Summary The concept of ‘natural’ populations is a foundation of modern ecology and conservation, with a large body of theoretical literature using these discrete demographic units to understand population dynamics and prioritize conservation strategies. To date, there are currently no objective methods for empirically delineating large‐scale population boundaries using demographic data. We present a novel approach for using large‐scale, citizen‐science monitoring data to quantify geographic structure in trend and abundance and identify distinct natural populations. We demonstrate this approach by delineating populations of eight passerine species using data collected as part of the North American Breeding Bird Survey. Our approach was able to identify geographic structure in both trend and abundance and to delineate distinct populations for all eight species. An independent validation of three species indicated this demographic variation was reflected in underlying vital rates. Synthesis and applications. Natural populations are biologically based alternatives to the traditional geographically defined units that can improve the ability of researchers and managers to quantify spatial variation in population dynamics. Our analysis of natural population structure in breeding songbirds demonstrates that species can show substantial geographic variation in population attributes and underlying demography. We recommend managers define spatial units using natural populations when setting regional population objectives for both single and multispecies conservation plans.

Abstract. Climate change is a serious challenge faced by all plant and animal species. Climate change vulnerability assessments (CCVAs) are one method to assess risk and are increasingly used as a tool to inform management plans. Migratory animals move across regions and continents during their annual cycles where they are exposed to diverse climatic conditions. Climate change during any period and in any region of the annual cycle could influence survival, reproduction, or the cues used to optimize timing of migration. Therefore, CCVAs for migratory animals best estimate risk when they include climate exposure during the entire annual cycle. We developed a CCVA incorporating the full annual cycle and applied this method to 46 species of migratory birds breeding in the Upper Midwest and Great Lakes (UMGL) region of the United States. Our methodology included background risk, climate change exposure × climate sensitivity, adaptive capacity to climate change, and indirect effects of climate change. We compiled information about migratory connectivity between breeding and stationary non-breeding areas using literature searches and U.S. Geological Survey banding and re-encounter data. Climate change exposure (temperature and moisture) was assessed using UMGL breeding season climate and winter climate from non-breeding regions for each species. Where possible, we focused on non-breeding regions known to be linked through migratory connectivity. We ranked 10 species as highly vulnerable to climate change and two as having low vulnerability. The remaining 34 species were ranked as moderately vulnerable. In general, including non-breeding data provided more robust results that were highly individualistic by species. Two species were found to be highly vulnerable throughout their annual cycle. Projected drying will have the greatest effect during the non-breeding season for species overwintering in Mexico and the Caribbean. Projected temperature increases will have the greatest effect during the breeding season in UMGL as well as during the non-breeding season for species overwintering in South America. We provide a model for adaptive management of migratory animals in the face of projected climate change, including identification of priority species, research needs, and regions within non-breeding ranges for potential conservation partnerships.

Research666 the probability that our method missed peaks (spatial: 0.12, temporal: 0.18) or detected false peaks (spatial: 0.11, temporal: 0.37) due to data gaps and showed that our approach remains useful even for sparse and/or sporadic location data. Our study presents a generalizable approach to evaluating migratory connectivity across the full annual cycle that can be used to focus migratory bird conservation towards places and times of the annual cycle where populations are more likely to be limited.