Coyote Habitat Selection and Management Implications for the Gaspésie Caribou
Bibliographic record
Abstract
ABSTRACT Anthropogenic disturbances can promote establishment and growth of predator populations in areas where secondary prey can then become threatened. In this study, we investigated habitat selection of eastern coyotes ( Canis latrans ), a relatively new predator in the vicinity of an endangered population of caribou ( Rangifer tarandus caribou ). We hypothesized that coyotes in the boreal forest depend mainly on disturbed habitat, particularly that of anthropogenic origin, because these habitats provide increased food accessibility. Coyotes would likely take advantage of moose ( Alces alces ) carcasses, berries, and snowshoe hares ( Lepus americanus ) found in open habitats created by logging. To test these predictions, we described coyote diet and habitat selection at different spatial and temporal levels and then compared resource availability between habitats. To do so, we installed Global Positioning System radiocollars on 23 individual coyotes in the Gaspésie Peninsula, eastern Québec, Canada. Coyotes selected clear‐cuts of 5–20 years and avoided mature coniferous forests both at the landscape and home‐range levels. Clear‐cuts of 5–20 years were found to contain a high availability of moose carcasses and berries, and vulnerability of snowshoe hares is known to increase in clear‐cuts. The importance of these 3 food resources was confirmed by the characteristics of core areas used by coyotes and diet analysis. Moose remains were found at 45% of core areas and coyote diet comprised 51% moose on an annual basis. Anthropogenic disturbances in the boreal forest thus seem to benefit coyotes. Our results indicated that the relationship between coyotes and caribou likely involves spillover predation. This knowledge allows managers to consider spillover predation by coyotes as a possible threat for endangered caribou population when the predator depends mainly on habitat of anthropogenic origin and to suggest methods to alleviate it when developing management plans.
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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 | 0.000 | 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".