Spatial and temporal interactions between female American black bears in mixed forests of eastern Canada
Bibliographic record
Abstract
Few studies have examined in detail the spacing patterns of American black bears (Ursus americanus), especially populations protected from hunting. We radio-tracked bears between 1990 and 1992 in La Mauricie National Park in southern Quebec to study their social interactions. We measured the zone of overlap between home-range core areas and evaluated the spatial and temporal use of the overlap zones for 12 adult females radio-tracked during 1992. The proportion of overlap between the core areas used by 22 pairs of females was variable but low (14.2 ± 17.6% (mean ± SD)). This proportion did not differ (p > 0.05) from that obtained from a random distribution of home ranges (17.1 ± 17.1%). For 12 (55%) of 22 pairs with overlapping core areas, at least one of the females was significantly attracted by the overlap zone, whereas one of the females of another pair significantly avoided it. Significant simultaneous use of the overlap zone was observed for 7 pairs and significant temporal avoidance of the overlap zone was noted for 1 pair. The overlap zone contained a significantly higher proportion of food-producing cover types (maplebeech and early-successional stands) than the overall study area. Our results indicate that although most females did not share a large proportion of their core area with their neighbours, the overlap zone was used intensively for foraging by more than one bear, often simultaneously. Some aggressive behaviours were noted when bears were seen foraging simultaneously in the same area. We discuss the influence of spatial and temporal interactions on the regulation of this unhunted population.
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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 | 0.001 | 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".