Extreme variability of cyanobacterial blooms in an urban drinking water supply
Bibliographic record
Abstract
Harmful cyanobacterial blooms are of increasing global concern and their prediction and management requires an improved understanding of the controlling factors for cyanobacterial growth and dominance. In Lake St Charles, the drinking water supply for Quebec City, Canada, harmful cyanobacterial blooms were first recorded in autumn 2006. Our aims were to define the temporal and spatial variations in the cyanobacterial community structure of this reservoir and to address the hypothesis that interannual variability in cyanobacterial biomass and species composition is mainly controlled by nutrients, temperature and water column stratification. Over five consecutive summers (2007–2011), the north basin had consistently higher concentrations of bloom-forming cyanobacteria than the south basin, and there were striking variations within and among years in total biomass and species composition. Correlation analysis underscored the contrasting environmental controls on different taxa of colonial cyanobacteria. Anabaena flos-aquae biovolume was correlated with surface temperature, water column stability (Schmidt index) and water residence time whereas Microcystis aeruginosa was highly correlated with total phosphorus and to a lesser extent with total nitrogen (TN), heat accumulation (degree-days above 20°C) and precipitation. Aphanocapsa/Aphanothece correlated significantly only with TN. These results also imply the sensitivity of high through-flow reservoir ecosystems to interannual variations in environmental forcing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".