Multiple movement modes by large herbivores at multiple spatiotemporal scales
Bibliographic record
Abstract
Recent theory suggests that animals should switch facultatively among canonical movement modes as a complex function of internal state, landscape characteristics, motion capacity, and navigational capacity. We tested the generality of this paradigm for free-ranging elk (Cervus elaphus) over 5 orders of magnitude in time (minutes to years) and space (meters to 100 km). At the coarsest spatiotemporal scale, elk shifted from a dispersive to a home-ranging phase over the course of 1-3 years after introduction into a novel environment. At intermediate spatiotemporal scales, elk continued to alternate between movement modes. During the dispersive phase, elk alternated between encamped and exploratory modes, possibly linked to changes in motivational goals from foraging to social bonding. During the home-ranging phase, elk movements were characterized by a complex interplay between attraction to preferred habitat types and memory of previous movements across the home-range. At the finest temporal and spatial scale, elk used area-restricted search while browsing, interspersed with less sinuous paths when not browsing. Encountering a patch of high-quality food plants triggered the switch from one mode to the next, creating biphasic movement dynamics that were reinforced by local resource heterogeneity. These patterns suggest that multiphasic structure is fundamental to the movement patterns of elk at all temporal and spatial scales tested.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".