Gut microbiota's temporal dynamics and relationships with individual traits in a wild eastern chipmunk population
Bibliographic record
Abstract
The composition and diversity of the gut microbiota are known to impact host biological processes, and variation among individuals is hypothesized to lead to differences in fitness. However, studies of the gut microbiota in natural contexts are still scarce, and the factors driving individual microbiota variation in wild populations remain unclear. In this study, we sampled the gut microbiota of wild eastern chipmunks (Tamias striatus) over two years to investigate host-related factors influencing microbiota α-diversity and composition. We assessed the relative contribution of individual identity and evaluated the stability of gut microbial communities. We amplified 16S rRNA gene sequences to quantify the bacterial community composition of 436 faecal samples. Our results revealed that juvenile chipmunks exhibited lower bacterial α-diversity compared to adults. Furthermore, the composition of the gut microbiota varied depending on chipmunk behavioural traits, where high exploration speed and centrality were linked to different microbial communities than those associated with trappability and trap diversity within an active season. Additionally, microbiota diversity was stable and highly individualized within a trapping season, though among-individual differences did not persist from one year to the next. Our findings support the relationship between gut microbiota and behaviour in wild mammals and add to the growing evidence that the individual signature of bacterial diversity and composition is time dependant.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".