Temporal variation in the population characteristics of harvested wolverine (Gulo gulo) in northwestern Canada
Bibliographic record
Abstract
Context Wolverines (Gulo gulo) are harvested for fur in northern Canada; however, the impacts of harvest are poorly known. Additionally, wolverine population data are largely absent for much of their northern range. Demographic data collected from harvested wolverines provide information on the vulnerability and variability of different sex and age cohorts to harvest, which, in turn, may have implications for harvest sustainability. Aims We examined the temporal variability of different sex and age cohorts in wolverine harvest among years, and within the harvest season, in Yukon, Canada. We also examined the pregnancy status of female wolverines in relation to the harvest date, so as to evaluate the impact of the harvest-season length on breeding wolverines. Methods We determined the sex and age composition of harvested wolverines via dissections of 655 carcasses collected from 2005 to 2014. We determined the reproductive status and fetal measurements for female wolverines via dissections of reproductive tracts. Key results The harvest consisted mostly of males, particularly of young individuals. The sex ratio of harvested animals did not fluctuate significantly, but we observed variation in the age structure among years. The age structure varied within the harvest season (November to March), with a greater proportion of adults being harvested in late winter. Active gestation was evident in females harvested after mid-January, and near-term or postpartum females were harvested during late February and March. Conclusions Late winter harvest is likely to have a more significant impact on populations than is early winter harvest, because of increased harvest of adults and breeding females. Wolverine harvest season extends to the onset of the denning season in late February and March, indicating a concern for ethical harvest. Implications Limiting the legal harvest season to early winter may contribute to improved harvest sustainability and protection of breeding wolverines in northern latitudes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".