Nitrogen Forms Influence Microcystin Concentration and Composition via Changes in Cyanobacterial Community Structure
Bibliographic record
Abstract
The eutrophication of freshwaters is a global health concern as lakes with excess nutrients are often subject to toxic cyanobacterial blooms. Although phosphorus is considered the main element regulating cyanobacterial biomass, nitrogen (N) concentration and more specifically the availability of different N forms may influence the overall toxicity of blooms. In this study of three eutrophic lakes prone to cyanobacterial blooms, we examined the effects of nitrogen species and concentrations and other environmental factors in influencing cyanobacterial community structure, microcystin (MC) concentrations and MC congener composition. The identification of specific MC congeners was of particular interest as they vary widely in toxicity. Different nitrogen forms appeared to influence cyanobacterial community structure leading to corresponding effects on MC concentrations and composition. Total MC concentrations across the lakes were largely explained by a combination of abiotic factors: dissolved organic nitrogen, water temperature and ammonium, but Microcystis spp. biomass was overall the best predictor of MC concentrations. Environmental factors did not appear to affect MC congener composition directly but there were significant associations between specific MC congeners and particular species. Based on redundancy analyses (RDA), the relative biomass of Microcystis aeruginosa was associated with MC-RR, M. wesenbergii with MC-LA and Aphanizomenon flos-aquae with MC-YR. The latter two species are not generally considered capable of MC production. Total nitrogen, water temperature, ammonium and dissolved organic nitrogen influenced the cyanobacterial community structure, which in turn resulted in differences in the dominant MC congener and the overall toxicity.
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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 | 0.000 | 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 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".