Cyanobacterial blooms in oligotrophic lakes: Shifting the high‐nutrient paradigm
Bibliographic record
Abstract
Abstract Freshwater cyanobacterial blooms have become ubiquitous, posing major threats to ecological and public health. Decades of research have focused on understanding drivers of these blooms with a primary focus on eutrophic systems; however, cyanobacterial blooms also occur in oligotrophic systems, but have received far less attention, resulting in a gap in our understanding of cyanobacterial blooms overall. In this review, we explore evidence of cyanobacterial blooms in oligotrophic freshwater systems and provide explanations for those occurrences. We show that through their unique physiological adaptations, cyanobacteria are able to thrive under a wide range of environmental conditions, including low‐nutrient waterbodies. We contend that to fully understand cyanobacterial blooms, and thereby mitigate and manage them, we must expand our inquiries to consider systems along the trophic gradient, and not solely focus on eutrophic systems, thus shifting the high‐nutrient paradigm to a trophic‐gradient paradigm .
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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) | 0.002 | 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".