Breeding and migration ecology of bar-headed goose Anser indicus and swan goose Anser cygnoides in Asia

Most waterfowl that breed in Mongolia, part of the semiarid northern region of East Asia, are long distant migrants. They depend on availability of lake, river, and wetland habitats on their breeding and wintering grounds and need suitable staging and stopover sites along their flight routes to complete their migration. Waterfowl in this region have developed important adaptations and strategies to ensure their survival and reproductive fitness across generations. I studied the ecology of two goose species endemic to this semiarid region, the bar-headed goose (Anser indicus) and swan goose (Anser cygnoides), to examine their use of highly-variable, wetland habitats. I studied the breeding biology of bar-headed geese across three summers (2009-2011) while conducting the first systematic nesting study in the semiarid Khangai Mountains region of west-central Mongolia. Bar-headed geese were found nesting on both islands and cliffs, but their daily nest survival was higher at cliff nests and ranged from 0.94 to 0.98 with average nest survival of 42.6% during the incubation period. Information-theoretic models indicated that nest survival decreased with nest age and varied annually. Waterfowl in this region may be limited by available nest sites, but disturbance and depredation also may play a critical role in their population dynamics. I also tracked the migration of both species via satellite telemetry from their breeding grounds to wintering grounds. Satellite tracking data revealed that swan geese migrated through the Yalu River Delta to a wintering area primarily restricted to Eastern China. In contrast, bar-headed geese had a much greater wintering area ranging from southern China to the southern tip of India. Recently, wintering grounds of both species have had significant land cover and land use changes related to global warming and human activities. For the first time, I was able to document unique and narrow migration corridors for both species that were related to landscape features. The migration corridor of bar-headed geese on the Qinghai-Tibetan Plateau was restricted to one biogeographic biome, while swan geese moved across biomes in a loop migration, preferred stopover sites in natural landscapes, avoided areas of eastern China with large scale developments and high human densities, and wintered in the Yangtze River Basin. Migration of bar-headed geese was associated with vegetation green-up as indicated by the Normalized Difference Vegetation Index (NDVI), and geese strategically moved between areas with peak NDVI values extending from their wintering grounds in India, migration stopover areas on the Qinghai-Tibetan Plateau, and breeding grounds in Mongolia. The arrival of bar-headed geese at staging areas during the spring migration was correlated with a decline of green vegetation biomass on their wintering grounds in India and advancement of vegetation green-up in northern latitudes. During the autumn migration, snow cover and land surface temperature corresponded well with their southward movement. These results will have important implications to improve understanding of wild bird biology in this region as well as disease ecology -- waterfowl may contribute to gene flow of avian influenza viruses among different geographical populations of wild and domestic birds through their long distance migration. Species distributions are expected to shift in response to climate change, and swan and bar-headed geese likely will alter their distribution and migratory behavior in response but constrained by both natural habitat availability and human effects limiting their habitats

WILD BIRDS AND EMERGING DISEASES: MODELING AVIAN INFLUENZA TRANSMISSION RISK BETWEEN DOMESTIC AND WILD BIRDS IN CHINA

Emerging infectious diseases in wildlife have become a growing concern to human health and biological systems with more than 75 percent of known emerging pathogens being transmissible from animals to humans. Highly pathogenic avian influenza (HPAI) H5N1 has caused major global concern over a potential pandemic and since its emergence in 1996 has become the longest persisting HPAI virus in history. HPAI viruses are generally restricted to domestic poultry populations, however, their origins are found in wild bird reservoirs (Anatidae waterfowl) in a low-pathogenic or non-lethal form. Understanding the spatial and temporal interface between wild and domestic populations is fundamental to taking action against the virus, yet this information is lacking. My dissertation takes two approaches to increase our understanding of wild bird and H5N1 transmission. The first includes a field component to track the migratory patterns of bar-headed geese (Anser indicus) and ruddy shelduck (Tadorna ferruginea) from the large H5N1 outbreak at Qinghai Lake, China. The satellite telemetry study revealed a new migratory connection between Qinghai Lake and outbreak regions in Mongolia, and provided ecological data that supplements phylogenetic analyses of virus movement. The second component of my dissertation research took a modeling approach to identify areas of high transmission risk between domestic poultry and wild waterfowl in China, the epicenter of H5N1. This effort required the development of spatial models for both the poultry and wild waterfowl species of China. Using multivariate regression and AIC to determine statistical relationships between poultry census data and remotely-sensed environmental predictors, I generated spatially explicit distribution models for China's three main poultry species: chickens, ducks, and geese. I then developed spatially explicit breeding and wintering season models of presence-absence, abundance, and H5N1 prevalence for each of China's 42 Anatidae waterfowl species. The poultry and waterfowl datasets were used as the main inputs for the transmission risk models. Distinct patterns in both the spatial and temporal distributions of H5N1 risk was observed in the model predictions. All models included estimates of uncertainty, and sensitivity analyses were performed for the risk models

RESIDUAL SPATIAL AUTOCORRELATION IN MACROECOLOGICAL AND BIOGEOGRAPHICAL MODELING: A REVIEW

Macroecological and biogeographical modelers have predicted the distribution of species across space relying on the relationship between biotic processes and environmental variables. Such a method employs data associated, for instance, with species abundance or presence/absence, climate, geomorphology, and soils. Statistical analyses found in previous studies have highlighted the importance of accounting for the effects of spatial autocorrelation (SAC), which indicates a level of dependence between pairs of nearby observations. A consensus has existed that residual spatial autocorrelation (rSAC) can substantially impact modeling processes and inferences. However, more emphasis should be put on identifying the sources of rSAC and the degree to which rSAC becomes detrimental. In this thesis, we review previous studies to identify various factors that potentially engender the presence of rSAC in macroecological and biogeographical models. Additionally, special attention is paid to the quantification of rSAC by attempting to bring out the magnitude to which the presence of SAC in model residuals impedes the modeling process. The review identified that five categories of factors potentially drive the presence of SAC in model residuals: the type of ecological data and the processes underlying it, scale and distance, missing variables, sampling design, as well as the assumptions and methodological perspectives of the investigator. Furthermore, we concluded that more explicit discussion of rSAC should be carried out in species distribution modeling. We recommend further investigations involving the quantification of rSAC to understand when rSAC can have a negative effect on the modeling process

Birds as indicators of change in the freshwater ecosystems of Botswana

Freshwater ecosystems support highly biodiverse plant and animal populations and provide crucial ecosystem services to human communities. Despite this importance, these systems are being degraded faster than terrestrial or marine environments, resulting in large global declines in freshwater biodiversity. To track such environmental change, birds are often used as indicator species. I focused on tracking changes in significant waterbird breeding colonies, rivers and internationally listed wetlands in Botswana facing a wide range of threats. I identified that riparian bird communities along the Chobe River were more biodiverse in sites with the presence of large herbivores, highlighting the direct and indirect relationships between these seemingly unconnected taxa. Using a drone, I explored the relationships between waterbird breeding and river levels and inundation. Drone imagery on the Chobe River provided comprehensive data on the reproductive success, size and composition of the Kasane waterbird breeding colony, which were linked to river levels and inundation, while citizen science collected abundance data helped identify a threshold river level to support large waterbird breeding colonies. This underlined the importance of river flows for waterbird populations and the potential for the breeding of waterbirds to inform river management. Similarly in the Okavango Delta, citizen science data highlighted positive relationships between waterbird abundance and river flows, but there were indications of long-term declines in waterbird abundances. River flows were again important for waterbird breeding, with key waterbird breeding colonies located in areas experiencing moderate to high flood frequencies. I also developed a semi-automated counting technique for investigating colony sizes with a drone, negating the need to physically enter a colony or manually count imagery, saving time in image processing and ensuring researcher safety. Finally, I investigated the potential effects of foraging at landfill on the marabou stork. Plastics formed a significant proportion of marabou regurgitant while trace metal concentrations in feathers were higher than in naturally foraging populations, indicating potential deleterious impacts. My work highlighted the value of riparian bird communities, predominantly waterbirds, as indicators of change, reflecting herbivore population structures, land use alterations and changes in freshwater flows and inundation

Landscape-Level Associations of Wintering Waterbird Diversity and Abundance from Remotely Sensed Wetland Characteristics of Poyang Lake

Poyang Lake, the largest freshwater wetland in China, provides critical habitat for wintering waterbirds from the East Asian Flyway; however, landscape drivers of non-uniform bird diversity and abundance are not yet well understood. Using a winter 2006 waterbird survey, we examined the relationships among metrics of bird community diversity and abundance and landscape characteristics of 51 wetland sub-lakes derived by an object-based classification of Landsat satellite data. Relative importance of predictors and their sets was assessed using information-theoretic model selection and the Akaike Information Criterion. Ordinary least squares regression models were diagnosed and corrected for spatial autocorrelation using spatial autoregressive lag and error models. The strongest and most consistent landscape predictors included Normalized Difference Vegetation Index for mudflat (negative effect) and emergent grassland (positive effect), total sub-lake area (positive effect), and proportion of submerged vegetation (negative effect). Significant spatial autocorrelation in linear regression was associated with local clustering of response and predictor variables, and should be further explored for selection of wetland sampling units and management of protected areas. Overall, results corroborate the utility of remote sensing to elucidate potential indicators of waterbird diversity that complement logistically challenging ground observations and offer new hypotheses on factors underlying community distributions