Influence of Season and Diet on Fiber Digestion and Bacterial Community Structure in the Rumen of Muskoxen (Ovibos moschatus)
Bibliographic record
Abstract
We studied the relationship between fiber digestion and the composition of the bacterial community in the rumen of muskoxen at the start and the end of the annual window of plant growth from spring to fall. Eight ruminally cannulated castrated males were fed brome hay or triticale straw (69.6% vs. 84.6% neutral detergent fiber, respectively) that were similar in fiber content to the sedges consumed by wild muskoxen (64.5 to 71.7% neutral detergent fiber). Muskoxen digested fiber from both forages faster and to a greater extent when straw rather than hay was consumed. Fiber digestion was therefore inducible by diet 4 in each season. We used 16S rRNA sequences from ruminal contents to study how season and diet affected the bacterial community and how the latter related to fiber digestion. We found that Bacteroidetes and Firmicutes accounted for 90% of the sequences at the level of Phylum, which is typical for the mammal gut microbiome. Using partial least square regressions, it was found that between 48% and 72% of the variation in fiber digestion was associated with 36⁻43 genera of bacteria. The main fibrolytic bacteria typical of domestic ruminants were generally not among the most important bacteria associated with fiber digestion in muskoxen. This reveals that muskoxen rely upon on a large suite of bacterial genera that are largely distinct from those used by other ruminants to digest the cell walls of plants that vary widely in both abundance and nutritional quality through the year.
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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".