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Record W3184087071 · doi:10.1111/gcb.15537

Long‐term increases in pathogen seroprevalence in polar bears (<i>Ursus maritimus</i>) influenced by climate change

2021· article· en· W3184087071 on OpenAlexafffundabout
Nicholas W. Pilfold, Evan S. Richardson, John Ellis, Emily Jenkins, W. Brad Scandrett, Adrián Hernández‐Ortiz, Kayla J. Buhler, David McGeachy, Batol Al‐Adhami, Kelly Konecsni, Vladislav A. Lobanov, Megan A. Owen, Bruce A. Rideout, Nicholas J. Lunn

Bibliographic record

VenueGlobal Change Biology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsCanadian Food Inspection AgencyUniversity of SaskatchewanEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of CanadaChurchill Northern Studies CentreCanadian Wildlife FederationWorld Wildlife FundParks CanadaQuark Expeditions
KeywordsSeroprevalenceUrsus maritimusBiologyToxoplasma gondiiTrichinellaBordetella bronchisepticaSerologyEcologyArcticAntibodyImmunology

Abstract

fetched live from OpenAlex

The influence of climate change on wildlife disease dynamics is a burgeoning conservation and human health issue, but few long-term studies empirically link climate to pathogen prevalence. Polar bears (Ursus maritimus) are vulnerable to the negative impacts of sea ice loss as a result of accelerated Arctic warming. While studies have associated changes in polar bear body condition, reproductive output, survival, and abundance to reductions in sea ice, no long-term studies have documented the impact of climate change on pathogen exposure. We examined 425 serum samples from 381 adult polar bears, collected in western Hudson Bay (WH), Canada, for antibodies to selected pathogens across three time periods: 1986-1989 (n = 157), 1995-1998 (n = 159) and 2015-2017 (n = 109). We ran serological assays for antibodies to seven pathogens: Toxoplasma gondii, Neospora caninum, Trichinella spp., Francisella tularensis, Bordetella bronchiseptica, canine morbillivirus (CDV) and canine parvovirus (CPV). Seroprevalence of zoonotic parasites (T. gondii, Trichinella spp.) and bacterial pathogens (F. tularensis, B. bronchiseptica) increased significantly between 1986-1989 and 1995-1998, ranging from +6.2% to +20.8%, with T. gondii continuing to increase into 2015-2017 (+25.8% overall). Seroprevalence of viral pathogens (CDV, CPV) and N. caninum did not change with time. Toxoplasma gondii seroprevalence was higher following wetter summers, while seroprevalences of Trichinella spp. and B. bronchiseptica were positively correlated with hotter summers. Seroprevalence of antibodies to F. tularensis increased following years polar bears spent more days on land, and polar bears previously captured in human settlements were more likely to be seropositive for Trichinella spp. As the Arctic has warmed due to climate change, zoonotic pathogen exposure in WH polar bears has increased, driven by numerous altered ecosystem pathways.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.029
GPT teacher head0.278
Teacher spread0.249 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations39
Published2021
Admission routes3
Has abstractyes

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