Symbiotic microbiota vary with breeding group membership in a highly social joint-nesting bird
Bibliographic record
Abstract
Abstract Symbiotic microbes affect the health, fitness, and behavior of their animal hosts, and can even affect the behavior of non-hosts. Living in groups presents numerous benefits and challenges to social animals, including exposure to symbiotic microbes, which can mediate both cooperation and competition. In social mammals, individuals from the same social group tend to share more similar microbes and this social microbiome, the microbial community of all hosts in the same social group, can shape the benefits and costs of group living. In contrast, little is known about the social microbiome of group living birds. We tested the predictions that communally breeding smooth-billed anis (Crotophaga ani) belonging to the same breeding group share more similar microbes and that microbial community composition differs between body regions. To test this, we used 16S rRNA gene sequencing to characterize the preen gland and body feather microbiota of adult birds from 16 breeding groups at a long-term study site in southwestern Puerto Rico. As predicted, individuals from the same breeding group shared more similar microbiota than non-group members and preen gland and body feathers harbored distinct microbial communities. Future research will evaluate whether this social microbiome affects the behavior of group living birds.
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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".