Diatom growth responses to photoperiod and light are predictable from diel reductant generation
Bibliographic record
Abstract
Light drives phytoplankton productivity, so phytoplankton must exploit variable intensities and durations of light exposure, depending upon season, latitude, and depth. We analyzed the growth, photophysiology and composition of small, Thalassiosira pseudonana , and large, Thalassiosira punctigera , centric diatoms from temperate, coastal marine habitats, responding to a matrix of photoperiods and growth light intensities. T. pseudonana showed fastest growth rates under long photoperiods and low to moderate light intensities, while the larger T. punctigera showed fastest growth rates under short photoperiods and higher light intensities. Photosystem II function and content responded primarily to instantaneous growth light intensities during the photoperiod, while diel carbon fixation and RUBISCO content responded more to photoperiod duration than to instantaneous light intensity. Changing photoperiods caused species‐specific changes in the responses of photochemical yield (e − /photon) to growth light intensity. These photophysiological variables showed complex responses to photoperiod and to growth light intensity. Growth rate also showed complex responses to photoperiod and growth light intensity. But these complex responses resolved into a close relation between growth rate and the cumulative daily generation of reductant, across the matrix of photoperiods and light intensities.
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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 | 0.001 | 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 | 0.000 | 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 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".