In an emerging climate crisis, effective conservation requires both adaptation and mitigation to improve the resilience of species. The currently pledged emissions reductions outlined in the Paris Agreement framework would still lead to a +3.2°C increase in global mean temperature by the end of this century. In this context, we assess the vulnerability of 604 North American bird species and identify the species and locations most at risk under climate change. We do this based on species distribution models for both the breeding and nonbreeding seasons, projected under two global warming scenarios (an optimistic mitigation scenario 1.5°C and an unmitigated 3.0°C scenario). We evaluate vulnerability under each season and scenario by assessing sensitivity and adaptive capacity based on modeled range loss and range gain, respectively, and based on species specific dispersal abilities. Our study, the first of its magnitude, finds that over two‐thirds of North American birds are moderately or highly vulnerable to climate change under a 3.0°C scenario. Of these climate‐vulnerable species, 76% would have reduced vulnerability and 38% of those would be considered nonvulnerable if warming were stabilized at 1.5°C. Thus, the current pledge in greenhouse gas reductions set by the Paris Agreement is inadequate to reduce vulnerability to North American birds. Additionally, if climate change proceeds on its current trajectory, arctic birds, waterbirds, and boreal and western forest birds will be highly vulnerable to climate change, groups that are currently not considered of high conservation concern. There is an urgent need for both (a) policies to mitigate emissions and (b) prioritization to identify where to focus adaptation actions to protect birds in a changing climate.

Biodiversity is being lost at an alarming rate across the globe, with extinction rates up to a hundred times greater than historical norms. Climate change will only exacerbate this crisis. The rapid pace of projected climate change is set to push birds to seek new locations, drastically reshuffling the avian communities of North America. In an emerging climate crisis, effective conservation requires both adaptation and mitigation to improve the resilience of species. However, the pledged reductions in greenhouse gas emissions outlined in the Paris Agreement framework would still lead to a 3.2°C or greater increase in global mean temperature by the end of this century. In this study, we use big data analytics to develop species distribution models and assess the vulnerability of 604 North American birds to multiple climate change scenarios. We assess how climate change mitigation can affect the number of species vulnerable to climate change, as well as the species and locations at risk if emissions continue unchecked. Our results indicate that over two-thirds of North American birds are moderately or highly vulnerable to climate change under a 3.0°C global warming scenario. Of these climate-vulnerable species, 76% would have reduced vulnerability and 38% of those would be considered non-vulnerable if warming were stabilized at 1.5°C. Thus, the current pledge in greenhouse gas reductions set by the Paris Agreement is inadequate to reduce vulnerability to birds. Additionally, if climate change proceeds on its current trajectory, arctic birds, waterbirds and boreal and western forest birds will be highly vulnerable to climate change; groups that are currently not considered of high conservation concern. Thus, there is an urgent need for both aggressive policies to mitigate emissions and focused conservation adaptation actions to protect birds and the places they need in a changing climate.

Grassland birds have suffered dramatic population declines and are under threat of further grassland conversion. Simultaneously, grassland regions are projected to have high rates of future climate change. We assessed the vulnerability of grassland birds in North America under scenarios of global climate change reflecting the objectives of the Paris Agreement. The assessment incorporated model‐based projections of range losses and gains as well as trait‐based information on adaptive capacity. Nearly half (42%) of grassland birds were highly vulnerable during the breeding season under a 3.0°C increase in global mean temperature scenario representing current commitments under the Paris Accord. This proportion declined to 13% with a 2.0°C increase and to 8% with a 1.5°C increase over preindustrial global mean temperature. Regardless of scenario, more than 70% of grassland birds had some vulnerability to climate change. Policy actions beyond the present‐day national commitments under the Paris Accord are needed to reduce vulnerability of grassland birds in a changing climate.

One of the most pressing questions in ecology and conservation centers on disentangling the relative impacts of concurrent global change drivers, climate and land-use/ land-cover (LULC), on biodiversity. Yet studies that evaluate the effects of both drivers on species' winter distributions remain scarce, hampering our ability to develop full-annual-cycle conservation strategies. Additionally, understanding how groups of species differentially respond to climate versus LULC change is vital for efforts to enhance bird community resilience to future environmental change. We analyzed long-term changes in winter occurrence of 89 species across nine bird groups over a 90-year period within the eastern United States using Audubon Christmas Bird Count (CBC) data. We estimated variation in occurrence probability of each group as a function of spatial and temporal variation in winter climate (minimum temperature, cumulative precipitation) and LULC (proportion of group-specific and anthropogenic habitats within CBC circle). We reveal that spatial variation in bird occurrence probability was consistently explained by climate across all nine species groups. Conversely, LULC change explained more than twice the temporal variation (i.e., decadal changes) in bird occurrence probability than climate change on average across groups. This pattern was largely driven by habitat-constrained species (e.g., grassland birds, waterbirds), whereas decadal changes in occurrence probabilities of habitat-unconstrained species (e.g., forest passerines, mixed habitat birds) were equally explained by both climate and LULC changes over the last century. We conclude that climate has generally governed the winter occurrence of avifauna in space and time, while LULC change has played a pivotal role in driving distributional dynamics of species with limited and declining habitat availability. Effective land management will be critical for improving species' resilience to climate change, especially during a season of relative resource scarcity and critical energetic trade-offs.

Birds in U.S. national parks find strong protection from many longstanding and pervasive threats, but remain highly exposed to effects of ongoing climate change. To understand how climate change is likely to alter bird communities in parks, we used species distribution models relating North American Breeding Bird Survey (summer) and Audubon Christmas Bird Count (winter) observations to climate data from the early 2000s and projected to 2041–2070 (hereafter, mid-century) under high and low greenhouse gas concentration trajectories, RCP8.5 and RCP2.6. We analyzed climate suitability projections over time for 513 species across 274 national parks, classifying them as improving, worsening, stable, potential colonization, and potential extirpation. U.S. national parks are projected to become increasingly important for birds in the coming decades as potential colonizations exceed extirpations in 62–100% of parks, with an average ratio of potential colonizations to extirpations of 4.1 in winter and 1.4 in summer under RCP8.5. Average species turnover is 23% in both summer and winter under RCP8.5. Species turnover (Bray-Curtis) and potential colonization and extirpation rates are positively correlated with latitude in the contiguous 48 states. Parks in the Midwest and Northeast are expected to see particularly high rates of change. All patterns are more extreme under RCP8.5 than under RCP2.6. Based on the ratio of potential colonization and extirpation, parks were classified into overall trend groups associated with specific climate-informed conservation strategies. Substantial change to bird and ecological communities is anticipated in coming decades, and current thinking suggests managing towards a forward-looking concept of ecological integrity that accepts change and novel ecological conditions, rather than focusing management goals exclusively on maintaining or restoring a static set of historical conditions.

Climate change is a significant threat to biodiversity globally. Here, we assessed the risk to 544 birds in the United States from future climate changerelated threats under a mitigation-dependent global warming scenario of 1.5 C and an unmitigated scenario of 3.0 C. Threats considered included sea level rise, human land cover conversion, and extreme weather events. We identified potential impacts to individual species by overlaying future bird ranges with threats to calculate the proportion of species' ranges affected, and mapped a place-based index of risk based on hazard (coincident threats), exposure (potential species richness), and vulnerability (potential richness of vulnerable species). Extreme weather events had the most extensive spatial coverage and contribution to risk, but urbanization and sea level rise also had disproportionate impacts on species relative to their coverage. With unmitigated climate change, multiple coincident threats affected over 88% of the area of the conterminous United States, and 97% of species could be affected by two or more climate-related threats. Some habitat groups will see up to 96% of species facing three or more threats. Species of conservation concern also faced more threats regardless of climate change scenario. However, climate change mitigation would reduce risk to birds from climate change-related threats across over 90% of the US.

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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 theeBird-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.