INFLUENCE OF LOW LIGHT AND A LIGHT: DARK CYCLE ON NO<sub>3</sub><sup>–</sup> UPTAKE, INTRACELLULAR NO<sub>3</sub><sup>–</sup>, AND NITROGEN ISOTOPE FRACTIONATION BY MARINE PHYTOPLANKTON<sup>1</sup>
Bibliographic record
Abstract
The nitrogen isotope enrichment factor (ɛ) of four species of marine phytoplankton grown in batch cultures was determined during growth in continuous saturating light, continuous low light, and a 12:12‐h light:dark cycle, with nitrate as a nitrogen source. The low growth rate that resulted from low irradiance caused an increased accumulation of the intracellular nitrate pool and/or a reduction in cell volume and was correlated to a species‐specific increase in the measured ɛ value, compared with the saturating light conditions. The largest response was in the diatom Thalassiosira weissflogii (Grun.) Fryxell et Hasle, which showed a nearly 3‐fold increase between high and low light conditions (6.2–15.2‰). The smallest response was in T. pseudonana (Hustedt) Hasle et Heimdal, which showed no change in the ɛ value of approximately 5‰ in both high and low light conditions. There was significant but smaller increases in the ɛ value for the diatom T. rotula Meunier (2.7–5.6‰) and the prymnesiophyte Emiliania huxleyi (Lohm.) Hay et Mohler (4.5–9.4‰) between high and low light levels. In the light:dark experiments, all three diatoms but not the prymnesiophyte exhibited an increase in ɛ. This increase was linked to the ability of diatoms to assimilate nitrate at night. The results of the these experiments suggest that the light regime influences the relative uptake, assimilation, and efflux rates of nitrate and results in differences in the expression of the isotope effect by the enzyme nitrate reductase. Therefore, variations in nitrate isotope fractionation in nature can be more accurately interpreted when the light regime and species composition are taken into consideration.
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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 | 0.001 |
| 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".