Uropygial gland microbiota differ between free-living and captive songbirds
Bibliographic record
Abstract
Symbiotic microbes can affect host behavior and fitness. Gut microbiota have received the most study, with less attention to other important microbial communities like those of scent-producing glands such as mammalian anal glands and the avian uropygial gland. However, mounting evidence suggests that microbes inhabiting scent-producing glands play an important role in animal behavior by contributing to variation in chemical signals. Free-living and captive conditions typically differ in social environment, food diversity and availability, disease exposure, and other factors-all of which can translate into differences in gut microbiota. However, whether extrinsic factors such as captivity alter microbial communities in scent glands remains an open question. We compared the uropygial gland microbiota of free-living and captive song sparrows (Melospiza melodia) and tested for an effect of dietary manipulations on the gland microbiota of captive birds. As predicted, the uropygial gland microbiota was significantly different between free-living and captive birds. Surprisingly, microbial diversity was higher in captive than free-living birds, and we found no effect of dietary treatments on captive bird microbiota. Identifying the specific factors responsible for microbial differences among groups and determining whether changes in symbiotic microbiota alter behavior and fitness are important next steps in this field.
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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) | 0.001 | 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".