Iron and iron‐binding ligands as cofactors that limit cyanobacterial biomass across a lake trophic gradient
Bibliographic record
Abstract
Summary The frequency and intensity of cyanobacterial blooms (cyanoblooms) is increasing globally. While cyanoblooms in eutrophic (nutrient‐rich) freshwater lakes are expected to persist and worsen with climate change projections, many of the ‘new’ cyanobloom reports pertain to oligotrophic (nutrient‐poor) freshwater lakes with no prior history of cyanobloom occurrence. Iron ( F e) is required in nearly all pathways of cyanobacterial macronutrient use, although its precise role in regulating cyanobacterial biomass across a lake trophic gradient is not fully understood. In all lakes sampled representing a gradient in trophic status from oligotrophic to hypereutrophic (2.2–561.2 μg L −1 total phosphorus), the relative cyanobacterial biomass was highest at low predicted Fe bioavailability in eutrophic A lberta lakes (<1.0 × 10 −22 mol L −1 ) and low F e concentration in oligotrophic O ntario L akes (<3.2 μg L −1 ). Fe‐binding organic ligands were measured within this range of low bioavailable F e. Concentrations of ligands with reactive hydroxamate moieties were positively correlated to cyanobacterial biomass in lakes with low F e bioavailability and supply, suggesting a possible cellular origin (i.e. siderophores) mediated by low F e. These findings suggest that F e serves as a possible cofactor that maintains cyanobacterial biomass across a lake trophic gradient and that cyanobacteria invoke a similar F e‐scavenging system to overcome F e limitation in lakes of all trophic states.
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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) | 0.001 | 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 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".