Coastal <i>Synechococcus</i> strains can exploit low-oxygen habitats
Bibliographic record
Abstract
We found that Phycoerythrin-rich Synechococcus achieved faster growth rates (µ), across the spectral bandwidths from 405 to 730 nm, under 2.5 µmol/L [O2], characteristic of oxygen minimum zones (OMZs), than under 250 µmol/L [O2], whereas phycocyanin-rich strain showed generally similar µ under 2.5 and 250 µmol/L [O2]. For phycocyanin- and phycoerythrin-rich Synechococcus, µ showed also positive linear responses to both phycobiliproteins:chlorophyll a, and to cumulative diel PSII electron flux, although the relations vary across strain and [O2]. Electron transport downstream of Photosystem II was generally higher for both phycocyanin- and phycoerythrin-rich strains under 250 µmol/L [O2], since cyanobacteria show strong capacity for electron flow away from PSII to O2, particularly under excess excitation. Even though electron transport was faster under 250 µmol/L [O2], the phycoerythrin-rich strain showed a higher growth yield of electron transport under 2.5 µmol/L [O2]. Phycoerythrin-rich Synechococcus are currently typically found at greater depths, and lower light, than are phycocyanin-rich strains, but we suggest that the phycoerythrin-rich strains are actually limited to lower light by an interaction between light and full air-saturated [O2]. In expanding OMZs phycoerythrin-rich strains will likely exploit higher light niches, across a wider spectral range.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".