Effects of non‐steady‐state iron limitation on nitrogen assimilatory enzymes in the marine diatom <i>thalassiosira weissflogii</i> (BACILLARIOPHYCEAE)
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Bibliographic record
Abstract
Since the recognition of iron‐limited high nitrate (or nutrient) low chlorophyll (HNLC) regions of the ocean, low iron availability has been hypothesized to limit the assimilation of nitrate by diatoms. To determine the influence of non‐steady‐state iron availability on nitrogen assimilatory enzymes, cultures of Thalassiosira weissflogii (Grunow) Fryxell et Hasle were grown under iron‐limited and iron‐replete conditions using artificial seawater medium. Iron‐limited cultures suffered from decreased efficiency of PSII as indicated by the DCMU‐induced variable fluorescence signal ( F v / F m ). Under iron‐replete conditions, in vitro nitrate reductase (NR) activity was rate limiting to nitrogen assimilation and in vitro nitrite reductase (NiR) activity was 50‐fold higher. Under iron limitation, cultures excreted up to 100 fmol NO 2 − ·cell −1 ·d −1 (about 10% of incorporated N) and NiR activities declined by 50‐fold while internal NO 2 − pools remained relatively constant. Activities of both NR and NiR remained in excess of nitrogen incorporation rates throughout iron‐limited growth. One possible explanation is that the supply of photosynthetically derived reductant to NiR may be responsible for the limitation of nitrogen assimilation at the NO 2 − reduction step. Urease activity showed no response to iron limitation. Carbon:nitrogen ratios were equivalent in both iron conditions, indicating that, relative to carbon, nitrogen was assimilated at similar rates whether iron was limiting growth or not. We hypothesize that, diatoms in HNLC regions are not deficient in their ability to assimilate nitrate when they are iron limited. Rather, it appears that diatoms are limited in their ability to process photons within the photosynthetic electron transport chain which results in nitrite reduction becoming the rate‐limiting step in nitrogenassimilation.
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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 | 0.000 |
| 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) | 0.001 | 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 it