The changing anthropogenic diets of American black bears over the past century in Yosemite National Park
Bibliographic record
Abstract
We used carbon (δ13C) and nitrogen (δ15N) stable isotopes derived from the tissues of American black bears ( Ursus americanus ) to estimate the proportion of human‐derived foodstuffs and food waste (“human foods”) in the diets of human food‐conditioned bears over the past century in Yosemite National Park, located in central–eastern California. Our goal was to understand how the foraging ecology of bears responded to changing management strategies. We found that the proportion of human foods increased in bear diets when park personnel and visitors fed bears intentionally in 1923–1971, remained relatively high and constant after artificial feeding areas were closed, and declined drastically in 1999–2007, following a $500 000 annual government appropriation used to mitigate human–bear conflicts in the park. This reduction in the amount of human foods in bear diets suggests that Yosemite managers have been successful in reducing the availability of human foods to bears. Yosemite bears currently consume human foods in the same proportion as they did in 1915–1919. This result indicates a notable management achievement in the park, considering that thousands of people visited Yosemite annually in the early 1900s while about four million people visit each year today.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".