Habitat use and home range size of red foxes in Prince Edward Island (Canada) based on snow-tracking and radio-telemetry data
Bibliographic record
Abstract
Abstract There is a lack of information regarding the ecology and behaviour of red foxes that can be used to elaborate effective management programs for this species on Prince Edward Island (Canada). The main goal of this study was to provide baseline information on habitat selection and home range size of red foxes on Prince Edward Island. Data were collected from snow-tracking and radio-telemetry sessions conducted in two study sites (including one site within Prince Edward Island National Park). Our results indicated that red foxes selected for roads and human-use areas during both the breeding and the kit-rearing seasons in the park. Outside the park, however, the data failed to conclusively show that foxes have a unique preference for human-use habitats or roads. Forests were selected against in both study sites. Although roads are frequently visited by foxes during the kit-rearing season in the park, each individual fox typically stays in this habitat only for short periods of time (< 15 min). This finding suggests that foraging efficiency along the roads is very high possibly reflecting the abundance of anthropogenic food sources. Overall, we present the largest amount of data on habitat selection ever collected for red foxes in Prince Edward Island, Canada. Our results show that food sources in human-use areas and roads are altering the selection and/or use of habitats of red foxes in some areas of Prince Edward Island.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".