Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere.

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Density-dependent winter survival of immatures in an irruptive raptor with pulsed breeding.

Highly mobile predators can show strong numerical responses to pulsed resources, sometimes resulting in irruptions where large numbers of young invade landscapes at a continental scale. High production of young in irruption years may have a strong influence on the population dynamics unless immature survival is reduced compared to non-irruption years. This could occur if subordinate individuals (mainly immatures) are forced into suboptimal habitats due to density-dependent effects in irruption years. To test whether irruptive individuals had lower survival than non-irruptive ones, we combined necropsy results (N = 365) with telemetry (N = 185) from more than 20 years to record timing and causes of mortality in snowy owls (Bubo scandiacus), which irrupt into eastern North America during winter following high breeding output caused by lemming peaks in the Arctic. Mortality was more than four times higher in irruption years than non-irruption years, but only for immatures, and occurred disproportionately in early winter for immatures, but not adults. Mortality was also higher in eastern North America, where owl abundance fluctuates considerably between years, compared to core winter regions of the Arctic and Prairies where populations are more stable. Most mortality was not due to starvation, but rather associated with human activity, especially vehicle collisions. We conclude that immature snowy owls that irrupt into eastern North America are limited by density-dependent factors, such as increased competition forcing individuals to occupy risky human-altered habitats. For highly mobile, irruptive animals, resource pulses may have a limited impact on population dynamics due to low subsequent survival of breeding output during the nonbreeding season.

Characterizing the microbiome of ectoparasitic louse flies feeding on migratory raptors.

Louse flies (Diptera: Hippoboscidae) are obligate ectoparasites that often cause behavioral, pathogenic, and evolutionary effects on their hosts. Interactions between ectoparasites and avian hosts, especially migrating taxa, may influence avian pathogen spread in tropical and temperate ecosystems and affect long-term survival, fitness and reproductive success. The purpose of this study was to characterize the vector-associated microbiome of ectoparasitic louse flies feeding on migrating raptors over the fall migration period. Surveys for louse flies occurred during fall migration (2015-2016) at a banding station in Pennsylvania, United States; flies were collected from seven species of migrating raptors, and we sequenced their microbial (bacteria and archaea) composition using high-throughput targeted amplicon sequencing of the 16S rRNA gene (V4 region). All louse flies collected belonged to the same species, Icosta americana. Our analysis revealed no difference in bacterial communities of louse flies retrieved from different avian host species. The louse fly microbiome was dominated by a primary endosymbiont, suggesting that louse flies maintain a core microbial structure despite receiving blood meals from different host species. Thus, our findings highlight the importance of characterizing both beneficial and potentially pathogenic endosymbionts when interpreting how vector-associated microbiomes may impact insect vectors and their avian hosts.