Artificial light is a pollutant of growing global concern. For nocturnally migrating birds, the consequences can be fatal. Attracted and disoriented by illuminated infrastructure, birds can become victims of collisions, especially when visibility is reduced by fog and clouds. Birds crossing large, predominantly dark bodies of water can suddenly be confronted with patches of lit coastal areas. In contrast, when flying over land along the coast, birds are sequentially confronted with lit areas and are likely to rely on different navigation cues. We deployed two ornithological radars in proximity along the Croatian coast: one at a light-polluted site and one at a near-natural site. The aim was to maximise the contrast in light pollution while keeping other site-specific factors similar. We monitored the consecutive spring migration seasons of 2023 and 2024 and modelled the effect of light pollution on the number of birds in the air, mean airspeeds and mean flight altitudes, considering atmospheric, temporal, and directional predictors. Our results are partially hampered by the fact that we had to exclude a second radar pair from the analysis due to a technical defect. Nevertheless, we found evidence for attraction towards light pollution of sea-crossing birds in the remaining radar pair. Furthermore, we found a significant contribution of light pollution to the reduction of mean airspeeds and altitudes, especially in an overcast context. Besides indicating disorientation, our results raise serious concerns about increased numbers of bird collisions associated with migration peaks and impaired visibility, even with lower-intensity light pollution.

Each spring, migratory birds converge along the Croatian coast from various directions, creating a dynamic intersection of flight paths. Many birds are thought to cross the Adriatic Sea, while others follow a northward route along the coastline. As most migratory birds initiate flight shortly after sunset, we hypothesized that sea-crossing migrants would arrive with a delay at the Croatian coast, compared to migrants that were following the coast, resulting in potentially intricate spatiotemporal patterns that remain poorly understood. We deployed four ornithological radar devices along the Croatian coastline: two in southwestern Istria and two in northern Dalmatia. These radars tracked migratory bird activity up to 1000 m above ground, recording intensity and flight directions and their variations across sites, seasons, and individual nights. We conducted an exploratory analysis of these variations, applied functional principal component analysis and hierarchical clustering to summarise within-night activity profiles, and compared these profiles between sites and across the migration season, alongside associated flight direction distributions. During the early migration season, migration intensity was similar across all technically active sites, but site-to-site variation increased markedly in May. In March, flight directions were predominantly towards NNE, indicating mainly sea-crossing migration throughout the night. In April, NW directions dominated the first half of the night, shifting to scattered N directions later; in Dalmatia, even strong W components were observed early in the night. By May, W to NW movement towards the Italian coast were typical for early-night activity. Later in the night, flight directions shifted towards NE over Istria and N at the Dalmatian site in Zadar, while the site at Vrana exhibited a wide scatter, warranting further discussion. Contrary to our expectations, within-night intensity profiles could not be fully linked to specific directional patterns. This study points to the complex interplay between coastal and sea-crossing migration along the Croatian coast. Our results demonstrate significant variability in the timing of migration within single nights in the context of aquatic barriers. Crossing such a barrier results in downstream delays compared to birds migrating along the barrier. Between nights, one behaviour or the other may dominate the overall activity, causing the shifts in within-night timing. In addition, barrier crossing is likely to be strongly influenced by weather conditions, contributing to the variability in the within-night timing of migration. However, measured flight directions were not always consistent with within-night timing, highlighting the complexity of avian migration in the context of aquatic barriers. This highlights the need for further research with high temporal resolution to gain a deeper understanding of migration behaviour in response to such barriers.

Bat migration is an ecologically important yet poorly understood phenomenon. This is in part because monitoring these migrations is challenging, due to bats' nocturnal behaviors and their sometimes high-altitude migratory flights. This study presents the first radar-based examination of multi-annual migratory bat phenology in Europe, utilizing vertical-looking radar data collected on the Swabian Plateau in Germany between September 2019 and December 2022. Bat activity was consistently low in winter and increased gradually from March onwards to a peak between July and September. Across all years, pre-maternity migration began between late February and mid-March, while post-maternity migration ended between late October and mid-November. We estimated peak radar-based migration traffic rates between 1159 and 2473 bats per km, with the highest peak recorded on 4 July 2022. Correlations between radar-derived nightly bat numbers and simultaneously acquired acoustic recordings ranged from 0.47 to 0.70 for the pre-maternity season, and from 0.14 to 0.71 during post-maternity migration. Both monitoring techniques showed peak bat activity during the summer, with smaller surges in September and October. The radar, however, detected significantly more bats overall. These findings showcase how vertical-looking radars can be used to quantify and characterize seasonal variability in high-altitude bat movements. Through strategic future radar deployments and the analysis of available historical datasets, our current understanding of migratory bat seasonality, routes, and intensity could increase drastically, and underpin the development of effective protocols for biodiversity conservation. Die Migration der Flederm & auml;use ist ein & ouml;kologisch wichtiges, aber noch wenig verstandenes Ph & auml;nomen. Dies liegt zum Teil daran, dass die & Uuml;berwachung der Flugbewegungen schwierig ist, da Flederm & auml;use nachtaktiv und h & auml;ufig in gro ss er H & ouml;he unterwegs sind. Diese Studie pr & auml;sentiert die erste radarbasierteUntersuchung von mehrj & auml;hrig erfassten ph & auml;nologischen Mustern ziehender Flederm & auml;use in Europa. Die Daten wurden mit einem vertikal ausgerichteten Radarger & auml;t erhoben, das zwischen September 2019 und Dezember 2022 in Deutschland auf der Schw & auml;bischen Alb in Betrieb war. Die Fledermausaktivit & auml;t war im Winter durchwegs gering und nahm ab M & auml;rz allm & auml;hlich zu, mit einem H & ouml;hepunkt zwischen Juli und September. In allen Jahren begann die pr & auml;-maternale Wanderung zwischen Ende Februar und Mitte M & auml;rz, w & auml;hrend die post-maternale Wanderung zwischen Ende Oktober und Mitte November endete. Wir ermittelten n & auml;chtliche Fledermausaktivit & auml;tspeaks zwischen 1159 und 2473 Flederm & auml;usen pro Kilometer, wobei der h & ouml;chste Wert am 4. Juli 2022 registriert wurde. Korrelationen zwischen radarerfassten n & auml;chtlichen Fledermauszahlen und gleichzeitig aufgezeichneten akustischen Daten lagen in der pr & auml;-maternalen Saison zwischen 0.47 und 0.70, und w & auml;hrend der post-maternalen Wanderung zwischen 0.14 und 0.71. Beide & Uuml;berwachungstechniken registrierten im Sommer die h & ouml;chste Fledermausaktivit & auml;t, mit kleineren Anstiegen im September und Oktober. Das Radar detektierte jedoch insgesamt deutlich mehr Flederm & auml;use. Diese Ergebnisse zeigen, wie vertikal ausgerichtete Radare verwendet werden k & ouml;nnen, um die saisonale Variabilit & auml;t von Fledermausbewegungen in gro ss er H & ouml;he zu quantifizieren und zu charakterisieren. Durch eine strategische Platzierung von Radarger & auml;ten und die Analyse verf & uuml;gbarer historischer Datens & auml;tze k & ouml;nnte unser derzeitiges Verst & auml;ndnis der Saisonalit & auml;t, des Verlaufs der Zugwege und der Anzahlen wandernder Flederm & auml;use erheblich erweitert werden, sowie die Entwicklung wirksamer Artenschutzprotokolle unterst & uuml;tzen.

Operational bird migration forecast models have recently offered promising perspectives for mitigating the impacts of human activities on avifauna. These models improve on simple phenological expectations by harnessing the intricate relationship between bird movements and weather conditions to forecast migration fluxes days in advance. However, state-of-the-art models face limitations as bird fluxes are often simply modelled as a response to local and instantaneous weather without accounting for previous and synoptic weather patterns. This study focuses on enhancing bird migration forecasts by evaluating the contributions of weather dynamics at various spatial and temporal scales. We use bird vertical density data from 9 French weather radars over 6 years and employ gradient-boosted regression trees for predictions. Dimension reduction tools are used to describe local and continental-scale weather conditions from the previous three days. We also explore the contributions of the different meteorological metrics considered using explainable regression trees tools. Our model improved phenology models by explaining about 1.3 and 2.25 times more additional variance than approaches based on local and instantaneous weather conditions in spring and autumn, respectively. Local and instantaneous weather metrics contributed the most, but they mainly helped identifying nights with low migration. In contrast, weather metrics for previous 3 days were crucial to forecast highest intensity migration events, as they enabled to account for bird accumulation in relation to unfavorable weather locally and remotely. This study enhanced forecast accuracy and contributed to a deeper understanding of the factors influencing bird migration. It enabled the identification local and synoptic weather patterns related to important migration events without a priori knowledge. It is therefore easy to interpret, easy to transfer to other ecological systems, and promising for the accurate forecast of migration peaks. Forecasted peaks can guide conservation efforts, for example by dimming lights for birds at night or by shutting down wind turbines.

The path-breaking work of Eastwood (1967) provided comprehensive information on the use of surveillance radar for the study of bird migration, reference to initial studies applying pencil-beam radar, and a first hint to the use of tracking radar. Pencil-beam radars can provide information on the temporal and spatial distribution of migrating birds. Radars with tracking capacity yield data on the flight behavior of individually tracked day and night migrants and on wind conditions at the altitudes where the birds fly. The Swiss Ornithological Institute used the military tracking radar “Superfledermaus” continuously from 1968 till 2010: a) to quantify migratory passage and vertical distribution, and b) to study migratory behavior by tracking single targets. In the early 1990s, the radar was adapted to become a dedicated bird radar, and the geographic range of studies was extended far beyond the boundaries of Switzerland, from Israel to Spain and from the Baltic Sea to the Sahara (Bruderer, Vogelwarte 58:255–272, 2020). Over a period of 42 years, more than 400,000 tracks of migrating birds were electronically recorded and are now available for further investigations. Positioning mobile radars at sites with challenging environmental conditions allows studying the response of migrating birds to particular requirements, such as flights across large water surfaces, mountain ranges or deserts under varying influence of meteorological factors. Covering the relevant parts of migratory seasons in spring and autumn, the available data sets comprise ample variation for the study of specific questions on in-flight behavior of migratory birds. In comparison with long-range individual tracking devices, the radar data comprise larger numbers of individuals from restricted areas, i.e. half-spheres of about 5 km radius. The available data offer possibilities for studies on the geographic, topographic, and meteorological particularities of bird migration at the various radar stations. They also cover a wide range of atmospheric conditions and wing-beat patterns of birds, allowing studies on the variation of flight behavior of selected bird types in varying environments.

Weather radars detect more than weather, they also continuously register the movements of billions of animals aloft in the lower atmosphere. This makes archived, unfiltered weather radar data a goldmine for biological monitoring purposes, providing coverage of the aerial habitat in a way no other method can. Here we present two datasets of biological data extracted from European weather radar data, obtained through a collaboration with the Operational Programme for the Exchange of Weather Radar Information (OPERA) and three national meteorological services. The datasets were created by processing weather radar data with methods optimized for extracting bird targets, resulting in vertical profiles of biological targets. The datasets collectively cover 141 radar stations in 18 countries, from 2008 to 2023. Data quality and coverage differs between years, countries, and radar stations, so care must be taken when evaluating data for each specific use case. Despite these challenges the datasets are currently the most comprehensive of their kind in Europe and open new avenues in understanding continental scale movements of aerial animals.

Abstract Studying nocturnal bird migration is challenging because direct visual observations are difficult during darkness. Radar has been the means of choice to study nocturnal bird migration for several decades, but provides limited taxonomic information. Here, to ascertain the feasibility of enhancing the taxonomic resolution of radar data, we combined acoustic data with vertical‐looking radar measurements to quantify thrush (Family: Turdidae) migration. Acoustic recordings, collected in Helsinki between August and October of 2021–2022, were used to identify likely nights of high and low thrush migration. Then, we built a random forest classifier that used recorded radar signals from those nights to separate all migrating passerines across the autumn migration season into thrushes and non‐thrushes. The classifier had a high overall accuracy (≈0.82), with wingbeat frequency and bird size being key for separation. The overall estimated thrush autumn migration phenology was in line with known migratory patterns and strongly correlated (Pearson correlation coefficient ≈0.65) with the phenology of the acoustic data. These results confirm how the joint application of acoustic and vertical‐looking radar data can, under certain migratory conditions and locations, be used to quantify ‘family‐level’ bird migration.

Abstract The Alps are a natural barrier for avian broad‐front migration in Central Europe. While most birds that approach the Alps are deflected and circumvent the mountains, some choose to make the crossing. Here, they are funnelled and channelled in valleys, leading to high bird densities. Many Alpine valleys are suitable locations for wind farms, potentially creating a conflict between wind energy production and bird conservation. Collisions can be reduced by temporarily shutting down wind turbines. This however requires timely coordination, either by locally monitoring migration intensity or by extrapolating and forecasting migratory fluxes from other sites. However, little is known about the timing and intensity of bird migration in valleys of the central Alps, especially during spring migration. This study presents a 2‐year quantification of avian migration across the Alps. We collected terrestrial radar data at three sites: two located in Alpine valleys and one in the lowland, close to the northern foothills of the Alps. We found high migration traffic rates (MTR) during both migration seasons in the Alpine valleys, with outstanding numbers of migrants during the spring season. The strong alignment of the flight directions with the main orientation of alpine valleys highlights the importance of valleys and the connected passes in channelling migratory fluxes through the Alps. However, extrapolating migration intensities and forecasting peak migration events for inner Alpine sites is difficult, likely due to how migratory patterns and activity are influenced by the complexity of the local topography and the associated dynamic wind and weather conditions. Instead, we call for year‐round on‐site monitoring of migration intensities and strategies tailored to the local context to reduce the risk of bird strikes at wind turbines in the Alps.

Insects are of increasing conservation concern as a severe decline of both biomass and biodiversity have been reported. At the same time, data on where and when they occur in the airspace is still sparse, and we currently do not know whether their density is linked to the type of landscape above which they occur. Here, we combined data of high-flying insect abundance from six locations across Switzerland representing rural, urban and mountainous landscapes, which was recorded using vertical-looking radar devices. We analysed the abundance of high-flying insects in relation to meteorological factors, daytime, and type of landscape. Air pressure was positively related to insect abundance, wind speed showed an optimum, and temperature and wind direction did not show a clear relationship. Mountainous landscapes showed a higher insect abundance than the other two landscape types. Insect abundance increased in the morning, decreased in the afternoon, had a peak after sunset, and then declined again, though the extent of this general pattern slightly differed between landscape types. We conclude that the abundance of high-flying insects is not only related to abiotic parameters, but also to the type of landscapes and its characteristics, which, on a long-term, should be taken into account for when designing conservation measures for insects.

Weather radar networks have great potential for continuous and long-term monitoring of aerial biodiversity of birds, bats, and insects. Biological data from weather radars can support ecological research, inform conservation policy development and implementation, and increase the public's interest in natural phenomena such as migration. Weather radars are already used to study animal migration, quantify changes in populations, and reduce aerial conflicts between birds and aircraft. Yet efforts to establish a framework for the broad utilization of operational weather radar for biodiversity monitoring are at risk without suitable data policies and infrastructure in place. In Europe, communities of meteorologists and ecologists have made joint efforts toward sharing and standardizing continent-wide weather radar data. These efforts are now at risk as new meteorological data exchange policies render data useless for biodiversity monitoring. In several other parts of the world, weather radar data are not even available for ecological research. We urge policy makers, funding agencies, and meteorological organizations across the world to recognize the full potential of weather radar data. We propose several actions that would ensure the continued capability of weather radar networks worldwide to act as powerful tools for biodiversity monitoring and research.

Wind has a significant yet complex effect on bird migration speed. With prevailing south wind, overall migration is generally faster in spring than in autumn. However, studies on the difference in airspeed between seasons have shown contrasting results so far, in part due to their limited geographical or temporal coverage. Using the first full-year weather radar data set of nocturnal bird migration across western Europe together with wind speed from reanalysis data, we investigate variation of airspeed across season. We additionally expand our analysis of ground speed, airspeed, wind speed, and wind profit variation across time (seasonal and daily) and space (geographical and altitudinal). Our result confirms that wind plays a major role in explaining both temporal and spatial variabilities in ground speed. The resulting airspeed remains relatively constant at all scales (daily, seasonal, geographically and altitudinally). We found that spring airspeed is overall 5% faster in Spring than autumn, but we argue that this number is not significant compared to the biases and limitation of weather radar data. The results of the analysis can be used to further investigate birds' migratory strategies across space and time, as well as their energy use.

Airspace is a key but not well-understood habitat for many animal species. Enormous amounts of insects and birds use the airspace to forage, disperse, and migrate. Despite numerous studies on migration, the year-round flight activities of both birds and insects are still poorly studied. We used a 2 year dataset from a vertical-looking radar in Central Europe and developed an iterative hypothesis-testing algorithm to investigate the general temporal pattern of migratory and local movements. We estimated at least 3 million bird and 20 million insect passages over a 1 km transect annually. Most surprisingly, peak non-directional bird movement intensities during summer were of the same magnitude as seasonal directional movement peaks. Birds showed clear peaks in seasonally directional movements during day and night, coinciding well with the main migration period documented in this region. Directional insect movements occurred throughout the year, paralleling non-directional movements. In spring and summer, insect movements were non-directional; in autumn, their movements concentrated toward the southwest, similar to birds. Notably, the nocturnal movements of insects did not appear until April, while directional movements mainly occurred in autumn. This simple monitoring reveals how little we still know about the movement of biomass through airspace.

Biodiversity is changing at an unprecedented rate, and long-term monitoring is key to quantifying these changes and identifying their drivers (1, 2). Weather radars are an essential tool for meeting these goals. However, recent policy changes make vital data unavailable. Data policy should be adjusted to take into account the broad role that weather radars play beyond meteorology.

To understand the influence of biomass flows on ecosystems, we need to characterize and quantify migrations at various spatial and temporal scales. Representing the movements of migrating birds as a fluid, we applied a flow model to bird density and velocity maps retrieved from the European weather radar network, covering almost a year. We quantified how many birds take-off, fly, and land across Western Europe to (1) track bird migration waves between nights, (2) cumulate the number of birds on the ground and (3) quantify the seasonal flow into and out of the study area through several regional transects. Our results identified several migration waves that crossed the study area in 4 days only and included up to 188 million (M) birds that took-off in a single night. In spring, we estimated that 494 M birds entered the study area, 251 M left it, and 243 M birds remained within the study area. In autumn, 314 M birds entered the study area while 858 M left it. In addition to identifying fundamental quantities, our study highlights the potential of combining interdisciplinary data and methods to elucidate the dynamics of avian migration from nightly to yearly time scales and from regional to continental spatial scales.

Recent and archived data from weather radar networks are extensively used for quantification of continent-wide bird migration pattern. While discriminating birds from weather signals is well established, insect contamination is still a problem. We present a simple method combining two doppler radar products within a single Gaussian-mixture model to estimate the proportions of birds and insects within a single measurement, as well as the density and speed of birds and insects. The method can be applied to any existing archives of vertical bird profiles, such as the ENRAM repository (enram.eu) with no need to recalculate the huge amount of original polar volume data, which often are not available.

Recent and archived data from weather radar networks are extensively used for the quantification of continent-wide bird migration patterns. While the process of discriminating birds from weather signals is well established, insect contamination is still a problem. We present a simple method combining two Doppler radar products within a Gaussian mixture model to estimate the proportions of birds and insects within a single measurement volume, as well as the density and speed of birds and insects. This method can be applied to any existing archives of vertical bird profiles, such as the European Network for the Radar surveillance of Animal Movement repository, with no need to recalculate the huge amount of original polar volume data, which often are not available.

The spatial and temporal patterns of broad front bird migration are governed by the geospatial distributions of landmasses, mountain ranges, and weather conditions. These distributions interact with the birds' innate program during migration and are critical to successful migration. Hence, favourable environmental conditions for migration consequently lead to spatio-temporal concentrations, and the evolution of specific migratory flyways. Based on the aerodynamic properties of the ten most abundant nocturnal long-distance migrants, we developed a computational framework to simulate millions of individual trajectories across Europe using an agent-based simulation approach. We simulated a three-week period of autumn migration with a temporal resolution of 30 s. Departure conditions were derived from bird densities observed within the first two hours after sunset, which were extracted from the weather radar network. Individual itineraries were strongly influenced by the behavioural reactions to the environment such as the wind flow, coastlines and mountain ranges. Wind speed and direction are among the key factors that shape migration patterns such as reverse movements observed within some nights. Accumulation of migration was triggered by the combined effect of geographic barriers (coastlines, mountain ranges) and wind. The overall result of the simulation corresponds well with the large-scale pattern of bird migration intensities measured across the study area, for instance the high migration intensity observed between the Atlantic coast and the Pyrenees. Our model framework conjoins all important domains, such as the birds' preconditions and behavioural scope, as well as the spatio-temporal dynamics of the environment. However, for the time being we cannot decide whether local discrepancies between model and data are due to environmental effects that are not yet captured by our simulation (i.e. effect of rain on migration intensity), or caused by differences in the sensitivity of the local weather radar systems. Due to the limited time period and lack of more accurate data for validation, our findings are preliminary. Further progress in data quality and hopefully better access of bird profiles from the continent-wide weather radar network will allow to improve model performance and implement a bird migration forecasting similar to weather forecasts. Apart from assessing conflicts between human activities and bird movements, this would greatly enhance our understanding of biomass flow on a large scale.

Description This dataset contains the vertical profiles and integrated time series of bird density and flight speed (NS and EW) used in Nussbaumer (2019) [open access: https://www.mdpi.com/2072-4292/11/19/2233]. Data are stored in a JavaScript Object Notation (JSON) file for each radar, with the following structure:{ "name" : "bejab", //code name of the radar (http://eumetnet.eu/wp-content/themes/aeron-child/observations-programme/current-activities/opera/database/OPERA_Database/index.html) "lat" : 51.1917, //Latitude "lon" : 3.0642, //Longitude "height" : 50, //Height of the radar antenna [m] a.s.l. "maxrange" : 25, //Maximum range [km] used for profile "alt" : [100, 300,...], "time" : ["19-Sep-2016 00:00:00", "19-Sep-2016 00:05:00",...], "dens" : [[...],...], //Vertical profile of bird density [1/km3] "u" : [[...],...], //Vertical profile of bird flight speed in East(+)/West(-) [m/s] "v" : [[...],...], //Vertical profile of bird flight speed in North(+)/South(-) [m/s] "denss" : [...], //Integrated profile of bird density [1/km2] "us" : [...], //Integrated profile of bird flight speed in East(+)/West(-) [m/s] "vs" : [...], //Integrated profile of bird flight speed in North(+)/South(-) [m/s] }Procedure The raw data are downloaded on the ENRAM repository,( see Dokter (2011) and (2019) for more details) and processed according to the procedure described below. Of the 84 radars contributing data during the study period, 11 radars are discarded because of their poor quality due to S-band radar type, poor processing or large gaps (temporal or altitude cut). The same radars were removed in Nilsson et al. (2019).In addition, the 4 radars from Bulgaria and Portugal were excluded because of their geographic isolation. The full vertical profile was discarded when rain was present at any altitude bin. A dedicated MATLAB GUI was used to visualise the data and manually set bird densities to “not-a-number” in such cases. Zones of high bird densities can sometimes be incorrectly eliminated in the raw data. To address this, Nilsson et al. (2019) excluded problematic time or height ranges from the data. Here, in order to keep as much data as possible, the data was manually edited to replace erroneous data either with “not-a-number”, or by cubic interpolation using the dedicated MATLAB GUI. Due to ground scattering,the lower altitude layers are sometimes contaminated by errors or excluded in the raw data. We vertically interpolated bird density by copying the first layer without error into to the lower ones. This approach is relatively conservative as bird migration intensity usually decreases with height in the absence of obstacles, and more so in autumn (Bruderer, 2018) The vertical profiles are vertically integrated from the radar altitude and up to 5000 m asl. The data recorded during daytime are excluded. Daytime is defined at each radar by the civil dawn and dusk (6° below horizon). Finally, the data of 10 radars with high temporal resolution (5-10minutes) was down-sampled to 15 minutes to preserve a balanced representation of each radar. The resulting cleaned vertical-integrated time series of nocturnal bird density can be viewed in vp_corrected.zip. More details and illustrations are available in Nussbaumer (2019) [open access: https://www.mdpi.com/2072-4292/11/19/2233], Acknowledgement We acknowledge the European Operational Program for Exchange of Weather Radar Information (EUMETNET/OPERA) for providing access to European radar data, faciliated through a research-only license agreement between EUMETNET/OPERA members and ENRAM. References Bruderer, B.; Liechti, F. Variation in density and height distribution of nocturnal migration in the south of israel. Israel Journal of Zoology 1995, 41, 477–487. doi:10.1080/00212210.1995.10688815. Dokter A. M. , F. Liechti, H. Stark, L. Delobbe, P. Tabary, and I. Holleman, “Bird migration flight altitudes studied by a network of operational weather radars,” J. R. Soc. Interface, vol. 8, no. 54, pp. 30–43, Jan. 2011. doi:10.1098/rsif.2010.0116 Dokter A. M. , P. Desmet, J. H. Spaaks, S. van Hoey, L. Veen, L. Verlinden, C. Nilsson, G. Haase, H. Leijnse, A. Farnsworth, W. Bouten, and J. Shamoun‐Baranes, “bioRad: biological analysis and visualization of weather radar data,” Ecography (Cop.)., vol. 42, no. 5, pp. 852–860, May 2019. doi: 10.1111/ecog.04028 Nilsson, C.; Dokter, A.M.; Verlinden, L.; Shamoun-Baranes, J.; Schmid, B.; Desmet, P.; Bauer, S.; Chapman, J.; Alves, J.A.; Stepanian, P.M.; Sapir, N.;Wainwright, C.; Boos, M.; Górska, A.; Menz, M.H.M.; Rodrigues, P.; Leijnse, H.; Zehtindjiev, P.; Brabant, R.; Haase, G.; Weisshaupt, N.; Ciach, M.; Liechti, F. Revealing patterns of nocturnal migration using the European weather radar network. Ecography 2019, 42, 876–886. doi:10.1111/ecog.04003. Nussbaumer R., L. Benoit, G. Mariethoz, F. Liechti, S. Bauer, and B. Schmid, “A Geostatistical Approach to Estimate High Resolution Nocturnal Bird Migration Densities from a Weather Radar Network,” Remote Sens., vol. 11, no. 19, p. 2233, Sep. 2019. doi: 10.3390/rs11192233