Extensive Predator Space Use Can Limit the Efficacy of a Control Program
Bibliographic record
Abstract
ABSTRACT Reduced to small isolated groups by anthropogenic habitat losses or habitat modifications, populations of many endangered species are sensitive to additive sources of mortality, such as predation. Predator control is often one of the first measures considered when predators threaten survival of a population. Unfortunately, predator ecology is often overlooked because relevant data are difficult to obtain. For example, the endangered Gaspésie caribou ( Rangifer tarandus caribou ) has benefited from 2 periods of predator control that targeted black bears ( Ursus americanus ) and coyotes ( Canis latrans ) in an attempt to reduce predation on caribou calves. Despite a high trapping effort, the number of predators removed has remained stable over time. To assess impact of predator movements on efficacy of a control program, we studied space use of 24 black bears and 16 coyotes over 3 years in and around the Gaspésie Conservation Park, Quebec, Canada, using Global Positioning System radiocollars. Annual home ranges of black bears averaged 260 km 2 and 10 individuals frequented area used by caribou. Annual home ranges of resident coyotes averaged 121 km 2 , whereas dispersing coyotes covered >2,600 km 2 . Coyotes were generally located at lower altitudes than caribou. However, because coyotes undertook long‐distance excursions, they overlapped areas used by caribou. Simulations based on observed patterns showed that 314 bears and 102 coyotes potentially shared part of their home range with areas used by female caribou during the calving period. Despite low densities of both predator species, extensive movement and use of nonexclusive territories seem to allow predators to rapidly occupy removal areas, demonstrating the need for recurrent predator removals. Our results underscore the necessity of considering complementary and alternative solutions to predator control to assure long‐term protection of endangered species.
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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 | 0.001 | 0.003 |
| 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".