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Migratory animals are affected by various factors during their journeys, and the study of animal movement by radars has been instrumental in revealing key influences of the environment on flying migrants. Radars enable the simultaneous tracking of many individuals of almost all sizes within the radar range during day and night, and under low visibility conditions. We review how atmospheric conditions, geographic features and human development affect the behavior of migrating insects and birds as recorded by radars. We focus on flight initiation and termination, as well as in‐flight behavior that includes changes in animal flight direction, speed and altitude. We have identified several similarities and differences in the behavioral responses of aerial migrants including an overlooked similarity in the use of thermal updrafts by very small (e.g. aphids) and very large (e.g. vultures) migrants. We propose that many aerial migrants modulate their migratory flights in relation to the interaction between atmospheric conditions and geographic features. For example, aerial migrants that encounter crosswind may terminate their flight or continue their migration and may also drift or compensate for lateral displacement depending on their position (over land, near the coast or over sea). We propose several promising directions for future research, including the development and application of algorithms for tracking insects, bats and large aggregations of animals using weather radars. Additionally, an important contribution will be the spatial expansion of aeroecological radar studies to Africa, most of Asia and South America where no such studies have been undertaken. Quantifying the role of migrants in ecosystems and specifically estimating the number of departing birds from stopover sites using low‐elevation radar scans is important for quantifying migrant–habitat relationships. This information, together with estimates of population demographics and migrant abundance, can help resolve the long‐term dynamics of migrant populations facing large‐scale environmental changes. [ABSTRACT FROM AUTHOR]

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]

Increasingly, data from weather surveillance radars are being used by biologists investigating the ecology and behavior of birds, insects, and bats in the aerosphere. Unfortunately, these radars quantify echoes caused by layered biological targets such as migrating birds in a manner that introduces bias in radar measures. We investigated the performance of a bias-adjustment algorithm that adjusts radar measures for vertical variation of reflectivity, nonstandard beam refraction, and spatial displacement of radar targets. We evaluated the efficacies of four variations of this algorithm by their ability to increase correspondence between radar reflectivity measured at two weather radar sites and the ground density of migrating birds measured during two autumn seasons and two spring seasons among 24 hardwood forest sites along the northern coast of the Gulf of Mexico. The algorithm integrated close-range reflectivity data from the five lowest elevation angle sweeps to derive high-resolution vertical profiles of reflectivity (VPRs) that closely corresponded to the observed vertical target density profiles based on a vertically oriented portable radar. The radar reflectivity of birds aloft near the onset of migratory flight was positively correlated with the bird density on the ground. All four radar data adjustment schemes that we tested produced significant improvement in the accuracy of bird density estimates relative to unadjusted radar data. In general, adjusting reflectivity based solely on the VPRs derived using observed refractive conditions yielded the most accurate radar-based estimates of bird density. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The distributions of birds during migratory stopovers are influenced by a hierarchy of factors. For example, in temperate regions, migrants are concentrated near areas of bright artificial light at night (ALAN) and also the coastlines of large water bodies at broad spatial scales. However, less is known about what drives broad-scale stopover distributions in the tropics. We quantified seasonal densities of nocturnally migrating landbirds during spring and fall of 2011–2015, using two weather radars on the Yucatan peninsula, Mexico (Sabancuy and Cancun). We tested the influence of environmental predictors in explaining broad-scale bird stopover densities. We predicted higher densities in areas (1) closer to the coast in the fall and farther away in spring and (2) closer to bright ALAN and with lower ALAN intensity in both seasons. We found that birds were more concentrated near the coastline in the fall and away from it in spring around Cancun but not Sabancuy. Counter to our expectations, we detected increased bird densities with increased distance from lights in spring around Sabancuy, and in both seasons around Cancun, suggesting avoidance of bright areas during those seasons. This is the first evidence of broad-scale bird avoidance of bright areas during stopover. [ABSTRACT FROM AUTHOR]