Tracking the upstream history of aquatic microbes in a boreal lake yields new insights on microbial community assembly
Bibliographic record
Abstract
Bacterial community structure can change rapidly across short spatial and temporal scales as environmental conditions vary, but the mechanisms underlying those changes are still poorly understood. Here, we assessed how a lake microbial community assembles by following its reorganization from the main tributary, which, when flowing into the lake, first traverses an extensive macrophyte-dominated vegetated habitat, before reaching the open water. Environmental conditions in the vegetated habitat changed drastically compared to both river and lake waters and represented a strong environmental gradient for the incoming bacteria. We used amplicon sequencing of the 16S rRNA gene and transcript to reconstruct the shifts in relative abundance of individual taxa and link this to their pattern in activity (here assessed with RNA:DNA ratios). Our results indicate that major shifts in relative abundance were restricted mostly to rare taxa (<0.1% of relative abundance), which seemed more responsive to environmental changes. Dominant taxa (>1% of relative abundance), on the other hand, traversed the gradient mostly unchanged with relatively low and stable RNA:DNA ratios. We also identified a high level of local recruitment and a seedbank of taxa capable of activating/inactivating, but these were almost exclusively associated with the rare biosphere. Our results suggest a scenario where the lake community results from a reshuffling of the rank abundance structure within the incoming rare biosphere, driven by selection and growth, and that numerical dominance is not a synonym of activity, growth rate, or environmental selection, but rather reflect mass effects structuring these freshwater bacterial 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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".