EFFECT OF ZINC AVAILABILITY ON GROWTH, MORPHOLOGY, AND NUTRIENT INCORPORATION IN A COASTAL AND AN OCEANIC DIATOM1
Bibliographic record
Abstract
We investigated the effect of Zn availability on growth rate (μ), cell morphology, and elemental stoichiometry and incorporation rate in two marine diatoms. For the coastal diatom Skeletonema costatum (Grev.) Cleve, the half-saturation constant (KS ) for growth was 4.1 pM Zn(2+) , and growth ceased at ≤ 2.6 pM Zn(2+) , whereas for the oceanic diatom Thalassiosira oceanica Hasle, KS was 0.5 pM Zn(2+) , and μ remained at ∼40%μmax even at 0.3 pM Zn(2+) . Under Zn-limiting (Zn-L) conditions, S. costatum decreased cell size significantly, leading to an 80% increase in surface area to volume ratio (SA/V) at Zn(2+) of 3.5 pM compared to Zn-replete (Zn-R) conditions (at Zn(2+) of 13.2 pM), whereas T. oceanica's morphology did not change appreciably. Cell quotas of C, N, P, Si, and chl a significantly decreased under Zn limitation in S. costatum (at Zn(2+) of 3.5 pM), whereas Zn limitation in T. oceanica (at Zn(2+) of 0.3 pM) had little effect on quotas. Elemental stoichiometry was ∼85C:10N:9Si:1P and 81C:9N:5Si:1P for S. costatum, and 66C:5N:2Si:1P and 52C:6N:2Si:1P for T. oceanica, under Zn-R and Zn-L conditions, respectively. Incorporation rates of all elements were significantly reduced under Zn limitation for both diatoms, but particularly for Si in S. costatum, and for C in T. oceanica, despite its apparent tolerance of low Zn conditions. With [Zn(2+) ] in some parts of the ocean being of the same order (∼0.2 to 2 pM) as our low Zn conditions for T. oceanica, our results support the hypothesis that in situ growth and C acquisition may be limited by Zn in some oceanic species.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".