Phytoplankton nutritional quality is altered by shifting Si:N ratios and selective grazing
Bibliographic record
Abstract
Abstract Diatoms often dominate phytoplankton in temperate, polar and upwelling regions. Decreases in silicate availability or silicon to nitrogen (Si:N) ratios may induce silicon limitation in diatoms and lower their proportion within phytoplankton communities. The effects of such changes on the nutritional quality of phytoplankton are not well understood. To examine how changing Si:N ratios affect plankton nutritional value, we applied a range of Si:N ratios on a natural plankton community and manipulated grazing pressure to assess top-down effects of copepod selective grazing. Diatom proportion in phytoplankton increased with increasing Si:N ratios and so did phytoplankton nutritional quality in terms of major fatty acid concentrations, such as polyunsaturated fatty acids, docosahexaenoic (DHA) and eicosapentaenoic (EPA) acids. However, stoichiometric quality (carbon to nitrogen and carbon to phosphorus ratios), DHA:EPA and omega 3:6 (ω3:ω6) ratios declined with increasing Si:N ratios, suggesting that proportions between essential compounds in copepod diet may be more favorable in lowered Si:N ratios. Copepods had a negative effect on DHA contents, DHA:EPA and ω3:ω6 ratios, indicating possible selective grazing on more nutritious plankton. Our findings show that declining silicate concentrations can affect stoichiometric and biochemical quality of phytoplankton, which copepods can also moderate by selective grazing.
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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 | 0.002 | 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 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".