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Abstract Time-synchronised data streams from bio-loggers are becoming increasingly important for analysing and interpreting intricate animal behaviour including split-second decision making, group dynamics, and collective responses to environmental conditions. With the increased use of AI-based approaches for behaviour classification, time synchronisation between recording systems is becoming an essential challenge. Current solutions in bio-logging rely on manually removing time errors during post processing, which is complex and typically does not achieve sub-second timing accuracies. We first introduce an error model to quantify time errors, then optimise three wireless methods for automated onboard time (re)synchronisation on bio-loggers (GPS, WiFi, proximity messages). The methods can be combined as required and, when coupled with a state-of-the-art real time clock, facilitate accurate time annotations for all types of bio-logging data without need for post processing. We analyse time accuracy of our optimised methods in stationary tests and in a case study on 99 Egyptian fruit bats (Rousettus aegyptiacus). Based on the results, we offer recommendations for projects that require high time synchrony. During stationary tests, our low power synchronisation methods achieved median time accuracies of 2.72 / 0.43 ms (GPS / WiFi), compared to UTC time, and relative median time accuracies of 5 ms between tags (wireless proximity messages). In our case study with bats, we achieved a median relative time accuracy of 40 ms between tags throughout the entire 10-day duration of tag deployment. Using only one automated resynchronisation per day, permanent UTC time accuracies of ≤ 185 ms can be guaranteed in 95% of cases over a wide temperature range between 0 and 50 °C. Accurate timekeeping required a minimal battery capacity, operating in the nano- to microwatt range. Time measurements on bio-loggers, similar to other forms of sensor-derived data, are prone to errors and so far received little scientific attention. Our combinable methods offer a means to quantify time errors and autonomously correct them at the source (i.e., on bio-loggers). This approach facilitates sub-second comparisons of simultaneously recorded time series data across multiple individuals and off-animal devices such as cameras or weather stations. Through automated resynchronisations on bio-loggers, long-term sub-second accurate timestamps become feasible, even for life-time studies on animals. We contend that our methods have potential to greatly enhance the quality of ecological data, thereby improving scientific conclusions.

Abstract Over the past five decades, a large number of wild animals have been individually identified by various observation systems and/or temporary tracking methods, providing unparalleled insights into their lives over both time and space. However, so far there is no comprehensive record of uniquely individually identified animals nor where their data and metadata are stored, for example photos, physiological and genetic samples, disease screens, information on social relationships. Databases currently do not offer unique identifiers for living, individual wild animals, similar to the permanent ID labelling for deceased museum specimens. To address this problem, we introduce two new concepts: (1) a globally unique animal ID (UAID) available to define uniquely and individually identified animals archived in any database, including metadata archived at the time of publication; and (2) the digital ‘home’ for UAIDs, the Movebank Life History Museum (MoMu), storing and linking metadata, media, communications and other files associated with animals individually identified in the wild. MoMu will ensure that metadata are available for future generations, allowing permanent linkages to information in other databases. MoMu allows researchers to collect and store photos, behavioural records, genome data and/or resightings of UAIDed animals, encompassing information not easily included in structured datasets supported by existing databases. Metadata is uploaded through the Animal Tracker app, the MoMu website, by email from registered users or through an Application Programming Interface (API) from any database. Initially, records can be stored in a temporary folder similar to a field drawer, as naturalists routinely do. Later, researchers and specialists can curate these materials for individual animals, manage the secure sharing of sensitive information and, where appropriate, publish individual life histories with DOIs. The storage of such synthesized lifetime stories of wild animals under a UAID (unique identifier or ‘animal passport’) will support basic science, conservation efforts and public participation.

The heterogeneity of the physical environment determines the cost of transport for animals, shaping their energy landscape. Animals respond to this energy landscape by adjusting their distribution and movement to maximize gains and reduce costs. Much of our knowledge about energy landscape dynamics focuses on factors external to the animal, particularly the spatio-temporal variations of the environment. However, an animal’s internal state can significantly impact its ability to perceive and utilize available energy, creating a distinction between the ‘fundamental’ and the ‘realized’ energy landscapes. Here, we show that the realized energy landscape varies along the ontogenetic axis. Locomotor and cognitive capabilities of individuals change over time, especially during the early life stages. We investigate the development of the realized energy landscape in the Central European Alpine population of the golden eagle Aquila chrysaetos, a large predator that requires negotiating the atmospheric environment to achieve energy-efficient soaring flight. We quantified weekly energy landscapes using environmental features for 55 juvenile golden eagles, demonstrating that energetic costs of traversing the landscape decreased with age. Consequently, the potentially flyable area within the Alpine region increased 2170-fold during their first three years of independence. Our work contributes to a predictive understanding of animal movement by presenting ontogeny as a mechanism shaping the realized energy landscape.

Abstract Background Bio-logging devices play a fundamental and indispensable role in movement ecology studies, particularly in the wild. However, researchers are aware of the influence that attaching devices can have on animals, particularly on their behaviour, energy expenditure and survival. The way a device is attached to an animal’s body has also potential consequences for the collected data, and quantifying the type and magnitude of such potential effects is fundamental to enable researchers to combine and compare data from different studies, as much as it is to improve animal welfare. For over two decades, large terrestrial birds have been in the focus of long-term movement ecology research, employing bio-logging devices attached with different types of harnesses. However, comparative studies investigating the effects of different harness types used on these species are scarce. Methods In this study, we tested for potential differences in data collected by two commonly used harness types, backpack and leg-loop, on the flight performance of 10 individuals from five soaring raptor species, equipped with high resolution bio-logging devices, in the same area and time. We explored the effect of harness type on vertical speed, airspeed, glide ratio, height above sea level, distance travelled, proportion of soaring and flapping behaviour, and VeDBA (a proxy for energy expenditure) between and within individuals, all used as fine-scale measures of flight performance. Results Birds equipped with leg-loops climbed up to 0.36 ms $$^{-1}$$ - 1 faster, reached 25.9% greater altitudes while soaring and spent less time in active flight compared to birds equipped with backpacks, suggesting that backpack harnesses, compared to leg-loops, might cause additional drag affecting the birds’ flight performance. A lower VeDBA, a lower rate of sinking while gliding and slightly higher glide ratio and airspeeds were also indicative of less drag using leg-loops, even though the effect on these parameters was comparable to inter-individual differences. Conclusions Our results add to the existing literature highlighting the design-related advantages of leg-loops, and support the use of leg-loops as a better alternative to backpack harnesses for large soaring birds, when possible. Our study also highlights how apparently small changes in device attachment can lead to notable improvements in tagging practice, with implications for animal welfare, data interpretation and comparability.

Abstract Background Connections between habitats are key to a full understanding of anthropic impacts on ecosystems. Freshwater habitats are especially biodiverse, yet depend on exchange with terrestrial habitats. White storks (Ciconia ciconia) are widespread opportunists that often forage in landfills and then visit wetlands, among other habitats. It is well known that white storks ingest contaminants at landfills (such as plastics and antibiotic resistant bacteria), which can be then deposited in other habitats through their faeces and regurgitated pellets. Methods We characterized the role of white storks in habitat connectivity by analyzing GPS data from populations breeding in Germany and wintering from Spain to Morocco. We overlaid GPS tracks on a land-use surface to construct a spatially-explicit network in which nodes were sites, and links were direct flights. We then calculated centrality metrics, identified spatial modules, and quantified overall connections between habitat types. For regional networks in southern Spain and northern Morocco, we built Exponential Random Graph Models (ERGMs) to explain network topologies as a response to node habitat. Results For Spain and Morocco combined, we built a directed spatial network with 114 nodes and 370 valued links. Landfills were the habitat type most connected to others, as measured by direct flights. The relevance of landfills was confirmed in both ERGMs, with significant positive effects of this habitat as a source of flights. In the ERGM for southern Spain, we found significant positive effects of rice fields and salines (solar saltworks) as sinks for flights. By contrast, in the ERGM for northern Morocco, we found a significant positive effect of marshes as a sink for flights. Conclusions These results illustrate how white storks connect landfills with terrestrial and aquatic habitats, some of which are managed for food production. We identified specific interconnected habitat patches across Spain and Morocco that could be used for further studies on biovectoring of pollutants, pathogens and other propagules.

Abstract Bio-telemetry from small tags attached to animals is one of the principal methods for studying the ecology and behaviour of wildlife. The field has constantly evolved over the last 80 years as technological improvement enabled a diversity of sensors to be integrated into the tags (e.g., GPS, accelerometers, etc.). However, retrieving data from tags on free-ranging animals remains a challenge since satellite and GSM networks are relatively expensive and or power hungry. Recently a new class of low-power communication networks have been developed and deployed worldwide to connect the internet of things (IoT). Here, we evaluated one of these, the Sigfox IoT network, for the potential as a real-time multi-sensor data retrieval and tag commanding system for studying fauna across a diversity of species and ecosystems. We tracked 312 individuals across 30 species (from 25 g bats to 3 t elephants) with seven different device concepts, resulting in more than 177,742 successful transmissions. We found a maximum line of sight communication distance of 280 km (on a flying cape vulture [Gyps coprotheres]), which sets a new documented record for animal-borne digital data transmission using terrestrial infrastructure. The average transmission success rate amounted to 68.3% (SD 22.1) on flying species and 54.1% (SD 27.4) on terrestrial species. In addition to GPS data, we also collected and transmitted data products from accelerometers, barometers, and thermometers. Further, we assessed the performance of Sigfox Atlas Native, a low-power method for positional estimates based on radio signal strengths and found a median accuracy of 12.89 km (MAD 5.17) on animals. We found that robust real-time communication (median message delay of 1.49 s), the extremely small size of the tags (starting at 1.28 g without GPS), and the low power demands (as low as 5.8 µAh per transmitted byte) unlock new possibilities for ecological data collection and global animal observation.

Abstract Biologging devices are deployed on animals to collect ultra‐fine‐scale movement data that reveal subsecond patterns in locomotion or long‐term patterns in motion and space use. Often these two data types, although complementary, are rarely collected within the same study, given the limiting factors of memory space, power requirements and the need to retrieve stored data from animals. Biologging requires a revolutionary advancement in data networking to overcome these restrictions that constrain big data collection; for the continuous recording and remote download of fine‐scale movement and environmental data, from long‐term deployments and multiple individuals. Here, we adopt a strategy from the Internet of Things and develop the use of Wi‐Fi as a solution for big data biologging. Our ‘WildFi’ tag uses pre‐existing, or easy‐to‐set‐up, infrastructure in smartphones and Wi‐Fi gateways. We demonstrate the power of memory management and an embedded modular software architecture for functionality, including collective data retrieval at multiple gateways. We find that Wi‐Fi, together with smart embedded software, increases the retrieval efficiency of biologging data by orders of magnitude compared to other available systems: with a transmission speed of 230 kByte/s and range of ≤200 m that is 11 times faster than Bluetooth low energy and >3000 times faster than LoRaWAN. Case studies on a domestic dog (Canis lupus familiaris), aviary‐housed cockatiels (Nymphicus hollandicus) and free‐roaming pangolins (Smutsia temminckii) demonstrate the functionality of the WildFi tag for remote and robust autonomous Wi‐Fi data transmission under a range of conditions. Modularity in software and hardware allows for project‐specific tailoring beyond reconfiguring sampling parameters of a biologger, which we encourage with open‐source sharing of our architecture design. Enhanced communication between animal‐attached devices, Wi‐Fi infrastructure and smartphones, alongside smart and collaborative data retrieval, eases restrictions for big data collection in animal ecology.

Abstract Estimating animal populations is essential for conservation. Censusing large congregations is especially important since these are priorities for protection, but efficiently counting hundreds of thousands of moving animals remains a challenge. We developed a deep learning‐based system using consumer cameras that not only counts but also records behavioral information for large numbers of flying animals in a range of lighting conditions including near darkness. We built a robust training set without human labeling by leveraging data augmentation and background subtraction. We demonstrate this approach by estimating the size of a straw‐colored fruit bat (Eidolon helvum) colony in Kasanka National Park, Zambia with cameras encircling the colony to record evening emergence. Detection of bats was robust to deteriorating lighting conditions and changing backgrounds. Combined over five days, our population estimates ranged between 750,000 and 976,000 bats with a mean of 857,233. In addition to counts, we extracted wingbeat frequency, flight altitude, and local group polarity for 639,414 individuals. This open access method is an inexpensive but powerful approach that, in addition to radial emergences from central locations, can also be applied to unidirectional movements of flying groups, such as migratory streams of birds.

Abstract Background Bio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills. Results We developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface. Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository. The platform was beta launched in spring 2021 and currently contains 49 Apps that are used by 316 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements. Conclusions The MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition.

Abstract Wind energy production has expanded as an alternative to carbon emitting fossil fuels, but is causing impacts on wildlife that need to be addressed. Soaring birds show concerning rates of collision with turbine rotor blades and losses of critical habitat. However, how these birds interact with wind turbines is poorly understood. We analyzed high-frequency GPS tracking data of 126 black kites (Milvus migrans) moving near wind turbines to identify behavioural mechanisms of turbine avoidance and their interaction with environmental variables. Birds flying within 1000 m from turbines and below the height of rotor blades were less likely to be oriented towards turbines than expected by chance, this pattern being more striking at distances less than 750 m. Within the range of 750 m, birds showed stronger avoidance when pushed by the wind in the direction of the turbines. Birds flying above the turbines did not change flight directions with turbine proximity. Sex and age of birds, uplift conditions and turbine height, showed no effect on flight directions although these factors have been pointed as important drivers of turbine collision by soaring birds. Our findings suggest that migrating black kites recognize the presence of wind turbines and behave in a way to avoid then. This may explain why this species presents lower collision rates with wind turbines than other soaring birds. Future studies should clarify if turbine avoidance behaviour is common to other soaring birds, particularly those that are facing high fatality rates due to collision.

Animal ecologists are increasingly limited by constraints in data processing. Here, Tuia and colleagues discuss how collaboration between ecologists and data scientists can harness machine learning to capitalize on the data generated from technological advances and lead to novel modeling approaches.

Abstract Background Although some migratory birds may take different routes during their outbound and inbound migration, the factors causing these differential migrations to and from the breeding grounds, have rarely been investigated. In Northeast Asia, Demoiselle crane (Anthropoides virgo) performs one of the most extreme “loop” migrations known to date. During outbound migration, they cross the Himalayas to non-breeding sites in northwest India. Contrastingly, during inbound migration to the breeding grounds, they fly around the western end of the Himalayas. We hypothesise that differences in prevailing environmental conditions aloft and/or on-ground during both seasonal migrations are at the core of this phenomenon. Methods Based on the tracking data of 16 individuals of tagged Demoiselle crane, we compared conditions during actual migration with those of simulated “reverse” migration (i.e. by adding 180 degrees to the flight direction and adding and subtracting half a year to the timestamps of outbound and inbound migration, respectively). Results The comparison of actual and simulated “reverse” migration indicated that cranes would have encountered poorer aloft (wind support and thermal uplift) and on-ground conditions (temperature) if they had migrated in a reverse outbound migration and poorer on-ground conditions (Normalised Difference Vegetation Indexes [NDVI]) if they had migrated in a reverse inbound direction. Conclusions Our analyses suggest that both on-ground and aloft conditions play a key role in explaining Demoiselle cranes’ loop migration, during the periods that they chose to use these alternative routes. Knowledge on the determinants of (differential) migration routes allow predicting migration decisions and may be critical in mitigating global change effects on animal migrations.

Wildlife tracking devices are key in obtaining detailed insights on movement, animal migration, natal dispersal, home-ranges, resource use and group dynamics of free-roaming animals. Despite a wide use of such devices, tracking for entire lifetimes is still a considerable challenge for most animals, mainly due to technological limitations. Deploying battery powered wildlife tags on smaller animals is limited by the mass of the devices. Micro-sized devices with solar panels sometimes solve this challenge, however, nocturnal species or animals living under low light conditions render solar cells all but useless. For larger animals, where battery weight can be higher, battery longevity becomes the main challenge. Several studies have proposed solutions to these limitations, including harvesting thermal and kinetic energy on animals. However, these concepts are limited by size and weight. In this study, we used a small, lightweight kinetic energy harvesting unit as the power source for a custom wildlife tracking device to investigate its suitability for lifetime animal tracking. We integrated a Kinetron MSG32 microgenerator and a state-of-the-art lithium-ion capacitor (LIC) into a custom GPS-enabled tracking device that is capable of remotely transmitting data via the Sigfox 'Internet of Things' network. Prototypes were tested on domestic dog (n = 4), wild-roaming Exmoor pony (n = 1) and wisent (n = 1). One of the domestic dogs generated up to 10.04 joules of energy in a day, while the Exmoor pony and wisent generated on average 0.69 joules and 2.38 joules per day, respectively. Our results show a significant difference in energy generation between animal species and mounting method, but also highlight the potential for this technology to be a meaningful advancement in ecological research requiring lifetime tracking of animals. The design of the Kinefox is provided open source.

Abstract In the present Anthropocene, wild animals are globally affected by human activity. Consumer fireworks during New Year (NY) are widely distributed in W‐Europe and cause strong disturbances that are known to incur stress responses in animals. We analyzed GPS tracks of 347 wild migratory geese of four species during eight NYs quantifying the effects of fireworks on individuals. We show that, in parallel with particulate matter increases, during the night of NY geese flew on average 5–16 km further and 40–150 m higher, and more often shifted to new roost sites than on previous nights. This was also true during the 2020–2021 fireworks ban, despite fireworks activity being reduced. Likely to compensate for extra flight costs, most geese moved less and increased their feeding activity in the following days. Our findings indicate negative effects of NY fireworks on wild birds beyond the previously demonstrated immediate response.

Abstract Background Many birds species range over vast geographic regions and migrate seasonally between their breeding and overwintering sites. Deciding when to depart for migration is one of the most consequential life-history decisions an individual may make. However, it is still not fully understood which environmental cues are used to time the onset of migration and to what extent their relative importance differs across a range of migratory strategies. We focus on departure decisions of a songbird, the Eurasian blackbird Turdus merula, in which selected Russian and Polish populations are full migrants which travel relatively long-distances, whereas Finnish and German populations exhibit partial migration with shorter migration distances. Methods We used telemetry data from the four populations (610 individuals) to determine which environmental cues individuals from each population use to initiate their autumn migration. Results When departing, individuals in all populations selected nights with high atmospheric pressure and minimal cloud cover. Fully migratory populations departed earlier in autumn, at longer day length, at higher ambient temperatures, and during nights with higher relative atmospheric pressure and more supportive winds than partial migrants; however, they did not depart in higher synchrony. Thus, while all studied populations used the same environmental cues, they used population-specific and locally tuned thresholds to determine the day of departure. Conclusions Our data support the idea that migratory timing is controlled by general, species-wide mechanisms, but fine-tuned thresholds in response to local conditions.

Abstract Background Different theories suggest birds may use compass or map navigational systems associated with Earth’s magnetic intensity or inclination, especially during migratory flights. These theories have only been tested by considering properties of the Earth’s magnetic field at coarse temporal scales, typically ignoring the temporal dynamics of geomagnetic values that may affect migratory navigational capacity. Methods We designed a simulation experiment to study if and how birds use the geomagnetic field during migration by using both high resolution GPS tracking data and geomagnetic data at relatively fine spatial and temporal resolutions in comparison to previous studies. Our simulations use correlated random walks (CRW) and correlated random bridge (CRB) models to model different navigational strategies based on underlying dynamic geomagnetic data. We translated navigational strategies associated with geomagnetic cues into probability surfaces that are included in the random walk models. Simulated trajectories from these models were compared to the actual GPS trajectories of migratory birds using 3 different similarity measurements to evaluate which of the strategies was most likely to have occurred. Results and conclusion We designed a simulation experiment which can be applied to different wildlife species under varying conditions worldwide. In the case of our example species, we found that a compass-type strategy based on taxis, defined as movement towards an extreme value, produced the closest and most similar trajectories when compared to original GPS tracking data in CRW models. Our results indicate less evidence for map navigation (constant heading and bi-gradient taxis navigation). Additionally, our results indicate a multifactorial navigational mechanism necessitating more than one cue for successful navigation to the target. This is apparent from our simulations because the modelled endpoints of the trajectories of the CRW models do not reach close proximity to the target location of the GPS trajectory when simulated with geomagnetic navigational strategies alone. Additionally, the magnitude of the effect of the geomagnetic cues during navigation in our models was low in our CRB models. More research on the scale effects of the geomagnetic field on navigation, along with temporally varying geomagnetic data could be useful for further improving future models.

Wildlife alter their behaviors in a trade-off between consuming food and fear of becoming food themselves. The risk allocation hypothesis posits that variation in the scale, intensity and longevity of predation threats can influence the magnitude of antipredator behavioral responses. Hunting by humans represents a threat thought to be perceived by wildlife similar to how they perceive a top predator, although hunting intensity and duration varys widely around the world. Here we evaluate the effects of hunting pressure on wildlife by comparing how two communities of mammals under different management schemes differ in their relative abundance and response to humans. Using camera traps to survey wildlife across disturbance levels (yards, farms, forests) in similar landscapes in southern Germany and southeastern USA, we tested the prediction of the risk allocation hypothesis: that the higher intensity and longevity of hunting in Germany (year round vs 3 months, 4x higher harvest/km2/year) would reduce relative abundance of hunted species and result in a larger fear-based response to humans (i.e., more spatial and temporal avoidance). We further evaluated how changes in animal abundance and behavior would result in potential changes to ecological impacts (i.e., herbivory and predation). We found that hunted species were relatively less abundant in Germany and less associated with humans on the landscape (i.e., yards and urban areas), but did not avoid humans temporally in hunted areas while hunted species in the USA showed the opposite pattern. These results are consistent with the risk allocation hypothesis where we would expect more spatial avoidance in response to threats of longer duration (i.e., year-round hunting in Germany vs. 3-month duration in USA) and less spatial avoidance but more temporal avoidance for threats of shorter duration. The expected ecological impacts of mammals in all three habitats were quite different between countries, most strikingly due to the decreases in the relative abundance of hunted species in Germany, particularly deer, with no proportional increase in unhunted species, resulting in American yards facing the potential for 25x more herbivory than German yards. Our results suggest that the duration and intensity of managed hunting can have strong and predictable effects on animal abundance and behavior, with the potential for corresponding changes in the ecological impacts of wildlife. Hunting can be an effective tool for reducing wildlife conflict due to overabundance but may require more intensive harvest than is seen in much of North America.

Summary: Quantifying stress and energetic responses in animals are major challenges, as existing methods lack temporal resolution and elevate animal stress. We propose “wake respirometry,” a new method of quantifying fine-scale changes in CO2 production in unrestrained animals, using a nondispersive infrared CO2 sensor positioned downwind of the animal, i.e., in its wake. We parameterize the dispersion of CO2 in wakes using known CO2 flow rates and wind speeds. Tests with three bird species in a wind tunnel demonstrated that the system can resolve breath-by-breath changes in CO2 concentration, with clear exhalation signatures increasing in period and integral with body size. Changes in physiological state were detectable following handling, flight, and exposure to a perceived threat. We discuss the potential of wake respirometry to quantify stress and respiratory patterns in wild animals and provide suggestions for estimating behavior-specific metabolic rates via full integration of CO2 production across the wake.

Understanding how individual niches vary can inform ecology and conservation. A study of 45 GPS-tracked white storks across three breeding populations reveals that individual environmental niches are nested, arranged along a specialist-generalist gradient that is highly consistent over time.

Abstract Finding food is perhaps the most important task for all animals. Birds often show up unexpectedly at novel food sources such as freshly tilled fields or mown meadows. Here we test whether wild European white storks primarily use visual, social, auditory or olfactory information to find freshly cut farm pastures where insects and rodents abound. Aerial observations of an entire local stork population documented that birds could not have become aware of a mown field through auditory, visual or social information. Only birds within a 75° downwind cone over 0.4–16.6 km approached any mown field. Placing freshly cut grass from elsewhere on selected unmown fields elicited similarly immediate stork approaches. Furthermore, uncut fields that were sprayed with a green leaf volatile organic compound mix ((Z)-3-hexenal, (Z)-3-hexenol, hexenyl acetate), the smell of freshly cut grass, immediately attracted storks. The use of long-distance olfactory information for finding food may be common in birds, contrary to current perception.

Migratory species have a limited time for habitat selection upon arrival at the breeding grounds. This is especially evident in arctic migrants, which are restricted by a narrow window of opportunity when environmental conditions are favorable for breeding. This general time constraint is amplified in rough-legged buzzards (Buteo lagopus) who, as many other arctic predators, rely on rodent (lemming) cycles during the breeding season, a 3–5 year period of waxing and waning local food abundance. It remains unclear how arctic predators, especially migrants, can find nesting areas where rodents are numerous when their selection time is so limited. We hypothesized that rough-legged buzzards select nesting areas during the previous breeding season. We tracked 43 rough-legged buzzards using GPS telemetry and assessed their movements post-breeding prospecting behavior to test our hypothesis. Here we show that rough-legged buzzards search for a nesting location during the previous breeding season in a post-breeding period. In the following year, individuals return to and attempt to breed in the area they inspected the year before. Rough-legged buzzards, regardless of breeding success, remained in the Arctic all breeding season until the end of September. Failed breeders prospected more than successful ones. At the same time, buzzards that bred in the rodent-free ecosystem prospected less and showed a high level of philopatry. Therefore, as rodent cycles have been predicted to collapse in the warming Arctic, we can expect arctic predators to change their movement patterns in the future with serious potential consequences for their conservation. We anticipate our study provides a step forward toward understanding movement and settlement decisions in animals experiencing high inter-annual environmental variation.

Abstract Monitoring and early detection of emerging infectious diseases in wild animals is of crucial global importance, yet reliable ways to measure immune status and responses are lacking for animals in the wild. Here we assess the usefulness of bio-loggers for detecting disease outbreaks in free-living birds and confirm detailed responses using leukocyte composition and large-scale transcriptomics. We simulated natural infections by viral and bacterial pathogens in captive mallards (Anas platyrhynchos), an important natural vector for avian influenza virus. We show that body temperature, heart rate and leukocyte composition change reliably during an acute phase immune response. Using genome-wide gene expression profiling of whole blood across time points we confirm that immunostimulants activate pathogen-specific gene regulatory networks. By reporting immune response related changes in physiological and behavioural traits that can be studied in free-ranging populations, we provide baseline information with importance to the global monitoring of zoonotic diseases.

Abstract Background The use of tracking technologies is key for the study of animal movement and pivotal to ecological and conservation research. However, the potential effects of devices attached to animals are sometimes neglected. The impact of tagging not only rises welfare concerns, but can also bias the data collected, causing misinterpretation of the observed behaviour which invalidates the comparability of information across individuals and populations. Patagial (wing) tags have been extensively used as a marking method for visual resightings in endangered vulture species, but their effect on the aerodynamics of the birds and their flight behaviour is yet to be investigated. Using GPS backpack mounted devices, we compared the flight performance of 27 captive and wild Cape Vultures (Gyps coprotheres), marked with either patagial tags or coloured leg bands. Results Individuals equipped with patagial tags were less likely to fly, travelled shorter distances and flew slower compared to individuals equipped with leg bands. These effects were also observed in one individual that recovered its flight performance after replacing its patagial tag by a leg band. Conclusions Although we did not measure the effects of patagial tags on body condition or survival, our study strongly suggests that they have severe adverse effects on vultures’ flight behaviour and emphasises the importance of investigating the effects that tagging methods can have on the behaviour and conservation of the study species, as well as on the quality of the scientific results.

Abstract Many bird species have the ability to navigate home after being brought to a remote, even unfamiliar location. Environmental odours have been demonstrated to be critical to homeward navigation in over 40 years of experiments, yet the chemical identity of the odours has remained unknown. In this study, we investigate potential chemical navigational cues by measuring volatile organic compounds (VOCs): at the birds’ home-loft; in selected regional forest environments; and from an aircraft at 180 m. The measurements showed clear regional, horizontal and vertical spatial gradients that can form the basis of an olfactory map for marine emissions (dimethyl sulphide, DMS), biogenic compounds (terpenoids) and anthropogenic mixed air (aromatic compounds), and temporal changes consistent with a sea-breeze system. Air masses trajectories are used to examine GPS tracks from released birds, suggesting that local DMS concentrations alter their flight directions in predictable ways. This dataset reveals multiple regional-scale real-world chemical gradients that can form the basis of an olfactory map suitable for homing pigeons.

Abstract Aim Understanding diversity patterns and identifying the environmental factors that shape these patterns are essential for ecology and conservation. The Afro‐Arabian region comprises one of the most important biogeographic areas connecting continents. Yet, little emphasis has been put on understanding its endemic fauna in relation to its biogeographic realms. Our objective is to fill the gaps in knowledge on diversity patterns and biogeography that are essential for prioritizing the overdue conservation efforts. Location The study area covers mostly the hot desert climate region in North Africa and Arabia, and includes the Mediterranean, Sahel, and Ethiopian highlands (hereafter “Afro‐Arabian region”). Methods We used distribution maps developed by IUCN and BirdLife for species endemic to the Afro‐Arabian region belonging to the four tetrapod classes, amphibians, reptiles, birds, and mammals, to identify the endemic richness hotspots. We then used multivariate analyses to delineate biogeographic regions and evaluate their relationship with the environmental factors. Results Our study reveals a complex map of the richness hotspots for the endemic tetrapod classes. The main hotspots of endemism were concentrated at the margins of the study area, along the Mediterranean coast, Ethiopian highlands, and along the Red Sea Mountains. We propose classifying the Afro‐Arabian region into three discrete biogeographic realms for endemic amphibians, four for reptiles and birds, and five discrete biogeographic realms for endemic mammals. The identified realms are defined by their environmental conditions and the historical geological processes. Main conclusions Richness hotspots of endemic tetrapod classes were heterogeneously distributed in the Afro‐Arabian region. Our results support the hypothesis that species diversity patterns and endemism have been shaped by the environmental conditions and the paleogeographic processes. Each of the identified bioregions is associated with a characteristic set of tetrapod species. Our results are a benchmark for assessing the effectiveness of the protected areas and for implementing conservation plans for biodiversity.

It is unclear whether bird migration patterns are restricted to interglacial periods or are maintained during glacial maxima. Somveille et al. apply a global migration simulation model to climate reconstruction to show that the prevalence of this phenomenon has likely been largely maintained up to 50,000 years ago.

GPS-enabled loggers have been proven as valuable tools for monitoring and understanding animal movement, behaviour and ecology. While the importance of recording accurate location estimates is well established, deployment on many, especially small species, has been limited by logger mass and cost. We developed an open-source and low-cost 0.65 g GPS logger with a simple smartphone-compatible user interface, that can record more than 10,000 GPS fixes on a single 30 mAh battery charge (resulting mass including battery: 1.3 g). This low-budget 'TickTag' (currently 32 USD) allows scientists to scale-up studies while becoming a 'wearable' for larger animals and simultaneously enabling high-definition studies on small animals. Tests on two different species (domestic dog, Canis lupus familiaris and greater mouse-eared bats, Myotis myotis) showed that our combination of optimised hardware design and software-based recording strategies increases the number of achievable GPS fixes per g device mass compared to existing micro-sized solutions. We propose that due to the open-source access, as well as low cost and mass, the TickTag fills a technological gap in wildlife ecology and will open up new possibilities for wildlife research and conservation.

Arctic migration presents unique challenges to circadian physiology. In addition to the metabolic cost of maintaining a relatively high body temperature (Tb) above ambient temperature, migratory birds are also exposed to rapidly changing light conditions as they transition between light-dark cycles and a 24-hour polar day. A previous study suggested that Arctic-migratory barnacle geese (Branta leucopsis) may utilise adaptive heterothermy (i.e., a controlled decrease in core Tb) during and around the autumn migratory period in order to minimise the metabolic cost of migration, but the impact of seasonally changing daylight conditions on other parameters of the circadian profile of Tb in these geese remained obscure. Here, we provide a detailed comparative analysis on the circadian rhythm of Tb and its seasonal development in free-living barnacle geese from three study populations that differ in their migratory behaviour and in the environments they occupy. We recorded abdominal Tb in non-migratory geese from a temperate breeding colony in Netherlands and in migratory geese from a colony in the Russian low Arctic, and analysed these data together with previously published Tb data on geese from a migratory colony in the high Arctic of Svalbard. We found that the circadian Tb profile in the barnacle goose was well aligned with the daily and seasonally changing daylight conditions. In the migratory populations, a fast re-entrainment of the rhythm and its phase was observed when zeitgeber conditions changed during migratory movements. The circadian rhythmicity of Tb was lost once the geese encountered permanent daylight at their northern staging and breeding sites. Circadian Tb rhythmicity was re-established when the period of permanent daylight ended, at rates corresponding to rates of seasonal changes in daylength in the high and low Arctic. Although our data corroborated findings of a decrease in daily mean Tb before autumn migration in both migratory populations in this study, the pre-migratory decrease in Tb was less drastic than previously reported. Moreover, in contrast to previous study, the decrease in Tb stopped at the onset of migration. Overall, our data reveal no evidence that heterothermy in the barnacle goose is functionally linked to migration.

Abstract Human‐induced changes in the climate and environment that occur at an unprecedented speed are challenging the existence of migratory species. Faced with these new challenges, species with diverse and flexible migratory behaviors may suffer less from population decline, as they may be better at responding to these changes by altering their migratory behavior. At the individual level, variations in migratory behavior may lead to differences in fitness and subsequently influence the population's demographic dynamics. Using lifetime GPS bio‐logging data from 169 white storks (Ciconia ciconia), we explore whether the recently shortened migration distance of storks affects their survival during different stages of their juvenile life. We also explore how other variations in migratory decisions (i.e., time, destination), movement activity (measured using overall body dynamic acceleration), and early life conditions influence juvenile survival. We observed that their first autumn migration was the riskiest period for juvenile white storks. Individuals that migrated shorter distances and fledged earlier experienced lower mortality risks. In addition, higher movement activity and overwintering “closer‐to‐home” (with 84.21% of the tracked individuals stayed Europe or North Africa) were associated with higher survival. Our study shows how avian migrants can change life history decisions over only a few decades, and thus it helps us to understand and predict how migrants respond to the rapidly changing world.

The ICARUS (International Cooperation for Animal Research Using Space) satellite IoT system was launched in 2020 to observe the life of animals on Earth: their migratory routes, living conditions, and causes of death. These findings will aid species conservation, protect ecosystem services by animals, measure weather and climate, and help forecast the spread of infectious zoonotic diseases and possibly natural disasters. The aim of this article is to explain the system design of ICARUS. Essential components are ‘wearables for wildlife’, miniature on-animal sensors, quantifying the health of animals and the surrounding environment on the move, and transmitting artificially intelligent summaries of these data globally. We introduce a new class of Internet-of-things (IoT) waveforms—the random-access, very-low-power, wide-area networks (RA-vLPWANs) which enable uncoordinated multiple access at very-low-signal power and low-signal-to-noise ratios. RA-vLPWANs used in ICARUS solve the problems hampering conventional low-power wide area network (LPWAN) IoT systems when applied to space communications. Prominent LPWANs are LoRA, SigFox, MIOTY, ESSA, NB-IoT (5G), or SCADA. Hardware and antenna aspects in the ground and the space segment are given to explain practical system constraints.

The power curve provides a basis for predicting adjustments that animals make in flight speed, for example in relation to wind, distance, habitat foraging quality and objective. However, relatively few studies have examined how animals respond to the landscape below them, which could affect speed and power allocation through modifications in climb rate and perceived predation risk. We equipped homing pigeons (Columba livia) with high-frequency loggers to examine how flight speed, and hence effort, varies in relation to topography and land cover. Pigeons showed mixed evidence for an energy-saving strategy, as they minimized climb rates by starting their ascent ahead of hills, but selected rapid speeds in their ascents. Birds did not modify their speed substantially in relation to land cover, but used higher speeds during descending flight, highlighting the importance of considering the rate of change in altitude before estimating power use from speed. Finally, we document an unexpected variability in speed and altitude over fine scales; a source of substantial energetic inefficiency. We suggest this may be a form of protean behaviour adopted to reduce predation risk when flocking is not an option, and that such a strategy could be widespread.

Populations of soaring birds are often impacted by wind-power generation. Sex and age bias in turbine collisions can exacerbate these impacts through demographic changes that can lead to population decline or collapse. While several studies have reported sex and age differences in the number of soaring birds killed by turbines, it remains unclear if they result from different abundances or group-specific turbine avoidance behaviours, the latter having severer consequences. We investigated sex and age effects on turbine avoidance behaviour of black kites (Milvus migrans) during migration near the Strait of Gibraltar. We tracked the movements of 135 individuals with GPS data loggers in an area with high density of turbines and then modelled the effect of proximity of turbines on bird utilization distribution (UD). Both sexes and age classes showed similar patterns of displacement, with reduced UD values in the proximity of turbines and a clear peak at 700–850 m away, probably marking the distance at which most birds turn direction to avoid approaching the turbines further. The consistency of these patterns indicates that displacement range can be used as an accurate proxy for collision risk and habitat loss, and should be incorporated in environmental impact assessment studies.

Intraspecific competition in large aggregations of animals should generate density-dependent effects on foraging patterns. To test how large differences in colony size affect foraging movements, we tracked seasonal movements of the African straw-coloured fruit bat (Eidolon helvum) from four colonies that range from 4000 up to 10 million animals. Contrary to initial predictions, we found that mean distance flown per night (9–99 km), number of nightly foraging sites (2–3) and foraging and commuting times were largely independent of colony size. Bats showed classic central-place foraging and typically returned to the same day roost each night. However, roost switching was evident among individuals in three of the four colonies especially towards the onset of migration. The relatively consistent foraging patterns across seasons and colonies indicate that these bats seek out roosts close to highly productive landscapes. Once foraging effort starts to increase due to local resource depletion they migrate to landscapes with seasonally increasing resources. This minimizes high intraspecific competition and may help to explain why long-distance migration, otherwise rare in bats, evolved in this highly gregarious species.

The disturbance of wildlife by humans is a worldwide phenomenon that contributes to the loss of biodiversity. It can impact animals' behaviour and physiology, and this can lead to changes in species distribution and richness. Wildlife disturbance has mostly been assessed through direct observation. However, advances in bio-logging provide a new range of sensors that may allow measuring disturbance of animals with high precision and remotely, and reducing the effects of human observers. We used tri-axial accelerometers to identify daytime flights of roosting straw-coloured fruit bats (Eidolon helvum), which were used as a proxy for roost disturbance. This bat species roosts on trees in large numbers (often reaching hundreds of thousands of animals), making them highly vulnerable to disturbance. We captured and tagged 46 straw-coloured fruit bats with dataloggers, containing a global positioning system (GPS) and an accelerometer, in five roosts in Ghana, Burkina Faso and Zambia. Daytime roost flights were identified from accelerometer signatures and modelled against our activity in the roosts during the days of trapping, as a predictor of roost disturbance, and natural stressors (solar irradiance, precipitation and wind speed). We found that daytime roost flight probability increased during days of trapping and with increasing solar irradiance (which may reflect the search for shade to prevent overheating). Our results validate the use of accelerometers to measure roost disturbance of straw-coloured fruit bats and suggest that these devices may be very useful in conservation monitoring programs for large fruit bat species.

Abstract Background Increases in landscape connectivity can improve a species’ ability to cope with habitat fragmentation and degradation. Wildlife corridors increase landscape connectivity and it is therefore important to identify and maintain them. Currently, corridors are mostly identified using methods that rely on generic habitat suitability measures. One important and widely held assumption is that corridors represent swaths of suitable habitat connecting larger patches of suitable habitat in an otherwise unsuitable environment. Using high-resolution GPS data of four large carnivore species, we identified corridors based on animal movement behavior within each individual’s home range and quantified the spatial overlap of these corridors. We thus tested whether corridors were in fact spatial bottle necks in habitat suitability surrounded by unsuitable habitat, and if they could be characterized by their coarse-scale environmental composition. Results We found that most individuals used corridors within their home ranges and that several corridors were used simultaneously by individuals of the same species, but also by individuals of different species. When we compared the predicted habitat suitability of corridors and their immediate surrounding area we found, however, no differences. Conclusions We could not find a direct correspondence between corridors chosen and used by wildlife on the one hand, and a priori habitat suitability measurements on the other hand. This leads us to speculate that identifying corridors relying on typically-used habitat suitability methods alone may misplace corridors at the level of space use within an individual’s home range. We suggest future studies to rely more on movement data to directly identify wildlife corridors based on the observed behavior of the animals.

Abstract Understanding how soaring birds use updrafts at small spatial scales is important to identify ecological constraints of movement, and may help to prevent conflicts between wind-energy development and the conservation of wildlife. We combined high-frequency GPS animal tracking and fine-spatial-scale uplift modelling to establish a link between flight behaviour of soaring birds and the distribution of updrafts. We caught 21 black kites (Milvus migrans) and GPS-tracked them while flying over the Tarifa region, on the Spanish side of the Strait of Gibraltar. This region has a diverse topography and land cover, favouring a heterogeneous updraft spatial distribution. Bird tracks were segmented and classified into flight modes from motion parameters. Thermal and orographic uplift velocities were modelled from publically available remote-sensing and meteorological data. We found that birds perform circular soaring in areas of higher predicted thermal uplift and linear soaring in areas of higher predicted orographic uplift velocity. We show that updraft maps produced from publically available data can be used to predict where soaring birds will concentrate their flight paths and how they will behave in flight. We recommend the use of this methodological approach to improve environmental impact assessments of new wind-energy installations.

In contrast to many other gull species, nominate lesser black-backed gulls (Larus fuscus fuscus, nLBBG) have shown generally decreasing population trends throughout their breeding area in northern and eastern Fennoscandia over the past decades and are now red-listed. Interspecific competition, predation, increased disturbance, organochlorine poisoning and food shortages were suggested as main reasons for the overall decrease. Here we contribute to a better understanding of population declines by comparing foraging movements of satellite tracked adult gulls in three geographical areas of Finland (West, South, and East) that differ in their population trends. Our analysis examines potential differences and preferences in the feeding site behaviour of adult gulls. Our comparison of the three geographical areas showed that nLBBGs preferred feeding at fur farms in West Finland, waste dumps in South Finland, and lakes and fields in East Finland. We found individual gulls of this purportedly generalist species to be highly specialised in their foraging behaviour, particularly those that might be associated with their survival probabilities. We hypothesise that differences in foraging behaviour and food availability during the breeding season are partially responsible for differences in demographic trends between populations. Specifically, we identify potential local conservation problems such as shooting in birds visiting fur farms. Our data suggest that the effective conservation and management of endangered nLBBGs could be aided by simple actions in the breeding areas in addition to better protection throughout the annual movement cycle.

Various natural patterns—such as terrestrial sand dune ripples, lamellae in vertebrate bones, growth increments in fish scales and corals, aortas and lamellar corpuscles in humans and animals—comprise layers of different thicknesses and lengths. Microstructures in manmade materials—such as alloys, perlite steels, polymers, ceramics, and ripples induced by laser on the surface of graphen—also exhibit layered structures. These layered patterns form a record of internal and external factors regulating pattern formation in their various systems, making it potentially possible to recognize and identify in their incremental sequences trends, periodicities, and events in the formation history of these systems. The morphology of layered systems plays a vital role in developing new materials and in biomimetic research. The structures and sizes of these two-dimensional (2D) patterns are characteristically anisotropic: That is, the number of layers and their absolute thicknesses vary significantly in different directions. The present work develops a method to quantify the morphological characteristics of 2D layered patterns that accounts for anisotropy in the object of study. To reach this goal, we use Boolean functions and an N-partite graph to formalize layer structure and thickness across a 2D plane and to construct charts of (1) “layer thickness vs. layer number” and (2) “layer area vs. layer number.” We present a parameter disorder of layer structure (DStr) to describe the deviation of a study object’s anisotropic structure from an isotropic analog and illustrate that charts and DStr could be used as local and global morphological characteristics describing various layered systems such as images of, for example, geological, atmospheric, medical, materials, forensic, plants, and animals. Suggested future experiments could lead to new insights into layered pattern formation.

Atmospheric conditions impact how animals use the aerosphere, and birds and bats should modify their flight to minimize energetic expenditure relative to changing wind conditions. To investigate how free-ranging straw-colored fruit bats (Eidolon helvum) fly with changing wind support, we use data collected from bats fit with GPS loggers and an integrated triaxial accelerometer and measure flight speeds, wingbeat frequency, and overall dynamic body acceleration (ODBA) as an estimate for energetic expenditure. We predicted that if ODBA reflects energetic expenditure, then we should find a curvilinear relationship between ODBA and airspeed consistent with aerodynamic theory. We expected that bats would lower their airspeed with tailwind support and that ODBA will decrease with increasing tailwinds and increase with wingbeat frequency. We found that wingbeat frequency has the strongest positive relationship with ODBA. There was a small, but negative, relationship between airspeed and ODBA, and bats decreased ODBA with increasing tailwind. Bats flew at ground speeds of 9.6 ± 2.4 ms−1 (Mean ± SD, range: 4.3–23.9 ms−1) and airspeeds of 10.2 ± 2.5 ms−1, and did not modify their wingbeat frequency with speed. Free-ranging straw-colored fruit bats therefore exerted more total ODBA in headwinds but not when they changed their airspeed. It is possible that the flexibility in wingbeat kinematics may make flight of free-ranging bats less costly than currently predicted or alternatively that the combination of ODBA and airspeed at our scales of measurement does not reflect this relationship in straw-colored fruit bats. Further work is needed to understand the full potential of free-ranging bat flight and how well bio-logging techniques reflect the costs of bat flight.

Long-distance seed dispersal is an important ecosystem service provided by migratory animals. Plants inhabiting discrete habitats, like lakes and wetlands, experience dispersal limitation, and rely heavily on zoochory for their spatial population dynamics. Granivorous waterbirds may disperse viable seeds of wetland plants over long distances during migration. The limited knowledge of waterbird migration has long hampered the evaluation of the importance of waterbirds in seed dispersal, requiring key metrics such as realistic dispersal distances. Using recent GPS tracking of mallards during spring migration, we built a mechanistic seed dispersal model to estimate realistic dispersal distances. Mallards are abundant, partially migratory ducks known to consume seeds of >300 European plant species. Based on the tracking data, we informed a mallard migration simulator to obtain a probabilistic spring migration model for the mallard population wintering at Lake Constance in Southern Germany. We combined the spring migration model with seed retention curves to develop seed dispersal kernels. We also assessed the effects of pre-migratory fasting and the availability of suitable deposition habitats for aquatic and wetland plants. Our results show that mallards at Lake Constance can disperse seeds in the northeastern direction over median distances of 293 and 413 km for seeds with short and long retention times, respectively, assuming a departure immediately after foraging. Pre-migratory fasting strongly affected the dispersal potential, with only 1–7% of ingested seeds left for dispersal after fasting for 12 h. Availability of a suitable deposition habitat was generally

Aerial habitats present a challenge to find food across a large potential search volume, particularly for insectivorous bats that rely on echolocation calls with limited detection range and may forage at heights over 1000 m. To understand how bats use vertical space, we tracked one to five foraging flights of eight common noctules (Nyctalus noctula). Bats were tracked for their full foraging session (87.27 ± 24 min) using high-resolution atmospheric pressure radio transmitters that allowed us to calculate height and wingbeat frequency. Bats used diverse flight strategies, but generally flew lower than 40 m, with scouting flights to 100 m and a maximum of 300 m. We found no influence of weather on height, and high-altitude ascents were not preceded by an increase in foraging effort. Wingbeat frequency was independent from climbing or descending flight, and bats skipped wingbeats or glided in 10% of all observations. Wingbeat frequency was positively related to capture mass, and wingbeat frequency was positively related to time of night, indicating an effect of load increase over a foraging bout. Overall, individuals used a wide range of airspace including altitudes that put them at increased risk from human-made structures. Further work is needed to test the context of these flight decisions, particularly as individuals migrate throughout Europe.

Soaring flight is a remarkable adaptation to reduce movement costs by taking advantage of atmospheric uplifts. The movement pattern of soaring birds is shaped by the spatial and temporal availability and intensity of uplifts, which result from an interaction of local weather conditions with the underlying landscape structure. We used soaring flight locations and vertical speeds of an obligate soaring species, the white stork (Ciconia ciconia), as proxies for uplift availability and intensity. We then tested if static landscape features such as topography and land cover, instead of the commonly used weather information, could predict and map the occurrence and intensity of uplifts across Europe. We found that storks encountering fewer uplifts along their routes, as determined by static landscape features, suffered higher energy expenditures, approximated by their overall body dynamic acceleration. This result validates the use of static features as uplift predictors and suggests the existence of a direct link between energy expenditure and static landscape structure, thus far largely unquantified for flying animals. Our uplift availability map represents a computationally efficient proxy of the distribution of movement costs for soaring birds across the world's landscapes. It thus provides a base to explore the effects of changes in the landscape structure on the energy expenditure of soaring birds, identify low-cost movement corridors and ultimately inform the planning of anthropogenic developments.

Whether and how birds sleep during long-distance flights has remained a mystery. Here, Rattenborg and colleagues show for the first time that frigatebirds can sleep during flight, but do so in remarkably small amounts.

Agro-ecological conditions associated with the spread and persistence of highly pathogenic avian influenza (HPAI) are not well understood, but the trade of live poultry is suspected to be a major pathway. Although market chains of live bird trade have been studied through indirect means including interviews and questionnaires, direct methods have not been used to identify movements of individual poultry. To bridge the knowledge gap on quantitative movement and transportation of poultry, we introduced a novel approach for applying telemetry to document domestic duck movements from source farms at Poyang Lake, China. We deployed recently developed transmitters that record Global Positioning System (GPS) locations and send them through the Groupe Spécial Mobile (GSM) cellular telephone system. For the first time, we were able to track individually marked ducks from 3 to 396 km from their origin to other farms, distribution facilities, or live bird markets. Our proof of concept test showed that the use of GPS-GSM transmitters may provide direct, quantitative information to document the movement of poultry and reveal their market chains. Our findings provide an initial indication of the complexity of source-market network connectivity and highlight the great potential for future telemetry studies in poultry network analyses.

On-going fragmentation of tropical forest ecosystems and associated depletion of seed dispersers threatens the long-term survival of animal-dispersed plants. These threats do not only affect biodiversity and species abundance, but ultimately ecosystem functions and services. Thus, seed dispersers such as the straw-coloured fruit bat, E. helvum, which traverse long distances across fragmented landscapes, are particularly important for maintaining genetic connectivity and colonizing new sites for plant species. Using high-resolution GPS-tracking of movements, field observations and gut retention experiments, we quantify dispersal distances for small- and large-seeded fruits foraged by E. helvum during periods of colony population low (wet season) and high (dry season) in an urban and a rural landscape in the forest zone of Ghana. Gut passage time averaged 116 min (range 4–1143 min), comparable to other fruit bats. Movements were generally longer in the urban than in the rural landscape and also longer in the dry than in the wet season. As the majority of seeds are dispersed only to feeding roosts, median dispersal distances were similar for both large (42–67 m) and small (42–65 m) seeds. However, small seeds were potentially dispersed up to 75.4 km, four times further than the previous maximum distance estimated for a similar-sized frugivore. Maximum seed dispersal distances for small seeds were almost twice as long in the rural (49.7 km) compare to the urban (31.2 km) landscape. Within the urban landscape, estimated maximum dispersal distances for small seeds were three times longer during the dry season (75.4 km) compared to the wet season (22.8 km); in contrast, distances in the rural landscape were three times longer in the wet season (67 km) compared to the dry season (24.4). Dispersal distances for large seeds during the dry season (551 m) in the rural landscape were almost twice that in the wet season (319 m). We found no influence of food phenology on dispersal distances. The maximum likelihood for seed dispersal beyond feeding roosts (mean distance from food tree 263 m) was 4.7%. Small seeds were dispersed over even longer distances, >500 and >1000 m, with a likelihood of 3.0 % and 2.3 % respectively. Our data show that E. helvum retains ingested seeds for very long periods and may traverse large distances, probably making it an important long distance seed disperser in tropical Africa. We suggest E. helvumis important for ecosystem functioning and urge its conservation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Biotelemetry is increasingly used to study animal movement at high spatial and temporal resolution and guide conservation and resource management. Yet, limited sample sizes and variation in space and habitat use across regions and life stages may compromise robustness of behavioral analyses and subsequent conservation plans. Here, we assessed variation in (i) home range sizes, (ii) home range selection, and (iii) fine-scale resource selection of white storks across breeding status and regions and test model transferability. Three study areas were chosen within the Central German breeding grounds ranging from agricultural to fluvial and marshland. We monitored GPS-locations of 62 adult white storks equipped with solar-charged GPS/3D-acceleration (ACC) transmitters in 2013–2014. Home range sizes were estimated using minimum convex polygons. Generalized linear mixed models were used to assess home range selection and fine-scale resource selection by relating the home ranges and foraging sites to Corine habitat variables and normalized difference vegetation index in a presence/pseudo-absence design. We found strong variation in home range sizes across breeding stages with significantly larger home ranges in non-breeding compared to breeding white storks, but no variation between regions. Home range selection models had high explanatory power and well predicted overall density of Central German white stork breeding pairs. Also, they showed good transferability across regions and breeding status although variable importance varied considerably. Fine-scale resource selection models showed low explanatory power. Resource preferences differed both across breeding status and across regions, and model transferability was poor. Our results indicate that habitat selection of wild animals may vary considerably within and between populations, and is highly scale dependent. Thereby, home range scale analyses show higher robustness whereas fine-scale resource selection is not easily predictable and not transferable across life stages and regions. Such variation may compromise management decisions when based on data of limited sample size or limited regional coverage. We thus recommend home range scale analyses and sampling designs that cover diverse regional landscapes and ensure robust estimates of habitat suitability to conserve wild animal populations.

To evolve and to be maintained, seasonal migration, despite its risks, has to yield fitness benefits compared with year-round residency. Empirical data supporting this prediction have remained elusive in the bird literature. To test fitness related benefits of migration, we studied a partial migratory population of European blackbirds (Turdus merula) over 7 years. Using a combination of capture-mark-recapture and radio telemetry, we compared survival probabilities between migrants and residents estimated by multi-event survival models, showing that migrant blackbirds had 16% higher probability to survive the winter compared to residents. A subsequent modelling exercise revealed that residents should have 61.25% higher breeding success than migrants, to outweigh the survival costs of residency. Our results support theoretical models that migration should confer survival benefits to evolve, and thus provide empirical evidence to understand the evolution and maintenance of migration.

Active flight requires the ability to efficiently fuel bursts of costly locomotion while maximizing energy conservation during non-flying times. We took a multi-faceted approach to estimate how fruit-eating bats (Uroderma bilobatum) manage a high-energy lifestyle fueled primarily by fig juice. Miniaturized heart rate telemetry shows that they use a novel, cyclic, bradycardic state that reduces daily energetic expenditure by 10% and counteracts heart rates as high as 900 bpm during flight. Uroderma bilobatum support flight with some of the fastest metabolic incorporation rates and dynamic circulating cortisol in vertebrates. These bats will exchange fat reserves within 24 hr, meaning that they must survive on the food of the day and are at daily risk of starvation. Energetic flexibly in U. bilobatum highlights the fundamental role of ecological pressures on integrative energetic networks and the still poorly understood energetic strategies of animals in the tropics.

Reduction in metabolic rate and body temperature is a common strategy for small endotherms to save energy. The daily reduction in metabolic rate and heterothermy, or torpor, is particularly pronounced in regions with a large variation in daily ambient temperature. This applies most strongly in temperate bat species (order Chiroptera), but it is less clear how tropical bats save energy if ambient temperatures remain high. However, many subtropical and tropical species use some daily heterothermy on cool days. We recorded the heart rate and the body temperature of free-ranging Pallas' mastiff bats (Molossus molossus) in Gamboa, Panamá, and showed that these individuals have low field metabolic rates across a wide range of body temperatures that conform to high ambient temperature. Importantly, low metabolic rates in controlled respirometry trials were best predicted by heart rate, and not body temperature. Molossus molossus enter torpor-like states characterized by low metabolic rate and heart rates at body temperatures of 32°C, and thermoconform across a range of temperatures. Flexible metabolic strategies may be far more common in tropical endotherms than currently known.