Gut microbiota composition in the sympatric and diet‐sharing <i>Drosophila simulans</i> and <i>Dicranocephalus wallichii bowringi</i> shaped largely by community assembly processes rather than regional species pool
Bibliographic record
Abstract
Abstract Clarifying the mechanisms underlying microbial community assembly from regional microbial pools is a central issue of microbial ecology, but remains largely unexplored. Here, we investigated the gut bacterial and fungal microbiome assembly processes and potential sources in Drosophila simulans and Dicranocephalus wallichii bowringi, two wild, sympatric insect species that share a common diet of waxberry. While some convergence was observed, the diversity, composition, and network structure of the gut microbiota significantly differed between these two host species. Null model analyses revealed that stochastic processes (e.g., drift, dispersal limitation) play a principal role in determining gut microbiota from both hosts. However, the strength of each ecological process varied with the host species. Furthermore, the source‐tracking analysis showed that only a minority of gut microbiota within D. simulans and D. wallichii bowringi are drawn from a regional microbial pool from waxberries, leaves, or soil. Results from function prediction implied that host species‐specific gut microbiota might arise partly through host functional requirement and specific selection across host–microbiota coevolution. In conclusion, our findings uncover the importance of community assembly processes over regional microbial pools in shaping sympatric insect gut microbiome structure and function.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".