Ironing Out the Question: What is Limiting Cyanobacteria in Freshwater Lakes in the Prairie Pothole Region?
Bibliographic record
Abstract
The Canadian Prairie Pothole Region is a hotspot for cyanobacteria-dominated lakes. Our study found significant differences in cyanobacteria biomass within lakes ranging from oligotrophic to hyper-eutrophic classifications. A correlational analysis of total phosphorus (TP) and total nitrogen (TN) revealed that limiting nutrients varied considerably across the region. Iron (Fe) emerged as the most likely limiting nutrient in lakes not limited by P or N. During Fe stress, cyanobacteria can create biomass by producing Fe-scavenging siderophores. However, in neither P- nor N-limited lakes, a lack of correlation (r = 0.05) indicated that siderophores could not scavenge Fe and produce further cyanobacterial biomass. Our findings suggest that Fe-starved eutrophic lakes exhibit a paradox of slow-growing, high cyanobacterial biomass, challenging the notion that only oligotrophic lakes embody slow-growing metabolisms. Our study highlights the importance of incorporating micro-nutrient (Fe) limitations into existing nutrient management strategies to mitigate cyanobacterial dominance effectively.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".