Habitat selection during ungulate dispersal and exploratory movement at broad and fine scale with implications for conservation management
Bibliographic record
Abstract
BACKGROUND: Dispersal has a critical influence on demography and gene flow and as such maintaining connectivity between populations is an essential element of modern conservation. Advances in satellite radiotelemetry are providing new opportunities to document dispersal, which previously has been difficult to study. This type of data also can be used as an empirical basis for defining landscapes in terms of resistance surfaces, enabling habitat corridors to be identified. However, despite the scale-dependent nature of habitat selection few studies have investigated selection specifically during dispersal. Here we investigate habitat selection during and around dispersal periods as well as the influence of age and sex on dispersal for a large ungulate. RESULTS: Of 158 elk (Cervus elaphus) tracked using GPS radiotelemetry almost all dispersers were males, with individuals dispersing up to 98 km. The dispersal period was distinct, with higher movement rates than before or after dispersal. At fine scale elk avoided the most rugged terrain in all time periods, but to a greater extent during and after dispersal, which we showed using step selection functions. In contrast, habitat selection by resident elk was less affected by ruggedness and more by an attraction to areas of higher forage availability. At the broad scale, however, movement corridors of dispersers were characterized by higher forage availability and slightly lower ruggedness then expected using correlated random walks. CONCLUSIONS: In one of the first examples of its kind we document complete long-distance dispersal events by an ungulate in detail. We find dispersal to be distinct in terms of movement rate and also find evidence that habitat selection during dispersal may differ from habitat selection in the home-range, with potential implications for the use of resistance surfaces to define conservation corridors.
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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 | 0.000 | 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 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".