Overwinter mass loss of snowshoe hares in the Yukon: starvation, stress, adaptation or artefact?
Bibliographic record
Abstract
1. Overwinter mass loss can reduce energetic requirements in mammals (Dehnel's phenomenon). Alternatively, mass loss can result from food limitation or high predation risk. 2. We use data from fertilizer, food-supplementation and predator-exclusion experiments in the Yukon during a population cycle from 1986 to 1996 to test the causes of overwinter mass loss by snowshoe hares (Lepus americanus). In all years, some hares on control sites gained mass overwinter. During the increase phase the majority gained mass, but in all other phases the majority lost mass. 3. Snowshoe hares weighing <1000 g in autumn always gained mass overwinter, as did the majority that weighed 1000-1400 g. Hares weighing >1800 g in autumn usually lost mass. 4. Snowshoe hares on the predator-exclosure + food site gained mass overwinter in all years. Hares on the food-supplementation sites lost mass during the decline but gained mass in all other phases. Fertilization had little effect on mass dynamics. 5. Snowshoe hares were more likely to lose mass during winters with low survival rates. Snowshoe hares on the predator-exclosure treatments were more likely to gain mass than were hares on control sites. 6. Overwinter mass loss was correlated with maximum snow depth. At equivalent snow depths, hares on food-supplemented areas lost 98 g (+/- 14.6 SE) less on average than hares on the controls and predator-exclosure treatment. 7. Bone-marrow fat was related to body mass and cause of death. Small hares had the lowest marrow fat. Hares killed by humans had higher marrow fat than those killed by predators; hares that simply died had the lowest marrow fat. Hares on food-supplemented sites had the highest kidney and marrow fat. 8. Overwinter-mass loss for snowshoe hares is explained interactively by winter conditions, food supply, predation risk and autumn mass. Some snowshoe hares lost mass overwinter in all years and on all treatments, suggesting that reducing body mass may facilitate survival, especially in cases where foraging costs are high energetically or increase predation risk.
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 | 0.001 | 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) | 0.003 | 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".