Herbivory Dominates the Spring Diet of American Black Bears (<scp><i>Ursus americanus</i></scp>) in a Wood Bison (<scp><i>Bison bison athabascae</i></scp>) Neonatal Range, Suggesting Minimal Bison Consumption
Bibliographic record
Abstract
ABSTRACT Studying an organism's foraging behavior, especially for predator species, provides insight into their ecology, habitat needs, and interspecific relationships. American black bears (Ursus americanus) are generalist omnivores, with a diet primarily composed of vegetation and are known predators of a number of ungulate species, particularly their neonates. In this study, we analyzed the spring diet of black bears occupying the neonatal range of a small, threatened wood bison (Bison bison athabascae) herd in the Ronald Lake area of northeast Alberta to determine the predation risk of neonate bison. To estimate black bear consumption rates of bison, we used scat analysis and DNA metabarcoding to describe the spring diet of bears occupying the Ronald Lake wood bison herd's (RLBH) neonatal range. If black bears occupying the RLBH's neonatal range are consuming bison, either through predation or scavenging, then we would expect bison DNA to be present in black bear scats. We predicted that the increased availability of neonate bison in the spring would provide bears with greater predation and scavenging opportunities. Conversely, if black bear predation risk is low within the RLBH's neonatal range, then we would predict that herbaceous plants would dominate black bear diet early in the spring and berries later in the spring and summer. The spring diet of black bears was dominated by herbaceous and fruiting plants. Bison DNA, without visual evidence of animal remains, was found in only 1 of 79 scat samples (1.3%). Our results suggest that consumption rates of bison are low and that predation risk to neonate wood bison, during the RLBH's occupancy of their neonatal range, from black bears is likely minimal despite the two species' overlap in space and time.
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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".