Temporal and Depth‐Driven Variability of Pelagic Bacterial Communities in Lake Erie: Biofilm and Plankton Dynamics
Bibliographic record
Abstract
Despite constituting an important component of freshwater ecosystems, biofilm assemblages have remained relatively understudied compared to plankton, especially in freshwater systems such as the western basin of Lake Erie (WBLE). This study therefore aimed to elucidate temporal and vertical shifts of microbial communities of planktonic and biofilm growth on artificial substrates in the WBLE water column at discrete depths, investigating the overlap of shared taxa between community types. Sequencing of the 16S rRNA gene revealed concurrent biofilm-plankton samples shared a low percentage (~10%) of amplicon sequence variants (ASVs) indicating distinct communities between free-living and substrate-attached bacteria. Plankton communities did not significantly differ between surface and bottom depths (1 and 8 m), whereas biofilm communities differed between upper (1-4 m) and lower (5-8 m) water columns. Temporal variation in community composition was observed in biofilm, with early periods (June-July) showing significant dissimilarity followed by compositional convergence in late summer onwards (August-October). With the expansion of artificial infrastructure in aquatic systems, there is novel substrate material to observe spatiotemporal patterns of microbial colonisation throughout the pelagic zone. These results demonstrate the complexity of bacterial biofilm communities from plankton in freshwater, providing insight into microbial assembly through temporal succession and across depth.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".