Echoes of the hunt? An inter-continental comparison of patterns of growth and determinants of size of brown bears in Canada and Sweden.
Bibliographic record
Abstract
Comparing life history traits among populations that have been separated genetically for several hundred thousand years, but live in similar habitats on different continents, may help us understand how ecological and anthropomorphic factors shape life histories. We compared patterns of growth in body length and mass, and the influence of population density, habitat quality (NDVI), and reproduction on age-specific length and mass of male and female brown bears between Alberta, Canada, and Sweden. We found that Swedish females were significantly smaller in both length and mass than Alberta females. Swedish females also reached primiparity earlier and at a smaller mass and length. However, there were no continental differences in the patterns of growth in males. We found strong positive effects of NDVI, but only weak negative effects of population density on female mass and length in both areas. Generally, especially mass of Alberta females was more strongly affected by NDVI and density than for Swedish females. Reproduction had stronger negative effects on female mass in Alberta than in Sweden. We found no effects of NDVI and population density on male mass and body length in both areas. The larger variation in female growth and size between the areas, in contrast to males, may be related to differences in female reproductive investment due to differences in population trends, i.e., earlier reproduction in increasing populations or populations below carrying capacity, or to different selection pressures in the past, potentially due to human persecution. Swedish females exhibited characteristics typical of increasing populations, whereas Alberta females exhibited characteristics typical of stable or decreasing populations. The difference in reproduction investment means that Swedish bears can be harvested at higher rates, whereas Alberta bears must be managed more conservatively.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".