Management implications for releasing orphaned, captive‐reared bears back to the wild
Bibliographic record
Abstract
ABSTRACT Orphaned bears have been captive‐reared and released back to the wild for more than 3 decades, often without a clear understanding of their fates because post‐release monitoring is not a common practice. As a result, management agencies lack efficacy data on post‐release success rates and are often reluctant to encourage increased use of this technique. We evaluated the potential management and conservation implications of releasing captive‐reared bears by documenting post‐release survival, cause‐specific mortality, human conflict activity, movements, and reproduction for 550 American black, brown and Asiatic black bears reared in 12 captive‐rearing programs around the world. Survival rates in these programs ranged from 0.50 to 1.00 and were similar among the 3 species. The primary causes of mortality were sport hunting and road kills for American black bears, intra‐specific predation and illegal kills for brown bears, and natural mortalities and illegal kills for Asiatic black bears. Although American and Asiatic black bears were involved in conflicts post‐release, the majority of released bears (94%) were not documented in conflict situations. Movement patterns of captive‐reared American black and brown bears showed no homing tendencies toward their rearing facility. Twenty captive‐reared bears produced 21 litters. Our analyses reduce many of the uncertainties surrounding the fate of bears released as yearlings and provide evidence that releasing captive‐reared bears is a defensible management alternative. © 2015 The Wildlife Society.
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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 | 0.002 | 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 | 0.001 | 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) | 0.002 | 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".