DNA metabarcoding of faecal pellets reveals high consumption of yew (<i>Taxus</i> spp.) by caribou (<i>Rangifer tarandus</i>) in a lichen-poor environment
Bibliographic record
Abstract
Woodland caribou ( Rangifer tarandus caribou) are threatened in Canada because of the drastic decline in population size caused primarily by human-induced landscape changes that decrease habitat and increase predation risk. Conservation efforts have largely focused on reducing predators and protecting critical habitat, whereas research on dietary niches and the role of potential food constraints in lichen-poor environments is limited. To improve our understanding of dietary niche variability, we used a next-generation sequencing approach with metabarcoding of DNA extracted from faecal pellets of woodland caribou located on Lake Superior in lichen-rich (mainland) and lichen-poor (island) environments. Amplicon sequencing of fungal ITS2 region revealed lichen-associated fungi as predominant in samples from both populations, but amplification at the chloroplast trnL region, which was only successful on island samples, revealed primary consumption of yew ( Taxus spp.) based on relative read abundance (83.68%) with dogwood ( Cornus spp.; 9.67%) and maple ( Acer spp.; 4.10%) also prevalent. These results suggest that conservation efforts for caribou need to consider the availability of food resources beyond lichen to ensure successful outcomes. More broadly, we provide a reliable methodology for assessing ungulate diet from archived faecal pellets that could reveal important dietary shifts over time in response to climate change.
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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 | 0.001 | 0.001 |
| 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".