Multicolony tracking reveals the winter distribution of a pelagic seabird on an ocean basin scale
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Bibliographic record
Abstract
Abstract Aim An understanding of the non‐breeding distribution and ecology of migratory species is necessary for successful conservation. Many seabirds spend the non‐breeding season far from land, and information on their distribution during this time is very limited. The black‐legged kittiwake, Rissa tridactyla , is a widespread and numerous seabird in the North Atlantic and Pacific, but breeding populations throughout the Atlantic range have declined recently. To help understand the reasons for the declines, we tracked adults from colonies throughout the Atlantic range over the non‐breeding season using light‐based geolocation. Location North Atlantic. Methods Geolocation data loggers were deployed on breeding kittiwakes from 19 colonies in 2008 and 2009 and retrieved in 2009 and 2010. Data from 236 loggers were processed and plotted using GIS. Size and composition of wintering populations were estimated using information on breeding population size. Results Most tracked birds spent the winter in the West Atlantic, between Newfoundland and the Mid‐Atlantic Ridge, including in offshore, deep‐water areas. Some birds (mainly local breeders) wintered in the North Sea and west of the British Isles. There was a large overlap in winter distributions of birds from different colonies, and colonies closer to each other showed larger overlap. We estimated that 80% of the 4.5 million adult kittiwakes in the Atlantic wintered west of the Mid‐Atlantic Ridge, with only birds from Ireland and western Britain staying mainly on the European side. Main conclusions The high degree of mixing in winter of kittiwakes breeding in various parts of the Atlantic range implies that the overall population could be sensitive to potentially deteriorating environmental conditions in the West Atlantic, e.g. owing to lack of food or pollution. Our approach to estimating the size and composition of wintering populations should contribute to improved management of birds faced with such challenges.
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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 | 0.001 | 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) | 0.001 | 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