Increased trophic position of black bear (<i>Ursus americanus</i>) at the northern fringe of its distribution range
Bibliographic record
Abstract
Studies describing the diet of omnivorous species are abundant, but the drivers affecting the balance between animal and plant resources remain unclear. Among those drivers, latitude has been reported to positively correlate with the trophic position of consumers. Using stable isotope analysis, we tested the hypothesis that trophic position of black bears (Ursus americanus Pallas, 1780) is positively correlated with latitude in eastern North America. We sampled 57 bears over a 15° latitudinal gradient in Quebec, Canada, and used stable isotope analysis to assess individual trophic position and metrics of dietary niches. We found a strong positive correlation between trophic position of bears and latitude (r2 = 0.76), which persisted throughout seasons. The width of the dietary niche of bears also appeared to follow a latitudinal pattern, even though bears foraging at the southernmost part of the gradient also showed a wide dietary niche. The impact of latitude on the foraging tactic of omnivores fosters our understanding of their capability to deal with contrasting environmental conditions, especially for species whose distribution ranges are expanding due to climate change. The flexibility of black bear foraging tactic likely allows this species to expand its geographical distribution range toward northern habitats.
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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".