Nutrient enrichment alters phytoplankton biomass and composition via silicon limitation
Bibliographic record
Abstract
Despite management efforts, anthropogenic nutrient enrichments continue to enhance phytoplankton blooms worldwide. Release of nitrogen and phosphorus compounds not only provides surplus of nutrients but also disbalances their stoichiometry. Declines in the relative availability of dissolved silicon might induce limitation in diatoms, major primary producers with silicified shells. We studied experimentally how nutrient enrichment and resulting decline in dissolved silicon to nitrogen ratios (Si:N) affect the structure and functioning of natural plankton communities. Nitrate was added to create a range of Si:N ratios and phosphate was supplied in Redfield ratio to nitrogen. We also manipulated copepod abundance to understand the top-down effects on communities experiencing nutrient enrichment. Nitrogen and phosphorus additions resulted in a steep phytoplankton biomass increase, followed by a post-bloom decline. Phytoplankton bloom biomass was higher in high nitrogen treatments but during the post-bloom period this trend switched. Biomass was sustained longer in high Si:N treatments, indicating that silicon limitation terminates the bloom. Many diatom species did not benefit from nitrogen and phosphorus enrichment and diatom dominance ceased below Si:N of 0.4:1. Under high grazing pressure, silicate was taken up faster suggesting that silicification is important in diatom defense. Copepods shaped plankton communities via feeding on dinoflagellates, chlorophytes and the diatom Skeletonema costatum but there was no significant effect of nitrogen and phosphorus enrichment on copepod abundance. Our results, combined with previous studies, show that while nutrient concentrations define the total phytoplankton bloom biomass, resource ratios are important in sustaining biomass and determining community structure and composition.
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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) | 0.001 | 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".