Diet flexibility of wolves and black bears in the range of migratory caribou
Bibliographic record
Abstract
Abstract The diet of predators can be highly variable, which is exemplified by their ability to acclimate to a wide range of ecological conditions. Such flexibility in foraging may be a key aspect of their performance in unpredictable environments such as at the edge of the range of a species or where food availability varies greatly in time and space. Gaining information on the diets of predators under such conditions could foster our comprehension of their ecological flexibility and the potential role of predation on the population dynamics of prey. We determined the diet of wolves (Canis lupus) and black bears (Ursus americanus) in northern Québec and Labrador (Canada) within the range of two migratory caribou (Rangifer tarandus) herds: the high-abundance Rivière-aux-Feuilles herd (RFH) and low-abundance Rivière-George herd (RGH). Worldwide, decline in caribou populations has become a concern, stressing the need to better understand the factors involved in these declines, including predation. In northern Québec (RFH range), caribou was the primary year-round prey of wolves while moose (Alces alces) and muskoxen (Ovibos moschatus) were consumed in some sectors. The diet of wolves in northern Labrador (RGH range) varied seasonally, with caribou, moose, and fish as main prey during different periods throughout the year. Black bear diets varied seasonally and regionally. Among the foods we analyzed, caribou was the main source of animal protein for bears in northern Québec and northern Labrador, except during a high abundance of Ungava collared lemming (Dicrostonyx hudsonius). Only bears in northern Québec ate caribou during late summer/fall. Our results highlight the diet flexibility of wolves and black bears in northern food webs, and how their diets change in relation to the distribution and abundance of prey. Our results will help quantify the potential impact of these predators on prey populations in northern systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".