Physical limits of flight performance in the heaviest soaring bird

Integrating eDNA metabarcoding and citizen science enhances avian ecological research

Research Highlight: Bourbour et al., 2024. Feeding en route: Prey availability and traits influence prey selection by an avian predator on migration. Journal of Animal Ecology. Diet selection plays a key role in the eco-evolutionary dynamics of animals, exhibiting substantial variability across species, environments and seasons. The complex interplay between movement capability, hunting strategies, habitat use, prey traits and availability shapes the foraging patterns of avian predators. However, detailed information on how these birds exploit their extensive territories remains limited. In this study, Bourbour et al. utilised a novel integration of eDNA metabarcoding and citizen science to explore predator-prey interactions between migrating sharp-shinned hawks (Accipiter striatus) and an ephemeral avian prey community along North America's Pacific flyway. The research identified 1396 detections from the diet (65 species) of 588 migrating sharp-shinned hawks. Hawks' diet composition correlated with prey abundance indices sourced from the eBird database throughout the migration season, highlighting the significant impact of prey availability-shaped by migration tendency, flocking behaviour, and habitat-on raptor-songbird interactions. Notably, the study also found significant differences in prey size between male and female hawks, indicating that sexual dimorphism has led to diverse foraging strategies during migration. These findings underscore the potential of combining eDNA metabarcoding with citizen science to deepen our understanding of the foraging ecology of highly mobile and wide-ranging birds, as well as to monitor complex and vast ecosystems.

Both movements and breeding performance are affected by individual experience in the Bonelli's eagle Aquila fasciata

Movement is a key behaviour to better understand how individuals respond to their environment. Movement behaviours are affected by both extrinsic factors that individuals face, such as weather conditions, and intrinsic factors, such as sex and experience. Because of the energy costs it entails, movement behaviours can have direct consequences on an individual's demographic parameters-and ultimately on population dynamics. However, the relationship between extrinsic factors, intrinsic factors, daily movement behaviour and demographic parameters such as breeding performance is poorly known, in particular for central place forager territorial species. We investigated here the link between movement behaviours and breeding performance of the French population of Bonelli's eagle (Aquila fasciata), a territorial and sedentary long-lived raptor, and how this link may depend on extrinsic and intrinsic factors. By using data from annual monitoring of breeding performance for the population and GPS tracking of 48 individuals (26 males and 22 females), we found that the breeding performance of this population was mainly driven by whether a new individual was recruited into the territory, and only slightly by weather conditions. Movement behaviours (proportion of time in flight, range of movement and straightness of trajectories) showed large between-individual variation. Those behaviours were related with weather conditions (wind and rainfall) at a daily scale, as well as with individual's experience. We found only one significant correlation between movements and breeding performance: male Bonelli's eagles spending more time flying during chick-rearing phase had lower productivity. Movement behaviours and breeding performance were also indirectly linked through individual's experience, with more experienced birds having better breeding success and a shorter range of movement and spent less time in flight. This suggests that experienced individuals progressively acquire knowledge of their breeding territory, are more efficient in finding prey, and adapt their foraging strategies to weather conditions to minimise energy costs, allowing them higher breeding performance.

Revealing principles of autonomous thermal soaring in windy conditions using vulture-inspired deep reinforcement-learning

Thermal soaring, a technique used by birds and gliders to utilize updrafts of hot air, is an appealing model-problem for studying motion control and how it is learned by animals and engineered autonomous systems. Thermal soaring has rich dynamics and nontrivial constraints, yet it uses few control parameters and is becoming experimentally accessible. Following recent developments in applying reinforcement learning methods for training deep neural-network (deep-RL) models to soar autonomously both in simulation and real gliders, here we develop a simulation-based deep-RL system to study the learning process of thermal soaring. We find that this process has learning bottlenecks, we define a new efficiency metric and use it to characterize learning robustness, we compare the learned policy to data from soaring vultures, and find that the neurons of the trained network divide into function clusters that evolve during learning. These results pose thermal soaring as a rich yet tractable model-problem for the learning of motion control.

Experience reduces route selection for conspecifics by the collectively migrating white stork

Migration can be an energetically costly behavior with strong fitness consequences in terms of mortality and reproduction.1,2,3,4,5,6,7,8,9,10,11 Migrants should select migratory routes to minimize their costs, but both costs and benefits may change with experience.12,13,14 This raises the question of whether experience changes how individuals select their migratory routes. Here, we investigate the effect of age on route selection criteria in a collectively migrating soaring bird, the white stork (Ciconia ciconia). We perform step-selection analysis on a longitudinal dataset tracking 158 white storks over up to 9 years to quantify how they select their routes based on the social and atmospheric environments and to examine how this selection changes with age. We find clear ontogenetic shifts in route selection criteria. Juveniles choose routes that have good atmospheric conditions and high conspecific densities. Yet, as they gain experience, storks' selection on the availability of social information reduces-after their fifth migration, experienced birds also choose routes with low conspecific densities. Thus, our results suggest that as individuals age, they gradually replace information gleaned from other individuals with information gained from experience, allowing them to shift their migration timing and increasing the timescale at which they select their routes.

Landing and take-off capabilities of bioinspired aerial vehicles: a review

Bioinspired flapping-wing micro aerial vehicles (FWMAVs) have emerged over the last two decades as a promising new type of robot. Their high thrust-to-weight ratio, versatility, safety, and maneuverability, especially at small scales, could make them more suitable than fixed-wing and multi-rotor vehicles for various applications, especially in cluttered, confined environments and in close proximity to humans, flora, and fauna. Unlike natural flyers, however, most FWMAVs currently have limited take-off and landing capabilities. Natural flyers are able to take off and land effortlessly from a wide variety of surfaces and in complex environments. Mimicking such capabilities on flapping-wing robots would considerably enhance their practical usage. This review presents an overview of take-off and landing techniques for FWMAVs, covering different approaches and mechanism designs, as well as dynamics and control aspects. The special case of perching is also included. As well as discussing solutions investigated for FWMAVs specifically, we also present solutions that have been developed for different types of robots but may be applicable to flapping-wing ones. Different approaches are compared and their suitability for different applications and types of robots is assessed. Moreover, research and technology gaps are identified, and promising future work directions are identified.

Learning shapes the development of migratory behavior

How animals refine migratory behavior over their lifetime (i.e., the ontogeny of migration) is an enduring question with important implications for predicting the adaptive capacity of migrants in a changing world. Yet, our inability to monitor the movements of individuals from early life onward has limited our understanding of the ontogeny of migration. The exploration-refinement hypothesis posits that learning shapes the ontogeny of migration in long-lived species, resulting in greater exploratory behavior early in life followed by more rapid and direct movement during later life. We test the exploration-refinement hypothesis by examining how white storks (Ciconia ciconia) balance energy, time, and information as they develop and refine migratory behavior during the first years of life. Here, we show that young birds reduce energy expenditure during flight while also increasing information gain by exploring new places during migration. As the birds age and gain more experience, older individuals stop exploring new places and instead move more quickly and directly, resulting in greater energy expenditure during migratory flight. During spring migration, individuals innovated novel shortcuts during the transition from early life into adulthood, suggesting a reliance on spatial memory acquired through learning. These incremental refinements in migratory behavior provide support for the importance of individual learning within a lifetime in the ontogeny of long-distance migration.

The use of social information in vulture flight decisions

Animals rely on a balance of personal and social information to decide when and where to move next in order to access a desired resource. The benefits from cueing on conspecifics to reduce uncertainty about resource availability can be rapidly overcome by the risks of within-group competition, often exacerbated toward low-ranked individuals. Being obligate soarers, relying on thermal updraughts to search for carcasses around which competition can be fierce, vultures represent ideal models to investigate the balance between personal and social information during foraging movements. Linking dominance hierarchy, social affinities and meteorological conditions to movement decisions of eight captive vultures, Gyps spp., released for free flights in natural soaring conditions, we found that they relied on social information (i.e. other vultures using/having used the thermals) to find the next thermal updraught, especially in unfavourable flight conditions. Low-ranked individuals were more likely to disregard social cues when deciding where to go next, possibly to minimize the competitive risk of social aggregation. These results exemplify the architecture of decision-making during flight in social birds. It suggests that the environmental context, the context of risk and the social system as a whole calibrate the balance between personal and social information use.

Advances in biologging can identify nuanced energetic costs and gains in predators

Foraging is a key driver of animal movement patterns, with specific challenges for predators which must search for mobile prey. These patterns are increasingly impacted by global changes, principally in land use and climate. Understanding the degree of flexibility in predator foraging and social strategies is pertinent to wildlife conservation under global change, including potential top-down effects on wider ecosystems. Here we propose key future research directions to better understand foraging strategies and social flexibility in predators. In particular, rapid continued advances in biologging technology are helping to record and understand dynamic behavioural and movement responses of animals to environmental changes, and their energetic consequences. Data collection can be optimised by calibrating behavioural interpretation methods in captive settings and strategic tagging decisions within and between social groups. Importantly, many species' social systems are increasingly being found to be more flexible than originally described in the literature, which may be more readily detectable through biologging approaches than behavioural observation. Integrating the effects of the physical landscape and biotic interactions will be key to explaining and predicting animal movements and energetic balance in a changing world.

Supervised versus unsupervised approaches to classification of accelerometry data

Sophisticated animal-borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for robust analytical methods for biological interpretation. Machine learning tools are often used to meet this need. However, their relative effectiveness is not well known and, in the case of unsupervised tools, given that they do not use validation data, their accuracy can be difficult to assess. We evaluated the effectiveness of supervised (n = 6), semi-supervised (n = 1), and unsupervised (n = 2) approaches to analyzing accelerometry data collected from critically endangered California condors (Gymnogyps californianus). Unsupervised K-means and EM (expectation-maximization) clustering approaches performed poorly, with adequate classification accuracies of <0.8 but very low values for kappa statistics (range: -0.02 to 0.06). The semi-supervised nearest mean classifier was moderately effective at classification, with an overall classification accuracy of 0.61 but effective classification only of two of the four behavioral classes. Supervised random forest (RF) and k-nearest neighbor (kNN) machine learning models were most effective at classification across all behavior types, with overall accuracies >0.81. Kappa statistics were also highest for RF and kNN, in most cases substantially greater than for other modeling approaches. Unsupervised modeling, which is commonly used for the classification of a priori-defined behaviors in telemetry data, can provide useful information but likely is instead better suited to post hoc definition of generalized behavioral states. This work also shows the potential for substantial variation in classification accuracy among different machine learning approaches and among different metrics of accuracy. As such, when analyzing biotelemetry data, best practices appear to call for the evaluation of several machine learning techniques and several measures of accuracy for each dataset under consideration.

The Influence of Age, Sex and Season on Andean Condor Ranging Behavior during the Immature Stage

Immature individuals move from their natal area to the area where they settle and reproduce, and this may take several years. This process is essential for long-lived species such as vultures and condors, which spend long periods as immature and move extensively. We studied the movement behavior of 26 GPS-tagged immature Andean condors (Vultur gryphus) from northwestern Patagonia throughout the immature stage, analyzing whether these patterns differed according to age, sex and season. We found that season and age influenced home range size and flight distances, the warm season being when immature condors move most; movement patterns were greater in sub-adults than in juveniles. The age effect was associated with the sex of individuals, with males increasing their home range more than females. Our results provide the first description of how immature Andean condor movement patterns are affected by internal and external factors. This information could be key to understanding condor responses to environmental change and threats at different stages during their immature phase. Until now, condor conservation efforts have not considered the areas used by dispersing individuals. Our results increase our understanding of ranging behavior during the immature stage of this threatened bird, enabling us to improve the conservation policies and management strategies designed to protect them.

Navigating Storms: Examining Vultures’ Behavior in Response to Extreme Weather Events

Extreme weather events such as hurricanes and tornadoes have been found to change the spatial and temporal abundance of raptors by decreasing survival and forcing the emigration of individuals, or by increasing habitat heterogeneity and facilitating recolonization of disturbed areas. Nonetheless, little is known about how extreme weather events could affect raptors’ movements and their space use in areas disturbed by large-scale weather events. We studied how extreme weather affected the movements of black and turkey vultures (Coragyps atratus and Cathartes aura, respectively) in Mississippi, USA, facing Hurricane Zeta in November 2020, winter storm Viola in February 2021, and tornados MS-43 and MS-44 in May 2021. We GPS-tracked 28 vultures in the paths of these events. We compared movement rates, net-squared displacements, and use of forest cover, before, during, and after the events. Since storm avoidance behavior has been observed in other birds, we expected that vultures would shift their movements out of the path of these events before storms hit. Further, we forecasted that vultures would make greater use of forested areas as protection against harsh conditions such as strong winds and heavy rain. Vultures responded differently to each weather event; they shifted their movements out of the predicted path of the hurricane and tornadoes but not the snowstorm. These findings reveal that both species use avoidance behavior and adjust their navigation and hazard detection accordingly. Avoidance behavior was more pronounced in turkey vultures than in black vultures. In general, vultures did not make greater use of forest areas as we expected, but turkey vultures did select forest areas during the snowstorm. We propose that olfaction and audition may be key in vultures’ response to extreme weather events.

High incidence of plastic debris in Andean condors from remote areas: Evidence for marine-terrestrial trophic transfer

Plastic pollution is an alarming environmental problem affecting diverse species worldwide. Scavenging birds are currently exposed to plastic due to contamination of their food sources. Here, we evaluated the ingestion of plastic by a threatened top scavenger, the Andean condor (Vultur gryphus), and the potential origin of the plastic. We analyzed the biotic (organic items from the diet) and abiotic (synthetic material) composition of regurgitated pellets in two remote areas of Peru associated with protected areas: a marine-coastal region and an Andean region. Condors consume mainly Pinnipeds and South American camelids in the marine-coastal region, and camelids and livestock in the Andean region. We found different sizes and varieties of plastic debris, with a very high frequency of occurrence (85-100%) of microplastics in pellets of both areas studied. The occurrence of microplastics differed between sites; although very high in general, the rate of occurrence and density were higher in the marine-coastal region. We also confirmed that carcasses consumed by condors in both study areas were contaminated with plastic. Therefore, plastic in Andean condors is most probably acquired through the food web in both the marine and terrestrial environments. Andean condors from Peru are highly contaminated with plastic, which may affect their health, population dynamics, and conservation. Moreover, as condors are apex scavengers, our results highlight the fact that plastic pollution in remote areas of Peru is present at different levels of the food web and in the environment. Urgent Action should be taken to reduce environmental contamination with this hazardous pollutant.

Built up areas in a wet landscape are stepping stones for soaring flight in a seabird

The energy exchange between the Earth's surface and atmosphere results in a highly dynamic habitat through which birds move. Thermal uplift is an atmospheric feature which many birds are able to exploit in order to save energy in flight, but which is governed by complex surface-atmosphere interactions. In mosaic landscapes consisting of multiple land uses, the spatial distribution of thermal uplift is expected to be heterogenous and birds may use the landscape selectively to maximise flight over areas where thermal soaring opportunities are best. Flight generalists such as the lesser black-backed gull, Larus fuscus, are expected to be less reliant on thermal uplift than obligate soaring birds. Nevertheless, gulls may select flight behaviours and routes in response to or in anticipation of thermal uplift in order to reduce their transport costs, even in landscapes where thermal uplift isn't prevalent. We explore thermal soaring over land in lesser black-backed gulls by using high-resolution GPS tracking to characterise individual instances of thermal soaring and detailed energy exchange modelling to map the thermal landscape which gulls experience. We determine that lesser black-backed gulls are regularly able to undertake thermal soaring, even in a wet temperate landscape below sea level. By examining the relationship between lesser black-backed gull flight, thermal uplift and land use, we determine that built up areas, particularly towns and cities, provide thermal uplift hotspots which lesser black-backed gulls preferentially make use of, resulting in more opportunities for energy saving flight through thermal soaring.

Migratory Movements and Home Ranges of Geographically Distinct Wintering Populations of a Soaring Bird

Migratory soaring birds exhibit spatiotemporal variation in their circannual movements. Nevertheless, it remains uncertain how different winter environments affect the circannual movement patterns of migratory soaring birds. Here, we investigated annual movement strategies of American white pelicans Pelecanus erythrorhynchos (hereafter, pelican) from two geographically distinct wintering grounds in the Southern and Northern Gulf of Mexico (GOM). We hypothesized that hourly movement distance and home range size of a soaring bird would differ between different geographic regions because of different thermals and wind conditions and resource availability. We calculated average and maximum hourly movement distances and seasonal home ranges of GPS-tracking pelicans. We then evaluated the effects of hour of the day, seasons, two wintering regions in the Southern and Northern GOM, human footprint index, and relative pelican abundance from Christmas Bird Count data on pelican hourly movement distances and seasonal home ranges using linear mixed models and generalized linear mixed models. American white pelicans moved at greatest hourly distance near 1200 h at breeding grounds and during spring and autumn migrations. Both wintering populations in the Northern and Southern GOM exhibited similar hourly movement distances and seasonal home ranges at the shared breeding grounds and during spring and autumn migrations. However, pelicans wintering in the Southern GOM showed shorter hourly movement distances and smaller seasonal home ranges than those in the Northern GOM. Hourly movement distances and home ranges of pelicans increased with increasing human footprint index. Winter hourly movements and home ranges of pelicans differed between the Northern and Southern GOM; however, the winter difference in pelican movements did not carry over to the shared breeding grounds during summers. Therefore, exogenous factors may be the primary drivers to shape the flying patterns of migratory soaring birds.

Experience does not change the importance of wind support for migratory route selection by a soaring bird

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.

Opportunistic soaring by birds suggests new opportunities for atmospheric energy harvesting by flying robots

The use of flying robots (drones) is increasing rapidly, but their utility is limited by high power demand, low specific energy storage and poor gust tolerance. By contrast, birds demonstrate long endurance, harvesting atmospheric energy in environments ranging from cluttered cityscapes to open landscapes, coasts and oceans. Here, we identify new opportunities for flying robots, drawing upon the soaring flight of birds. We evaluate mechanical energy transfer in soaring from first principles and review soaring strategies encompassing the use of updrafts (thermal or orographic) and wind gradients (spatial or temporal). We examine the extent to which state-of-the-art flying robots currently use each strategy and identify several untapped opportunities including slope soaring over built environments, thermal soaring over oceans and opportunistic gust soaring. In principle, the energetic benefits of soaring are accessible to flying robots of all kinds, given atmospherically aware sensor systems, guidance strategies and gust tolerance. Hence, while there is clear scope for specialist robots that soar like albatrosses, or which use persistent thermals like vultures, the greatest untapped potential may lie in non-specialist vehicles that make flexible use of atmospheric energy through path planning and flight control, as demonstrated by generalist flyers such as gulls, kites and crows.

Estimating fine-scale changes in turbulence using the movements of a flapping flier

All animals that operate within the atmospheric boundary layer need to respond to aerial turbulence. Yet little is known about how flying animals do this because evaluating turbulence at fine scales (tens to approx. 300 m) is exceedingly difficult. Recently, data from animal-borne sensors have been used to assess wind and updraft strength, providing a new possibility for sensing the physical environment. We tested whether highly resolved changes in altitude and body acceleration measured onboard solo-flying pigeons (as model flapping fliers) can be used as qualitative proxies for turbulence. A range of pressure and acceleration proxies performed well when tested against independent turbulence measurements from a tri-axial anemometer mounted onboard an ultralight flying the same route, with stronger turbulence causing increasing vertical displacement. The best proxy for turbulence also varied with estimates of both convective velocity and wind shear. The approximately linear relationship between most proxies and turbulence levels suggests this approach should be widely applicable, providing insight into how turbulence changes in space and time. Furthermore, pigeons were able to fly in levels of turbulence that were unsafe for the ultralight, paving the way for the study of how freestream turbulence affects the costs and kinematics of animal flight.

Postcranial skeletal pneumaticity in non-aquatic neoavians: Insights from accipitrimorphae

Postcranial skeletal pneumaticity, air-filled bones of the trunk and limbs, is exclusive to birds among extant tetrapods and exhibits significant variation in its expression among different species. Such variation is not random but exhibits relationships with both body mass and locomotor specializations. Most species-level comparative research to date has focused on aquatic-oriented taxa (e.g., Anseriformes). The lack of data from non-aquatic birds constrains our ability to characterize global (i.e., avian-wide) patterns of this trait complex. To address this gap, the study conducted herein quantified postcranial pneumaticity in Accipitrimorphae, a mostly terrestrial clade composed of species that span a range of body sizes and exhibit diverse flight/foraging behaviors. All examined species (n = 88) invariably pneumatized the postaxial through pre-caudal vertebrae, sternum, coracoid, humerus, vertebral and sternal ribs, and pelvic girdle, a pattern herein referred to as the accipitrimorph baseline. Of the 88 sampled species, 41 expanded upon this pattern, whereas 10 species exhibited a reduction. No species deviated from the accipitrimorph baseline by more than two anatomical regions. A phylogenetically-informed regression analysis failed to identify a significant relationship between body mass and pneumaticity. However, specific pneumaticity phenotypes deviating from the baseline were correlated with aspects of wing morphology, tail length, and home range size. Results from this and previous studies provide clarity on two hypotheses: (1) aquatic taxa display distinct pneumaticity expression patterns relative to non-aquatic birds, notably with reductions in the proportion of the skeleton filled with air in diving specialists and (2) contemporary comparative studies, including the one herein, that explicitly account for phylogenetic relationships consistently fail to support the oft-cited positive relationship between pneumaticity and body mass. Instead, historical relationships and functional/ecological attributes (e.g., diving, specialized flight behaviors) appear to be the primary drivers underlying patterns of variation in this trait complex.

Highlighting when animals expend excessive energy for travel using Dynamic Body Acceleration

Travel represents a major cost for many animals so there should be selection pressure for it to be efficient – at minimum cost. However, animals sometimes exceed minimum travel costs for reasons that must be correspondingly important. We use Dynamic Body Acceleration (DBA), an acceleration-based metric, as a proxy for movement-based power, in tandem with vertical velocity (rate of change in depth) in a shark (Rhincodon typus) to derive the minimum estimated power required to swim at defined vertical velocities. We show how subtraction of measured DBA from the estimated minimum power for any given vertical velocity provides a “proxy for power above minimum” metric (PPA_min), highlighting when these animals travel above minimum power. We suggest that the adoption of this metric across species has value in identifying where and when animals are subject to compelling conditions that lead them to deviate from ostensibly judicious energy expenditure.

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Plots of vertical speed vs DBA in sharks show swimming with minimum power

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DBA values above this minimum indicate higher speeds or increases in drag

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Linked to space use, this can identify regions and times of excess power use

How Reproducibility Will Accelerate Discovery Through Collaboration in Physio-Logging

What new questions could ecophysiologists answer if physio-logging research was fully reproducible? We argue that technical debt (computational hurdles resulting from prioritizing short-term goals over long-term sustainability) stemming from insufficient cyberinfrastructure (field-wide tools, standards, and norms for analyzing and sharing data) trapped physio-logging in a scientific silo. This debt stifles comparative biological analyses and impedes interdisciplinary research. Although physio-loggers (e.g., heart rate monitors and accelerometers) opened new avenues of research, the explosion of complex datasets exceeded ecophysiology’s informatics capacity. Like many other scientific fields facing a deluge of complex data, ecophysiologists now struggle to share their data and tools. Adapting to this new era requires a change in mindset, from “data as a noun” (e.g., traits, counts) to “data as a sentence”, where measurements (nouns) are associate with transformations (verbs), parameters (adverbs), and metadata (adjectives). Computational reproducibility provides a framework for capturing the entire sentence. Though usually framed in terms of scientific integrity, reproducibility offers immediate benefits by promoting collaboration between individuals, groups, and entire fields. Rather than a tax on our productivity that benefits some nebulous greater good, reproducibility can accelerate the pace of discovery by removing obstacles and inviting a greater diversity of perspectives to advance science and society. In this article, we 1) describe the computational challenges facing physio-logging scientists and connect them to the concepts of technical debt and cyberinfrastructure, 2) demonstrate how other scientific fields overcame similar challenges by embracing computational reproducibility, and 3) present a framework to promote computational reproducibility in physio-logging, and bio-logging more generally.

Energy economy in flight

Emily Shepard introduces ways flying animals conserve energy inflight.

How did extinct giant birds and pterosaurs fly? A comprehensive modeling approach to evaluate soaring performance

The largest extinct volant birds (Pelagornis sandersi and Argentavis magnificens) and pterosaurs (Pteranodon and Quetzalcoatlus) are thought to have used wind-dependent soaring flight, similar to modern large birds. There are 2 types of soaring: thermal soaring, used by condors and frigatebirds, which involves the use of updrafts to ascend and then glide horizontally; and dynamic soaring, used by albatrosses, which involves the use of wind speed differences with height above the sea surface. Previous studies have suggested that P. sandersi used dynamic soaring, while A. magnificens and Quetzalcoatlus used thermal soaring. For Pteranodon, there is debate over whether they used dynamic or thermal soaring. However, the performance and wind speed requirements of dynamic and thermal soaring for these species have not yet been quantified comprehensively. We quantified these values using aerodynamic models and compared them with that of extant birds. For dynamic soaring, we quantified maximum travel speeds and maximum upwind speeds. For thermal soaring, we quantified the animal's sinking speed circling at a given radius and how far it could glide losing a given height. Our results confirmed those from previous studies that A. magnificens and Pteranodon used thermal soaring. Conversely, the results for P. sandersi and Quetzalcoatlus were contrary to those from previous studies. P. sandersi used thermal soaring, and Quetzalcoatlus had a poor ability both in dynamic and thermal soaring. Our results demonstrate the need for comprehensive assessments of performance and required wind conditions when estimating soaring styles of extinct flying species.

Possible link between brain size and flight mode in birds: Does soaring ease the energetic limitation of the brain?

Elucidating determinants of interspecies variation in brain size has been a long-standing challenge in cognitive and evolutionary ecology. As the brain is an energetically expensive organ, energetic tradeoffs among organs are considered to play a key role in brain size evolution. This study examined the tradeoff between the brain and locomotion in birds by testing the relationship between brain size, flight modes with different energetic costs (flapping and soaring), and migratory behavior, using published data on the whole-brain mass of 2242 species. According to comparative analyses considering phylogeny and body mass, soarers, who can gain kinetic energy from wind shear or thermals and consequently save flight costs, have larger brains than flappers among migratory birds. Meanwhile, the brain size difference was not consistent in residents, and the size variation appeared much larger than that in migrants. In addition, the brain size of migratory birds was smaller than that of resident birds among flappers, whereas this property was not significant in soarers. Although further research is needed to draw a definitive conclusion, these findings provide further support for the energetic tradeoff of the brain with flight and migratory movements in birds and advance the idea that a locomotion mode with lower energetic cost could be a driver of encephalization during the evolution of the brain.

Big-data approaches lead to an increased understanding of the ecology of animal movement

Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal "movement ecology" (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.

Control of leading-edge separation on bioinspired airfoil with fluttering coverts

In this work, the aerodynamic role of the artificial covert feathers (i.e., coverts) on an airfoil is experimentally studied in a wind tunnel to investigate the flow control effect on the leading-edge separation. We apply flexible featherlike devices on a high-angle-of-attack airfoil. We use a hot-wire anemometer to measure the velocity profiles and turbulent fluctuations in the downstream wake flow. As a baseline of flow separation, a two-dimensional NACA 0018 airfoil model is set at the angle of attack of 15 ° at the chord-based Reynolds number of 1.0×10^{5}, causing strong leading-edge and trailing-edge shear layers and a low-speed wake flow area in between as large as 0.35 chord length. When deployed on the upper wing surface, the flexible coverts adaptively flutter under the influence of the local unsteady airflow. Hot-wire measurement results show that the leading-edge coverts effectively suppress the flow separation and reduce the size of the wake flow area. The change of power spectral density shows that the predominant peaks as the fundamental and harmonic frequencies are both attenuated due to the suppression of unsteady motions of the shear layers. On the other hand, the fluttering coverts at the trailing edge modify the trailing-edge shear layer by redistributing the turbulent kinetic energy to the high-frequency components. By simultaneous double-point measurement, we find that the leading-edge and trailing-edge shear layers are drawn closer to each other, and the two shear layers show an increased peak in the coherence spectrum. Further multiscale wavelet analysis shows that the perturbations at the 60% chord length increase the large-scale amplitude modulation of small-scale turbulence and therefore they stabilize the leading-edge and trailing-edge shear layers. Meanwhile, the flow intermittency outside of the wake flow area is attenuated as well. The effective flow control effects in the present work are in good agreement with the previous direct observations of bird flight in literature that the coverts on the upper wing surface play an important role in flow separation control during high-angle-of-attack flight. These findings advance the understanding of aerodynamic contribution of the covers on bird wings and reveal the engineering potential of bioinspired coverts for flow separation control of aircrafts and unmanned air vehicles.

How often should dead-reckoned animal movement paths be corrected for drift?

BACKGROUND

Understanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System, 'GPS') is typically used to verify an animal's location periodically. Straight lines are typically drawn between these 'Verified Positions' ('VPs') so the interpolation of space-use is limited by the temporal and spatial resolution of the system's measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear.

METHODS AND RESULTS

Here, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy.

CONCLUSIONS

We review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal-barrier interactions and foraging strategies.

Mitogenomic analysis of extant condor species provides insight into the molecular evolution of vultures

The evolution of large vultures linked to mountainous habitats was accompanied by extreme physiological and behavioral specializations for energetically efficient flights. However, little is known on the genetic traits associated with the evolution of these obligate soaring scavengers. Mitochondrial DNA plays a vital role in regulating oxidative stress and energy production, and hence may be an important target of selection for flight performance. Herein, we characterized the first mitogenomes of the Andean and California condors, the world's heaviest flying birds and the only living representatives of the Vultur and Gymnogyps genus. We reconstructed the phylogenetic relationships and evaluated possible footprints of convergent evolution associated to the life-history traits and distributional range of vultures. Our phylogenomic analyses supported the independent evolution of vultures, with the origin of Cathartidae in the early Paleogene (~ 61 Mya), and estimated the radiation of extant condors during the late Miocene (~ 11 Mya). Selection analyses indicated that vultures exhibit signals of relaxation of purifying selection relative to other accipitrimorph raptors, possibly indicating the degeneration of flapping flight ability. Overall, our results suggest that the extreme specialization of vultures for efficient soaring flight has compensated the evolution of large body sizes mitigating the selection pressure on mtDNA.

Animal tag technology keeps coming of age: an engineering perspective

Animal-borne tags (biologgers) have now become extremely sophisticated, recording data from multiple sensors at high frequencies for long periods and, as such, have become a powerful tool for behavioural ecologists and physiologists studying wild animals. But the design and implementation of these tags is not trivial because engineers have to maximize performance and ability to function under onerous conditions while minimizing tag mass and volume (footprint) to maximize the wellbeing of the animal carriers. We present some of the major issues faced by tag engineers and show how tag designers must accept compromises while maintaining systems that can answer the questions being posed. We also argue that basic understanding of engineering issues in tag design by biologists will help feedback to engineers to better tag construction but also reduce the likelihood that tag-deploying biologists will misunderstand their own results. Finally, we suggest that proper consideration of conventional technology together with new approaches will lead to further step changes in our understanding of wild-animal biology using smart tags. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.

What is physiologging? Introduction to the theme issue, part 2

The physiological mechanisms by which animals regulate energy expenditure, respond to stimuli and stressors, and maintain homeostasis at the tissue, organ and whole organism levels can be described by 'physiologging'-that is, the use of onboard miniature electronic devices to record physiological metrics of animals in captivity or free-living in the wild. Despite its origins in the 1960s, physiologging has evolved more slowly than its umbrella field of biologging. However, the recording of physiological metrics in free-living animals will be key to solving some of the greatest challenges in biodiversity conservation, issues pertaining to animal health and welfare, and for inspiring future therapeutic strategies for human health. Current physiologging technologies encompass the measurement of physiological variables such as heart rate, brain activity, body temperature, muscle stimulation and dynamic movement, yet future developments will allow for onboard logging of metrics relating to organelle, molecular and genetic function. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.

Certainty and integration of options in animal movement

Physical energy defines the energy landscape and determines the species-specific cost of movement, thus influencing movement decisions. In unpredictable and dynamic environments, observing the locomotion of others increases individual certainty in the distribution of physical energy to increase movement efficiency. Beyond the physical energy landscape, social sampling increases certainty in all ecological landscapes that influence animal movement (including fear and resource landscapes), and individuals use energy to express each of these. We call for the development of an 'optimal movement theory' (OMT) that integrates the multidimensional reality of movement decisions by combining ecological landscapes according to a single expectation of energy cost-benefit, where social sampling provides up-to-date information under uncertain conditions. This mechanistic framework has implications for predicting individual movement patterns and for investigating the emergence of aggregations.

The evolution of darker wings in seabirds in relation to temperature-dependent flight efficiency

Seabirds have evolved numerous adaptations that allow them to thrive under hostile conditions. Many seabirds share similar colour patterns, often with dark wings, suggesting that their coloration might be adaptive. Interestingly, these darker wings become hotter when birds fly under high solar irradiance, and previous studies on aerofoils have provided evidence that aerofoil surface heating can affect the ratio between lift and drag, i.e. flight efficiency. However, whether this effect benefits birds remains unknown. Here, we first used phylogenetic analyses to show that strictly oceanic seabirds with a higher glide performance (optimized by reduced sink rates, i.e. the altitude lost over time) have evolved darker wings, potentially as an additional adaptation to improve flight. Using wind tunnel experiments, we then showed that radiative heating of bird wings indeed improves their flight efficiency. These results illustrate that seabirds may have evolved wing pigmentation in part through selection for flight performance under extreme ocean conditions. We suggest that other bird clades, particularly long-distance migrants, might also benefit from this effect and therefore might show similar evolutionary trajectories. These findings may also serve as a guide for bioinspired innovations in aerospace and aviation, especially in low-speed regimes.

A revision of vulture feeding classification

Pioneering fieldwork identified the existence of three feeding groups in vultures: gulpers, rippers and scrappers. Gulpers engulf soft tissue from carcasses and rippers tear off pieces of tough tissue (skin, tendons, muscle), whereas scrappers peck on small pieces of meat they find on and around carcasses. It has been shown that these feeding preferences are reflected in the anatomy of the skull and neck. Here, we demonstrate that these three feeding groups also emerge when body core and limb bones are added to the analysis. However, the resulting classification differs from that which is based on skull morphology for three species, namely Gypaetus barbatus (Linnaeus, 1758), Gypohierax angolensis (Gmelin, 1788) and Gyps indicus (Scopoli, 1786). The proposed classification would improve the interrelationship between form and feeding habits in vultures. Moreover, the results of this study reinforce the value of the categorisation system introduced by Kruuk (1967), and expanded by König (1974, 1983), Houston (1988) and Hertel (1994), as it would affect not only the skull morphology but the whole-body architecture.