Gut microbiome composition predicts summer core range size in two divergent ungulates
Bibliographic record
Abstract
The gut microbiome of animals vary by age, diet, and habitat, and directly influences an individual's health. Similarly, variation in home ranges is linked to feeding strategies and fitness. Ungulates (hooved mammals) exhibit species-specific microbiomes and habitat use patterns. We combined gut microbiome and movement data to assess relationships between space use and the gut microbiome in a specialist and a generalist ungulate. We GPS radiocollared 24 mountain goats (Oreamnos americanus) and 34 white-tailed deer (Odocoileus virginianus), collected fecal samples, and conducted high-throughput sequencing of the 16S rRNA gene. We generated gut diversity metrics and key bacterial ratios. Our research question centred around the idea that larger Firmicutes to Bacteroidetes ratios confer body size or fat advantages that allow for larger home ranges, and relationships of disproportionate habitat use are stronger in the habitat specialist mountain goat. Firmicutes to Bacteroidetes ratios were positively correlated with core range area in both species. Mountain goats exhibited a negative relationship between gut diversity and proportional use of treed areas and escape terrain, and no relationships were detected in the habitat generalist white-tailed deer. This is the first study to relate range size to the gut microbiome in wild ungulates and is an important proof of concept that advances the information that can be gleaned from non-invasive sampling.
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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) | 0.001 | 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 | 0.001 | 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 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".