Bibliographic record
Abstract
I examined the effects of predation risk on the behaviour and population dynamics of snowshoe hares (Lepus americanus) during a cyclic peak and decline (1989-1993) near Kluane Lake, Yukon. Like most heavily preyed upon animals, snowshoe hares have to balance conflicting demands of obtaining food at a high rate and avoiding predators. The consequences of adopting predator avoidance behaviours under high risk of predation in winter may influence population dynamics of hares. Changes in patterns of winter habitat use, survival, body mass, and female reproduction were compared on four experimental areas: (i) where predation risk was reduced by excluding-out terrestrial predators (FENCE), (ii) where food supply was supplemented with ad lib rabbit chow (FOOD), (iii) a combination of these two treatments (FENCE+FOOD), and (iv) an unmanipulated CONTROL. Three hypotheses were compared. The food hypothesis predicts that hares use habitats with the highest amounts of food: body mass remains high, but survival is reduced. The predator avoidance hypothesis predicts that hares use habitats with the lowest risk: survival is high, but body mass decreases. The predation-sensitive foraging (PSF) hypothesis predicts that both survival and body mass decline because a trade-off exists between predation risk and food availability. At peak densities hares used open habitats where food was readily available. However, as predation risk increased during the population decline, hares increased their use of safer, closed habitat and shifted their diet to include a greater proportion of poorer quality spruce twigs. This change in behaviour resulted in lower female body mass and reduced fecundity on the CONTROL area, even though sufficient winter forage was available. A similar decrease in body mass was observed on the FOOD treatment during the third year of the population decline. On FENCE+FOOD, female body mass and fecundity remained high during the decline. Similarly, body mass did not decline on the FENCE treatment. These results supported the PSF hypothesis where terrestrial predators were present (CONTROL and FOOD), and the food hypothesis where terrestrial predators were absent (FENCE and FENCE+FOOD). Hares appear to have a limited ability to reduce exposure to predators because they have no absolutely safe refuge from predators, and they have limited reserves of energy during winter. Preliminary evidence suggests that physiological stress associated with high risk and poor condition is elevated during the population decline. I suggest that deleterious maternal effects mediated by predation risk may introduce a lag of one generation into the 10- year population cycle of snowshoe hares.
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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) | 0.019 | 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".