Adult survival of Arctic terns in the Canadian High Arctic
Bibliographic record
Abstract
Arctic tern (Sterna paradisaea) populations are thought to be in decline across much of their range. For long-lived seabirds, determining adult survival rates is key to understanding current population trends and predicting trajectories. We therefore examined adult survival of terns banded at our field site in the Canadian High Arctic between 2007 and 2016. Apparent adult survival was 0.883, comparable to values for other tern species and for other Arctic larids. However, using this survival rate plus first year survival values from a recent study in Iceland, we project a declining trend for terns in the Canadian High Arctic, consistent with recent reports from local ecological knowledge and limited regional surveys. Our data suggest that low adult survival is not responsible for declining tern populations, and that studies should investigate whether dispersal to new nesting locations may be underway, or that young terns are not surviving well or recruiting to the population.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".