Growth and Sustainability of Black Bears at White River National Wildlife Refuge, Arkansas
Bibliographic record
Abstract
The black bear (Ursus americanus) population at White River National Wildlife Refuge is isolated and genetically distinct, but hunting occurs adjacent to refuge boundaries and females with cubs are removed annually for a reintroduction project. We trapped and radiotracked bears to determine level of exploitation and compare methods for estimating population growth and sustainability. We captured 260 bears (113 M:147 F), 414 times, from 1998 through 2003. Survival estimates based on radiotracking and mark–recapture indicated that hunting and translocations were significant sources of loss. Based on mark–recapture data (Pradel estimator), the annual population growth rate (λ) averaged 1.066 (SE = 0.077) when translocation removals occurred and averaged 0.961 (SE = 0.155) when both harvest and translocations occurred. Estimates of λ based on a population simulation model (program RISKMAN) averaged 1.061 (SD = 0.104) and 1.100 (SD = 0.111) when no removals occurred, 1.003 (SD = 0.097) and 1.046 (SD = 0.102) when translocations occurred, and 0.973 (SD = 0.096) and 1.006 (SD = 0.099) when both harvest and translocations occurred, depending on the survival rate estimates we used. The probability of population decline by >25% over a 10-year period ranged from 13.8 to 68.8%, given our estimated removal rates. We conclude that hunting and translocation losses are at or exceed the maximum the population is capable of sustaining. Although extinction risks of this important bear population are low over the near term, it should continue to be closely monitored by state and federal agencies. The mark–recapture method we used to estimate λ proved to be a reliable alternative to more costly population modeling methods.
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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".