IRIS PIGMENTATION IRREGULARITIES FOLLOWING AN AVIAN INFLUENZA OUTBREAK: IMPLICATIONS FOR DISEASE SURVEILLANCE AND POPULATION MONITORING IN A COLONIAL SEABIRD
Bibliographic record
Abstract
Abstract Emerging infectious diseases can have catastrophic impacts on wildlife populations, yet identifying individuals that survived exposure, especially when external symptoms are absent, remains challenging. Since 2021, a virulent strain of highly pathogenic avian influenza virus (HPAIV H5N1 clade 2.3.4.4b) has caused unprecedented mortality in wild birds across continents. Northern Gannets ( Morus bassanus ) are among the species that suffered significant population declines in Europe and North America. At North America’s largest gannet colony (Bonaventure Island) dramatic mortality and reproductive failure occurred in 2022. Following this event, researchers noted a subset of gannets displaying irregular iris pigmentation, raising the possibility that this visible change may indicate a lasting effect of infection. Here, we build on earlier observations linking irregular iris pigmentation to HPAIV exposure in gannets using anti-nucleoprotein (NP) and anti-hemagglutinin (H5) antibodies. This provides the first quantitative test of this relationship using serological data and field-based digital photography. Iris irregularities were strongly associated (ρ = –0.72) with antibodies to NP, supporting the hypothesis that they can indicate past exposure. The likelihood of NP antibody detection increased with iris pigment irregularity—about 50% likelihood at 40% irregularity, 65% at 50%, 77% at 60%, and over 90% above 77% irregularity. Moderate correlations (ρ = 0.30) were observed for H5 antibodies. Our findings provide quantitative support for the hypothesis that iris pigmentation irregularities may serve as a visible, non-invasive marker of past HPAIV exposure in gannets. If validated across colonies and years, iris assessment could offer a rapid tool for tracking population health and recovery following HPAIV outbreaks, enhancing conservation monitoring and disease surveillance. Lay Summary Our research shows clear evidence that irregular iris pigmentation in Northern Gannets is strongly linked to past infection with a deadly bird flu strain. This visible marker could allow scientists to rapidly identify surviving birds and monitor population health after outbreaks, helping conservation efforts across affected colonies. Highlights Iris pigmentation irregularities reveal past avian influenza exposure. Extent of iris pigmentation irregularity correlates with antibody levels. Exposure likelihood increases with degree of iris pigmentation irregularity. Could provide a rapid, non-invasive tool for wildlife disease and conservation monitoring. Graphical abstracts
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".