Movement and Spread of a Founding Population of Reintroduced Elk (<i>Cervus elaphus</i>) in Ontario, Canada
Bibliographic record
Abstract
Monitoring the distribution and movements of a species following reintroduction can aid resource managers in assessing release‐site fidelity, rates of spread, initial project success, and feasibility of (or need for) future releases. We used radio‐telemetry to monitor an entire founding population of 70 elk (Cervus elaphus) during 16 months following their reintroduction to eastern Ontario, Canada. At the end of the study, elk were widely scattered over a 27,000 km2area. Dispersal distances ranged from 2 to 142 km; 50% of animals moved >40 km from the release site. Dispersal distances differed by time periods and age but not sex. Calves dispersed significantly shorter distances than adults and many mature elk were isolated during the rut. In contrast to a random distribution model, movements had a strongly southwestern directional bias, perhaps owing to prevailing winds from the same direction. Mortality during the study period was 27%; the primary causes of known mortalities were emaciation, collision with automobiles, and illegal shooting. During the first 11 / 2 years, lack of release‐site fidelity and high dispersal coupled with animal‐human conflicts and mortalities likely contributed to an initial lag in population growth. Resource managers planning animal reintroductions should consider using methodologies that enhance site fidelity following release.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".