CYANOBACTERIAL ACCLIMATION TO RAPIDLY FLUCTUATING LIGHT IS CONSTRAINED BY INORGANIC CARBON STATUS<sup>1</sup>
Bibliographic record
Abstract
Acclimation to rapidly fluctuating light, simulating shallow aquatic habitats, is altered depending on inorganic carbon (C i ) availability. Under steady light of 50 μmol photons·m −2 ·s −1 , the growth rate of Synechococcus elongatus PCC7942 was similar in cells grown in high C i (4 mM) and low C i (0.02 mM), with induced carbon concentrating mechanisms compensating for low C i . Growth under fluctuating light of a 1‐s period averaging 50 μmol photons·m −2 ·s −1 caused a drop in growth rate of 28%±6% in high C i cells and 38%±8% in low C i cells. In high C i cells under fluctuating light, the PSI/PSII ratio increased, the PSII absorption cross‐section decreased, and the PSII turnover rate increased in a pattern similar to high‐light acclimation. In low C i cells under fluctuating light, the PSI/PSII ratio decreased, the PSII absorption cross‐section decreased, and the PSII turnover remained slow. Electron transport rate was similar in high and low C i cells but in both was lower under fluctuating than under steady light. After acclimation to a 1‐s period fluctuating light, electron transport rate decreased under steady or long‐period fluctuating light. We hypothesize that high C i cells acclimated to exploit the bright phases of the fluctuating light, whereas low C i cells enlarged their PSII pool to integrate the fluctuating light and dampen the variation of the electron flux into a rate‐restricted C i pool. Light response curves measured under steady light, widely used to predict photosynthetic rates, do not properly predict photosynthetic rates achieved under fluctuating light, and exploitation of fluctuating light is altered by C i status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.010 | 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 teacher head, 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".