Winter Resource Selection of Reintroduced Elk and Sympatric White-tailed Deer at Multiple Spatial Scales
Bibliographic record
Abstract
Understanding limiting factors and interspecific interactions is fundamental to wildlife management and can be inferred from multiscale patterns of resource selection. We studied winter resource selection and overlap of white-tailed deer (Odocoileus virginianus) and translocated female elk (Cervus elaphus) over 2 winters in central Ontario, Canada. Microhabitat data were collected along 4 organism-centered spatial scales: site, trail, feeding station, and diet. Although winter conditions varied between years, white-tailed deer consistently traveled and fed in habitats with greater coniferous basal area than elk. Neither species demonstrated selection for coniferous basal area or snow depth across scales. At successively finer scales, female elk selected increased understory cover of trembling aspen (Populus tremuloides). For white-tailed deer, across-scale selection of sugar maple (Acer saccharum) understory cover was exhibited when winter conditions were more severe. Dietary overlap was moderate during both winters (50–57%) and coniferous forage was more important to deer than elk. Using canonical variate analysis, a gradient from shade-intolerant hardwoods to mature coniferous vegetation was found to discriminate significantly between elk and deer habitat use at trails and feeding stations. These results indicate that deer were closely associated with conifers regardless of winter conditions and that both ungulates may have been limited by forage abundance.
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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 | 0.001 | 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) | 0.001 | 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 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".