The EDGE2 protocol: Advancing the prioritisation of Evolutionarily Distinct and Globally Endangered species for practical conservation action.

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.

Accelerometer-based detection of African swine fever infection in wild boar.

Infectious wildlife diseases that circulate at the interface with domestic animals pose significant threats worldwide and require early detection and warning. Although animal tracking technologies are used to discern behavioural changes, they are rarely used to monitor wildlife diseases. Common disease-induced behavioural changes include reduced activity and lethargy ('sickness behaviour'). Here, we investigated whether accelerometer sensors could detect the onset of African swine fever (ASF), a viral infection that induces high mortality in suids for which no vaccine is currently available. Taking advantage of an experiment designed to test an oral ASF vaccine, we equipped 12 wild boars with an accelerometer tag and quantified how ASF affects their activity pattern and behavioural fingerprint, using overall dynamic body acceleration. Wild boars showed a daily reduction in activity of 10-20% from the healthy to the viremia phase. Using change point statistics and comparing healthy individuals living in semi-free and free-ranging conditions, we show how the onset of disease-induced sickness can be detected and how such early detection could work in natural settings. Timely detection of infection in animals is crucial for disease surveillance and control, and accelerometer technology on sentinel animals provides a viable complementary tool to existing disease management approaches.

The interplay of wind and uplift facilitates over-water flight in facultative soaring birds.

Flying over the open sea is energetically costly for terrestrial birds. Despite this, over-water journeys of many birds, sometimes hundreds of kilometres long, are uncovered by bio-logging technology. To understand how these birds afford their flights over the open sea, we investigated the role of atmospheric conditions, specifically wind and uplift, in subsidizing over-water flight at a global scale. We first established that ΔT, the temperature difference between sea surface and air, is a meaningful proxy for uplift over water. Using this proxy, we showed that the spatio-temporal patterns of sea-crossing in terrestrial migratory birds are associated with favourable uplift conditions. We then analysed route selection over the open sea for five facultative soaring species, representative of all major migratory flyways. The birds maximized wind support when selecting their sea-crossing routes and selected greater uplift when suitable wind support was available. They also preferred routes with low long-term uncertainty in wind conditions. Our findings suggest that, in addition to wind, uplift may play a key role in the energy seascape for bird migration that in turn determines strategies and associated costs for birds crossing ecological barriers such as the open sea.

Comparative analyses of evolutionary rates reveal different pathways to encephalization in bats, carnivorans, and primates.

Variation in relative brain size is commonly interpreted as the result of selection on neuronal capacity. However, this approach ignores that relative brain size is also linked to another highly adaptive variable: body size. Considering that one-way tradeoff mechanisms are unlikely to provide satisfactory evolutionary explanations, we introduce an analytical framework that describes and quantifies all possible evolutionary scenarios between two traits. To investigate the effects of body mass changes on the interpretation of relative brain size evolution, we analyze three mammalian orders that are expected to be subject to different selective pressures on body size due to differences in locomotor adaptation: bats (powered flight), primates (primarily arboreal), and carnivorans (primarily terrestrial). We quantify rates of brain and body mass changes along individual branches of phylogenetic trees using an adaptive peak model of evolution. We find that the magnitude and variance of the level of integration of brain and body mass rates, and the subsequent relative influence of either brain or body size evolution on the brain-body relationship, differ significantly between orders and subgroups within orders. Importantly, we find that variation in brain-body relationships was driven primarily by variability in body mass. Our approach allows a more detailed interpretation of correlated trait evolution and variation in the underlying evolutionary pathways. Results demonstrate that a principal focus on interpreting relative brain size evolution as selection on neuronal capacity confounds the effects of body mass changes, thereby hiding important aspects that may contribute to explaining animal diversity.

Developmental stage shapes the realized energy landscape for a flight specialist.

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.

Beyond the horizon: immersive developments for animal ecology research.

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.

Effect of harness design for tag attachment on the flight performance of five soaring species.

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[Formula: see text] 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.

Seabird morphology determines operational wind speeds, tolerable maxima, and responses to extremes.

Storms can cause widespread seabird stranding and wrecking,1,2,3,4,5 yet little is known about the maximum wind speeds that birds are able to tolerate or the conditions they avoid. We analyzed >300,000 h of tracking data from 18 seabird species, including flapping and soaring fliers, to assess how flight morphology affects wind selectivity, both at fine scales (hourly movement steps) and across the breeding season. We found no general preference or avoidance of particular wind speeds within foraging tracks. This suggests seabird flight morphology is adapted to a "wind niche," with higher wing loading being selected in windier environments. In support of this, wing loading was positively related to the median wind speeds on the breeding grounds, as well as the maximum wind speeds in which birds flew. Yet globally, the highest wind speeds occur in the tropics (in association with tropical cyclones) where birds are morphologically adapted to low median wind speeds. Tropical species must therefore show behavioral responses to extreme winds, including long-range avoidance of wind speeds that can be twice their operable maxima. By contrast, Procellariiformes flew in almost all wind speeds they encountered at a seasonal scale. Despite this, we describe a small number of cases where albatrosses avoided strong winds at close range, including by flying into the eye of the storm. Extreme winds appear to pose context-dependent risks to seabirds, and more information is needed on the factors that determine the hierarchy of risk, given the impact of global change on storm intensity.6,7.

A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement.

1. The recently developed Brownian bridge movement model (BBMM) has advantages over traditional methods because it quantifies the utilization distribution of an animal based on its movement path rather than individual points and accounts for temporal autocorrelation and high data volumes. However, the BBMM assumes unrealistic homogeneous movement behaviour across all data. 2. Accurate quantification of the utilization distribution is important for identifying the way animals use the landscape. 3. We improve the BBMM by allowing for changes in behaviour, using likelihood statistics to determine change points along the animal's movement path. 4. This novel extension, outperforms the current BBMM as indicated by simulations and examples of a territorial mammal and a migratory bird. The unique ability of our model to work with tracks that are not sampled regularly is especially important for GPS tags that have frequent failed fixes or dynamic sampling schedules. Moreover, our model extension provides a useful one-dimensional measure of behavioural change along animal tracks. 5. This new method provides a more accurate utilization distribution that better describes the space use of realistic, behaviourally heterogeneous tracks.

Hunting and persecution drive mammal declines in Iran.

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.

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.

Home range size and habitat quality affect breeding success but not parental investment in barn owl males.

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.

MoveApps: a serverless no-code analysis platform for animal tracking data.

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.

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.

Behaviour-specific habitat selection patterns of breeding barn owls.

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.

Simulation experiment to test strategies of geomagnetic navigation during long-distance bird migration.

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.

Bats use topography and nocturnal updrafts to fly high and fast.

During the day, flying animals exploit the environmental energy landscape by seeking out thermal or orographic uplift, or extracting energy from wind gradients.1-6 However, most of these energy sources are not thought to be available at night because of the lower thermal potential in the nocturnal atmosphere, as well as the difficulty of locating features that generate uplift. Despite this, several bat species have been observed hundreds to thousands of meters above the ground.7-9 Individuals make repeated, energetically costly high-altitude ascents,10-13 and others fly at some of the fastest speeds observed for powered vertebrate flight.14 We hypothesized that bats use orographic uplift to reach high altitudes,9,15-17 and that both this uplift and bat high-altitude ascents would be highly predictable.18 By superimposing detailed three-dimensional GPS tracking of European free-tailed bats (Tadarida teniotis) on high-resolution regional wind data, we show that bats do indeed use the energy of orographic uplift to climb to over 1,600 m, and also that they reach maximum sustained self-powered airspeeds of 135 km h-1. We show that wind and topography can predict areas of the landscape able to support high-altitude ascents, and that bats use these locations to reach high altitudes while reducing airspeeds. Bats then integrate wind conditions to guide high-altitude ascents, deftly exploiting vertical wind energy in the nocturnal landscape.

Classifying biogeographic realms of the endemic fauna in the Afro-Arabian region.

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.

Author Correction: Arctic avian predators synchronise their spring migration with the northern progression of snowmelt.

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

Arctic avian predators synchronise their spring migration with the northern progression of snowmelt.

Migratory species display a range of migration patterns between irruptive (facultative) to regular (obligate), as a response to different predictability of resources. In the Arctic, snow directly influences resource availability. The causes and consequences of different migration patterns of migratory species as a response to the snow conditions remains however unexplored. Birds migrating to the Arctic are expected to follow the spring snowmelt to optimise their arrival time and select for snow-free areas to maximise prey encounter en-route. Based on large-scale movement data, we compared the migration patterns of three top predator species of the tundra in relation to the spatio-temporal dynamics of snow cover. The snowy owl, an irruptive migrant, the rough-legged buzzard, with an intermediary migration pattern, and the peregrine falcon as a regular migrant, all followed, as expected, the spring snowmelt during their migrations. However, the owl stayed ahead, the buzzard stayed on, and the falcon stayed behind the spatio-temporal peak in snowmelt. Although none of the species avoided snow-covered areas, they presumably used snow presence as a cue to time their arrival at their breeding grounds. We show the importance of environmental cues for species with different migration patterns.