Cell size trade‐offs govern light exploitation strategies in marine phytoplankton
Bibliographic record
Abstract
Marine phytoplankton show complex community structures and biogeographic distributions, the net results of physiological and ecological trade-offs of species responses to fluctuating, heterogeneous environments. We analysed photosynthesis, responses to variable light and macromolecular allocations across a size panel of marine centric diatoms. The diatoms have strong capacities to withstand and exploit fluctuating light, when compared with picophytoplankton. Within marine diatoms, small species show larger effective cross-sections for photochemistry, and fast metabolic repair of photosystem II after photoinactivation. In contrast, large diatoms show lower susceptibility to photoinactivation, and therefore incur lower costs to endure short-term exposures to high light, especially under conditions that limit metabolic rates. This size scaling of key photophysiological parameters thus helps explain the relative competitive advantages of larger versus smaller species under different environmental regimes, with implications for the function of the biogenic carbon pump. These results provide a mechanistic framework to explain and predict shifts in marine phytoplankton community size structure with changes in surface irradiance and mixed layer depth.
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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 | 0.001 | 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".