Bacteriophage richness reduces bacterial niche overlap in experimental microcosms
Bibliographic record
Abstract
Antagonistic interactions such as competition and predation shape the structure and dynamics of ecological communities. Their combined effects can affect the species richness within a particular trophic level. Despite theory linking the complementarity of interactions across trophic levels and ecosystem functioning, there is a shortage of empirical tests of such predictions. We present an experimental investigation of these combined effects within a bacteria-phage interaction network. We measured the biomass yield of combinations of bacterial strains under increasing levels of bacteriophage richness. Our results show an increasing impact of phage on bacteria with increasing phage diversity. In contrast, no combination of phages significantly changed the overall productivity of bacterial mixed cultures when compared with expectations based on bacterial monocultures. Finally, we found that the addition of phages decreases the realized niche overlap among pair of bacterial species with the greatest reduction occurring when all phages were present. Our results show that the productivity of this system is the results from the combined effects of exploitative (shared resources between bacteria) and apparent (shared phages between bacteria) competition.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".