Photoperiods and light differentially influence growth and potential niches of phycocyanin‐ and phycoerythrin‐rich picocyanobacteria
Bibliographic record
Abstract
Abstract Strains from the picocyanobacteria genus Synechococcus are currently found across a wide range of photoperiods and photosynthetically active radiation. Future scenarios now forecast range expansions of marine Synechococcus into new photic regimes. We found that strains of temperate, coastal phycocyanin‐rich and phycoerythrin‐rich Synechococcus grew fastest under moderate photosynthetically active radiation, and a 24‐h photoperiod, despite a cumulative diel photon dose equivalent to conditions where growth was slower, under higher light and shorter photoperiods. Under optimal conditions, a phycoerythrin‐rich Synechococcus strain achieved a highest recorded cyanobacterial chlorophyll‐specific exponential growth rate (μ) of 4.5 d−1. Two phycoerythrin‐rich strains demonstrated wider ability to modulate light capture capacity, whereas two phycocyanin‐rich strains showed less change in light capture across increasing cumulative diel photon dose. All four coastal strains showed a decrease of effective absorption cross‐section for photosystem II photochemistry, vs. increasing cumulative diel photosynthetically active radiation doses. Within each strain, μ showed consistent, saturating responses to increasing cumulative diel photosystem II electron flux, with more variations in responses of μ to cumulative photosynthetically usable radiation. As photoperiod opportunists, coastal picocyanobacteria show potential to expand into longer photic regimes as higher latitudes warm.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".