Lifestyle preferences drive the structure and diversity of bacterial and archaeal communities in a small riverine reservoir
Bibliographic record
Abstract
Spatial heterogeneity along river networks is interrupted by dams, affecting the transport, processing, and storage of organic matter, as well as the distribution of biota. We here investigated the structure of planktonic (free-living, FL), particle-attached (PA) and sediment-associated (SD) bacterial and archaeal communities within a small reservoir. We combined targeted-amplicon sequencing of bacterial and archaeal 16S rRNA genes in the DNA and RNA community fractions from FL, PA and SD, followed by imputed functional metagenomics, in order to unveil differences in their potential metabolic capabilities within the reservoir (tail, mid, and dam sections) and lifestyles (FL, PA, SD). Both bacterial and archaeal communities were structured according to their life-style preferences rather than to their location in the reservoir. Bacterial communities were richer and more diverse when attached to particles or inhabiting the sediment, while Archaea showed an opposing trend. Differences between PA and FL bacterial communities were consistent at functional level, the PA community showing higher potential capacity to degrade complex carbohydrates, aromatic compounds, and proteinaceous materials. Our results stressed that particle-attached prokaryotes were phylogenetically and metabolically distinct from their free-living counterparts, and that performed as hotspots for organic matter processing within the small reservoir.
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 | 0.000 |
| 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 | 0.001 | 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".