Summer diet selection of snowshoe hares: a test of nutritional hypotheses
Bibliographic record
Abstract
We examined summer diet selection by snowshoe hares in the southwestern Yukon, Canada, and attempted to explain how plant qualities such as nutritional content (protein, energy, fiber, water) and defensive compounds affect hare food choice. Male hares were placed in enclosures in natural vegetation areas dominated by shrubs and in both open and closed spruce forests. Each site contained a variety of herbaceous plant species. After 24 h, hares were sacrificed, their stomachs collected, and the contents removed and analyzed. Of the 30 plant species recorded in the enclosures only 10 were identified in the stomach contents of the hares. The summer diet is composed predominantly of five plant species; Lupinus arcticus, Salix spp. Shepherdia canadensis , Betula glandulosa and Festuca altaica. The selection of these species changes between sampling times. Protein, energy and water contents were highest in leaf tissues of most species early in the season, and most species had an increase in fiber through the summer. Protein content consistently explains the largest amount of variation in diet selection, although protein selection is modified by extremely high concentrations of defence compounds. It is likely that hares are not protein limited and are selecting for other plant characteristics correlated with protein content such as energy content. It is significant that hares continue to ingest heavily defended species (e.g. Shepherdia canadensis, B. glandulosa and L. arcticus) when many less defended plants are available to be eaten (e.g. F. altaica, Epilobium latifolium and Anemone parviflora). Our results support the idea that hares are selecting dietary items on the basis of energy content. No single plant species can satisfy all of the hares’ nutritional requirements and the selection patterns may reflect the need to balance many conflicting plant qualities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.002 | 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".