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Current climate models and observations indicate that atmospheric circulation is being affected by global climate change. To assess how these changes may affect nocturnally migrating bird populations, we need to determine how current patterns of wind assistance at migration altitudes will be enhanced or reduced under future atmospheric conditions. Here, we use information compiled from 143 weather surveillance radars stations within the contiguous United States to estimate the daily altitude, density, and direction of nocturnal migration during the spring and autumn. We intersected this information with wind projections to estimate how wind assistance is expected to change during this century at current migration altitudes. The prevailing westerlies at midlatitudes are projected to increase in strength during spring migration and decrease in strength to a lesser degree during autumn migration. Southerly winds will increase in strength across the continent during both spring and autumn migration, with the strongest gains occurring in the center of the continent. Wind assistance is projected to increase across the central (0.44 m/s; 10.1%) and eastern portions of the continent (0.32 m/s; 9.6%) during spring migration, and wind assistance is projected to decrease within the central (0.32 m/s; 19.3%) and eastern portions of the continent (0.17 m/s; 6.6%) during autumn migration. Thus, across a broad portion of the continent where migration intensity is greatest, the efficiency of nocturnal migration is projected to increase in the spring and decrease in the autumn, potentially affecting time and energy expenditures for many migratory bird species. These findings highlight the importance of placing climate change projections within a relevant ecological context informed through empirical observations, and the need to consider the possibility that climate change may generate both positive and negative implications for natural systems.

 

Quantifying the timing and intensity of migratory movements is imperative for understanding impacts of changing landscapes and climates on migratory bird populations. Billions of birds migrate in the Western Hemisphere, but accurately estimating the population size of one migratory species, let alone hundreds, presents numerous obstacles. Here, we quantify the timing, intensity, and distribution of bird migration through one of the largest migration corridors in the Western Hemisphere, the Gulf of Mexico (the Gulf). We further assess whether there have been changes in migration timing or intensity through the Gulf. To achieve this, we integrate citizen science (eBird) observations with 21 years of weather surveillance radar data (1995–2015). We predicted no change in migration timing and a decline in migration intensity across the time series. We estimate that an average of 2.1 billion birds pass through this region each spring en route to Nearctic breeding grounds. Annually, half of these individuals pass through the region in just 18 days, between April 19 and May 7. The western region of the Gulf showed a mean rate of passage 5.4 times higher than the central and eastern regions. We did not detect an overall change in the annual numbers of migrants (2007–2015) or the annual timing of peak migration (1995–2015). However, we found that the earliest seasonal movements through the region occurred significantly earlier over time (1.6 days decade⁻¹). Additionally, body mass and migration distance explained the magnitude of phenological changes, with the most rapid advances occurring with an assemblage of larger‐bodied shorter‐distance migrants. Our results provide baseline information that can be used to advance our understanding of the developing implications of climate change, urbanization, and energy development for migratory bird populations in North America.

 

Millions of nocturnally migrating birds die each year from collisions with built structures, especially brightly illuminated buildings and communication towers. Reducing this source of mortality requires knowledge of important behavioral, meteorological, and anthropogenic factors, yet we lack an understanding of the interacting roles of migration, artificial lighting, and weather conditions in causing fatal bird collisions. Using two decades of collision surveys and concurrent weather and migration measures, we model numbers of collisions occurring at a large urban building in Chicago. We find that the magnitude of nocturnal bird migration, building light output, and wind conditions are the most important predictors of fatal collisions. The greatest mortality occurred when the building was brightly lit during large nocturnal migration events and when winds concentrated birds along the Chicago lakeshore. We estimate that halving lighted window area decreases collision counts by 11× in spring and 6× in fall. Bird mortality could be reduced by ∼60% at this site by decreasing lighted window area to minimum levels historically recorded. Our study provides strong support for a relationship between nocturnal migration magnitude and urban bird mortality, mediated by light pollution and local atmospheric conditions. Although our research focuses on a single site, our findings have global implications for reducing or eliminating a critically important cause of bird mortality.

 

Monitoring avian migration within subarctic regions of the globe poses logistical challenges. Populations in these regions often encounter the most rapid effects of changing climates, and these seasonally productive areas are especially important in supporting bird populations—emphasizing the need for monitoring tools and strategies. To this end, we leverage the untapped potential of weather surveillance radar data to quantify active migration through the airspaces of Alaska. We use over 400 000 NEXRAD radar scans from seven stations across the state between 1995 and 2018 (86% of samples derived from 2013 to 2018) to measure spring and autumn migration intensity, phenology and directionality. A large bow-shaped terrestrial migratory system spanning the southern two-thirds of the state was identified, with birds generally moving along a northwest–southeast diagonal axis east of the 150th meridian, and along a northeast–southwest axis west of this meridian. Spring peak migration ranged from 3 May to 30 May and between, 18 August and 12 September during the autumn, with timing across stations predicted by longitude, rather than latitude. Across all stations, the intensity of migration was greatest during the autumn as compared to spring, highlighting the opportunity to measure seasonal indices of net breeding productivity for this important system as additional years of radar measurements are amassed. 

The US weather radar archive holds detailed information about biological phenomena in the atmosphere over the last 20 years. Communally roosting birds congregate in large numbers at nighttime roosting locations, and their morning exodus from the roost is often visible as a distinctive pattern in radar images. This paper describes a machine learning system to detect and track roost signatures in weather radar data. A significant challenge is that labels were collected opportunistically from previous research studies and there are systematic differences in labeling style. We contribute a latent-variable model and EM algorithm to learn a detection model together with models of labeling styles for individual annotators. By properly accounting for these variations we learn a significantly more accurate detector. The resulting system detects previously unknown roosting locations and provides comprehensive spatio-temporal data about roosts across the US. This data will provide biologists important information about the poorly understood phenomena of broad-scale habitat use and movements of communally roosting birds during the non-breeding season. 

The dynamic weather conditions that migrating birds experience during flight likely influence where they stop to rest and refuel, particularly after navigating inhospitable terrain or large water bodies, but effects of weather on stopover patterns remain poorly studied. We examined the influence of broad-scale weather conditions encountered by nocturnally migrating Nearctic-Neotropical birds during northward flight over the Gulf of Mexico (GOM) on subsequent coastal stopover distributions. We categorized nightly weather patterns using historic maps and quantified region-wide densities of birds in stopover habitat with data collected by 10 weather surveillance radars from 2008 to 2015. We found spring weather patterns over the GOM were most often favorable for migrating birds, with winds assisting northward flight, and document regional stopover patterns in response to specific unfavorable weather conditions. For example, Midwest Continental High is characterized by strong northerly winds over the western GOM, resulting in high-density concentrations of migrants along the immediate coastlines of Texas and Louisiana. We show, for the first time, that broad-scale weather experienced during flight influences when and where birds stop to rest and refuel. Linking synoptic weather patterns encountered during flight with stopover distributions contributes to the emerging macro-ecological understanding of bird migration, which is critical to consider in systems undergoing rapid human-induced changes.