Terrestrialization of sediment bacterial assemblages when temporary rivers run dry
Bibliographic record
Abstract
Bacterial communities in river sediments are shaped by a trade-off between dispersal from upstream or nearby land and selection by the local environmental conditions. In temporary rivers (i.e. those characterized by long drying periods and subsequent rewetting) seasonal hydrological dynamics shape bacterial communities by connecting or disconnecting different river habitats. In this study, we tracked and compared the temporal and spatial changes in the composition of bacterial communities in streambed sediments and floodplain habitats across both permanent and intermittent river segments. Our findings revealed that environmental selection played a key role in assembling bacterial communities in both segments. We argue that distinct environmental features act as filters at the local scale, favoring specific bacterial taxa in isolated pools and promoting some typically terrestrial taxa in dry areas. Considering the prospective extension of drying intervals due to climate change, our results suggest an emerging trend wherein bacterial assemblages in temporary streams progressively incorporate microorganisms of terrestrial origin, well-adapted to tolerate desiccation phases. This phenomenon may constitute an integral facet of the broader adaptive dynamics of temporary river ecosystems in response to the impacts of climate change.
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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 | 0.001 |
| 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".