Trends in intensive management of Alaska's grizzly bears, 1980–2010
Bibliographic record
Abstract
Abstract Hunting regulations for grizzly bears ( Ursus arctos ) in much of Alaska since 1980 increasingly were designed to reduce bear abundance in the expectation such regulations would lead to increased harvests by hunters of moose ( Alces alces ) and caribou ( Rangifer tarandus ). Regulations were liberalized during 1980–2010 primarily in the area we termed the Liberal Grizzly Bear Hunting Area (hereafter Liberal Hunt Area) which encompassed 76.2% of Alaska. By 2010, these changes resulted in longer hunting seasons (100% of Liberal Hunt Area had seasons > 100 days, 99.7% > 200 days, and 67.8% > 300 days), more liberal bag limits (99.1% of the Liberal Hunt Area with a bag limit ≥ 1/yr and 10.1% with a bag limit ≥ 2/yr), and widespread waiver of resident tag fees (waived in 95.7% of the Liberal Hunt Area). During 1995–2010, there were 124 changes that made grizzly bear hunting regulations more liberal and two making them more conservative. The 4‐year mean for grizzly bear kills by hunters increased 213% between 1976–1980 (387 grizzly bears) and 2005–2008 (823 grizzly bears). Since 2000, long‐term research studies on grizzly populations in the Liberal Hunt Area have been terminated without replacement. Management of large predators by the State of Alaska is constrained by a 1994 state statute mandating “intensive management” in areas classified as important for human consumptive use of ungulates. Current grizzly bear management in the Liberal Hunt Area is inconsistent with the recommendations of the National Research Council's 1997 report on predator management in Alaska. Current attitudes, policies and absence of science‐based management of grizzly bears in Alaska are increasingly similar to those that resulted in the near extirpation of grizzly bears south of Canada in the 19th and 20th centuries. If current trends continue, they increase risks to portions of the largest and most intact population of grizzly bears in North America. © 2011 The Wildlife Society.
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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 | 0.001 |
| 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 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".