Effects of hunting on demographic parameters of American black bears
Bibliographic record
Abstract
We conducted an experiment to test competing hypotheses regarding the effects of hunting on American black bear (Ursus americanus) demographic parameters. Specifically, we tested for the existence and the relative influence of sexually selected infanticide (SSI) and density dependence in regulating demographic parameters. We monitored 290 bears in 2 hunted areas and an adjoining unhunted area in the boreal forest of Alberta, Canada, during a 4-year study (2002–2005). We manipulated the areas using a modified before–after control–impact (BACI) design whereby bait sites for hunting were closed in 1 of the 2 hunted areas in years 3 and 4 and adult males in the unhunted area were removed in year 3. Results did not support a significant influence of SSI, if it occurs, on population parameters compared with the effects of density dependence. We found lower cub survival (66% versus 83%) and older age of first reproduction in the unhunted, higher-density area than in the lower-density, hunted area. We found no difference in body condition of males and females between areas, suggesting that if SSI restricted females to suboptimal areas, the effect was not strong enough to affect reproduction. We did not detect an influx of new males or a change in cub survival after removal of adult males from the unhunted area (66% before versus 73% after). Our results suggest that SSI does not affect the population growth rate of hunted black bear populations, and that target hunting quotas do not require including potential effects of SSI in population projections. However, SSI should be considered in unhunted or lightly hunted populations approaching carrying capacity (K). We advocate the inclusion of density dependence in population projection models for bear populations. However, for specific cases where harvesting maintains a population size well below K, density-dependent effects are predicted to be negligible due to the non-linear relationship between demographic parameters and density.
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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 | 0.000 | 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 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".