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

2024· other· en· W6958847190 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Ecology and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInfluenza A virus subtype H5N1OutbreakHighly pathogenicBird fluWildlifeInfluenza A virusAvian influenza virusRange (aeronautics)Mortality rate

Abstract

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<b>About this repository</b>This repository contains *data* and *code* associated with the following publication:<br><br>Avery-Gomm, S., Barychka, T., English, M., Ronconi, R., Wilhelm, S. I., Rail, J.-F., Cormier, T., Beaumont, M., Bowser, C., Burt, T. V., Collins, S., Duffy, S., Giacinti, J. A., Gilliland, S., Giroux, J.-F., Gjerdrum, C., Guillemette, M., Hargan, K. E., Jones, M., Kennedy, A., Kusalik, L., Lair, S., Lang, A., Lavoie, R., Lepage, C., McPhail, G., Montevecchi, W. A., Parsons, G. J., Provencher, J. F., Rahman, I., Robertson, G. J., Seyer, Y., Soos, C., Ward, C. R. E., Wells, R., &amp; Wight, J. 2024. <b>Wild bird mass mortalities in eastern Canada associated with the Highly Pathogenic Avian Influenza A(H5N1) virus</b>. <i>Ecosphere.</i><br><b>Abstract </b>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 non-governmental 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<i> (Morus bassanus</i>; 25,669), Common Murres (<i>Uria aalge</i>; 8,133), and American Common Eiders (<i>Somateria mollissima dresseri;</i> 1,894) 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.<b>Data</b>This repository contains the complete collated dataset of reported wild bird mortalities in eastern Canada from<b>,</b> April 1, 2022, to September 30, 2022 with anonymized personal information. See the manuscript above for details. Metadata describing the data is provided in Sheet: Metadata. Instructions for how to use the dataset are provided in Instructions for DataS1.txt.<br>Data S1. Reported mortalities and morbidities in eastern Canada.xlsxInstructions for DataS1.txtThis repository also contains three .csv files with information on colony surveys from 2022 for Common Eiders (Data S2), Northern Gannets (Data S3) and Common Murres (Data S4). Also included in Data S2-4 are the best available information on recent breeding pair numbers and locations for all known colonies in eastern Canada, for each species, but this should not be construed or used as the official records on colony locations for Common Eiders or Common Mures.<br>Data S2. American Common Eider (ACOEI) colony survey information.xlsxData S3. Northern Gannet (NOGA) colony survey information.xlsxData S4. Common Murre (COMU) colony survey information.xlsx<b>Code</b>The code required to reproduce the double count analysis is in Scenario_Analysis.Rmd (input files are Data S1.csv and SpeciesAlphaCode_KEY.csv).<b>Software Requirements</b>Scripts are written for R version 4.2.2 (2022-10-31 ucrt). See scripts and the publication for packages and software citations.<b>Terms of use:</b>Anyone can share this material, provided it remains unaltered in any way, this is not done for commercial purposes, and the original authors are credited and cited (Attribution CC-BY-NC-ND).

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.829
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0550.001

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.

Opus teacher head0.031
GPT teacher head0.199
Teacher spread0.168 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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