Status assessment and conservation priorities for a circumpolar raptor: the Snowy Owl <i>Bubo scandiacus</i>
Why this work is in the frame
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Bibliographic record
Abstract
Summary The global population and status of Snowy Owls Bubo scandiacus are particularly challenging to assess because individuals are irruptive and nomadic, and the breeding range is restricted to the remote circumpolar Arctic tundra. The International Union for Conservation of Nature (IUCN) uplisted the Snowy Owl to “Vulnerable” in 2017 because the suggested population estimates appeared considerably lower than historical estimates, and it recommended actions to clarify the population size, structure, and trends. Here we present a broad review and status assessment, an effort led by the International Snowy Owl Working Group (ISOWG) and researchers from around the world, to estimate population trends and the current global status of the Snowy Owl. We use long-term breeding data, genetic studies, satellite-GPS tracking, and survival estimates to assess current population trends at several monitoring sites in the Arctic and we review the ecology and threats throughout the Snowy Owl range. An assessment of the available data suggests that current estimates of a worldwide population of 14,000–28,000 breeding adults are plausible. Our assessment of population trends at five long-term monitoring sites suggests that breeding populations of Snowy Owls in the Arctic have decreased by more than 30% over the past three generations and the species should continue to be categorised as Vulnerable under the IUCN Red List Criterion A2. We offer research recommendations to improve our understanding of Snowy Owl biology and future population assessments in a changing world.
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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) | 0.001 | 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 it