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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.

Abstract Studying animal movement is key to understanding ecological processes and studying the impacts of global change. The pivotal importance of collecting movement data drives technological development, and as a consequence, movement trajectories are gathered at unprecedented rates. For the analysis of the ever‐increasing volume of movement tracks, software packages that bridge between data storage, analysis and visualization are crucial. To facilitate analysis, it is key that the metadata, as well as projections, measurements units, and attributes for the track as a whole and auxiliary sensor measurements, are retained. At the same time, the software needs to be flexible enough to accommodate data from the multitude of different sources and tracking technologies. Here, we present the newly developed R package move2 that facilitates import, manipulation, analysis and visualization of movement tracks. The package enables the usage of new programming techniques developed in recent years and has been developed based on the experiences made in the past decade with the move package. The package is tightly integrated into the Movebank ‘ecosystem’ by being a key data format in MoveApps and providing a direct download option from movebank. However, move2 allows the integration of movement data sources of any provenance, providing a generic entry point for movement data analysis in R.

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 More diverse data on animal ecology are now available. This “data deluge” presents challenges for both biologists and computer scientists; however, it also creates opportunities to improve analysis and answer more holistic research questions. We aim to increase awareness of the current opportunity for interdisciplinary research between animal ecology researchers and computer scientists. Immersive analytics (IA) is an emerging research field in which investigations are performed into how immersive technologies, such as large display walls and virtual reality and augmented reality devices, can be used to improve data analysis, outcomes, and communication. These investigations have the potential to reduce the analysis effort and widen the range of questions that can be addressed. We propose that biologists and computer scientists combine their efforts to lay the foundation for IA in animal ecology research. We discuss the potential and the challenges and outline a path toward a structured approach. We imagine that a joint effort would combine the strengths and expertise of both communities, leading to a well-defined research agenda and design space, practical guidelines, robust and reusable software frameworks, reduced analysis effort, and better comparability of results.

Abstract The negative impacts of human activities on biodiversity are well documented. However, extinction risk studies incorporating direct human threats particularly direct killing remain limited. Here, we evaluate the potential role that direct killing through hunting and persecution, indirect human threats via land-use change, and environmental and species traits such as reproductive rate and trophic level among others, may play in driving mammal species to extinction. Based on data for 156 mammal species from Iran, we applied generalized linear models to investigate correlates of extinction risk for: (1) all mammalian species, (2) large- and (3) small-bodied species. We show that hunting vulnerability is the most important predictor to affect extinction risk across all species. We also found that the small-bodied species are impacted by indirect human influence, whereas large species are highly affected by direct killing. Overall, the extrinsic environmental factors and intrinsic species traits had lower importance in our models. Our study gives insight into the dominant role of direct killing on mammal species decline and extinction, emphasizing the need to account for the different sources of threats when analysing the correlates of extinction risk.

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 Life-history theory predicts that parents should balance their limited resources to maximize lifetime fitness, limiting their investment in current reproduction when the fitness value of current progeny is lower than that gained by producing offspring in the future. Here, we examined whether male barn owls (Tyto alba) breeding in low-quality habitats increased their parental effort to successfully complete offspring rearing or limited their investment by paying a fitness cost while saving energy for the future. We equipped 128 males with GPS devices between 2016 and 2020 to collect information on home range size, habitat composition, food provisioning rate to the brood and nightly distances covered. We also recorded nestlings’ growth and survival, as well as males’ body mass variation and future reproductive success. Males living in lower-quality habitats exploited bigger home ranges compared to individuals whose nests were settled in prey-rich habitats. They fed their brood less frequently, while covering longer nightly distance, resulting in a slower growth of late-hatched nestlings and ultimately in a lower fledging success. As males did not differ in body mass variation or future reproductive success our findings suggest that males hunting in home ranges with less prey-rich structures do not jeopardize future reproduction by investing disproportionately larger resources to compensate for their current low home range quality.

The conservation of evolutionary history has been linked to increased benefits for humanity and can be captured by phylogenetic diversity (PD). The Evolutionarily Distinct and Globally Endangered (EDGE) metric has, since 2007, been used to prioritise threatened species for practical conservation that embody large amounts of evolutionary history. While there have been important research advances since 2007, they have not been adopted in practice because of a lack of consensus in the conservation community. Here, building from an interdisciplinary workshop to update the existing EDGE approach, we present an "EDGE2" protocol that draws on a decade of research and innovation to develop an improved, consistent methodology for prioritising species conservation efforts. Key advances include methods for dealing with uncertainty and accounting for the extinction risk of closely related species. We describe EDGE2 in terms of distinct components to facilitate future revisions to its constituent parts without needing to reconsider the whole. We illustrate EDGE2 by applying it to the world's mammals. As we approach a crossroads for global biodiversity policy, this Consensus View shows how collaboration between academic and applied conservation biologists can guide effective and practical priority-setting to conserve biodiversity.

Migration is a complex behaviour that is costly in terms of time, energy and risk of mortality. Thermal soaring birds rely on airflow, specifically wind support and uplift, to offset their energetic costs of flight. Their migratory routes are a record of movement decisions to negotiate the atmospheric environment and achieve efficiency. We expected that, regardless of age, birds use wind support to select their routes. Because thermal soaring is a complex flight behaviour that young birds need to learn, we expected that, as individuals gain more experience, their movement decisions will also increasingly favour the best thermal uplift conditions. We quantified how route choice during autumn migration of young European honey buzzards (Pernis apivorus) was adjusted to wind support and uplift over up to 4 years of migration and compared this with the choices of adult birds. We found that wind support was important in all migrations. However, we did not find an increase in the use of thermal uplifts. This could be due to the species-specific learning period and/or an artefact of the spatio-temporal scale of our uplift proxies.

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.

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 Background The intensification of agricultural practices over the twentieth century led to a cascade of detrimental effects on ecosystems. In Europe, agri-environment schemes (AES) have since been adopted to counter the decrease in farmland biodiversity, with the promotion of extensive habitats such as wildflower strips and extensive meadows. Despite having beneficial effects documented for multiple taxa, their profitability for top farmland predators, like raptors, is still debated. Such species with high movement capabilities have large home ranges with fluctuation in habitat use depending on specific needs. Methods Using GPS devices, we recorded positions for 134 barn owls (Tyto alba) breeding in Swiss farmland and distinguished three main behavioural modes with the Expectation-Maximization binary Clustering (EMbC) method: perching, hunting and commuting. We described barn owl habitat use at different levels during the breeding season by combining step and path selection functions. In particular, we examined the association between behavioural modes and habitat type, with special consideration for AES habitat structures. Results Despite a preference for the most common habitats at the home range level, behaviour-specific analyses revealed more specific habitat use depending on the behavioural mode. During the day, owls roosted almost exclusively in buildings, while pastures, meadows and forest edges were preferred as nocturnal perching sites. For hunting, barn owls preferentially used AES habitat structures though without neglecting more intensively exploited areas. For commuting, open habitats were preferred over wooded areas. Conclusions The behaviour-specific approach used here provides a comprehensive breakdown of barn owl habitat selection during the reproductive season and highlights its importance to understand complex animal habitat preferences. Our results highlight the importance of AES in restoring and maintaining functional trophic chains in farmland.

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 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.

Abstract Land cover is a key variable in monitoring applications and new processing technologies made deriving this information easier. Yet, classification algorithms remain dependent on samples collected on the field and field campaigns are limited by financial, infrastructural and political boundaries. Here, animal tracking data could be an asset. Looking at the land cover dependencies of animal behaviour, we can obtain land cover samples over places that are difficult to access. Following this premise, we evaluated the potential of animal movement data to map land cover. Specifically, we used 13 White Storks (Cicona cicona) individuals of the same population to map agriculture within three test regions distributed along their migratory track. The White Stork has adapted to foraging over agricultural lands, making it an ideal source of samples to map this land use. We applied a presence–absence modelling approach over a Normalized Difference Vegetation Index (NDVI) time series and validated our classifications, with high‐resolution land cover information. Our results suggest White Stork movement is useful to map agriculture, however, we identified some limitations. We achieved high accuracies (F1‐scores > 0.8) for two test regions, but observed poor results over one region. This can be explained by differences in land management practices. The animals preferred agriculture in every test region, but our data showed a biased distribution of training samples between irrigated and non‐irrigated land. When both options occurred, the animals disregarded non‐irrigated land leading to its misclassification as non‐agriculture. Additionally, we found difference between the GPS observation dates and the harvest times for non‐irrigated crops. Given the White Stork takes advantage of managed land to search for prey, the inactivity of these fields was the likely culprit of their underrepresentation. Including more species attracted to agriculture – with other land‐use dependencies and observation times – can contribute to better results in similar applications.

Abstract Background Global positioning systems (GPS) and altimeters are increasingly used to monitor vertical space use by aerial species, a key aspect of their ecological niche, that we need to know to manage our own use of the airspace, and to protect those species. However, there are various sources of error in flight height data (“height” above ground, as opposed to “altitude” above a reference like the sea level). First the altitude is measured with a vertical error from the devices themselves. Then there is error in the ground elevation below the tracked animals, which translates into error in flight height computed as the difference between altitude and ground elevation. Finally, there is error in the horizontal position of the animals, which translates into error in the predicted ground elevation below the animals. We used controlled field trials, simulations, and the reanalysis of raptor case studies with state-space models to illustrate the effect of improper error management. Results Errors of a magnitude of 20 m appear in benign conditions for barometric altimeters and GPS vertical positioning (expected to be larger in more challenging context). These errors distort the shape of the distribution of flight heights, inflate the variance in flight height, bias behavioural state assignments, correlations with environmental covariates, and airspace management recommendations. Improper data filters such as removing all negative flight height records introduce several biases in the remaining dataset, and preclude the opportunity to leverage unambiguous errors to help with model fitting. Analyses that ignore the variance around the mean flight height, e.g., those based on linear models of flight height, and those that ignore the variance inflation caused by telemetry errors, lead to incorrect inferences. Conclusion The state-space modelling framework, now in widespread use by ecologists and increasingly often automatically implemented within on-board GPS data processing algorithms, makes it possible to fit flight models directly to the output of GPS devices, with minimal data pre-selection, and to analyse the full distribution of flight heights, not just the mean. In addition to basic research about aerial niches, behaviour quantification, and environmental interactions, we highlight the applied relevance of our recommendations for airspace management and the conservation of aerial wildlife.

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 Background Ectotherms are assumed to be strongly influenced by the surrounding ambient and environmental conditions for daily activity and movement. As such, ecological and physiological factors contribute to stimuli influencing navigation, extent of movement, and therefore habitat use. Our study focused on the intensity of activity (from acceleration data) and extent of movement (from GPS and thread trailing data) of Eastern box turtles (Terrapene carolina carolina) in a fragmented landscape near their northern population limit. First, we quantified the thermal performance curve of box turtles using activity as a measure of performance. Second, we investigated ecological factors that could influence activity and movement and characterized the movement as extensive (exploration) and intensive (foraging). Results In contrast to previous lab work investigating effects of temperature on activity, we found no relationship between box turtle activity and temperature in the field. Furthermore, box turtle activity was consistent over a wide range of temperatures. Cluster analysis categorized movement recorded with GPS more as intensive than as extensive, while thread trailing had more movement categorized as extensive than intensive. Box turtle activity was higher during the morning hours and began to decrease as the day progressed. Based on the microclimate conditions tested, we found that box turtle movement was influenced by precipitation and time of day, and activity was most influenced by absolute humidity, ambient temperature, cloud cover, and time of day. Conclusions Our model ectotherm in this study, the Eastern box turtle, had activity patterns characteristic of a thermal generalist. Sampling resolution altered the characterization of movement as intensive or extensive movement, possibly altering interpretation. More information on the resolution needed to definitively identify foraging and exploratory behavior in turtles is needed. Activity and movement were nearly independent of environmental conditions, which supports the overall interpretation that turtle performance is that of a broad environmental generalist. Future studies of movement of other turtle and reptile species are needed to determine the generality of these findings.

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

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.

Flapping flight is relatively costly for soaring birds such as raptors. To avoid costly flight, migrating raptors generally avoid flying over water. As a result, all but one of the global raptor migration flyways are largely over land. The East Asian oceanic flyway for raptors is the exception. Raptor species using this flyway migrate by island-hopping, flying over open ocean for distances of up to 300 km between islands. We used satellite telemetry data for grey-faced buzzards Butastur indicus, a species that dominates the southern part of the flyway, to investigate the geographical and atmospheric factors responsible for the suitability of this flyway for raptor migration. Using a combination of least-cost path analysis and a step selection function, we found that the occurrence of numerous islands and also suitable wind support along the oceanic flyway are responsible for route selection in grey-faced buzzards. These results confirm the role of islands, but also wind, in shaping the East Asian oceanic flyway of long-distance raptor migration.

Being faced with unknown environments is a concomitant challenge of species' range expansions. Strategies to cope with this challenge include the adaptation to local conditions and a flexibility in resource exploitation. The gulls of the Larus argentatus-fuscus-cachinnans group form a system in which ecological flexibility might have enabled them to expand their range considerably, and to colonize urban environments. However, on a population level both flexibility and local adaptation lead to signatures of differential habitat use in different environments, and these processes are not easily distinguished. Using the lesser black-backed gull (Larus fuscus) as a system, we put both flexibility and local adaptation to a test. We compare habitat use between two spatially separated populations, and use a translocation experiment during which individuals were released into novel environment. The experiment revealed that on a population-level flexibility best explains the differences in habitat use between the two populations. We think that our results suggest that the range expansion and huge success of this species complex could be a result of its broad ecological niche and flexibility in the exploitation of resources. However, this also advises caution when using species distribution models to extrapolate habitat use across space.

Digitized species occurrence data provide an unprecedented source of information for ecologists and conservationists. Species distribution model (SDM) has become a popular method to utilise these data for understanding the spatial and temporal distribution of species, and for modelling biodiversity patterns. Our objective is to study the impact of noise in species occurrence data (namely sample size and positional accuracy) on the performance and reliability of SDM, considering the multiplicative impact of SDM algorithms, species specialisation, and grid resolution. We created a set of four 'virtual' species characterized by different specialisation levels. For each of these species, we built the suitable habitat models using five algorithms at two grid resolutions, with varying sample sizes and different levels of positional accuracy. We assessed the performance and reliability of the SDM according to classic model evaluation metrics (Area Under the Curve and True Skill Statistic) and model agreement metrics (Overall Concordance Correlation Coefficient and geographic niche overlap) respectively. Our study revealed that species specialisation had by far the most dominant impact on the SDM. In contrast to previous studies, we found that for widespread species, low sample size and low positional accuracy were acceptable, and useful distribution ranges could be predicted with as few as 10 species occurrences. Range predictions for narrow-ranged species, however, were sensitive to sample size and positional accuracy, such that useful distribution ranges required at least 20 species occurrences. Against expectations, the MAXENT algorithm poorly predicted the distribution of specialist species at low sample size.

Olfaction represents an important sensory modality for navigation of both homing pigeons and wild birds. Experimental evidence in homing pigeons showed that airborne volatile compounds carried by the winds at the home area are learned in association with wind directions. When displaced, pigeons obtain information on the direction of their displacement using local odours at the release site. Recently, the role of olfactory cues in navigation has been reported also for wild birds during migration. However, the question whether wild birds develop an olfactory navigational map similar to that described in homing pigeons or, alternatively, exploit the distribution of volatile compounds in different manners for reaching the goal is still an open question. Using an interdisciplinary approach, we evaluate the possibilities of reconstructing spatio-temporally explicit aerosol dispersion at large spatial scales using the particle dispersion model FLEXPART. By combining atmospheric information with particle dispersion models, atmospheric scientists predict the dispersion of pollutants for example, after nuclear fallouts or volcanic eruptions or wildfires, or in retrospect reconstruct the origin of emissions such as aerosols. Using simple assumptions, we reconstructed the putative origin of aerosols traveling to the location of migrating birds. We use the model to test whether the putative odour plume could have originated from an important stopover site. If the migrating birds knew this site and the associated plume from previous journeys, the odour could contribut to the reorientation towards the migratory corridor, as suggested for the model scenario in displaced Lesser black-backed gulls migrating from Northern Europe into Africa.

Investigating animal energy expenditure across space and time may provide more detailed insight into how animals interact with their environment. This insight should improve our understanding of how changes in the environment affect animal energy budgets and is particularly relevant for animals living near or within human altered environments where habitat change can occur rapidly. We modeled fisher (Pekania pennanti) energy expenditure within their home ranges and investigated the potential environmental and spatial drivers of the predicted spatial patterns. As a proxy for energy expenditure we used overall dynamic body acceleration (ODBA) that we quantified from tri-axial accelerometer data during the active phases of 12 individuals. We used a generalized additive model (GAM) to investigate the spatial distribution of ODBA by associating the acceleration data to the animals' GPS-recorded locations. We related the spatial patterns of ODBA to the utilization distributions and habitat suitability estimates across individuals. The ODBA of fishers appears highly structured in space and was related to individual utilization distribution and habitat suitability estimates. However, we were not able to predict ODBA using the environmental data we selected. Our results suggest an unexpected complexity in the space use of animals that was only captured partially by re-location data-based concepts of home range and habitat suitability. We suggest future studies recognize the limits of ODBA that arise from the fact that acceleration is often collected at much finer spatio-temporal scales than the environmental data and that ODBA lacks a behavioral correspondence. Overcoming these limits would improve the interpretation of energy expenditure in relation to the environment.

The last decade has seen a surge in research on avian influenza A viruses (IAVs), in part fuelled by the emergence, spread and potential zoonotic importance of highly pathogenic virus subtypes. The mallard (Anas platyrhynchos) is the most numerous and widespread dabbling duck in the world, and one of the most important natural hosts for studying IAV transmission dynamics. In order to predict the likelihood of IAV transmission between individual ducks and to other hosts, as well as between geographical regions, it is important to understand how IAV infection affects the host. In this study, we analysed the movements of 40 mallards equipped with GPS transmitters and three-dimensional accelerometers, of which 20 were naturally infected with low pathogenic avian influenza virus (LPAIV), at a major stopover site in the Northwest European flyway. Movements differed substantially between day and night, as well as between mallards returning to the capture site and those feeding in natural habitats. However, movement patterns did not differ between LPAIV infected and uninfected birds. Hence, LPAIV infection probably does not affect mallard movements during stopover, with high possibility of virus spread along the migration route as a consequence.

The performance capabilities of flying animals reflect the interplay of biomechanical and physiological constraints and evolutionary innovation. Of the two extant groups of vertebrates that are capable of powered flight, birds are thought to fly more efficiently and faster than bats. However, fast-flying bat species that are adapted for flight in open airspace are similar in wing shape and appear to be similar in flight dynamics to fast-flying birds that exploit the same aerial niche. Here, we investigate flight behaviour in seven free-flying Brazilian free-tailed bats (Tadarida brasiliensis) and report that the maximum ground speeds achieved exceed speeds previously documented for any bat. Regional wind modelling indicates that bats adjusted flight speeds in response to winds by flying more slowly as wind support increased and flying faster when confronted with crosswinds, as demonstrated for insects, birds and other bats. Increased frequency of pauses in wing beats at faster speeds suggests that flap-gliding assists the bats' rapid flight. Our results suggest that flight performance in bats has been underappreciated and that functional differences in the flight abilities of birds and bats require re-evaluation.

The mallard (Anas platyrhynchos) is a focal species in game management, epidemiology and ornithology, but comparably little research has focused on the ecology of the migration seasons. We studied habitat use, time-budgets, home-range sizes, habitat selection, and movements based on spatial data collected with GPS devices attached to wild mallards trapped at an autumn stopover site in the Northwest European flyway. Sixteen individuals (13 males, 3 females) were followed for 15-38 days in October to December 2010. Forty-nine percent (SD = 8.4%) of the ducks' total time, and 85% of the day-time (SD = 28.3%), was spent at sheltered reefs and bays on the coast. Two ducks used ponds, rather than coast, as day-roosts instead. Mallards spent most of the night (76% of total time, SD = 15.8%) on wetlands, mainly on alvar steppe, or in various flooded areas (e.g. coastal meadows). Crop fields with maize were also selectively utilized. Movements between roosting and foraging areas mainly took place at dawn and dusk, and the home-ranges observed in our study are among the largest ever documented for mallards (mean = 6,859 ha; SD = 5,872 ha). This study provides insights into relatively unknown aspects of mallard ecology. The fact that autumn-staging migratory mallards have a well-developed diel activity pattern tightly linked to the use of specific habitats has implications for wetland management, hunting and conservation, as well as for the epidemiology of diseases shared between wildlife and domestic animals.

Long-distance migration is a rare phenomenon in European bats. Genetic analyses and banding studies show that females can cover distances of up to 1,600 km, whereas males are sedentary or migrate only short distances. The onset of this sex-biased migration is supposed to occur shortly after rousing from hibernation and when the females are already pregnant. We therefore predicted that the sexes are exposed to different energetic pressures in early spring, and this should be reflected in their behavior and physiology. We investigated this in one of the three Central European long-distance migrants, the common noctule (Nyctalus noctula) in Southern Germany recording the first individual partial migration tracks of this species. In contrast to our predictions, we found no difference between male and female home range size, activity, habitat use or diet. Males and females emerged from hibernation in similar body condition and mass increase rate was the same in males and females. We followed the first migration steps, up to 475 km, of radio-tagged individuals from an airplane. All females, as well as some of the males, migrated away from the wintering area in the same northeasterly direction. Sex differences in long-distance migratory behavior were confirmed through stable isotope analysis of hair, which showed greater variation in females than in males. We hypothesize that both sexes faced similarly good conditions after hibernation and fattened at maximum rates, thus showing no differences in their local behavior. Interesting results that warrant further investigation are the better initial condition of the females and the highly consistent direction of the first migratory step in this population as summering habitats of the common noctule occur at a broad range in Northern Europe. Only research focused on individual strategies will allow us to fully understand the migratory behavior of European bats.

BackgroundConservation of phylogenetic diversity allows maximising evolutionary information preserved within fauna and flora. The "EDGE of Existence" programme is the first institutional conservation initiative that prioritises species based on phylogenetic information. Species are ranked in two ways: one according to their evolutionary distinctiveness (ED) and second, by including IUCN extinction status, their evolutionary distinctiveness and global endangerment (EDGE). Here, we describe the global patterns in the spatial distribution of priority ED and EDGE species, in order to identify conservation areas for mammalian and amphibian communities. In addition, we investigate whether environmental conditions can predict the observed spatial pattern in ED and EDGE globally.Methods and principal findingsPriority zones with high concentrations of ED and EDGE scores were defined using two different methods. The overlap between mammal and amphibian zones was very small, reflecting the different phylo-biogeographic histories. Mammal ED zones were predominantly found on the African continent and the neotropical forests, whereas in amphibians, ED zones were concentrated in North America. Mammal EDGE zones were mainly in South-East Asia, southern Africa and Madagascar; for amphibians they were in central and south America. The spatial pattern of ED and EDGE was poorly described by a suite of environmental variables.ConclusionsMapping the spatial distribution of ED and EDGE provides an important step towards identifying priority areas for the conservation of mammalian and amphibian phylogenetic diversity in the EDGE of existence programme.

Stable isotope and fatty acid signatures of biomaterials can provide important information about the dietary niche of animals. Stable isotope and fatty acid signatures differ between aquatic and terrestrial food webs, and therefore can be used to assess the aquatic and terrestrial contributions to the diets of species. We studied faecal samples of three co-occurring bat species with known differences in feeding preferences. The aim was to assess whether stable isotope and fatty acid signatures of faeces can be used to determine feeding preferences. We used bat faeces because they can be easily and non-invasively collected. We hypothesised that faeces stable isotope and fatty acid signatures will reveal the terrestrial, aquatic and mixed feeding niches of Myotis myotis, M. daubentonii, and M. mystacinus, respectively. As predicted, the faeces of M. myotis were characterized by higher δ(13)C values and higher concentrations of linoleic acid and total ω6 polyunsaturated fatty acids (PUFAs), which are typically higher in terrestrial food webs. The faeces of M. daubentonii had higher δ(15)Ν values and higher concentrations of docosahexaenoic acid and total ω3 PUFAs, characteristic features of aquatic systems. Myotis mystacinus faeces had intermediate δ(15)Ν values and concentrations of both types of fatty acids. Our results show that analysing stable isotope and/or fatty acid signatures of faeces provides a promising, non-invasive tool to study the feeding ecology of bats and to assess aquatic-terrestrial interactions.

Predicting the consequences of climate change is a major challenge in ecology and wildlife management. While the impact of changes in climatic conditions on distribution ranges has been documented for many organisms, the consequences of changes in resource dynamics for species' overall performance have seldom been investigated. This study addresses this gap by identifying the factors shaping the reproductive synchrony of ungulates. In temporally-variable environments, reproductive phenology of individuals is a key determinant of fitness, with the timing of reproduction affecting their reproductive output and future performance. We used a satellite-based index of resource availability to explore how the level of seasonality and inter-annual variability in resource dynamics affect birth season length of ungulate populations. Contrary to what was previously thought, we found that both the degree of seasonal fluctuation in resource dynamics and inter-annual changes in resource availability influence the degree of birth synchrony within wild ungulate populations. Our results highlight how conclusions from previous interspecific analyses, which did not consider the existence of shared life-history among species, should be treated with caution. They also support the existence of a multi-faceted link between temporal variation in resource availability and breeding synchrony in terrestrial mammals, and increase our understanding of the mechanisms shaping reproductive synchrony in large herbivores, thus enhancing our ability to predict the potential impacts of climate change on biodiversity.

The amphibian decline and extinction crisis demands urgent action to prevent further large numbers of species extinctions. Lists of priority species for conservation, based on a combination of species' threat status and unique contribution to phylogenetic diversity, are one tool for the direction and catalyzation of conservation action. We describe the construction of a near-complete species-level phylogeny of 5713 amphibian species, which we use to create a list of evolutionarily distinct and globally endangered species (EDGE list) for the entire class Amphibia. We present sensitivity analyses to test the robustness of our priority list to uncertainty in species' phylogenetic position and threat status. We find that both sources of uncertainty have only minor impacts on our 'top 100' list of priority species, indicating the robustness of the approach. By contrast, our analyses suggest that a large number of Data Deficient species are likely to be high priorities for conservation action from the perspective of their contribution to the evolutionary history.

How migration evolved represents one of the most poignant questions in evolutionary biology. While studies on the evolution of migration in birds are well represented in the literature, migration in bats has received relatively little attention. Yet, more than 30 species of bats are known to migrate annually from breeding to non-breeding locations. Our study is the first to test hypotheses on the evolutionary history of migration in bats using a phylogenetic framework.In addition to providing a review of bat migration in relation to existing hypotheses on the evolution of migration in birds, we use a previously published supertree to formulate and test hypotheses on the evolutionary history of migration in bats. Our results suggest that migration in bats has evolved independently in several lineages potentially as the need arises to track resources (food, roosting site) but not through a series of steps from short- to long-distance migrants, as has been suggested for birds. Moreover, our analyses do not indicate that migration is an ancestral state but has relatively recently evolved in bats. Our results also show that migration is significantly less likely to evolve in cave roosting bats than in tree roosting species.This is the first study to provide evidence that migration has evolved independently in bat lineages that are not closely related. If migration evolved as a need to track seasonal resources or seek adequate roosting sites, climate change may have a pivotal impact on bat migratory habits. Our study provides a strong framework for future research on the evolution of migration in chiropterans.