Metabolic insight into bacterial community assembly across ecosystem boundaries
Bibliographic record
Abstract
ABSTRACT The movement of organisms across habitat boundaries has important consequences for populations, communities, and ecosystems. However, because most species are not well adapted to all habitat types, dispersal into suboptimal habitats could induce physiological changes associated with persistence strategies that influence community assembly. For example, high rates of cross-boundary dispersal are thought to maintain sink populations of terrestrial bacteria in aquatic habitats, but these bacteria may also persist by lowering their metabolic activity, introducing metabolic heterogeneity that buffers the population against niche selection. To differentiate between these assembly processes, we analyzed bacterial composition along a hydrological flow path from terrestrial soils through an aquatic reservoir by sequencing the active and total (active + inactive) portions of the community. When metabolic heterogeneity was ignored, our data were consistent with views that cross-boundary dispersal is important for structuring aquatic bacterial communities. In contrast, we found evidence for strong niche selection when metabolic heterogeneity was explicitly considered, suggesting that, relative to persistence strategies, dispersal may have a weaker effect on aquatic community assembly than previously thought. By accounting for metabolic heterogeneity in complex communities, our findings clarify the roles of local- and regional-scale assembly processes in terrestrial-aquatic meta-ecosystems.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".