BATScan: A radar classification tool reveals large‐scale bat migration patterns

Bach P., Voigt C.C., Göttsche M., Bach L., Brust V., Hill R., Hüppop O., Lagerveld S., Schmaljohann H., Seebens‐Hoyer A.

Addison F.I., Dally T., Duncan E.J., Rouse J., Evans W.L., Hassall C., Neely R.R.

Electromagnetic modelling may be used as a tool for understanding the radar cross section (RCS) of volant animals. Here, we examine this emerging method in detail and delve deeper into the specifics of the modelling process for a single noctuid moth, with the hope of illuminating the importance of different aspects of the process by varying the morphometric and compositional properties of the model. This was accomplished by creating a high-fidelity three-dimensional insect model by micro-CT scanning a gold-palladium-coated insect. Electromagnetic simulations of the insect model were conducted by applying different morphological and compositional configurations using the WiPL-D Pro 3D Electromagnetic Solver. The simulation results show that high-resolution modelling of insects has advantages compared to the simple ellipsoidal models used in previous studies. We find that the inclusion of wings and separating the composition of the body, wings, and legs and antennae have an impact on the resulting RCS of the specimen. Such modifications to the RCS are missed when a prolate spheroid model is used and should not be ignored in future studies. Finally, this methodology has been shown to be useful in exploring the changes in the RCS that result from variations in specimen size. As such, utilising this methodology further for more species will improve the ability to quantitatively interpret aeroecological observations of weather surveillance radars and special-purpose entomological radars.

Zhai J., Qi J., Shen C.

In many practical applications, the data are class imbalanced. Accordingly, it is very meaningful and valuable to investigate the classification of imbalanced data. In the framework of binary imbalanced data classification, the synthetic minority oversampling technique (SMOTE) is the best-known oversampling method. However, for each positive sample, SMOTE generates only k synthetic samples on the lines between the positive sample and its k-nearest neighbors, resulting in three drawbacks: (1) SMOTE cannot effectively extend the training field of positive samples; (2) the generated positive samples lack diversity; (3) SMOTE does not accurately approximate the probability distribution of the positive samples. Therefore, two binary imbalanced data classification methods named BIDC1 and BIDC2 based on diversity oversampling by generative models are proposed. The BIDC1 and BIDC2 conduct diversity oversampling using extreme learning machine autoencoder and generative adversarial network, respectively. Extensive experiments on 26 data sets are conducted to compare the two methods with 14 state-of-the-art methods using five metrics: F-measure, G-means, AUC-area, MMD-score, and Silhouette-score. The experimental results demonstrate that the two methods outperform the other 14 methods.

Shi X., Schmid B., Tschanz P., Segelbacher G., Liechti F.

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.

Castillo-Figueroa D.

New World bats play a significant role in ecosystem functioning and are imperative for maintaining environmental services. Nevertheless, human-caused environmental changes are jeopardizing bat communities, which results in the loss of functional roles provided by them. It is important, therefore, to assess ecological processes performed by bats in the Neotropics to define priorities in further research for better conservation planning. In this systematic review, I identify general trends, advances, bias, and knowledge gaps in bat-mediated ecological processes across Neotropical ecosystems. I conducted an extensive search on Google scholar, Scopus, Web of science, and Bat Eco–Interactions Database resulting in 538 references, of which 185 papers were included in the review. The papers were published in 76 peer-reviewed journals, with the highest peak between 2006-2010. From the six biomes recorded, Moist broadleaf tropical forest was the most researched, contrary to Montane biomes (<2000 m), where few studies have been conducted. Seed dispersal was the process with more studies (44%), followed by pollination (38%), nutrient cycling (10%) and arthropod suppression (8%). Seed dispersal and pollination displayed large bias on specific bat-plant systems and ecoregions, thus being important to explore other bat and plant species as well as other ecosystems. Arthropod suppression and nutrient cycling were largely overlooked despite to constitute essential functions in ecosystem resilience; particularly, more research is needed to know cascading effects on plant fitness in different agroforestry systems, but also is key the understanding of how bats can be pivotal mobile links in terrestrial ecosystems and cave environments. I highlight the importance to consider bats with multiple roles and functional trait-based approach to gain a comprehensive understanding of their functionality. Bat extirpations are likely to affect their ecological roles, therefore, mitigating major threats of bats are urgently needed to sustain ecosystem integrity in the Neotropics. Even though functional studies have increased in the last two decades, several aspects of bat roles are still obscured and is necessary to keep evaluating their ecological and economic importance to provide useful information for major decision-makings in Neotropical ecosystems' conservation.

Schmaljohann H.

Brunton D.F.

It seems reasonable that birds that court or mate in the air over lakes or rivers should be capable of taking off from water or be able to swim, as they might find themselves in the water as a result of this activity. Nonetheless, interaction with water has rarely been documented in the wild and has not been reported for any species of swift in Canada. I report an incident of such activity, however, from Oliver, British Columbia. In this case, I observed a White-throated Swift (Aeronautes saxatalis) swimming vigorously for over 10 minutes before reaching dry land approximately 85 m away. The bird likely fell into the water as a result of flight miscalculations during aerial courtship or mating. I speculate that its swimming capability was aided by the long, narrow, flipper-like wings of the species. I did not observe the bird take flight from the water surface. From these observations, it is evident that White-throated Swifts are relatively strong, capable swimmers, at least for short periods.

Lacher T.E., Davidson A.D., Fleming T.H., Gómez-Ruiz E.P., McCracken G.F., Owen-Smith N., Peres C.A., Vander Wall S.B.

The diverse functional roles of over 6,000 species of extant mammals that range in body size across eight orders of magnitude, from blue whales (Balaenoptera musculus) to tiny Etruscan shrews (Suncus etruscus), contribute to shaping Earth's ecosystems. Large mammalian herbivores (e.g., African elephants [Loxodonta africana], American bison [Bison bison], hippopotamuses [Hippopotamus amphibius]) and carnivores (e.g., wolves [Canis lupus], pumas [Puma concolor], sea otters [Enhydra lutris]) often have significant effects on primary producers in terrestrial, aquatic, and marine systems through nutrient cycling, energy flow, and the exertion of bottom-up and top-down processes. Small mammals, like bats, are important pollinators, dispersers of fruits, and consumers of arthropods, and others, especially rodents and primates, are important predators and dispersers of seeds. Many of these mammal-mediated processes occur simultaneously in the same ecosystem, and have significant effects on community structure of primary producers that in turn alter communities of other vertebrates and invertebrates. Many mammals also are ecosystem engineers (e.g., elephants, American beavers [Castor canadensis], porcupines [Erithezon dorsatum], prairie dogs [Cynomys spp.]) that create, significantly modify, or destroy habitat, and by doing so, they alter ecosystem structure and function and increase habitat heterogeneity and biodiversity. The extensive influence mammals have on ecosystems results in important services that contribute to human well-being, such as pollination, insect pest control, and bioturbation of soils. The rapid declines in abundance of many mammal populations and the associated increase in extinction risk raise conservation concerns for mammals. To maintain mammalian diversity and the critical ecosystem processes they provide, scientists need to mobilize concern for their status and strive for more effective and comprehensive conservation action. We provide insights and synthesis on the ecological role of mammals and highlight key research questions and future directions for their conservation.

Phillips E.M., Horne J.K., Zamon J.E., Felis J.J., Adams J.

Studies estimating species' distributions require information about animal locations in space and time. Location data can be collected using surveys within a predetermined frame of reference (i.e., Eulerian sampling) or from animal-borne tracking devices (i.e., Lagrangian sampling). Integration of observations obtained from Eulerian and Lagrangian perspectives can provide insights into animal movement and habitat use. However, contemporaneous data from both perspectives are rarely available, making examination of biases associated with each sampling approach difficult. We compared distributions of a mobile seabird observed concurrently from ship, aerial, and satellite tag surveys during May, June, and July 2012 in the northern California Current. We calculated utilization distributions to quantify and compare variability in common murre (Uria aalge) space use and examine how sampling perspective and platform influence observed patterns. Spatial distributions of murres were similar in May, regardless of sampling perspective. Greatest densities occurred in coastal waters off southern Washington and northern Oregon, near large murre colonies and the mouth of the Columbia River. Density distributions of murres estimated from ship and aerial surveys in June and July were similar to those observed in May, whereas distributions of satellite-tagged murres in June and July indicated northward movement into British Columbia, Canada, resulting in different patterns observed from Eulerian and Lagrangian perspectives. These results suggest that the population of murres observed in the northern California Current during spring and summer includes relatively stationary individuals attending breeding colonies and nonstationary, vagile adults and subadults. Given the expected growth of telemetry studies and advances in survey technology (e.g., unmanned aerial systems), these results highlight the importance of considering methodological approaches, spatial extent, and synopticity of distribution data sets prior to integrating data from different sampling perspectives.

Schmid B., Zaugg S., Votier S.C., Chapman J.W., Boos M., Liechti F.

Quantitative radar studies are an important component of studying the movements of birds. Whether a bird, at a certain distance from the radar, is detected or not depends on its size. The volume monitored by the radar is therefore different for birds of different sizes. Consequently, an accurate quantification of bird movements recorded by small-scale radar requires an accurate determination of the monitored volume for the objects in question, although this has tended to be ignored. Here, we demonstrate the importance of sensitivity settings for echo detection on the estimated movement intensities of birds of different sizes. The amount of energy reflected from a bird and detected by the radar receiver (echo power) depends not only on the bird's size and on the distance from the radar antenna, but also on the beam shape and the bird's position within this beam. We propose a method to estimate the size of a bird based on the wingbeat frequency, retrieved from the echo-signal, independent of the absolute echo power. The estimated bird-size allows calculation of size-specific monitored volumes, allowing accurate quantification of movement intensities. We further investigate the importance of applying size-specific monitored volumes to quantify avian movements instead of using echo counts. We also highlight the importance of accounting for size-specific monitored volume of small scale radar systems, and the necessity of reporting technical information on radar parameters. Applying this framework will increase the quality and validity of quantitative radar monitoring.

Fleming T.H.

This article summarizes current knowledge about the migratory behavior of temperate and tropical bats. A close association between migration and hibernation exists in temperate, but not in tropical, bats. Compared with birds, bats are relatively short-distance migrators, with maximum migration distances being

Dokter A.M., Desmet P., Spaaks J.H., van Hoey S., Veen L., Verlinden L., Nilsson C., Haase G., Leijnse H., Farnsworth A., Bouten W., Shamoun‐Baranes J.

Weather surveillance radars are increasingly used for monitoring the movements and abundances of animals in the airspace. However, analysis of weather radar data remains a specialised task that can be technically challenging. Major hurdles are the difficulty of accessing and visualising radar data on a software platform familiar to ecologists and biologists, processing the low-level data into products that are biologically meaningful, and summarizing these results in standardized measures. To overcome these hurdles, we developed the open source R package bioRad, which provides a toolbox for accessing, visualizing and analyzing weather radar data for biological studies. It provides functionality to access low-level radar data, process these data into meaningful biological information on animal speeds and directions at different altitudes in the atmosphere, visualize these biological extractions, and calculate further summary statistics. The package aims to standardize methods for extracting and reporting biological signals from weather radars. Here we describe a roadmap for analyzing weather radar data using bioRad. We also define weather radar equivalents for familiar measures used in the field of migration ecology, such as migration traffic rates, and recommend several good practices for reporting these measures. The bioRad package integrates with low-level data from both the European radar network (OPERA) and the radar network of the United States (NEXRAD). bioRad aims to make weather radar studies in ecology easier and more reproducible, allowing for better inter-comparability of studies.

Egert-Berg K., Hurme E.R., Greif S., Goldstein A., Harten L., Herrera M. L.G., Flores-Martínez J.J., Valdés A.T., Johnston D.S., Eitan O., Borissov I., Shipley J.R., Medellin R.A., Wilkinson G.S., Goerlitz H.R., et. al.

Observations of animals feeding in aggregations are often interpreted as events of social foraging, but it can be difficult to determine whether the animals arrived at the foraging sites after collective search [1-4] or whether they found the sites by following a leader [5, 6] or even independently, aggregating as an artifact of food availability [7, 8]. Distinguishing between these explanations is important, because functionally, they might have very different consequences. In the first case, the animals could benefit from the presence of conspecifics, whereas in the second and third, they often suffer from increased competition [3, 9-13]. Using novel miniature sensors, we recorded GPS tracks and audio of five species of bats, monitoring their movement and interactions with conspecifics, which could be inferred from the audio recordings. We examined the hypothesis that food distribution plays a key role in determining social foraging patterns [14-16]. Specifically, this hypothesis predicts that searching for an ephemeral resource (whose distribution in time or space is hard to predict) is more likely to favor social foraging [10, 13-15] than searching for a predictable resource. The movement and social interactions differed between bats foraging on ephemeral versus predictable resources. Ephemeral species changed foraging sites and showed large temporal variation nightly. They aggregated with conspecifics as was supported by playback experiments and computer simulations. In contrast, predictable species were never observed near conspecifics and showed high spatial fidelity to the same foraging sites over multiple nights. Our results suggest that resource (un)predictability influences the costs and benefits of social foraging.

Niemi J., Tanttu J.

An automatic bird identification system is required for offshore wind farms in Finland. Indubitably, a radar is the obvious choice to detect flying birds, but external information is required for actual identification. We applied visual camera images as external data. The proposed system for automatic bird identification consists of a radar, a motorized video head and a single-lens reflex camera with a telephoto lens. A convolutional neural network trained with a deep learning algorithm is applied to the image classification. We also propose a data augmentation method in which images are rotated and converted in accordance with the desired color temperatures. The final identification is based on a fusion of parameters provided by the radar and the predictions of the image classifier. The sensitivity of this proposed system, on a dataset containing 9312 manually taken original images resulting in 2.44 × 106 augmented data set, is 0.9463 as an image classifier. The area under receiver operating characteristic curve for two key bird species is 0.9993 (the White-tailed Eagle) and 0.9496 (The Lesser Black-backed Gull), respectively. We proposed a novel system for automatic bird identification as a real world application. We demonstrated that our data augmentation method is suitable for image classification problem and it significantly increases the performance of the classifier.

Voigt C.C., Currie S.E., Fritze M., Roeleke M., Lindecke O.

Werber Y., Sapir N.

Rafiq K., Beery S., Palmer M.S., Harchaoui Z., Abrahms B.

The emergence of generative artificial intelligence (AI) models specializing in the generation of new data with the statistical patterns and properties of the data upon which the models were trained has profoundly influenced a range of academic disciplines, industry and public discourse. Combined with the vast amounts of diverse data now available to ecologists, from genetic sequences to remotely sensed animal tracks, generative AI presents enormous potential applications within ecology. Here we draw upon a range of fields to discuss unique potential applications in which generative AI could accelerate the field of ecology, including augmenting data-scarce datasets, extending observations of ecological patterns and increasing the accessibility of ecological data. We also highlight key challenges, risks and considerations when using generative AI within ecology, such as privacy risks, model biases and environmental effects. Ultimately, the future of generative AI in ecology lies in the development of robust interdisciplinary collaborations between ecologists and computer scientists. Such partnerships will be important for embedding ecological knowledge within AI, leading to more ecologically meaningful and relevant models. This will be critical for leveraging the power of generative AI to drive ecological insights into species across the globe. This Progress discusses potential applications of artificial intelligence models that generate new data and how they can be used to advance ecology research.

Lagerveld S., de Vries P., Harris J., Parsons S., Debusschere E., Hüppop O., Brust V., Schmaljohann H.

Migratory bats perform seasonal movements between their summer and winter areas. When crossing ecological barriers, like the open sea, they are exposed to an increased mortality risk due to energetically demanding long-distance flights and unexpected inclement weather events. How such barriers affect bat migratory movements is still poorly known. To study bat migration patterns in response to an ecological barrier, we tagged 44 Nathusius’ pipistrelles Pipistrellus nathusii with radio-transmitters on the East coast of the United Kingdom (UK) in spring 2021 and 2022. Subsequently, we assessed their movements to continental Europe using the MOTUS Wildlife Tracking System. We investigated route selection, timing of migration, overall migration speed and the influence of wind on airspeed, groundspeed and flight altitude during migratory overseas flights. Barrier effects cause migratory movements along the coast, and crossings over sea are shortened by deviating from the general migration direction. Males depart from the UK later in the season compared to females. The overall migration speed of females was 61 km/day and 88 km/day after their last detection in the UK. Our estimated airspeeds during oversea flights correspond well with airspeeds measured in a wind tunnel. Bats use wind adaptively to reduce airspeed when flying under tailwind and increase airspeed when flying under crosswind conditions. Departures over sea coincidence with tailwinds, enabling bats to more than double their airspeed, reaching ground speeds of up to 16.8 m/s (60.5 km/h). Our analysis suggests that bats select altitudes with favourable wind conditions and that they seek altitudes of several hundred meters, possibly extending up to 2,500 m. Low-altitude migration occurs when wind conditions are less favourable. Our study demonstrates that bat migratory movements are highly influenced by barrier effects, sex-biased timing of migration and the adaptive use of winds. The results of our study contribute to a more comprehensive understanding of the decision-making process and adaptations bats employ during their migration. Elucidating bat migration patterns will enable us to develop effective conservation measures, for example in relation to the development and operation of coastal and offshore wind farms.

Dai D., Jiang X., Chen K., Wei X., Zhang Y.

Lourie E., Shamay T., Toledo S., Nathan R.

According to the information centre hypothesis (ICH), colonial species use social information in roosts to locate ephemeral resources. Validating the ICH necessitates showing that uninformed individuals follow informed ones to the new resource. However, following behaviour may not be essential when individuals have a good memory of the resources’ locations. For instance, Egyptian fruit bats forage on spatially predictable trees, but some bear fruit at unpredictable times. These circumstances suggest an alternative ICH pathway in which bats learn when fruits emerge from social cues in the roost but then use spatial memory to locate them without following conspecifics. Here, using an unique field manipulation and high-frequency tracking data, we test for this alternative pathway: we introduced bats smeared with the fruit odour of the unpredictably fruiting Ficus sycomorus trees to the roost, when they bore no fruits, and then tracked the movement of conspecifics exposed to the manipulated social cue. As predicted, bats visited the F. sycomorus trees with significantly higher probabilities than during routine foraging trips (of >200 bats). Our results show how the integration of spatial memory and social cues leads to efficient resource tracking and highlight the value of using large movement datasets and field experiments in behavioural ecology. This article is part of the theme issue ‘The spatial–social interface: a theoretical and empirical integration’.

DeSimone J.G., DeGroote L.W., MacKenzie S.A., Owen J.C., Patterson A.J., Cohen E.B.

Global migrations of diverse animal species often converge along the same routes, bringing together seasonal assemblages of animals that may compete, prey on each other, and share information or pathogens. These interspecific interactions, when energetic demands are high and the time to complete journeys is short, may influence survival, migratory success, stopover ecology, and migratory routes. Numerous accounts suggest that interspecific co-migrations are globally distributed in aerial, aquatic, and terrestrial systems, although the study of migration to date has rarely investigated species interactions among migrating animals. Here, we test the hypothesis that migrating animals are communities engaged in networks of ecological interactions. We leverage over half a million records of 50 bird species from five bird banding sites collected over 8 to 23 y to test for species associations using social network analyses. We find strong support for persistent species relationships across sites and between spring and fall migration. These relationships may be ecologically meaningful: They are often stronger among phylogenetically related species with similar foraging behaviors and nonbreeding ranges even after accounting for the nonsocial contributions to associations, including overlap in migration timing and habitat use. While interspecific interactions could result in costly competition or beneficial information exchange, we find that relationships are largely positive, suggesting limited competitive exclusion at the scale of a banding station during migratory stopovers. Our findings support an understanding of animal migrations that consist of networked communities rather than random assemblages of independently migrating species, encouraging future studies of the nature and consequences of co-migrant interactions.

Lochmann M., Kalesse-Los H., Haest B., Vogl T., van Klink R., Addison F., Maahn M., Schimmel W., Wirth C., Quaas J.

AbstractAerial insects are vital for nature and society. Though methods to observe flying insects have consistently improved in the last decades, insects remain difficult to monitor systematically and consistently over large spatial and temporal scales. Remote sensing with radars has proved to be one of the more effective tools for observation. However, as radars are most sensitive to targets similar in size to the radar wavelength, the detectable sub-group of aerial insects of a certain size range depends on the employed radar. Here, we present a novel method based on data of a zenith-pointing W-band (94 GHz,λ= 0.32 cm) Doppler cloud radar to estimate insect concentration in a vertical profile. Multiple meteorological state-of-the-art algorithms are combined to extract insect signals from the radar data and quantify their abundance from 50 m to 1000 m above the ground. For evaluation, this method is applied to Doppler cloud radar data from a summertime 30 day observation period in central Germany. Results are compared to data from an X-band (9.4 GHz,λ= 3.2 cm) radar in the same region. Aerial insect concentration derived from the W-band radar, which is sensitive to insects in the mm size range, is substantially higher than from the X-band radar, detecting insects in the cm size range. In addition, diel flight timings vary between the different sub-groups of aerial insects observed by the two radar instruments. With its superior sensitivity to smaller insects like aphids, the proposed methodology complements existing entomological radar techniques and contributes to achieving a more complete description of aerial insect activity.

Evsyukov A.P., Potapenko I.O., Tsygankova M.G.

Introduction. The class Cestoda is divided into two subclasses: the Cestodaria — unsegmented tapeworms, and the Eucestoda — true cestodes. The representatives of the orders Pseudophyllidea and Cyclophyllidae, which are part of the subclass of true cestodes parasitize in carnivorous mammals. At the same time, only representatives of the latter order parasitize in chiropterans. Data on the species composition and distribution of cestodes in the Rostov region have not been published yet. The list of bat species living in the Rostov region have been compiled previously. In this article, the authors study the cestode fauna parasitizing in chiropterans in the region under study. This review aims to analyse the current state of knowledge about the species composition of helminths parasitizing in bats in the Rostov region.Materials and Methods. The research materials have been obtained from the libraries and open access resources: PubMed (pubmed.ncbi.nlm.nih.gov), CyberLeninka (cyberleninka.ru), Google Scholar (scholar.google.com), BHL (www.biodiversitylibrary.org ), JSTOR (www.jstor.org), etc. Some data has been provided by the colleagues. Results. 17 species of cestodes of 4 genera, 1 family and 1 order can be found in 15 species of bats living in the Rostov region. Among them dominate the species of the genus Vampirolepis (11 species).Discussion and Conclusion. The results of the review carried out showed that maximum diversity of cestodes was found in one species of bats — the serotine bat (10 species). The smallest number of cestode species (1 per each) was found in the giant and lesser noctules. None of the cestode species found in bats in the Rostov region were recorded in companion animals or humans. However, some cestode species of the Hymenolepididae family, common in rodents, can infect the humans.

Ai Y., Zhai H., Sun Z., Yan W., Hu T.

AbstractBird flocking is a paradigmatic case of self‐organised collective behaviours in biology. Stereo camera systems are employed to observe flocks of starlings, jackdaws, and chimney swifts, mainly on a spot‐fixed basis. A portable non‐fixed stereo vision‐based flocking observation system, namely FlockSeer, is developed by the authors for observing more species of bird flocks within field scenarios. The portable flocking observer, FlockSeer, responds to the challenges in extrinsic calibration, camera synchronisation and field movability compared to existing spot‐fixed observing systems. A measurement and sensor fusion approach is utilised for rapid calibration, and a light‐based synchronisation approach is used to simplify hardware configuration. FlockSeer has been implemented and tested across six cities in three provinces and has accomplished diverse flock‐tracking tasks, accumulating behavioural data of four species, including egrets, with up to 300 resolvable trajectories. The authors reconstructed the trajectories of a flock of egrets under disturbed conditions to verify the practicality and reliability. In addition, we analysed the accuracy of identifying nearest neighbours, and then examined the similarity between the trajectories and the Couzin model. Experimental results demonstrate that the developed flocking observing system is highly portable, more convenient and swift to deploy in wetland‐like or coast‐like fields. Its observation process is reliable and practical and can effectively support the study of understanding and modelling of bird flocking behaviours.

Krapivnitckaia P., Kreutzfeldt J., Schritt H., Reimers H., Floeter C., Reich M., Kunz V.D.

This paper presents the results of bats detected with marine radar and their validation with acoustic detectors in the vicinity of a wind turbine with a hub height of 120 m. Bat detectors are widely used by researchers, even though the common acoustic detectors can cover only a relatively small volume. In contrast, radar technology can overcome this shortcoming by offering a large detection volume, fully covering the rotor-swept areas of modern wind turbines. Our study focused on the common noctule bats (Nyctalus noctula). The measurement setup consisted of a portable X-band pulse radar with a modified radar antenna, a clutter shielding fence, and an acoustic bat detector installed in the wind turbine’s nacelle. The radar’s detection range was evaluated using an analytical simulation model. We developed a methodology based on a strict set of criteria for selecting suitable radar data, acoustic data and identified bat tracks. By applying this methodology, the study data was limited to time intervals with an average duration of 48 s, which is equal to approximately 20 radar images. For these time intervals, 323 bat tracks were identified. The most common bat speed was extracted to be between 9 and 10 m/s, matching the values found in the literature. Of the 323 identified bat tracks passed within 80 m of the acoustic detector, 32% had the potential to be associated with bat calls due to their timing, directionality, and distance to the acoustic bat detector. The remaining 68% passed within the studied radar detection volume but out of the detection volume of the acoustic bat detector. A comparison of recorded radar echoes with the expected simulated values indicated that the in-flight radar cross-section of recorded common noctule bats was mostly between 1.0 and 5.0 cm2, which is consistent with the values found in the literature for similar sized wildlife.

Werber Y.

The aerial habitat occupies an enormous three-dimensional space around Earth and is inhabited by trillions of animals. Humans have been encroaching on the aerial habitat since the time of the pyramids, but the last century ushered in unprecedented threats to aerial wildlife. Skyscrapers, jet-age transportation and recently huge wind turbines kill millions of flying animals annually and despite substantial efforts, our detection and mitigation capabilities are lagging far behind. Given the situation, our readiness to handle the impact of millions of drones buzzing through the sky carrying batteries, payloads and soon also people, is questionable at best. In radar aero-ecology, radars are used to document and analyse animal movement high above the ground, opening a hatch to ecological processes in the aerial habitat. Differentiating bats from birds, a simple task at ground level, was impossible aloft, which limited our ability to study and characterise high-altitude bat behaviour. Many high-altitude infrastructure developments around the world were thus planned and executed with no regard to possible impacts on bats and caused millions of bat fatalities. BATScan, the first automatic bat identifier for radar, demonstrates how artificial intelligence can be implemented together with ecological insight to solve basic scientific questions and minimise negative human impact on natural habitats. We demonstrate a facet of the complexity of bat aero-ecology using the Israeli BATScan database and substantiate the claim that activities taken by the wind energy industry to minimise bat mortality may prove limited and leave bats unprotected. We further discuss upcoming challenges in the face of a forthcoming transportation revolution that will change the human–aerial wildlife conflict from a conservation concern to a major human safety issue.