Phylogenies of Microcystin-Producing Cyanobacteria in the Lower Laurentian Great Lakes Suggest Extensive Genetic Connectivity
Bibliographic record
Abstract
Lake St. Clair is the smallest lake in the Laurentian Great Lakes system. MODIS satellite imagery suggests that high algal biomass events have occurred annually along the southern shore during late summer. In this study, we evaluated these events and tested the hypothesis that summer bloom material derived from Lake St. Clair may enter Lake Erie via the Detroit River and represent an overlooked source of potentially toxic Microcystis biomass to the western basin of Lake Erie. We conducted a seasonally and spatially resolved study carried out in the summer of 2013. Our goals were to: 1) track the development of the 2013 summer south-east shore bloom 2) conduct a spatial survey to characterize the extent of toxicity, taxonomic diversity of the total phytoplankton population and the phylogenetic diversity of potential MC-producing cyanobacteria (Microcystis, Planktothrix and Anabaena) during a high biomass event, and 3) compare the strains of potential MC-producers in Lake St. Clair with strains from Lake Erie and Lake Ontario. Our results demonstrated a clear predominance of cyanobacteria during a late August bloom event, primarily dominated by Microcystis, which we traced along the Lake St. Clair coastline downstream to the Detroit River's outflow at Lake Erie. Microcystin levels exceeded the Province of Ontario Drinking Water Quality Standard (1.5 µg L(-1)) for safe drinking water at most sites, reaching up to five times this level in some areas. Microcystis was the predominant microcystin producer, and all toxic Microcystis strains found in Lake St. Clair were genetically similar to toxic Microcystis strains found in lakes Erie and Ontario. These findings suggest extensive genetic connectivity among the three systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".