Phenology and productivity in a montane bird assemblage: Trends and responses to elevation and climate variation.

Climate variation has been linked to historical and predicted future distributions and dynamics of wildlife populations. However, demographic mechanisms underlying these changes remain poorly understood. Here, we assessed variation and trends in climate (annual snowfall and spring temperature anomalies) and avian demographic variables from mist-netting data (breeding phenology and productivity) at six sites along an elevation gradient spanning the montane zone of Yosemite National Park between 1993 and 2017. We implemented multi-species hierarchical models to relate demographic responses to elevation and climate covariates. Annual variation in climate and avian demographic variables was high. Snowfall declined (10 mm/year at the highest site, 2 mm at the lowest site), while spring temperature increased (0.045°C/year) over the study period. Breeding phenology (mean first capture date of juvenile birds) advanced by 0.2 day/year (5 days); and productivity (probability of capturing a juvenile bird) increased by 0.8%/year. Breeding phenology was 12 days earlier at the lowest compared to highest site, 18 days earlier in years with lowest compared to highest snowfall anomalies, and 6 d earlier in relatively warm springs (after controlling for snowfall effects). Productivity was positively related to elevation. However, elevation-productivity responses varied among species; species with higher productivity at higher compared to lower elevations tended to be species with documented range retractions during the past century. Productivity tended to be negatively related to snowfall and was positively related to spring temperature. Overall, our results suggest that birds have tracked the variable climatic conditions in this system and have benefited from a trend toward warmer, drier springs. However, we caution that continued warming and multi-year drought or extreme weather years may alter these relationships in the future. Multi-species demographic modeling, such as implemented here, can provide an important tool for guiding conservation of species assemblages under global change.

Persistent impacts of West Nile virus on North American bird populations.

Since its introduction to North America in 1999, West Nile virus (WNV) has had devastating impacts on native host populations, but to date these impacts have been difficult to measure. Using a continental-scale dataset comprised of a quarter-million birds captured over nearly two decades and a recently developed model of WNV risk, we estimated the impact of this emergent disease on the survival of avian populations. We find that populations were negatively affected by WNV in 23 of the 49 species studied (47%). We distinguished two groups of species: those for which WNV negatively impacted survival only during initial spread of the disease (n = 11), and those that show no signs of recovery since disease introduction (n = 12). Results provide a novel example of the taxonomic breadth and persistent impacts of this wildlife disease on a continental scale. Phylogenetic analyses further identify groups (New World sparrows, finches, and vireos) disproportionally affected by temporary or persistent WNV effects, suggesting an evolutionary dimension of disease risk. Identifying the factors affecting the persistence of a disease across host species is critical to mitigating its effects, particularly in a world marked by rapid anthropogenic change.

Mapping migration in a songbird using high-resolution genetic markers.

Neotropic migratory birds are declining across the Western Hemisphere, but conservation efforts have been hampered by the inability to assess where migrants are most limited-the breeding grounds, migratory stopover sites or wintering areas. A major challenge has been the lack of an efficient, reliable and broadly applicable method for measuring the strength of migratory connections between populations across the annual cycle. Here, we show how high-resolution genetic markers can be used to identify genetically distinct groups of a migratory bird, the Wilson's warbler (Cardellina pusilla), at fine enough spatial scales to facilitate assessing regional drivers of demographic trends. By screening 1626 samples using 96 highly divergent single nucleotide polymorphisms selected from a large pool of candidates (~450 000), we identify novel region-specific migratory routes and timetables of migration along the Pacific Flyway. Our results illustrate that high-resolution genetic markers are more reliable, precise and amenable to high throughput screening than previously described intrinsic marking techniques, making them broadly applicable to large-scale monitoring and conservation of migratory organisms.

Novel statistical methods for integrating genetic and stable isotope data to infer individual-level migratory connectivity.

Methods for determining patterns of migratory connectivity in animal ecology have historically been limited due to logistical challenges. Recent progress in studying migratory bird connectivity has been made using genetic and stable-isotope markers to assign migratory individuals to their breeding grounds. Here, we present a novel Bayesian approach to jointly leverage genetic and isotopic markers and we test its utility on two migratory passerine bird species. Our approach represents a principled model-based combination of genetic and isotope data from samples collected on the breeding grounds and is able to achieve levels of assignment accuracy that exceed those of either method alone. When applied at large scale the method can reveal specific migratory connectivity patterns. In Wilson's warblers (Wilsonia pusilla), we detect a subgroup of birds wintering in Baja that uniquely migrate preferentially from the coastal Pacific Northwest. Our approach is implemented in a way that is easily extended to accommodate additional sources of information (e.g. bi-allelic markers, species distribution models, etc.) or adapted to other species or assignment problems.

Modeling spatial variation in avian survival and residency probabilities.

The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.

Mapping the risk of avian influenza in wild birds in the US.

BACKGROUND: Avian influenza virus (AIV) is an important public health issue because pandemic influenza viruses in people have contained genes from viruses that infect birds. The H5 and H7 AIV subtypes have periodically mutated from low pathogenicity to high pathogenicity form. Analysis of the geographic distribution of AIV can identify areas where reassortment events might occur and how high pathogenicity influenza might travel if it enters wild bird populations in the US. Modelling the number of AIV cases is important because the rate of co-infection with multiple AIV subtypes increases with the number of cases and co-infection is the source of reassortment events that give rise to new strains of influenza, which occurred before the 1968 pandemic. Aquatic birds in the orders Anseriformes and Charadriiformes have been recognized as reservoirs of AIV since the 1970s. However, little is known about influenza prevalence in terrestrial birds in the order Passeriformes. Since passerines share the same habitat as poultry, they may be more effective transmitters of the disease to humans than aquatic birds. We analyze 152 passerine species including the American Robin (Turdus migratorius) and Swainson's Thrush (Catharus ustulatus). METHODS: We formulate a regression model to predict AIV cases throughout the US at the county scale as a function of 12 environmental variables, sampling effort, and proximity to other counties with influenza outbreaks. Our analysis did not distinguish between types of influenza, including low or highly pathogenic forms. RESULTS: Analysis of 13,046 cloacal samples collected from 225 bird species in 41 US states between 2005 and 2008 indicates that the average prevalence of influenza in passerines is greater than the prevalence in eight other avian orders. Our regression model identifies the Great Plains and the Pacific Northwest as high-risk areas for AIV. Highly significant predictors of AIV include the amount of harvested cropland and the first day of the year when a county is snow free. CONCLUSIONS: Although the prevalence of influenza in waterfowl has long been appreciated, we show that 22 species of song birds and perching birds (order Passeriformes) are influenza reservoirs in the contiguous US.