Seasonal regulation of the coupling between photosynthetic electron transport and carbon fixation in the Southern Ocean
Bibliographic record
Abstract
Abstract Active fluorescence measurements can provide rapid, non‐intrusive estimates of phytoplankton primary production at high spatial and temporal resolution, but there is uncertainty in converting from electrons to ecologically relevant rates of CO2 assimilation. In this study, we examine the light‐dependent rates of photosynthetic electron transport and 13C‐uptake in the Atlantic sector of the Southern Ocean to derive a conversion factor for both winter (July 2015–August 2015) and summer (December 2015–February 2016). The results revealed significant seasonal differences in the light‐saturated chlorophyll specific rate of 13C‐uptake, ( ), with mean summer values 2.3 times higher than mean winter values, and the light limited chlorophyll specific efficiency, (αB), with mean values 2.7 times higher in summer than in winter. Similar patterns were observed in the light‐saturated photosynthetic electron transport rates ( , 1.5 times higher in summer) and light limited photosynthetic electron transport efficiency (αRCII, 1.3 times higher in summer). The conversion factor between carbon and electrons (Φe:C (mol e− mol C−1)) was derived utilizing in situ measurements of the chlorophyll‐normalized number of reaction centers (nRCII), resulting in a mean summer Φe:C which was ∼ 3 times lower than the mean winter Φe:C. Empirical relationships were established between Φe:C, light and NPQ, however they were not consistent across locations or seasons. The seasonal decoupling of Φe:C is the result of differences in Ek‐dependent and Ek‐independent variability, which require new modelling approaches and improvements to bio‐optical techniques to account for these inter‐seasonal differences in both taxonomy and environmental mean conditions.
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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".