Immature Northern Gannets (<i>Morus bassanus</i>) increase colony attendance following highly pathogenic avian influenza
Bibliographic record
Abstract
The emergence of Highly Pathogenic Avian Influenza (HPAI) H5N1 in wild bird populations in 2020 changed the landscape of this disease for seabird populations, including Northern Gannets Morus bassanus. In 2023, we photographed the three Northern Gannet colonies in Newfoundland and Labrador, Canada (Funk Island, Baccalieu Island and Cape St Mary's), following an HPAI outbreak in 2022 and documented an overall 43% decline in apparently occupied sites (AOS) from the last population survey in 2018. During the photo analyses, we assigned immature birds present in the core breeding area to one of four age categories according to their plumage characteristics, and estimated that 9% (inter‐colony variance ranging from 7 to 14%) of all AOS in 2023 hosted at least one immature bird, an increase compared with rates of 2% or less before the outbreak. Further, 16% of all immature birds present in the core breeding area showed evidence of breeding and were probably 2‐ and 3‐year‐old birds. Our results support the social competition theory whereby a higher proportion of immature and/or younger immature birds occupying an AOS within the core breeding area is observed following significant reductions in numbers of established breeders, suggesting the presence of a pool of immature birds capable of recruiting into the Newfoundland Northern Gannet breeding population and help its recovery.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".