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To model the effects of global climate phenomena on avian population dynamics, we must identify and quantify the spatial and temporal relationships between climate, weather and bird populations. Previous studies show that in Europe, the North Atlantic Oscillation (NAO) influences winter and spring weather that in turn affects resident and migratory landbird species. Similarly, in North America, the El Niño/ Southern Oscillation (ENSO) of the Pacific Ocean reportedly drives weather patterns that affect prey availability and population dynamics of landbird species which winter in the Caribbean. Here we show that ENSO-and NAO-induced seasonal weather conditions differentially affect neotropicaland temperate-wintering landbird species that breed in Pacific North-west forests of North America. For neotropical species wintering in western Mexico, El Niño conditions correlate with cooler, wetter conditions prior to spring migration, and with high reproductive success the following summer. For temperate wintering species, springtime NAO indices correlate strongly with levels of forest defoliation by the larvae of two moth species and also with annual reproductive success, especially among species known to prey upon those larvae. Generalized linear models incorporating NAO indices and ENSO precipitation indices explain 50 -90% of the annual variation in productivity reported for 10 landbird species. These results represent an important step towards spatially explicit modelling of avian population dynamics at regional scales.

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.