Winter foraging strategy of white-tailed deer at the northern limit of its range
Why this work is in the frame
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Bibliographic record
Abstract
:In winter ungulates must compete for forage of low quality that may be energetically costly to obtain due to high locomotion costs associated with snow. We hypothesized that white-tailed deer would select plant species and plant parts to maximize their net energy budget based on snow conditions and forage availability. We predicted that as winter progress or under deep snow conditions, deer would 1) reduce selectivity, 2) enlarge bite size, and 3) increase cropping rate. For three winters, we studied white-tailed deer found in the Pohénégamook wintering area (southeastern Québec), at the northeastern periphery of the species range. Utilization rates of plant species varied in relation to fibre contents but were not related to protein, ash, or phenolic contents, suggesting that energy represented the key nutritive element during winter. Deer were less selective as winter progressed and snow depth increased. Deer consumed all available plant species, but their foraging strategy was centred around deciduous twigs; deer were reluctant to increase the amount of coniferous twigs in their diet. However, snow conditions affected diet composition. During a very mild winter, deer reduced their intake of balsam fir and consumed some species that were likely unavailable when snow was deep. Bite size increased over the winter, whereas cropping rate increased with snow sinking depth. To cope with changing locomotion costs in snow, white-tailed deer adjusted three variables: travelling distance, forage intake, and cropping rate.
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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) | 0.003 | 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 it