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Satellite-based tracking of migratory waterfowl is an important tool for understanding the potential role of wild birds in the long-distance transmission of highly pathogenic avian influenza. However, employing this technique on a continental scale is prohibitively expensive. This study explores the utility of stable isotope ratios in feathers in examining both the distances traveled by migratory birds and variation in migration behavior. We compared the satellite-derived movement data of 22 ducks from 8 species captured at wintering areas in Bangladesh, Turkey, and Hong Kong with deuterium ratios (δD) of these and other individuals captured at the same locations. We derived likely molting locations from the satellite tracking data and generated expected isotope ratios based on an interpolated map of δD in rainwater. Although δD was correlated with the distance between wintering and molting locations, surprisingly, measured δD values were not correlated with either expected values or latitudes of molting sites. However, population-level parameters derived from the satellite-tracking data, such as mean distance between wintering and molting locations and variation in migration distance, were reflected by means and variation of the stable isotope values. Our findings call into question the relevance of the rainfall isotope map for Asia for linking feather isotopes to molting locations, and underscore the need for extensive ground truthing in the form of feather-based isoscapes. Nevertheless, stable isotopes from feathers could inform disease models by characterizing the degree to which regional breeding populations interact at common wintering locations. Feather isotopes also could aid in surveying wintering locations to determine where high-resolution tracking techniques (e.g. satellite tracking) could most effectively be employed. Moreover, intrinsic markers such as stable isotopes offer the only means of inferring movement information from birds that have died as a result of infection. In the absence of feather based-isoscapes, we recommend a combination of isotope analysis and satellite-tracking as the best means of generating aggregate movement data for informing disease models.

Avian influenza has advanced from a regional concern to a global health issue with significant economic, trade, and public health implications. Wild birds, particularly waterfowl (Anseriformes), are known reservoirs for low-pathogenic avian influenza viruses (AIV) and recent studies have shown their potential in the spread of highly pathogenic forms of virus. East Asia remains an epicenter for the emergence of novel strains of AIV, however, information on movement ecology of waterfowl, and subsequently a clearer understanding of disease transmission risks in this region has been greatly lacking. To address this, we marked two species of wild waterfowl, northern pintail (Anas acuta) and Eurasian wigeon (Anas penelope), with satellite transmitters on their wintering grounds in Hong Kong, China to study the northward spring migration in the East Asian-Australasian Flyway in relation to disease transmission factors. Northern pintail were found to initiate migration 42 days earlier, travel 2,150 km farther, and perform 4.4 more stopovers than Eurasian wigeon. We found both species used similar stopover locations including areas along the Yangtze River near Shanghai, Bohai Bay and Korea Bay in rapidly developing regions of the Yellow Sea, and the Sea of Okhotsk where the species appeared to funnel through a migratory bottleneck. Both species appeared to exhibit strong habitat selection for rice paddies during migration stopovers, a habitat preference which has the potential to influence risks of AIV outbreaks as rapid land use and land cover changes occur throughout China. Both species had greatest association with H5N1 outbreaks during the early stages of migration when they were at lower latitudes. While Eurasian wigeon were not associated with outbreaks after the mean date of wintering ground departures, northern pintail were associated with outbreaks until the majority of individuals departed from the Yellow Sea, a migratory stopover location. Our results show species-level differences in migration timing and behavior for these common and widespread species, demonstrating the need to consider their unique temporal and spatial movement ecology when incorporating wild birds into AIV risk modeling and management.

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