Seasonal variation in size and composition of elk (<i>Cervus canadensis</i>) home range in central Appalachia
Bibliographic record
Abstract
Home ranges are vitally important to an animal's behavior, survival, and reproduction. Variation in environmental conditions and landscape composition coupled with differences between sexes can influence home range structure, and understanding these differences is important for species management. Elk ( Cervus canadensisErxleben, 1777) are a widespread culturally important ungulate that has been well studied over portions of its range. Reintroduced populations in eastern North America, where conditions differ dramatically from those in the west, are comparatively understudied. Using Ornstein–Uhlenbeck movement models, we calculated season- and sex-specific home range and core areas for elk in Pennsylvania, USA. Results showed strong seasonal variation in sizes of core areas and home ranges, with summer ranges consistently smaller than other seasons. Home ranges were largely forested. However, forest cover of core areas was lower than home ranges. Proportion of open cover types was greater in core areas than home ranges. Use of timber harvests overall was low. However, among individuals with highly forested home ranges, timber harvests were strongly selected for in spring. This work highlights the regional specificity in the size, composition, and seasonality of elk home ranges, and stresses the need for additional context-specific research in understudied elk populations of forested eastern landscapes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".