Factors influencing bacterial microbiome composition in a wild non-human primate community in Taï National Park, Côte d’Ivoire
Bibliographic record
Abstract
Microbiomes impact a variety of processes including a host's ability to access nutrients and maintain health. While host species differences in microbiomes have been described across ecosystems, little is known about how microbiomes assemble, particularly in the ecological and social contexts in which they evolved. We examined gut microbiome composition in nine sympatric wild non-human primate (NHP) species. Despite sharing an environment and interspecific interactions, individuals harbored unique and persistent microbiomes influenced by host species, social group, and parentage, but surprisingly not by social relationships among members of a social group. We found a branching order of host-species networks constructed using the composition of their microbiomes as characters, which was incongruent with known NHP phylogenetic relationships, with chimpanzees (Pan troglodytes verus) sister to colobines, upon which they regularly prey. In contrast to phylogenetic clustering found in all monkey microbiomes, chimpanzee microbiomes were unique in that they exhibited patterns of phylogenetic overdispersion. This reflects unique ecological processes impacting microbiome composition in chimpanzees and future studies will elucidate the aspects of chimpanzee ecology, life history, and physiology that explain their unique microbiome community structure. Our study of contemporaneous microbiomes of all sympatric diurnal NHP in an ecosystem highlights the diverse dispersal routes shaping these complex communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".