Straight from the caribou’s (<i>Rangifer tarandus</i>) mouth: detailed observations of tame caribou reveal new insights into summer–autumn diets
Bibliographic record
Abstract
High-quality habitats for caribou (Rangifer tarandus (L., 1758)) are associated primarily with lichens, but lichens alone fail to satisfy summer nutritional requirements. To evaluate the summer forage value of plant communities across northeastern British Columbia (BC), where populations of northern and boreal ecotypes of caribou are declining, we observed foraging by tame, female caribou. We compared diet composition with forage abundance to determine forage selection and to quantify forage availability. Deciduous shrubs, not lichens, largely dominated summer diets. Caribou were highly selective foragers, with 28 species comprising 78% of diets. Caribou avoided ≥50% of understory vegetation in all communities, especially conifers, evergreen shrubs, mosses, and two genera of terrestrial lichens. Availability of accepted forage (species not avoided) was strongly heterogeneous across landscapes. Alpine shrub areas and mid-elevation spruce–fir stands in the mountains, as well as treed rich fens and white spruce communities in the boreal forests, provided the greatest quantities of accepted forage for caribou. Dry alpine sites and unproductive black spruce communities provided the least accepted forage. Our work has direct implications to caribou conservation by contributing to a greater understanding of the forage value of summer habitats, with implications to habitat selection, seasonal movements, and distribution ecology.
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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 | 0.001 | 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".