Avoidance of roads and selection for recent cutovers by threatened caribou: fitness-rewarding or maladaptive behaviour?
Bibliographic record
Abstract
The impact of anthropogenic disturbance on the fitness of prey should depend on the relative effect of human activities on different trophic levels. This verification remains rare, however, especially for large animals. We investigated the functional link between habitat selection of female caribou (Rangifer tarandus) and the survival of their calves, a fitness correlate. This top-down controlled population of the threatened forest-dwelling caribou inhabits a managed forest occupied by wolves (Canis lupus) and black bears (Ursus americanus). Sixty-one per cent of calves died from bear predation within two months following their birth. Variation in habitat selection tactics among mothers resulted in different mortality risks for their calves. When calves occupied areas with few deciduous trees, they were more likely to die from predation if the local road density was high. Although caribou are typically associated with pristine forests, females selected recent cutovers without negative impact on calf survival. This selection became detrimental, however, as regeneration took place in harvested stands owing to increased bear predation. We demonstrate that human disturbance has asymmetrical consequences on the trophic levels of a food web involving multiple large mammals, which resulted in habitat selection tactics with a greater short-term fitness payoff and, therefore, with higher evolutionary opportunity.
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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 | 0.002 |
| 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 | 0.001 |
| 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".