Habitat preferences of adult Canada Jays (<i>Perisoreus canadensis</i>) during the post-breeding period in Algonquin Provincial Park, Ontario, Canada
Bibliographic record
Abstract
Habitat preferences in animals are often examined during the breeding period when individuals are easier to observe. However, habitat use may change once young become independent and if resource availability shifts with seasonality. While Canada Jays ( Perisoreus canadensis (Linnaeus, 1766)) in Algonquin Provincial Park, Ontario, Canada, have been studied for several decades, there is no information on habitat use outside of the fall and late-winter nesting period, where they primarily used conifer forests. Using radio telemetry and resource selection functions comparing used versus available habitats, we estimated home-range size and habitat preferences of 12 adult Canada Jays ( n = 334 locations) in the spring and summer. Mean (±SD) home-range size from minimum convex polygons was 84 (±48 ha) and ranged from 35 to 201 ha. Canada Jays strongly preferred forest–wetland edges, showed a weak preference for coniferous forests, a corresponding weak avoidance of shade-tolerant hardwood forests, and used mixed forest and wetlands in proportion to their availability. Our results suggest that, while adult Canada Jays use multiple types of habitat during the post-breeding period, they also key into forest–wetland edges, likely to take advantage of emergent prey while remaining near forested areas to maximize protection from predators.
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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 | 0.000 | 0.000 |
| 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".