Growth and Elemental Stoichiometry of the Ecologically-Relevant Arctic Diatom Chaetoceros gelidus: A Mix of Polar and Temperate
Bibliographic record
Abstract
In the wake of modest surface blooms that occur at the onset of the growth season in the nitrogen-poor surface waters of the Beaufort Sea, subsurface chlorophyll maxima (SCM) develop and persist within the nutrient-rich halocline. Algal communities of these SCM can realize a major portion of annual net primary production and are often dominated by the widespread diatom Chaetoceros gelidus in coastal waters. In order to assess how changing growth conditions at the SCM may affect the biological carbon pump, grazer nutrition and dissolved nutrient inventories across the transpolar Pacific-Atlantic conduit, the elemental stoichiometry of a C. gelidus strain (RCC2046) isolated from the Beaufort Sea and its response to the availability of light and different forms of nitrogen (N) were examined in the laboratory. The cells were grown in semi-continuous batch cultures at 0 °C under sub-saturating (LL ; 5.5 µmol photons m-2 s-1) or saturating irradiance (HL ; 200 5.5 µmol photons m-2 s-1) and with ammonium (NH4+), nitrate (NO3-) or urea as sole N form in nutrient-replete conditions. The growth rate, cell size, maximum quantum efficiency of photosystem II (Fv/Fm) and the concentrations of chlorophyll a (Chl a), biogenic silica (Si) and particulate N, phosphorus (P) and organic carbon (C) were measured during the exponential growth phase. Despite a clear response of volumetric quotas to N form, the growth rates and elemental ratios of the cells were unaffected by N form in the two irradiance treatments. Elemental ratios were affected by light and the responses were remarkably similar to those observed for temperate diatoms. Overall, this study shows that the growth and elemental composition of C. gelidus in the Arctic Ocean are highly resistant to changes in nitrogen form at near-freezing temperatures and suggests that this diatom possesses the ability to remain competitive despite ongoing environmental changes.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".