The short-term effect of nitrogen on freshwater cyanobacteria and cyanotoxins
Bibliographic record
Abstract
Toxic cyanobacterial blooms are a worldwide concern. Nutrients are among the numerous factors that trigger cyanobacterial blooms and the production of cyanotoxins. This study aimed to assess the effect of nitrogen on cyanobacteria and cyanotoxins through a short-term mesocosm experiment. To achieve this, mesocosms were installed in situ in two lakes (the Missisquoi Bay of Lake Champlain and Petit-Lac-St-François) and received 700 μg/L of ammonium or 500 μg/L of nitrate. A shift to Microcystis in the mesocosms with nitrogen addition was observed 2 days after the addition in Missisquoi Bay, where nitrogen was more limited than Petit-Lac-St-François based on nutrient ratios. There was a significant increase of extracellular ΣMCs and MC-LR in mesocosms with the addition of ammonium or nitrate after 48 h compared to control mesocosms. Intracellular and extracellular microcystin concentrations were associated with Microcystis. Microcystis presence was associated with ammonium 48 h after N was added at both sites. Therefore, toxin production following sudden nitrogen addition can occur on short time scales relevant to drinking water treatment plant operations. This information will help treatment plant operators better anticipate the arrival of potentially higher concentrations of cyanotoxins.
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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".