Assessing the status and conservation priorities of the short‐eared owl in North America
Bibliographic record
Abstract
Abstract The North American Breeding Bird Survey, Christmas Bird Count, and regional and national conservation assessments provide convincing evidence that the short‐eared owl ( Asio flammeus ) is experiencing a range‐wide, long‐term decline in abundance in North America. However, the species has received little conservation or research attention. The short‐eared owl is vulnerable to decline because it relies heavily on large, intact grasslands and a specialized diet of unpredictable small mammal prey. The species' nomadic movements compound these vulnerabilities by making a decline difficult to detect with current monitoring programs while obfuscating stewardship responsibilities for managers. The primary threat to the species is loss, fragmentation, and degradation of large tracts of native grasslands and wetlands. We propose the following conservation priorities to better understand and begin addressing the short‐eared owl's decline: 1) better define and protect important habitats; 2) improve population monitoring; 3) determine seasonal and annual movements; 4) re‐evaluate NatureServe's short‐eared owl national conservation classifications; 5) develop management plans and tools; and 6) classify raptors, including short‐eared owls, as migratory birds in Canada. We contend that the short‐eared owl's need for habitat conservation at large spatial scales, status as a predator, and high reproductive potential that affords the species capacity to recover, make it an effective and useful candidate as an umbrella species for grassland conservation. © 2014 The Wildlife Society.
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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".