Demography and Viability of a Hunted Population of Polar Bears
Why this work is in the frame
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Bibliographic record
Abstract
We estimated demographic parameters and harvest risks for a population of polar bears (Ursus maritimus) inhabiting Baffin Bay, Canada and Greenland, from 1974 to 1997. Our demographic analysis included a detailed assessment of age- and sex-specific survival and recruitment from 1221 marked polar bears, which used information contained within the standing age distribution of captures and mark-recapture analysis performed with Program MARK. Unharvested (natural) survival rates for females (± 1 SE) from mark-recapture analysis were 0.620 ± 0.095 (cubs), 0.938 ± 0.042 (ages 1–4), 0.953 ± 0.020 (ages 5–20), and 0.919 ± 0.046 (ages 21+). Total (harvested) survival rates for females were reduced to 0.600 ± 0.096 (cubs), 0.901 ± 0.045 (ages 1–4), 0.940 ± 0.021 (ages 5–20), and 0.913 ± 0.047 (ages 21+). Mean litter size was 1.59 ± 0.07 cubs, with a mean reproductive interval of 2.5 ± 0.01 years. By age 5, on average 0.88 ± 0.40 of females were producing litters. We estimated the geometric means (± bootstrapped SDs) for population growth rates at stable age distribution as 1.055 ± 0.011 (unharvested) and 1.019 ± 0.015 (harvested). The model-averaged, mark-recapture estimate of mean abundance (± 1 SE) for years 1994–97 was 2074 ± 266 bears, which included 1017 ± 192 females and 1057 ± 124 males. We incorporated demographic parameters and their error terms into a harvest risk analysis designed to consider demographic, process, and sampling uncertainty in generating likelihoods of persistence (i.e., a stochastic, harvest-explicit population viability analysis). Using our estimated harvest of polar bears in Baffin Bay (88 bears/yr), the probability that the population would decline no more than could be recovered in five years was 0.95, suggesting that the current hunt is sustainable.
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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 | 0.000 | 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) | 0.000 | 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 it