Population ecology of polar bears in Davis Strait, Canada and Greenland
Bibliographic record
Abstract
Abstract Until recently, the sea ice habitat of polar bears was understood to be variable, but environmental variability was considered to be cyclic or random, rather than progressive. Harvested populations were believed to be at levels where density effects were considered not significant. However, because we now understand that polar bear demography can also be influenced by progressive change in the environment, and some populations have increased to greater densities than historically lower numbers, a broader suite of factors should be considered in demographic studies and management. We analyzed 35 years of capture and harvest data from the polar bear (Ursus maritimus) subpopulation in Davis Strait, including data from a new study (2005–2007), to quantify its current demography. We estimated the population size in 2007 to be 2,158 ± 180 (SE), a likely increase from the 1970s. We detected variation in survival, reproductive rates, and age‐structure of polar bears from geographic sub‐regions. Survival and reproduction of bears in southern Davis Strait was greater than in the north and tied to a concurrent dramatic increase in breeding harp seals (Pagophilus groenlandicus) in Labrador. The most supported survival models contained geographic and temporal variables. Harp seal abundance was significantly related to polar bear survival. Our estimates of declining harvest recovery rate, and increasing total survival, suggest that the rate of harvest declined over time. Low recruitment rates, average adult survival rates, and high population density, in an environment of high prey density, but deteriorating and variable ice conditions, currently characterize the Davis Strait polar bears. Low reproductive rates may reflect negative effects of greater densities or worsening ice conditions. © 2013 The Wildlife Society.
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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 | 0.000 |
| 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".