Temporal patterns of gut microbiota in lemurs (<i>Eulemur rubriventer</i>) living in intact and disturbed habitats in a novel sample type
Bibliographic record
Abstract
The gut microbiome is a plastic phenotype; gut microbial composition is highly variable across an individual host's lifetime and between host social groups, and this variation has consequences for host health. However, we do not yet fully understand how longitudinal microbial dynamics and their social drivers may be influenced by ecological stressors, such as habitat degradation. Answering these questions is difficult in most wild animal systems, as it requires long-term collections of matched host, microbiome, and environmental trait data. To test if temporal and social influences on microbiome composition differ by the history of human disturbance, we leveraged banked, desiccated fecal samples collected over 5 months in 2004 from two ecologically distinct populations of wild, red-bellied lemurs (Eulemur rubriventer) that are part of a long-term study system. We found that social group explained more variation in microbiome composition than host population membership did, and that temporal variation in common microbial taxa was similar between populations, despite differences in history of human disturbance. Furthermore, we found that social group membership and collection month were both more important than individual lemur identity. Taken together, our results suggest that synchronized environments use can lead to synchronized microbial dynamics over time, even between habitats of varying quality, and that desiccated samples could become a viable approach for studying primate gut microbiota. Our work opens the door for other projects to utilize historic biological sample data sets to answer novel temporal microbiome questions in an ecological context.
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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 | 0.000 | 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 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".