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Waterfowl migrations are large‐scale events that involve millions of birds moving over broad geographic extents, which make them difficult to quantify and study. Historically, wildlife managers have relied mostly on field surveys, such as visual counts from the ground or air that sample at small spatial or temporal extents, or both. Combining field surveys with remote sensing data comprehensively collected over large spatial extents at high temporal frequency may improve the study of migrating waterfowl distributions. We tested the strength of the relationship between broad‐scale weather surveillance radar data and fine‐scale field surveys of waterfowl abundance at wetlands within the Rainwater Basin of Nebraska, USA, from 2017–2019. Radar reflectivity of waterfowl at the peak exodus of evening flights was positively correlated with diurnal waterfowl count data, although there was unexplained variation in the relationship. The association was also very similar across various time scales ranging from daily to monthly averages of waterfowl abundance. We suggest that human‐based ground surveys can calibrate and leverage more comprehensive remote sensing data to get a broad understanding of waterfowl distributions during migration. Several confounding factors, such as spatial displacement between radar and survey observation, individual variation in orientation and body size, and identification of avian species sampled by radar, remain on the path to improving radar‐based waterfowl estimates. [ABSTRACT FROM AUTHOR]

Migratory landbirds in North America are experiencing dramatic population declines. Although considerable research and conservation attention have been directed toward these birds' breeding and wintering grounds, far less is known about the areas used as stopover sites during migration. To address this knowledge gap, we used 5 years of weather surveillance radar data to map seasonal stopover densities of landbirds across the eastern United States during spring and autumn migration. We identified stopover hotspots covering 2.47 million ha that consistently support high densities of migratory landbirds in spring or autumn. However, only 16.7% of these sites are hotspots in both seasons. The distribution of hotspots is shifted eastward in autumn compared with spring. Deciduous forest is the most important habitat type in both seasons, with deciduous forest fragments embedded in broadly deforested regions having the highest probability of being hotspots. The concentration of birds in these forest fragments is stronger in spring, especially in the agricultural Midwest. We found generally higher stopover densities in protected areas than in unprotected areas in both seasons. Nonetheless, only one-third of identified stopover hotspots have some sort of protected status, and more than half of these protected hotspots are subject to extractive uses. A well-distributed network of well-protected stopover areas, complementing conservation efforts on the breeding and wintering grounds, is essential to sustaining healthy populations of migratory landbirds in North America. • Weather radar can map seasonal stopover hotspots for landbirds in the eastern US • There is little spatial overlap between spring and autumn hotspots • Birds concentrate in deciduous forest fragments at stopover, especially in spring • Only one-third of identified hotspots are in protected areas Using weather radar, Guo et al. map the seasonal stopover density of migratory landbirds and identify stopover hotspots across the eastern United States. They find little overlap in the distribution of spring versus autumn hotspots. Most of these hotspots do not fall within protected areas, especially for deciduous forest fragments where birds concentrate. [ABSTRACT FROM AUTHOR]

Migrating birds require en route habitats to rest and refuel. Yet, habitat use has never been integrated with passage to understand the factors that determine where and when birds stopover during spring and autumn migration. Here, we introduce the stopover‐to‐passage ratio (SPR), the percentage of passage migrants that stop in an area, and use 8 years of data from 12 weather surveillance radars to estimate over 50% SPR during spring and autumn through the Gulf of Mexico and Atlantic coasts of the south‐eastern US, the most prominent corridor for North America's migratory birds. During stopovers, birds concentrated close to the coast during spring and inland in forested landscapes during autumn, suggesting seasonal differences in habitat function and highlighting the vital role of stopover habitats in sustaining migratory communities. Beyond advancing understanding of migration ecology, SPR will facilitate conservation through identification of sites that are disproportionally selected for stopover by migrating birds. [ABSTRACT FROM AUTHOR]

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There are several remote-sensing tools readily available for the study of nocturnally flying animals (e.g., migrating birds), each possessing unique measurement biases. We used three tools (weather surveillance radar, thermal infrared camera, and acoustic recorder) to measure temporal and spatial patterns of nocturnal traffic estimates of flying animals during the spring and fall of 2011 and 2012 in Lewes, Delaware, USA. Our objective was to compare measures among different technologies to better understand their animal detection biases. For radar and thermal imaging, the greatest observed traffic rate tended to occur at, or shortly after, evening twilight, whereas for the acoustic recorder, peak bird flight-calling activity was observed just prior to morning twilight. Comparing traffic rates during the night for all seasons, we found that mean nightly correlations between acoustics and the other two tools were weakly correlated (thermal infrared camera and acoustics, r -- 0.004 ± 0.04 SE, n -- 100 nights; radar and acoustics, r -- 0.14 ± 0.04 SE, n -- 101 nights), but highly variable on an individual nightly basis (range -- --0.84 to 0.92, range -- --0.73 to 0.94). The mean nightly correlations between traffic rates estimated by radar and by thermal infrared camera during the night were more strongly positively correlated (r -- 0.39 ± 0.04 SE, n -- 125 nights), but also were highly variable for individual nights (range -- --0.76 to 0.98). Through comparison with radar data among numerous height intervals, we determined that flying animal height above the ground influenced thermal imaging positively and flight call detections negatively. Moreover, thermal imaging detections decreased with the presence of cloud cover and increased with mean ground flight speed of animals, whereas acoustic detections showed no relationship with cloud cover presence but did decrease with increased flight speed. We found sampling methods to be positively correlated when comparing mean nightly traffic rates across nights. The strength of these correlations generally increased throughout the night, peaking 2-3 hours before morning twilight. Given the convergence of measures by different tools at this time, we suggest that researchers consider sampling flight activity in the hours before morning twilight when differences due to detection biases among sampling tools appear to be minimized. [ABSTRACT FROM AUTHOR]