Contrasting photoacclimation costs in ecotypes of the marine eukaryotic picoplankter <i>Ostreococcus</i>
Bibliographic record
Abstract
Ostreococcus , the smallest known marine picoeukaryote, includes low‐ and high‐light ecotypes. To determine the basis for niche partitioning between Ostreococcus sp. RCC809, isolated from the bottom of the tropical Atlantic euphotic zone, and the lagoon strain Ostreococcus tauri , we studied their photophysiologies under growth irradiances from 15 µmol photons m −2 s −1 to 800 µmol photons m −2 s −1 with a common nutrient replete regime. With increasing growth irradiance, both strains down‐regulated cellular chlorophyll a and chlorophyll b (Chl a and Chl b ) content, increased xanthophyll de‐epoxidation correlated with nonphotochemical excitation quenching, and accumulated lutein. Ribulose‐1,5‐bisphosphate carboxylase/oxygenase content remained fairly stable. Under low‐growth irradiances of 15‐80 µmol photons m −2 s −1 , O. sp. RCC809 had equivalent or slightly higher growth rates, lower Chl a , a higher Chl b : Chl a ratio, and a larger photosystem II (PSII) antenna than O. tauri . O. tauri was more phenotypically plastic in response to growth irradiance, with a larger dynamic range in growth rate, Chl a , photosystem cell content, and cellular absorption cross‐section of PSII. Estimating the amino acid and nitrogen costs for photoacclimation showed that the deep‐sea oceanic O. sp. RCC809 relies largely on lower nitrogen cost changes in PSII antenna size to achieve a limited range of σ‐type light acclimation. O. sp. RCC809, however, suffers photoinhibition under higher light. This limited capacity for photoacclimation is compatible with the stable low‐light and nutrient conditions at the base of the euphotic layer of the tropical Atlantic Ocean. In the more variable, high‐nutrient, lagoon environment, O. tauri can afford to use a higher cost n‐type acclimation of photosystem contents to exploit a wider range of light.
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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) | 0.000 | 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 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".