Marked recent increases of colonial scaled chrysophytes in boreal lakes: implications for the management of taste and odour events
Bibliographic record
Abstract
Summary 1. Lake managers suspect that taste and odour‐causing algal blooms are increasing in frequency and intensity, although long‐term monitoring records are scarce, and a number of critical scientific and management questions remain unanswered. 2. In nutrient‐poor lakes and reservoirs, these events are caused primarily by sporadic outbreaks of some chrysophyte algae, which leave identifiable markers in lake sediments. We examine the siliceous remains of these organisms in more than fifty boreal lakes at broad temporal and spatial scales. 3. Colonial scaled chrysophytes, including the taste and odour‐causing Synura petersenii, have increased markedly in more that 90% of the lakes examined since pre‐industrial times. 4. Detailed stratigraphic analyses of two lakes show a rise in the abundance of colonial taxa in the 1930s to 1950s, with a sharp increase over the past two decades. 5. An examination of biogenic silica and biological ratios in Crosson Lake, Ontario, Canada, indicate that these changes represent true increases in the absolute abundance of colonial chrysophytes. 6. Rapid increases over the past two decades indicate that these trends are the result of one or more anthropogenic stressors that are operating at a broad, regional scale.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".