International consensus principles for the sustainable harvest of polar bears
Bibliographic record
Abstract
Multilateral agreements are required for the effective management of large carnivores with ranges that cross geopolitical boundaries. This is particularly important for species subject to rapid changes in distribution or demographic status due to climate warming. We considered 3 international consensus principles for the sustainable harvest of polar bears (Ursus maritimus), a circumpolar species threatened by sea-ice loss and harvested by Indigenous Peoples for subsistence. First, we defined a biologically sustainable harvest as one that occurs at a rate likely to maintain subpopulation abundance above maximum net productivity level. Second, we determined the type of scientific assessment needed to identify a sustainable harvest, which includes synthesizing or collecting information on habitat conditions, spatial population structure, and human-caused removals and conducting a field study to estimate ecological indices or demographic parameters. Third, we delineated the components of a sustainable harvest management regime, which include implementing harvest at a biologically sustainable rate, having the ability to monitor and adjust harvest levels, and following a state-dependent management approach. The consensus principles are supported by the 5 nations with polar bears (Canada, Greenland, Norway, Russia, and the United States) under an international treaty. They are designed to provide consistent guidance while allowing different jurisdictions the flexibility to tailor harvest strategies to their situations. Adapting similar principles to other systems could help mitigate the global conservation crisis for large carnivores.
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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 | 0.043 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".