Passive environmental and group-level processes drive gut microbiome composition in a wild corvid
Bibliographic record
Abstract
BACKGROUND: The gut microbiome is known from laboratory studies to be essential to host function and sociality, yet comparatively little is known about this association in wild animals. In wild birds, the gut microbiome seems to be broadly driven by environmental factors, and there is mixed evidence for a link with sociality. Here, we describe the gut microbiome composition of the Siberian jay (Perisoreus infaustus), a highly social group-living and food-caching corvid of the Eurasian boreal forest. RESULTS: We present evidence of potential environment-related variation in the gut microbiome of wild Siberian jays. Environmental acquisition of microbes may be an important process shaping their gut microbiome composition based on similarities to the local environmental microbial community, for which we propose an environment–oral–gut route as a potential underlying mechanism. We also identify an unexpected group-level convergence, wherein social horizontal transmission of gut microbes may be an incidental consequence of reciprocal cache pilfering among group members. CONCLUSIONS: While the ecological significance of gut microbiome variation in Siberian jays is still unclear, our results paint a picture of passive microbiome assembly resulting from a combination of environmental acquisition and social transmission in a wild bird species.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".