Nutrient-Controlled Niche Differentiation of Western Lake Erie Cyanobacterial Populations Revealed via Metatranscriptomic Surveys
Bibliographic record
Abstract
Although toxic cyanobacterial blooms in western Lake Erie threaten drinking water supplies and are promoted by nutrient loading, the precise nutrient regime that selects specific cyanobacteria populations is poorly understood. Here, we assess shifts in cyanobacterial abundances and global gene-expression patterns in response to natural and manipulated gradients in nitrogen and phosphorus to identify gene pathways that facilitate dominance by different cyanobacteria. Gradients in soluble reactive phosphorus shaped cyanobacterial communities and elicited the largest transcriptomic responses. Under high-P conditions (closest to the mouth of the Maumee River), Anabaena and Planktothrix were the dominant cyanobacterial populations, and experimental P and ammonium enrichment promoted nitrogen fixation gene (nifH) expression in Anabaena. For Microcystis, experimental additions of P up-regulated genes involved in phage defense, genomic rearrangement, and nitrogen acquisition but led to lower abundances. Within offshore, low-P regions of the western basin of Lake Erie, Microcystis up-regulated genes associated with P scavenging (pstSCAB, phoX) and dominated cyanobacterial communities. Experimental additions of ammonium and urea did not alter Microcystis abundances but did up-regulate protease inhibitors (aer and mcn gene sets) and microcystin synthetase genes (mcy), with urea enrichment yielding significant increases in microcystin concentrations. Our findings suggest that management plans that reduce P loads alone may not significantly reduce the risk of cyanobacterial blooms in western Lake Erie but rather may promote a shift among cyanobacterial populations (Microcystis, Anabaena, and Planktothrix) toward a greater dominance by toxic strains of Microcystis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".