Assessment of the Sustainability of Wolverine Harvest in British Columbia, Canada
Bibliographic record
Abstract
ABSTRACT Wolverines ( Gulo gulo ) are distributed across much of northern and western Canada and Alaska, USA, and they extend south into the mountainous western United States. Wolverines occur in most regions of British Columbia, Canada, with the highest population densities occurring in the interior mountainous areas. Wolverine populations in British Columbia have been primarily managed to provide a sustainable harvest for trappers and hunters. We used spatially based population estimates, population vital rate data, and spatially based harvest data to evaluate the sustainability of wolverine harvest (trapping and hunting) from 1985 to 2004. The median annual provincial wolverine harvest from 1985 to 2004 was 172 wolverines per year ( = 174.8), which was less than the median simulated estimate of provincial recruitment (195.9 wolverines/yr; = 209.7). Harvests in individual population units ranged from 0 to 280 over the 20‐year period. Spatially, wolverine harvest was likely to have been unsustainable in 15 of the 71 population units with wolverines, and it was likely to have been sustainable in the remaining population units. Harvest in 5 of the other 56 population units was marginally sustainable and thus of potential management concern. To improve harvest management of wolverines in British Columbia, wildlife managers should focus on improved data collection and monitoring at a provincial scale, and they should work with trappers and hunters at regional scales to address issues specific to individual population units. Further research is required to improve the reliability of wolverine vital rate and population data.
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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 | 0.002 | 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".