Algal blooms in Ontario, Canada: Increases in reports since 1994
Bibliographic record
Abstract
The Ontario Ministry of the Environment provides an algal identification service as part of the Ministry's response to algal bloom events, and we have been tracking the reports since 1994. From 1994 through 2009, we noted a significant increase in the number of algal blooms reported each year (P < 0.001). There was also an increase in the number of blooms in which cyanobacteria were dominant (P < 0.001), with these samples making up >50% of the total during peak years. The most common taxa of cyanobacteria identified were Anabaena, Aphanizomenon, Microcystis, Gloeotrichia, and various Oscillatoriales. The remaining samples were dominated by filamentous green algae, or occasionally by chrysophytes. We also noted geographic and seasonal trends in the bloom reports. Most of the increase in the number of cyanobacterial bloom reports was accounted for from lakes on the Canadian Shield (located within the boundary of the Ministry's Northern Region). Algal blooms are now being reported later into the fall than they were during the 1990s; bloom reports have extended well into November in recent years. We attributed these trends to (1) increased nutrient inputs in some areas, which promote the growth of algae; (2) factors associated with climate warming, which may exacerbate bloom conditions; and (3) an increase in public awareness of algal issues. An increase in algal bloom reports is a management issue in Ontario, and blooms of potentially toxin-producing cyanobacteria prompted a formal response protocol to be followed.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".