 |
| 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".