Endangered Deep‐Snow Mountain Caribou Have a Distinct Winter Diet and Gut Microbiome That May Be Altered by Maternal Penning
Bibliographic record
Abstract
Understanding species- or population-specific dietary specialisation is key to informing habitat conservation needs and successful ex situ recovery programs for many endangered species. One of the most endangered populations in Canada, the behaviourally distinct deep-snow ecotype of the Southern Mountain caribou, is characterised by a winter diet of arboreal rather than terrestrial lichens. We hypothesised that this dietary variation would produce a distinct gut microbiome in deep-snow mountain caribou relative to their shallow-snow counterparts. We additionally hypothesised that the temporary alteration of natural diets for ex situ conservation programs, including the provision of commercial pelleted feed and volunteer-collected lichens during maternity penning of pregnant cows, may alter this specialised microbiome. Here, we use faecal DNA metabarcoding to compare diet and gut microbiome composition among various herds of deep- and shallow-snow caribou, captive deep-snow caribou from the Revelstoke maternity pen, and semi-domesticated reindeer. Our results confirm that free-ranging deep-snow caribou specialise on the arboreal hair lichens Bryoria and Nodobryoria, and we show that this correlates with a microbiome distinct from that of shallow-snow caribou specialising on the terrestrial lichens Cladonia and Stereocaulon. We also show that maternity penning of deep-snow caribou significantly altered forage consumption and microbiome composition: penned caribou consumed more foliose lichens and had a distinct microbiome compared to free-ranging caribou. Our results suggest that managers should carefully consider the preferred forage of caribou populations when designing interventions that require diet modification. We further suggest that faecal samples of caribou and other dietary specialists be routinely monitored for diet and microbiome composition, especially during periods of captivity or diet modification, as an additional component of conservation assessments.
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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".