Understanding how environmental conditions, especially wind, influence birds' flight speeds is a prerequisite for understanding many important aspects of bird flight, including optimal migration strategies, navigation, and compensation for wind drift. Recent developments in tracking technology and the increased availability of data on large-scale weather patterns have made it possible to use path annotation to link the location of animals to environmental conditions such as wind speed and direction. However, there are various measures available for describing not only wind conditions but also the bird's flight direction and ground speed, and it is unclear which is best for determining the amount of wind support (the length of the wind vector in a bird’s flight direction) and the influence of cross-winds (the length of the wind vector perpendicular to a bird’s direction) throughout a bird's journey. We compared relationships between cross-wind, wind support and bird movements, using path annotation derived from two different global weather reanalysis datasets and three different measures of direction and speed calculation for 288 individuals of nine bird species. Wind was a strong predictor of bird ground speed, explaining 10-66% of the variance, depending on species. Models using data from different weather sources gave qualitatively similar results; however, determining flight direction and speed from successive locations, even at short (15 min intervals), was inferior to using instantaneous GPS-based measures of speed and direction. Use of successive location data significantly underestimated the birds' ground and airspeed, and also resulted in mistaken associations between cross-winds, wind support, and their interactive effects, in relation to the birds' onward flight. Wind has strong effects on bird flight, and combining GPS technology with path annotation of weather variables allows us to quantify these effects for understanding flight behaviour. The potentially strong influence of scaling effects must be considered and implemented in developing sampling regimes and data analysis.

In 2008–09, evidence of Reston ebolavirus (RESTV) infection was found in domestic pigs and pig workers in the Philippines. With species of bats having been shown to be the cryptic reservoir of filoviruses elsewhere, the Philippine government, in conjunction with the Food and Agriculture Organization of the United Nations, assembled a multi-disciplinary and multi-institutional team to investigate Philippine bats as the possible reservoir of RESTV. The team undertook surveillance of bat populations at multiple locations during 2010 using both serology and molecular assays. A total of 464 bats from 21 species were sampled. We found both molecular and serologic evidence of RESTV infection in multiple bat species. RNA was detected with quantitative PCR (qPCR) in oropharyngeal swabs taken from Miniopterus schreibersii, with three samples yielding a product on conventional hemi-nested PCR whose sequences differed from a Philippine pig isolate by a single nucleotide. Uncorroborated qPCR detections may indicate RESTV nucleic acid in several additional bat species (M. australis, C. brachyotis and Ch. plicata). We also detected anti-RESTV antibodies in three bats (Acerodon jubatus) using both Western blot and ELISA. The findings suggest that ebolavirus infection is taxonomically widespread in Philippine bats, but the evident low prevalence and low viral load warrants expanded surveillance to elaborate the findings, and more broadly, to determine the taxonomic and geographic occurrence of ebolaviruses in bats in the region.

Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors.

Virological, molecular and serological studies were carried out to determine the status of infections with avian influenza viruses (AIV) in different species of wild waterbirds in Iran during 2003-2007. Samples were collected from 1146 birds representing 45 different species with the majority of samples originating from ducks, coots and shorebirds. Samples originated from 6 different provinces representative for the 15 most important wintering sites of migratory waterbirds in Iran.

Evaluating the potential involvement of wild avifauna in the emergence of highly pathogenic avian influenza H5N1 (hereafter H5N1) requires detailed analyses of temporal and spatial relationships between wild bird movements and disease emergence. The death of wild swans (Cygnus spp.) has been the first indicator of the presence of H5N1 in various Asian and European countries; however their role in the geographic spread of the disease remains poorly understood. We marked 10 whooper swans (Cygnus cygnus) with GPS transmitters in northeastern Mongolia during autumn 2006 and tracked their migratory movements in relation to H5N1 outbreaks. The prevalence of H5N1 outbreaks among poultry in eastern Asia during 2003–2007 peaked during winter, concurrent with whooper swan movements into regions of high poultry density. However outbreaks involving poultry were detected year round, indicating disease perpetuation independent of migratory waterbird presence. In contrast, H5N1 outbreaks involving whooper swans, as well as other migratory waterbirds that succumbed to the disease in eastern Asia, tended to occur during seasons (late spring and summer) and in habitats (areas of natural vegetation) where their potential for contact with poultry is very low to nonexistent. Given what is known about the susceptibility of swans to H5N1, and on the basis of the chronology and rates of whooper swan migration movements, we conclude that although there is broad spatial overlap between whooper swan distributions and H5N1 outbreak locations in eastern Asia, the likelihood of direct transmission between these groups is extremely low. Thus, our data support the hypothesis that swans are best viewed as sentinel species, and moreover, that in eastern Asia, it is most likely that their infections occurred through contact with asymptomatic migratory hosts (e.g., wild ducks) at or near their breeding grounds.

Highly pathogenic avian influenza H5N1 remains a serious concern for both poultry and human health. Wild waterfowl are considered to be the reservoir for low pathogenic avian influenza viruses; however, relatively little is known about their movement ecology in regions where HPAI H5N1 outbreaks regularly occur. We studied movements of the ruddy shelduck (Tadorna ferruginea), a wild migratory waterfowl species that was infected in the 2005 Qinghai Lake outbreak. We defined their migration with Brownian Bridge utilization distribution models and their breeding and wintering grounds with fixed kernel home ranges. We correlated their movements with HPAI H5N1 outbreaks, poultry density, land cover, and latitude in the Central Asian Flyway. Our Akaike Information Criterion analysis indicated that outbreaks were correlated with land cover, latitude, and poultry density. Although shelduck movements were included in the top two models, they were not a top parameter selected in AICc stepwise regression results. However, timing of outbreaks suggested that outbreaks in the flyway began during the winter in poultry with spillover to wild birds during the spring migration. Thus, studies of the movement ecology of wild birds in areas with persistent HPAI H5N1 outbreaks may contribute to understanding their role in transmission of this disease.