Upwelling periodically disturbs the ecological assembly of microbial communities in Lake Ontario
Bibliographic record
Abstract
Abstract The Laurentian Great Lakes hold 21% of the world’s surface freshwater and supply drinking water to nearly 40 million people. We provide the first evidence that wind-driven upwelling restructures microbial communities in Lake Ontario, with its effects sustained and redistributed by an internal Kelvin wave propagating along the shoreline. We combine 16S rRNA metabarcoding, absolute abundance quantification via flow cytometry, and hydrodynamic profiling to link physical processes to community composition. While thermal stratification organizes microbial communities by depth and season, this vertical structure arises from contrasting mechanisms: homogenizing selection in surface waters and dispersal limitation and drift in the hypolimnion. Kelvin wave-driven upwelling disrupts this scaffold, displacing rare taxa into the surface and creating novel coastal communities predicted to be enriched in methane oxidation and sulfur metabolism genes—functional traits absent elsewhere in the lake. We observed a Kelvin wave lasting over two weeks and propagating eastward at ∼60 km day⁻¹. Given the ∼10–12 day recurrence of wind events during the stratified season, at any time at least one segment of Lake Ontario’s coastline is experiencing upwelling. These recurrent upwellings, sustained and redistributed by Kelvin waves, remodel microbial communities on ecologically relevant timescales. They act as a biological disturbance overriding stratification, mobilizing rare functional potential, and assembling novel coastal microbial communities. As climate change lengthens and intensifies stratified periods and reshapes large-lake circulation, understanding how physical forcing governs microbial assembly is essential for forecasting the biogeochemical future of Earth’s great lakes—especially in shoreline zones where ecological shifts directly affect human communities.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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".