Seabird and sea duck mortalities were lower during the second breeding season in eastern Canada following the introduction of highly pathogenic avian influenza A H5Nx viruses
Bibliographic record
Abstract
Capsule H5N1 clade 2.3.4.4b viruses have caused significant mortality events in various wild bird species across Europe, North America, South America, and Africa. In North America, the largest impacts on wild birds have been in eastern Canada, where at least 40,391 wild birds were reported to have died from highly pathogenic avian influenza (HPAI) between April and September 2022.Aims To apply previously established methods to collect and quantify the total reported wild bird mortality in eastern Canada from October 2022 to September 2023.Methods We documented the spatial, temporal, and taxonomic patterns of wild bird mortality in the 12 months that followed a mass mortality event in the summer of 2022, and then quantified the observed differences in mortality across the spring and summer (April to September) of 2022 and 2023. In eastern Canada, there was high uncertainty about whether 2023 would bring another year of devastating HPAI-linked mortalities.Results Mortalities in the spring and summer of 2023 were 93% lower than in 2022, but encompassed a wider diversity of species. Mortalities in the fall/autumn and winter (non-breeding season) were dominated by waterfowl, while mortalities during the spring and summer (breeding season) were dominated by seabirds. Due to a low prevalence of HPAI among a subset of tested birds, we cannot broadly attribute the reported mortalities in 2023 to HPAI. However, our analysis did identify three notable mortality events linked to HPAI, involving at least 1646 Greater Snow Geese Anser caerulescens atlanticus, 232 Canada Geese Branta canadensis, and 212 Northern Gannets Morus bassanus. The latter reflected the continuation of a mortality event from the Northern Gannet’s 2022 breeding season.Conclusions This study emphasizes the ongoing need for H5Nx surveillance and mortality assessments as the patterns of mortality in wild populations continue to change.
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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".