Terrestrial connectivity, upstream aquatic history and seasonality shape bacterial community assembly within a large boreal aquatic network
Bibliographic record
Abstract
During transit from soils to the ocean, microbial communities are modified and re-assembled, generating complex patterns of ecological succession. The potential effect of upstream assembly on downstream microbial community composition is seldom considered within aquatic networks. Here, we reconstructed the microbial succession along a land-freshwater-estuary continuum within La Romaine river watershed in Northeastern Canada. We captured hydrological seasonality and differentiated the total and reactive community by sequencing both 16 S rRNA genes and transcripts. By examining how DNA- and RNA-based assemblages diverge and converge along the continuum, we inferred temporal shifts in the relative importance of assembly processes, with mass effects dominant in spring, and species selection becoming stronger in summer. The location of strongest selection within the network differed between seasons, suggesting that selection hotspots shift depending on hydrological conditions. The unreactive fraction (no/minor RNA contribution) was composed of taxa with diverse potential origins along the whole aquatic network, while the majority of the reactive pool (major RNA contribution) could be traced to soil/soilwater-derived taxa, which were distributed along the entire rank-abundance curve. Overall, our findings highlight the importance of considering upstream history, hydrological seasonality and the reactive microbial fraction to fully understand microbial community assembly on a network scale.
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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 | 0.001 |
| 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".