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Animal migration is one of nature’s most spectacular phenomena, but migratory animals and their journeys are imperiled across the globe. Migratory birds are among the most well-studied animals on Earth, yet relatively little is known about in-flight behavior during nocturnal migration. Because many migrating bird species vocalize during flight, passive acoustic monitoring shows great promise for facilitating widespread monitoring of bird migration.Here, we present Nighthawk, a deep learning model designed to detect and identify the vocalizations of nocturnally migrating birds. We trained Nighthawk on the in-flight vocalizations of migratory birds using a diverse dataset of recordings from across the Americas.Our results demonstrate that Nighthawk performs well as a nocturnal flight call detector and classifier for dozens of avian taxa, both at the species level and for broader taxonomic groups (e.g., orders and families). The model accurately quantified nightly nocturnal migration intensity and species phenology and performed well on data from across North America. Incorporating modest amounts of additional annotated audio (50-120 h) into model training yielded high performance on target datasets from both North and South America.By monitoring the vocalizations of actively migrating birds, Nighthawk provides a detailed window onto nocturnal bird migration that is not presently attainable by other means (e.g., radar or citizen science). Scientists, managers, and practitioners could use acoustic monitoring with Nighthawk for a number of applications, including: monitoring migration passage at wind farms; studying airspace usage during migratory flights; monitoring the changing migrations of species susceptible to climate change; and revealing previously unknown migration routes and behaviors. Overall, this work will empower diverse stakeholders to efficiently monitor migrating birds across the Western Hemisphere and collect data in aid of science and conservation. Nighthawk is freely available athttps://github.com/bmvandoren/Nighthawk.

Structural variants (SVs) are a major source of genetic variation, but accurate descriptions in natural populations and connections with phenotypic traits remain scarce. We integrated advances in genomic sequencing and animal tracking to begin filling this knowledge gap in the Eurasian blackcap. Specifically, we (i) characterized the genome-wide distribution, frequency and overall fitness effects of SVs using haplotype-resolved assemblies for 79 birds, and (ii) used these SVs to study the genetics of seasonal migration. We detected >15K SVs. Many SVs overlapped repetitive regions and exhibited evidence of purifying selection suggesting they have overall deleterious effects on fitness. We used estimates of genomic differentiation to identify SVs exhibiting evidence of selection in blackcaps with different migratory strategies. Insertions and deletions dominated these SVs and were associated with genes that are either directly (e.g., regulatory motifs that maintain circadian rhythms) or indirectly (e.g., through immune response) related to migration. We also broke migration down into individual traits (direction, distance and timing) using existing tracking data and tested if genetic variation at the SVs we identified could account for phenotypic variation at these traits. This was only the case for one trait – direction – and one specific SV (a deletion on chromosome 27) accounted for much of this variation. Our results highlight the evolutionary importance of SVs in natural populations and provide insight into the genetic basis of seasonal migration.

1.Aircraft collisions with birds span the entire history of human aviation, including fatal collisions during some of the first powered human flights. Much effort has been expended to reduce such collisions, but increased knowledge about bird movements and species occurrence could dramatically improve decision support and proactive measures to reduce them. Migratory movements of birds pose a unique, often overlooked, threat to aviation that is particularly difficult for individual airports to monitor and predict the occurrence of birds vary extensively in space and time at the local scales of airport responses. 2. We use two publicly available datasets, radar data from the US NEXRAD network characterizing migration movements and eBird data collected by citizen scientists to map bird movements and species composition with low human effort expenditures but high temporal and spatial resolution relative to other large-scale bird survey methods. As a test case, we compare results from weather radar distributions and eBird species composition with detailed bird strike records from three major New York airports. 3. We show that weather radar-based estimates of migration intensity can accurately predict the probability of bird strikes, with 80% of the variation in bird strikes across the year explained by the average amount of migratory movements captured on weather radar. We also show that eBird-based estimates of species occurrence can, using species’ body mass and flocking propensity, accurately predict when most damaging strikes occur.4. Synthesis and applications. By better understanding when and where different bird species occur, airports across the world can predict seasonal periods of collision risks with greater temporal and spatial resolution; such predictions include potential to predict when the most severe and damaging strikes may occur. Our results highlight the power of federating datasets with bird movement and distribution data for developing better and more taxonomically and ecologically tuned models of likelihood of strikes occurring and severity of strikes.

The steady decline of avian populations worldwide urgently calls for a cyber-physical system to monitor bird migration at the continental scale. Compared to other sources of information (radar and crowdsourced observations), bioacoustic sensor networks combine low latency with a high taxonomic specificity. However, the scarcity of flight calls in bioacoustic monitoring scenes (below 0.1% of total recording time) requires the automation of audio content analysis. In this article, we address the problem of scaling up the detection and classification of flight calls to a full-season dataset: 6672 hours across nine sensors, yielding around 480 million neural network predictions. Our proposed pipeline, BirdVox, combines multiple machine learning modules to produce per-species flight call counts. We evaluate BirdVox on an annotated subset of the full season (296 hours) and discuss the main sources of estimation error which are inherent to a real-world deployment: mechanical sensor failures, sensitivity to background noise, misdetection, and taxonomic confusion. After developing dedicated solutions to mitigate these sources of error, we demonstrate the usability of BirdVox by reporting a species-specific temporal estimate of flight call activity for the Swainson’s Thrush (Catharus ustulatus).

The likelihood of a new migratory route evolving is a function of the associated fitness payoff, and the probability that the route arises in the first place. Cross-breeding studies suggest that young birds migrate in a direction intermediate between their parents, though this would seemingly not explain how highly divergent migratory trajectories arise in apparently sympatric populations. It has been suggested that diametrically opposed ‘reverse’ migratory trajectories might be surprisingly common, and if such routes were heritable it follows that they could underlie the rapid evolution of divergent migratory trajectories. Here, we used Eurasian blackcap (Sylvia atricapilla; ‘blackcap’) ringing recoveries and geolocator trajectories to investigate whether a recently-evolved northwards autumn migratory route could be explained by the reversal of each individual’s expected southwards migratory direction. We found that northwards migrants were recovered closer to the sites specified by a precise axis reversal than would be expected by chance, consistent with the rapid evolution of new migratory routes via bi-axial variation in orientation. We suggest that the surprisingly high probability of axis reversal might allow birds to expand their wintering ranges rapidly, and hence propose that understanding how direction is encoded is crucial when characterising the genetic basis of migratory direction and how this relates to route evolution.

A goal of the genomic era is to infer the evolutionary dynamics at play during the process of speciation by analysing the genomic landscape of divergence. However, empirical assessments of genomic landscapes under varying evolutionary scenarios are few, limiting the ability to achieve this goal. Here we combine RAD-sequencing and individual-based simulations to evaluate the genomic landscape in the silvereye (Zosterops lateralis). Using comparisons matched for divergence timeframe and gene flow context, we document how genomic patterns accumulate along the speciation continuum. In contrast to previous predictions, our results provide limited support for the idea that divergence accumulates around loci under divergent selection or that genomic islands widen with time. While a small number of genomic islands were found in populations diverging with and without gene flow, in few cases were SNPs putatively under selection tightly associated with genomic islands. Furthermore, we modelled the transition from localised to genome-wide levels of divergence using individual-based simulations that considered only neutral processes. Our results challenge the ubiquity of existing verbal models that explain the accumulation of genomic differences across the speciation continuum and instead support the idea that divergence both within and outside of genomic islands is important during the speciation process.DATA ACCESSION NUMBERSResequencing data from this study have been submitted to the National Center for Biotechnology Information (NCBI; https://www.ncbi.nlm.nih.gov) under accession number PRJNA489169.

Large-scale monitoring of seasonal animal movement is integral to science, conservation, and outreach. However, gathering representative movement data across entire species ranges is frequently intractable. Citizen science databases collect millions of animal observations throughout the year, but it is challenging to infer individual movement behavior solely from observational data. We present BirdFlow, a probabilistic modeling framework that draws on citizen science data from the eBird database to model the population flows of migratory birds. We apply the model to 11 species of North American birds, using GPS and satellite tracking data to tune and evaluate model performance. We show that BirdFlowmodels can accurately infer individual seasonal movement behavior directly from eBird relative abundance estimates. Supplementing the model with a sample of tracking data from wild birds improves performance. Researchers can extract a number of behavioral inferences from model results, including migration routes, timing, connectivity, and forecasts. The BirdFlowframework has the potential to advance migration ecology research, boost insights gained from direct tracking studies, and serve a number of applied functions in conservation, disease surveillance, aviation, and public outreach.

The Leon Levy Foundation; The Wolf Creek Charitable Foundation; Lyda Hill Philanthropies; Amon G. Carter Foundation; National Science Foundation, Grant/Award Number: ABI sustaining DBI-1939187 and ICER-1927743. Computing support was provided by the National Science Foundation, Grant/Award Number: CNS-1059284 and CCF-1522054, and the Extreme Science and Engineering Discovery Environment (XSEDE), National Science Foundation, Grant/Award Number: ACI-1548562, through allocation TG-DEB200010 run on Bridges at the Pittsburgh Supercomputing Center. Aim: Artificial light at night (ALAN) and roads are known threats to nocturnally migrating birds. How associations with ALAN and roads are defined in combination for these species at the population level across the full annual cycle has not been explored. Location: Western Hemisphere. Methods: We estimated range‐wide exposure, predictor importance and the prevalence of positive associations with ALAN and roads at a weekly temporal resolution for 166 nocturnally migrating bird species in three orders: Passeriformes (n = 104), Anseriformes (n = 27) and Charadriiformes (n = 35). We clustered Passeriformes based on the prevalence of positive associations. Results: Positive associations with ALAN and roads were more prevalent for Passeriformes during migration when exposure and importance were highest. Positive associations with ALAN and roads were more prevalent for Anseriformes and Charadriiformes during the breeding season when exposure was lowest. Importance was uniform for Anseriformes and highest during migration for Charadriiformes. Our cluster analysis identified three groups of Passeriformes, each having similar associations with ALAN and roads. The first occurred in eastern North America during migration where exposure, prevalence, and importance were highest. The second wintered in Mexico and Central America where exposure, prevalence and importance were highest. The third occurred throughout North America where prevalence was low, and exposure and importance were uniform. The first and second were comprised of dense habitat specialists and long‐distance migrants. The third was comprised of open habitat specialists and short distance migrants. Main conclusions: Our findings suggest ALAN and roads pose the greatest risk during migration for Passeriformes and during the breeding season for Anseriformes and Charadriiformes. Our results emphasise the close relationship between ALAN and roads, the diversity of associations dictated by taxonomy, exposure, migration strategy and habitat and the need for more informed and comprehensive mitigation strategies where ALAN and roads are treated as interconnected threats. Publisher PDF

There is increasing evidence for impacts of light pollution on the physiology and behaviour of wild animals. Nocturnally active Procellariiform seabirds are often found grounded in areas polluted by light and struggle to take to the air again without human intervention. Hence, understanding their responses to different wavelengths and intensities of light is urgently needed to inform mitigation measures. Here, we demonstrate how different light characteristics can affect the nocturnal flight of Manx shearwaters Puffinus puffinus by experimentally introducing lights at a colony subject to low levels of light pollution due to passing ships and coastal developments. The density of birds in flight above the colony was measured using a thermal imaging camera. We compared number of flying shearwaters under dark conditions and in response to an artificially introduced light, and observed fewer birds in flight during ‘light-on’ periods, suggesting that adult shearwaters were repelled by the light. This effect was stronger with higher light intensity, increasing duration of ‘light-on’ periods and with green and blue compared to red light. Thus, we recommend lower light intensity, red colour, and shorter duration of ‘light-on’ periods as mitigation measures to reduce the effects of light at breeding colonies and in their vicinity.

Near-term ecological forecasting has the potential to mitigate negative impacts of human modifications on wildlife by directing efficient action through relevant and timely predictions. We used the U.S. avian migration system to highlight ecological forecasting applications for aeroconservation. We used millions of observations from 143 weather surveillance radars to construct and evaluate a migration forecasting system for nocturnal bird migration over the contiguous United States. We identified the number of nights of mitigation required to reduce the risk of aerial hazards to 50% of avian migrants passing a given area in spring and autumn based on dynamic forecasts of migration activity. We also investigated an alternative approach, that is, employing a fixed conservation strategy based on time windows that historically capture 50% of migratory passage. In practice, during both spring and autumn, dynamic forecasts required fewer action nights compared with fixed window selection at all locations (spring: mean of 7.3 more alert days; fall: mean of 12.8 more alert days). This pattern resulted in part from the pulsed nature of bird migration captured in the radar data, where the majority (54.3%) of birds move on 10% of a migration season's nights. Our results highlight the benefits of near-term ecological forecasting and the potential advantages of dynamic mitigation strategies over static ones, especially in the face of increasing risks to migrating birds from light pollution, wind energy infrastructure, and collisions with structures.La estimación ecológica a corto plazo tiene el potencial para mitigar los impactos negativos de las modificaciones humanas sobre la fauna al dirigir las acciones eficientes mediante predicciones relevantes y oportunas. Usamos el sistema de migración de aves de Estados Unidos para resaltar las aplicaciones de la estimación ecológica para la aeroconservación. Usamos millones de observaciones tomadas de 143 radares de vigilancia climática para construir y evaluar un sistema de estimaciones migratorias para la migración de aves nocturnas en los Estados Unidos contiguos. Identificamos el número de noches de mitigación requeridas para reducir el riesgo de peligros aéreos para el 50% de las aves migratorias que pasan por un área específica en la primavera y en el otoño con base en las estimaciones dinámicas de la actividad migratoria. También investigamos una estrategia alternativa: el uso de una estrategia fija de conservación basada en las ventanas temporales que históricamente han capturado el 50% del pasaje migratorio. En la práctica, durante la primavera y el otoño, las estimaciones dinámicas requirieron menos noches de acción en comparación con la selección de ventana fija en todas las localidades (primavera: promedio de 7.3 más días de alerta; otoño: promedio de 12.8 más días de alerta). Este patrón resultó en parte por la naturaleza pulsada de las migraciones aviarias capturadas en los datos del radar, en los cuales la mayoría de las aves (54.3%) se mueven durante el 10% de las noches durante la temporada migratoria. Nuestros resultados resaltan los beneficios que tienen las estimaciones ecológicas a corto plazo en comparación con las estáticas, especialmente de frente a los riesgos crecientes que encaran las aves migratorias por la contaminación lumínica, la infraestructura de energía eólica y las colisiones con las estructuras.【摘要】 短期生态预测可以提供及时的相关预测来指导有效的行动, 从而减轻人类改造自然对野生动物造成的负面影响。本研究利用美国鸟类迁徙系统, 展示了生态预测在鸟类飞行保护方面的应用。我们利用 143 个气象监视雷达的数百万次观测, 构建并评估了一个针对美国境内鸟类夜间迁徙的迁徙预测系统。根据对迁徙活动的动态预测, 我们确定了鸟类迁徙所需夜晚的天数, 从而可以降低春秋季节通过特定地区 50%候鸟面临的空中危害的风险。我们还研究了另一种替代方法, 它采用基于时间窗口的固定保护策略, 可以覆盖历史上50%的迁徙通道。我们在实践中发现, 春秋两季, 基于动态预报的所有位点需要采取保护行动的夜晚数都比基于固定窗口选择所需的夜晚数要少 (春季平均相差 7.3 个警戒日, 秋季平均相差 12.8 个警戒日) 。出现这种模式的部分原因是因为雷达数据捕捉到的鸟类迁徙具有脉冲属性, 其中大多数鸟类 (53.4%) 会在一个迁徙季节 10%的夜晚中完成迁徙。我们的研究结果强调了短期生态预测的好处, 以及动态减缓策略相对于静态策略的潜在优势, 特别是在光污染、风能基础设施以及与构筑物碰撞对候鸟造成的风险日益增加的情况下。【翻译:胡怡思;审校:聂永刚】.

Human behavior profoundly affects the natural world. Migratory birds are particularly susceptible to adverse effects of human activities because the global networks of ecosystems on which birds rely are undergoing rapid change. In spite of these chal-lenges, the blackcap (Sylvia atricapilla) is a thriving migratory species. Its recent es-tablishment of high- latitude wintering areas in Britain and Ireland has been linked to climate change and backyard bird feeding, exemplifying the interaction between human activity and migrant ecology. To understand how anthropogenic influences shape avian movements and ecology, we marked 623 wintering blackcaps at 59 sites across Britain and Ireland and compiled a dataset of 9929 encounters. We investi-gated visitation behavior at garden feeding sites, inter-annual site fidelity, and move-ments within and across seasons. We analyzed migration tracks from 25 geolocators fitted to a subset of individuals to understand how garden behavior may impact sub-sequent migration and breeding. We found that blackcaps wintering in Britain and Ireland showed high site fidelity and low transience among wintering sites, in contrast to the itinerant movements characteristic of blackcaps wintering in their traditional winter range. First-winter birds showed lower site fidelity and a greater likelihood of transience than adults. Adults that frequented gardens had better body condition, smaller fat stores, longer bills, and rounder wingtips. However, blackcaps did not ex-clusively feed in gardens; visits were linked to harsher weather. Individuals generally stayed at garden sites until immediately before spring departure. Our results suggest that supplementary feeding is modifying blackcap winter ecology and driving mor-phological evolution. Supplemental feeding may have multifaceted benefits on win-ter survival, and these positive effects may carry over to migration and subsequent breeding. Overall, the high individual variability in blackcap movement and foraging ecology, and the flexibility it imparts, may have allowed this species to flourish during rapid environmental change.

Seasonal migration is a complex and variable behaviour with the potential to promote reproductive isolation. In Eurasian blackcaps ( Sylvia atricapilla ), a migratory divide in central Europe separating populations with southwest (SW) and southeast (SE) autumn routes may facilitate isolation, and individuals using new wintering areas in Britain show divergence from Mediterranean winterers. We tracked 100 blackcaps in the wild to characterize these strategies. Blackcaps to the west and east of the divide used predominantly SW and SE directions, respectively, but close to the contact zone many individuals took intermediate (S) routes. At 14.0° E, we documented a sharp transition from SW to SE migratory directions across only 27 (10–86) km, implying a strong selection gradient across the divide. Blackcaps wintering in Britain took northwesterly migration routes from continental European breeding grounds. They originated from a surprisingly extensive area, spanning 2000 km of the breeding range. British winterers bred in sympatry with SW-bound migrants but arrived 9.8 days earlier on the breeding grounds, suggesting some potential for assortative mating by timing. Overall, our data reveal complex variation in songbird migration and suggest that selection can maintain variation in migration direction across short distances while enabling the spread of a novel strategy across a wide range.

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.

Increasing global urbanisation has steered research towards understanding biodiversity in urban areas. Old city spaces throughout Europe have a proliferation of urban court gardens, which can create a mosaic of habitat pockets in an urban area. This article examines the patterns and drivers of avian species richness and community structure in 20 gardens of the constituent colleges of the University of Oxford. We conducted morning surveys across 7 weeks in May and June 2017 and used an information-theoretic approach and model averaging to identify important habitat predictors of species richness. We also studied community structure with Sorensen indices and non-metric multi-dimensional analysis. A total of 43 avian species were observed across all sites. Our sites generally differed in their avian assemblages, with greater species turnover than nestedness between sites. Site area was the strongest predictor of site species richness and surrounding habitat composition was the dominant driver of community structure. Thus, the largest gardens were the most species rich, but species composition among gardens differed based on the habitats in which they were embedded. We support using island biogeography theory to understand the avian species assemblages of urban ecosystems and stress the suitability of our study sites for future urban ecosystem research and generating wildlife awareness.

Summary Climate change is rapidly advancing spring phenology [ 1 , 2 , 3 ] but at different rates in different species [ 1 , 4 ]. Whether these advances are solely driven by phenotypic plasticity [ 2 , 5 ] or also involve evolution is hotly debated (e.g., [ 5 , 6 , 7 ]). In some species, including avian long-distance migrants, plastic responses to early springs may be constrained by inherited circannual timing programs [ 8 , 9 ], making evolutionary adjustment the only viable mechanism for keeping pace with shifting phenology [ 5 , 10 ]. This constraint may be contributing to population declines in migratory species [ 5 , 10 , 11 , 12 ]. To test whether a migrant’s timing program has evolved [ 10 , 12 ], we replicated an experimental study of the annual cycle of long-distance migratory pied flycatchers (Ficedula hypoleuca) after 21 years of warming. Flycatchers are a model for studying constrained ecological responses to climate change [ 6 , 10 , 12 , 13 ]. We show that the phase of the flycatcher circannual clock controlling spring moult, migration, and reproductive timing advanced by 9 days. A nearby wild population mirrored these changes, concurrently advancing egg-laying by 11 days. Furthermore, the time window during which wild flycatcher reproductive timing was most sensitive to ambient temperature advanced by 0.8 days year–1. These results support a role of phenotypic evolution [ 14 ] in changing spring phenology [ 15 , 16 ]. We suggest that the timing programs of long-distance migratory birds may have greater adaptive potential than previously thought, leaving some scope for evolutionary rescue in a changing climate.

Large networks of weather radars are comprehensive instruments for studying bird migration. For example, the US WSR-88D network covers the entire continental US and has archived data since the 1990s. The data can quantify both broad and fine-scale bird movements to address a range of migration ecology questions. However, the problem of automatically discriminating precipitation from biology has significantly limited the ability to conduct biological analyses with historical radar data. We develop MistNet, a deep convolutional neural network to discriminate precipitation from biology in radar scans. Unlike prior machine learning approaches, MistNet makes fine-scaled predictions and can collect biological information from radar scans that also contain precipitation. MistNet is based on neural networks for images, and includes several architecture components tailored to the unique characteristics of radar data. To avoid a massive human labelling effort, we train MistNet using abundant noisy labels obtained from dual polarization radar data. In historical and contemporary WSR-88D data, MistNet identifies at least 95.9% of all biomass with a false discovery rate of 1.3%. Dual polarization training data and our radar-specific architecture components are effective. By retaining biomass that co-occurs with precipitation in a single radar scan, MistNet retains 15% more biomass than traditional whole-scan approaches to screening. MistNet is fully automated and can be applied to datasets of millions of radar scans to produce fine-grained predictions that enable a range of applications, from continent-scale mapping to local analysis of airspace usage. Radar ornithology is advancing rapidly and leading to significant discoveries about continent-scale patterns of bird movements. General-purpose and empirically validated methods to quantify biological signals in radar data are essential to the future development of this field. MistNet can enable large-scale, long-term, and reproducible measurements of whole migration systems.

Many species of migratory birds have evolved the ability to migrate at night, and the recent and rapid expansion of artificial light at night has markedly altered the nighttime sky through which they travel. Migrating birds regularly pass through heavily illuminated landscapes, and bright lights affect avian orientation. But risks to migrating birds from artificial light are not spatially or temporally uniform, representing a challenge for mitigating potential hazards and developing action plans to catalog risks at continental scales. We leveraged over two decades of remote-sensing data collected by weather surveillance radar and satellite-based sensors to identify locations and times of year when the highest numbers of migrating birds are exposed to light pollution in the contiguous US. Our continental-scale quantification of light exposure provides a novel opportunity for dynamic and targeted conservation strategies to address the hazards posed by light pollution to nocturnally migrating birds.

The natural history of the Sapayoa Sapayoa aenigma, the sole member of the Sapayoidae and the only New World representative of the ‘Old World suboscines’, is poorly known. Previously, we reported a pair of adult Sapayoas breeding with assistance from two immature males, but their kinship was unknown. Here, we use double-digest restriction site-associated DNA sequencing (ddRAD-seq) to conduct parentage and relatedness analyses among this group. We found that the members of the adult pair were unrelated, but all other dyads were probably first order (parent-offspring or full sibling). In addition, the helper males were very unlikely to have sired either of the chicks. We conclude that the group consisted of two unrelated adults and two offspring from a previous brood. These results provide important context for social behaviours observed within the group, which included mounting events; such behaviour may be involved in group cohesion.

Migrating birds make strategic decisions at multiple temporal and spatial scales. They must select flight altitudes, speeds, and orientations in order to maintain preferred directions of movement and to minimize energy expenditure and risk. Spring flights follow a rapid phenology, but how this rapid transit translates to in-flight decisions is not clear. We described flight strategies of nocturnally migrating landbirds using 6 weather surveillance radars during spring (2013–2015) and fall (2013–2014) migratory periods in the eastern United States to investigate seasonal decision-making patterns and how climate change may influence these trends. During spring, we found groundspeed and airspeed of migrants to be significantly higher than those of fall migrants; compensation for wind drift was also significantly greater during spring. Our results indicate that birds make more rapid and precise flights in spring that are only partially explained by meteorological phenomena. Future applications at gre...

The Sapayoa (Sapayoa aenigma), a low-density resident of Choco rainforests from Panama to Ecuador, has long perplexed ornithologists. It was originally described as a manakin (Pipridae), but molecular work has revealed its closest living relatives to be Old World suboscines (Eurylaimides) and supported its placement in the monotypic family of Sapayoidae. Despite such phylogenetic intrigue, little is known about the Sapayoa's general life history or reproductive biology; only one nest has been described. We present information on 2 actively attended and 13 inactive Sapayoa nests in Darien National Park, Panama. We provide the first detailed description of individual effort at an active nest, family group dynamics during the nesting period, the plumage of immature birds, and the range of vocalizations produced. We also present the first documentation of cooperative breeding and compile several recent nesting observations, extending the published Sapayoa breeding period by several months. Furthermor...

The migratory patterns of birds have been the focus of ecologists for millennia. What behavioural traits underlie these remarkably consistent movements? Addressing this question is central to advancing our understanding of migratory flight strategies and requires the integration of information across levels of biological organisation, e.g. species to communities. Here, we combine species-specific observations from the eBird citizen-science database with observations aggregated from weather surveillance radars during spring migration in central North America. Our results confirm a core prediction of migration theory at an unprecedented national scale: body mass predicts variation in flight strategies across latitudes, with larger-bodied species flying faster and compensating more for wind drift. We also find evidence that migrants travelling northward earlier in the spring increasingly compensate for wind drift at higher latitudes. This integration of information across biological scales provides new insight into patterns and determinants of broad-scale flight strategies of migratory birds.

Light cues elicit strong responses from nearly all forms of life, perhaps most notably as circadian rhythms entrained by periods of daylight and darkness. Atypical periods of darkness, like solar eclipses, provide rare opportunities to study biological responses to light cues. By using a continental scale radar network, we investigated responses of flying animals to the total solar eclipse of 21 August 2017. We quantified the number of biological targets in the atmosphere at 143 weather radar stations across the continental United States to investigate whether the decrease in light and temperature at an atypical time would initiate a response like that observed at sunset, when activity in the atmosphere usually increases. Overall, biological activity decreased in the period leading to totality, followed by a short low-altitude spike of biological activity during totality in some radars. This pattern suggests that cues associated with the eclipse were insufficient to initiate nocturnal activity comparable to that occurring at sunset but sufficient to suppress diurnal activity.

Heterogeneous patterns of genomic differentiation are commonly documented between closely related populations and there is considerable interest in identifying factors that contribute to their formation. These factors could include genomic features (e.g., areas of low recombination) that promote processes like linked selection (positive or purifying selection that affects linked neutral sites) at specific genomic regions. Examinations of repeatable patterns of differentiation across population pairs can provide insight into the role of these factors. Birds are well suited for this work, as genome structure is conserved across this group. Accordingly, we re-estimated relative (FST) and absolute (dXY) differentiation between eight sister pairs of birds that span a broad taxonomic range using a common pipeline. Across pairs, there were modest but significant correlations in window-based estimates of differentiation (up to 3% of variation explained forFSTand 26% fordXY), supporting a role for processes at conserved genomic features in generating heterogeneous patterns of differentiation. This suggestion was reinforced by linear models identifying several genomic features (e.g., gene densities) as significant predictors ofFSTanddXYrepeatability.FSTrepeatability was higher among pairs that were further along the speciation continuum (i.e., more reproductively isolated), suggesting that early stages of speciation may be dominated by positive selection that is different between pairs and replaced by processes acting according to shared genomic features as speciation proceeds.

Billions of animals cross the globe each year during seasonal migrations, but efforts to monitor them are hampered by the irregularity and relative unpredictability of their movements. We developed a bird migration forecast system with continental scope by leveraging 23 years of spring observations to learn associations between atmospheric conditions and bird migration intensity. Our models explained up to 81% of variation in migration intensity across the United States at altitudes of 0-3000 m, and performance remained high when forecasting events 24-72 h into the future (68-72% variation explained). We infer that avian migratory movements across the United States frequently exceed 200 million individuals per night and exceed 500 million individuals per night during peak passage. Accurately forecasting bird migration will allow stakeholders to reduce collisions with illuminated buildings, airplanes, and wind turbines, predict movements under climate change scenarios, and engage the public.

Remote sensors such as Doppler radars are providing novel insights into the migrations of diverse animal taxa, but limits in scope and sensitivity can hamper the utility of these tools. For example, studies investigating whether songbirds compensate effectively for wind displacement during nocturnal migration have been challenged by the need to assess behavior on a large scale. In addition, these studies typically overlook the potential role low-altitude diurnal flights play in dealing with unfavorable winds. In such cases, a combination of approaches—new and traditional—may be necessary to understand behavior more completely. Here, we unite ground-based visual observations with a new radar analysis method to investigate how songbirds deal with crosswinds over the northeast United States. We find that nocturnally migrating birds experienced significant wind drift, even though they often flew at 90° or more to the wind direction. Significantly, more birds undertook reoriented diurnal flights after nocturnal wind drift, and wind influence, nocturnal migration intensity, and time of season together explained the majority of variation in counts of these "morning flights." This study shows that bird behavior during migration can be strongly shaped by the danger of wind drift and that some songbird species respond to drift with reoriented diurnal migratory flights. Knowledge of birds’ interactions with wind is essential for successfully modeling migratory behavior and assessing the risks associated with changing habitats and meteorological patterns. Furthermore, an understanding of the degree to which drift defines migratory behaviors may have value across animal taxa.

Many passerines that typically migrate at night also engage in migratory flights just after sunrise. These widely observed “morning flights” often involve birds flying in directions other than those aimed toward their ultimate destinations, especially in coastal areas. Morning flights have received little formal investigation, and their study may improve our understanding of how birds orient themselves during and after nocturnal movements and how they use stopover habitat. We studied autumn morning flights in the northeastern United States to identify associations between the number of birds undertaking morning flights and the magnitude of nocturnal migratory movements, nocturnal winds, and local topography. Our analyses included observations of more than 15,000 passerines at 7 locations. We found positive relationships between morning flight size and nocturnal migration density and winds aloft: Significantly more birds flew following larger nocturnal movements, quantified from weather surveillan...

Comparative studies of genomic differentiation among independent lineages can provide insights into aspects of the speciation process, such as the relative importance of selection and drift in shaping genomic landscapes, the role of genomic regions of high differentiation, and the prevalence of convergent molecular evolution. We investigated patterns of genetic diversity and divergence in stonechats (genusSaxicola), a widely distributed avian species complex with phenotypic variation in plumage, morphology, and migratory behavior, to ask whether similar genomic regions are important in the evolution of independent, but closely related, taxa. We used whole-genome pooled sequencing of 262 individuals from 5 taxa and found that patterns of genetic diversity and divergence are highly similar among different stonechat taxa. We then asked if these patterns remain correlated at deeper evolutionary scales and found that homologous genomic regions have become differentiated in stonechats and the closely relatedFicedulaflycatchers. Such correlation across a range of evolutionary divergence and among phylogenetically independent comparisons suggests that similar processes may be driving the differentiation of these independently evolving lineages, which in turn may be the result of intrinsic properties of particular genomic regions (e.g., areas of low recombination). Consequently, studies employing genome scans to search for areas important in reproductive isolation should account for corresponding regions of differentiation, as these regions may not necessarily represent speciation islands or facilitate local adaptation.

Bird migration occurs at the largest of global scales, but monitoring such movements can be challenging. In the US there is an operational network of weather radars providing freely accessible data for monitoring meteorological phenomena in the atmosphere. Individual radars are sensitive enough to detect birds, and can provide insight into migratory behaviors of birds at scales that are not possible using other sensors. Archived data from the WSR-88D network of US weather radars hold valuable and detailed information about the continent-scale migratory movements of birds over the last 20 years. However, significant technical challenges must be overcome to understand this information and harness its potential for science and conservation. We describe recent work on an AI system to quantify bird migration using radar data, which is part of the larger BirdCast project to model and forecast bird migration at large scales using radar, weather, and citizen science data.

The shortest possible migratory route for birds is not always the best route to travel. Substantial research effort has established that birds in captivity are capable of orienting toward the direction of an intended goal, but efforts to examine how free-living birds use navigational information under conditions that potentially make direct flight toward that goal inefficient have been limited in spatiotemporal scales and in the number of individuals observed because of logistical and technological limitations. Using novel and recently developed techniques for analysis of Doppler polarimetric weather surveillance radar data, we examined two impediments for nocturnally migrating songbirds in eastern North America following shortest-distance routes: crosswinds and oceans. We found that migrants in flight often drifted sideways on crosswinds, but most strongly compensated for drift when near the Atlantic coast. Coastal migrants’ tendency to compensate for wind drift also increased through the night, while no strong temporal differences were observed at inland sites. Such behaviors suggest that birds migrate in an adaptive way to conserve energy by assessing while airborne the degree to which they must compensate for wind drift.

The Rusty-breasted Antpitta (Grallaricula f 33 errugineipectus) is widely distributed within the tropical Andes of South America. We analyzed 73 study specimens, 25 vouchered tissue samples and 123 audio recordings to assess geographic genetic, vocal, and morphological variation and evaluate species limits. We found that Grallaricula ferrugineipectus as currently defined is polyphyletic because populations from Colombia and Venezuela form a clade that is closely related to Andean populations of G. nana, whereas populations from Peru and Bolivia are recovered as sister to G. lineifrons. Birds in Colombia and Venezuela (the northern group) last shared a common ancestor with birds from Peru and Bolivia (the southern group) more than 10 million years ago. Northern and southern groups additionally differ in song, suggesting that they may have evolved substantial premating reproductive isolation. Discriminant function analysis reliably distinguished songs from northern and southern groups in multivariate acoustic space, but univariate analyses found non-overlapping acoustic variation between northern and southern groups in only one trait, mean note maximum frequency (and other correlated measures of song pitch). This suggests that the “three-trait” threshold for using vocalizations to inform species limits, which was developed for another suboscine group, the antbirds (Thamnophilidae), may be conservative when applied to antpittas (Grallariidae). In addition, we document apparent clinal variation in song pace within the southern group, a rare example of a suboscine with geographic clinal variation in a vocal trait. Finally, we show that northern and southern groups differ markedly in morphology. In summary, northern and southern groups of Rusty-breasted Antpittas are divergent in genetics, vocalizations and morphology, demonstrating that these taxa are best classified as two monophyletic, biological species with allopatric distributions.

Wind plays a significant role in the flight altitudes selected by nocturnally migrating birds. At mid-latitudes in the Northern Hemisphere, atmospheric conditions are dictated by the polar-front jet stream, whose amplitude increases in the autumn. One consequence for migratory birds is that the region’s prevailing westerly winds become progressively stronger at higher migration altitudes. We expect this seasonality in wind speed to result in migrants occupying progressively lower flight altitudes, which we test using density estimates of nocturnal migrants at 100 m altitudinal intervals from 12 weather surveillance radar stations located in the northeastern USA. Contrary to our expectations, median migration altitudes deviated little across the season, and the variance was lower during the middle of the season and higher during the beginning and especially the end of the season. Early-season migrants included small- to intermediate-sized long-distance migrants in the orders Charadriiformes and Passeriformes, and late-season migrants included large-bodied and intermediate-distance migrants in the order Anseriformes. Therefore, seasonality in the composition of migratory species, and related variation in migration strategies and behaviours, resulted in a convex–concave bounded distribution of migration altitudes. Our results provide a basis for assessing the implications for migratory bird populations of changes in mid-latitude atmospheric conditions probably occurring under global climate change.

1. Migration is a common strategy used by birds that breed in seasonal environments, and multiple environmental and biological factors determine the timing of migration. How these factors operate in combination during autumn migration, which is considered to be under weaker time constraints relative to spring migration, is not clear. 2. Here, we examine the patterns and determinants of migration timing for nocturnal migrants during autumn migration in the north-eastern USA using nocturnal reflectivity data from 12 weather surveillance radar stations and modelled diurnal probability of occurrence for 142 species of nocturnal migrants. We first model the capacity of seasonal atmospheric conditions (wind and precipitation) and ecological productivity (vegetation greenness) to predict autumn migration intensity. We then test predictions, formulated under optimal migration theory, on how migration timing should be related to assemblage-level estimates of body size and total migration distance within the context of dietary guild (insectivore and omnivore) and level of dietary plasticity during autumn migration. 3. Our results indicate seasonal declines in ecological productivity delineate the beginning and end of peak migration, whose intensity is best predicted by the velocity of winds at migration altitudes. Insectivorous migrants departed earlier in the season and, consistent with our predictions, large-bodied and long-distance insectivorous migrants departed the earliest. Contrary to our predictions, large-bodied and some long-distance omnivorous migrants departed later in the season, patterns that were replicated in part by insectivorous migrants that displayed dietary plasticity during autumn migration. 4. Our findings indicate migration timing in the region is dictated by optimality strategies, modified based on the breadth and flexibility of migrant's foraging diets, with declining ecological productivity defining possible resource thresholds during which migration occurs when winds at migration altitudes are mild. These observations provide the basis to assess how avian migration strategies may be affected by adjustments in seasonal patterns of atmospheric circulation and ecological productivity that may occur under global climate change.

The lower atmosphere (i.e. aerosphere) is critical habitat for migrant birds. This habitat is vast and little is known about the spatio-temporal patterns of distribution and abundance of migrants in it. Increased human encroachment into the aerosphere makes understanding where and when migratory birds use this airspace a key to reducing human–wildlife conflicts. We use weather surveillance radar to describe large-scale height distributions of nocturnally migrating birds and interpret these distributions as aggregate habitat selection behaviours of individual birds. As such, we detail wind cues that influence selection of flight heights. Using six radars in the eastern USA during the spring (2013–2015) and autumn (2013 and 2014), we found migrants tended to adjust their heights according to favourable wind profit. We found that migrants' flight altitudes correlated most closely with the altitude of maximum wind profit; however, absolute differences in flight heights and height of maximum wind profit were large. Migrants tended to fly slightly higher at inland sites compared with coastal sites during spring, but not during autumn. Migration activity was greater at coastal sites during autumn, but not during spring. This characterization of bird migration represents a critical advance in our understanding of migrant distributions in flight and a new window into habitat selection behaviours.

Billions of birds migrate at night over North America each year. However, few studies have described the phenology of these movements, such as magnitudes, directions, and speeds, for more than one migration season and at regional scales. In this study, we characterize density, direction, and speed of nocturnally migrating birds using data from 13 weather surveillance radars in the autumns of 2010 and 2011 in the northeastern USA. After screening radar data to remove precipitation, we applied a recently developed algorithm for characterizing velocity profiles with previously developed methods to document bird migration. Many hourly radar scans contained windborne "contamination," and these scans also exhibited generally low overall reflectivities. Hourly scans dominated by birds showed nightly and seasonal patterns that differed markedly from those of low reflectivity scans. Bird migration occurred during many nights, but a smaller number of nights with large movements of birds defined regional nocturnal migration. Densities varied by date, time, and location but peaked in the second and third deciles of night during the autumn period when the most birds were migrating. Migration track (the direction to which birds moved) shifted within nights from south-southwesterly to southwesterly during the seasonal migration peaks; this shift was not consistent with a similar shift in wind direction. Migration speeds varied within nights, although not closely with wind speed. Airspeeds increased during the night; groundspeeds were highest between the second and third deciles of night, when the greatest density of birds was migrating. Airspeeds and groundspeeds increased during the fall season, although groundspeeds fluctuated considerably with prevailing winds. Significant positive correlations characterized relationships among bird densities at southern coastal radar stations and northern inland radar stations. The quantitative descriptions of broadscale nocturnal migration patterns presented here will be essential for biological and conservation applications. These descriptions help to define migration phenology in time and space, fill knowledge gaps in avian annual cycles, and are useful for monitoring long-term population trends of migrants. Furthermore, these descriptions will aid in assessing potential risks to migrants, particularly from structures with which birds collide and artificial lighting that disorients migrants.