The spatiotemporal distribution of potential saxitoxin-producing cyanobacteria in western Lake Erie
Bibliographic record
Abstract
Cyanobacterial blooms in the western basin of Lake Erie have been well studied with a focus on planktonic Microcystis and the cyanotoxin microcystin, but recent research has shown that blooms are not entirely Microcystis. Previous studies have documented other taxa in blooms capable of producing other cyanotoxins. Furthermore, benthic cyanobacteria have historically been overlooked in Lake Erie. Saxitoxin is a cyanotoxin of emerging concern in freshwater, and the sxtA gene which encodes its production has been found in the Maumee River and central basin of Lake Erie. Collectively, these points indicated that saxitoxin-producing cyanobacteria may also occur in the western basin. We utilized three sources of data to determine the spatial and temporal distribution of potential saxitoxin-producing cyanobacteria in the water column (years 2018–2022) and deployed nutrient diffusing substrata (NDS) to determine the impact of nutrients, depth, and season on potential-STX producing benthic cyanobacteria (years 2018 & 2019). The water column datasets showed that “hotspots” of sxtA lasted only a few weeks. sxtA gene copies per mL did not correlate with Dolichospermum or Aphanizomenon biovolume, which have been associated with sxtA elsewhere. In the NDS, saxitoxin (ng/cm2) and cyanobacteria chlorophyll were inversely correlated with the highest saxitoxin in September and at the deeper depth, whereas cyanobacteria chlorophyll was highest during June and at the shallower depth. This research suggests continued monitoring is needed to determine drivers of saxitoxin in the western basin, and we recommend that future Lake Erie cyanobacteria research should not solely focus on microcystins and planktonic blooms.
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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 | 0.005 | 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 | 0.000 |
| 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 | 0.000 |
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".