Dynamics of disease : origins and ecology of avian cholera in the eastern Canadian arctic
Bibliographic record
Abstract
Avian cholera, caused by infection with Pasteurella multocida, is an important infectious disease of wild birds in North America Since it was first confirmed in 2005, annual outbreaks of avian cholera have had a dramatic effect on common eiders on East Bay Island, Nunavut, one of the largest breeding colonies of northern common eiders (Somateria mollissima borealis) in the eastern Arctic. I investigated potential avian and environmental reservoirs of P. multocida on East Bay Island and other locations in the eastern Canadian Arctic by collecting cloacal and oral swabs from live or harvested, apparently healthy, common eiders, lesser snow geese, Ross’s geese, king eiders, herring gulls, and snow buntings. Water and sediment from ponds on East Bay Island were sampled before and during outbreaks. Avian and environmental samples were tested using a real-time polymerase chain reaction (PCR) assay to detect P. multocida. PCR positive birds were found in every species except for snow buntings, and PCR positive common eiders were found in most locations, supporting the hypothesis that apparently healthy wild birds can act as a reservoir for avian cholera. In all years, P. multocida DNA was detected in ponds both before and after the avian cholera outbreak began each year, suggesting that the environment also plays a role in outbreak dynamics. Contrary to our expectations, model results revealed that ponds were generally more likely to be positive earlier in the season, before the outbreaks began. Whereas average air temperature at the beginning of the breeding season was not an important predictor for detecting P. multocida in ponds, eiders were more likely to be PCR positive under cooler conditions, pointing to an important link between disease and weather. Potential origins of P. multocida causing avian cholera in Arctic eider colonies were investigated by comparing eastern Arctic isolates of P. multocida to isolates from wild birds across Canada, and the central flyway in the United States. Using repetitive extragenic palindromic-PCR (REP-PCR) and multi-locus sequence typing (MLST), we detected a low degree of genetic diversity among isolates, and P. multocida genotypes were correlated with somatic serotype. Isolates from East Bay Island were distinct from P. multocida from eider colonies in the St. Lawrence Estuary, Quebec, however, East Bay Island isolates were indistinguishable from isolates collected from a 2007 pelagic avian cholera outbreak on the east coast of Canada. Isolates from East Bay Island and Nunavik shared sequence types, indicating possible transmission of isolates among eider colonies in the eastern Arctic. Previously, feather corticosterone in eiders was found to be significantly associated with environmental temperature during the moulting period. In my study, path analysis revealed that environmental conditions experienced during the moulting period had direct impacts on arrival date and pre-breeding body condition of common eiders during the subsequent breeding period on East Bay Island, with indirect impacts on both reproductive success and survival. Higher temperatures experienced during the fall moulting period appear to impose significant costs to eiders, with subsequent carry-over effects on both survival and reproduction many months later during avian cholera outbreaks. This thesis describes several important features of the host, agent and environmental dynamics of avian cholera in North America with a particular focus on the disease in the eastern Canadian Arctic. Continued exploration of infectious wildlife disease dynamics is needed to better predict, detect, manage, and mitigate disease emergence that can threaten human and animal health and species conservation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".