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Record W4402346527 · doi:10.1002/ecs2.4980

Wild bird mass mortalities in eastern Canada associated with the Highly Pathogenic Avian Influenza A( <scp>H5N1</scp> ) virus, 2022

2024· article· en· W4402346527 on OpenAlex
Stephanie Avery‐Gomm, Tatsiana Barychka, Matthew D. English, Robert A. Ronconi, Sabina I. Wilhelm, Jean‐François Rail, Tabatha L. Cormier, Matthieu Beaumont, Campbell Bowser, Tori V. Burt, Sydney M. Collins, Steven Duffy, Jolene A. Giacinti, Scott G. Gilliland, Jean‐François Giroux, Carina Gjerdrum, Magella Guillemette, Kathryn E. Hargan, Megan Jones, Andrew C. Kennedy, Liam Kusalik, Stéphane Lair, Andrew S. Lang, Raphaël A. Lavoie, Christine Lepage, Gretchen McPhail, William A. Montevecchi, Glen J. Parsons, Jennifer F. Provencher, Ishraq Rahman, Gregory J. Robertson, Yannick Seyer, Catherine Soos, Christopher R. E. Ward, Regina Wells, Jordan Wight

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEcosphere · 2024
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsUniversité de MontréalCégep de Rivière-du-LoupUniversité du Québec à MontréalMemorial University of NewfoundlandUniversity of Prince Edward IslandUniversité du Québec à RimouskiEnvironment and Climate Change Canada
FundersEnvironment and Climate Change CanadaNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsInfluenza A virus subtype H5N1OutbreakGeographyPopulationUria aalgeWaterfowlWildlifeBiologyDemographyMortality rateFisheryEcologySeabirdVirusPredationVirologyHabitat

Abstract

fetched live from OpenAlex

Abstract In 2022, a severe outbreak of disease caused by clade 2.3.4.4b Highly Pathogenic Avian Influenza (HPAI) H5N1 virus resulted in unprecedented mortality among wild birds in eastern Canada. Tens of thousands of birds were reported sick or dead, prompting a comprehensive assessment of mortality spanning the breeding season between April 1 and September 30, 2022. Mortality reports were collated from federal, Indigenous, provincial, and municipal agencies, the Canadian Wildlife Health Cooperative, and other nongovernmental organizations, universities, and citizen science platforms. A scenario analysis was conducted to refine mortality estimates, accounting for potential double counts from multiple sources under a range of spatial and temporal overlaps. Correcting for double counting, HPAI is estimated to have caused 40,391 wild bird mortalities in eastern Canada during the spring and summer of 2022; however, this figure underestimates total mortality as it excludes unreported deaths on land and at sea. Seabirds and sea ducks, long‐lived species that are slow to recover from perturbations, accounted for 98.7% of estimated mortalities. Our study provides estimates of bird mortality, with Northern Gannets ( Morus bassanus ; 25,669), Common Murres ( Uria aalge ; 8133), and American Common Eiders ( Somateria mollissima dresseri ; 1894) exhibiting the highest mortality figures. We then compare these mortality estimates with recent population estimates and trends and make an initial assessment of whether biologically meaningful population‐level impacts are possible. Specifically, we focus on the Northern Gannet, a species that has suffered significant global mortality, and two harvested species, Common Murre and American Common Eider, to inform management decisions. Our analysis suggests population‐level impacts in eastern Canada are possible for Northern Gannets and American Common Eiders, but are unlikely for Common Murres. This study demonstrates a comprehensive approach to assessing mortality and underscores the urgent need for further research to understand the broader ecological ramifications of the HPAI outbreak on wild bird populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.235
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it