New frontiers in bird migration research.

Bird migrations are impressive behavioral phenomena, representing complex spatiotemporal strategies to balance costs of living while maximizing fitness. The field of bird migration research has made great strides over the past decades, yet fundamental gaps remain. Technologies have sparked a transformation in the study of bird migration research by revealing remarkable insights into the underlying behavioral, cognitive, physiological and evolutionary mechanisms of these diverse journeys. Here, we aim to encourage broad discussions and promote future studies by highlighting research fields that are characterized by major knowledge gaps or conflicting evidence, namely the fields of navigation, social learning, individual development, energetics and conservation. We approach each topic by summarizing the current state of knowledge and provide a future outlook of ideas and state-of-the-art methods to further advance the field. Integrating knowledge across these disciplines will allow us to understand the adaptive abilities of different species and to develop effective conservation strategies in a rapidly changing world.

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analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills.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.

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.

Longer days enable higher diurnal activity for migratory birds.

Seasonal geophysical cycles strongly influence the activity of life on Earth because they affect environmental conditions like temperature, precipitation and day length. An increase in daylight availability during summer is especially enhanced when animals migrate along a latitudinal gradient. Yet, the question of how day length (i.e. daylight availability) influences the activity patterns of long-distance, latitudinal migrants is still unclear. Here, we ask whether migration provides benefits to long-distance migrants by enabling them to increase their diurnal movement activities due to an increase in daylight availability. To answer this question, we tested whether four vastly different species of long-distance migratory birds-two arctic migrants and two mid-latitude migrants-can capitalise on day length changes by adjusting their daily activity. We quantified the relationship between daily activity (measured using accelerometer data) and day length, and estimated each species' daily activity patterns. In addition, we evaluated the role of day length as an ultimate driver of bird migration. All four species exhibited longer activity periods during days with more daylight hours, showing a strong positive relationship between total daily activity and day length. The slope of this relationship varied between the different species, with activity increasing 1.5-fold on average when migrating from wintering to breeding grounds. Underlying mechanisms of these relationships reveal two distinct patterns of daily activity. Flying foragers showed increasing activity patterns, that is, their daytime activities rose uniformly up to solar noon and decreased until dusk, thereby exhibiting a season-specific activity slope. In contrast, ground foragers showed a constant activity pattern, whereby they immediately increased their activity to a certain level and maintained this level throughout the day. Our study reveals that long days allow birds to prolong their activity and increase their total daily activity. These findings highlight that daylight availability could be an additional ultimate cause of bird migration and act as a selective agent for the evolution of migration.

Los ciclos geofísicos estacionales influyen fuertemente la actividad de la vida en la Tierra ya que afectan diversas condiciones ambientales como la temperatura, la precipitación y la duración del día. El aumento de la disponibilidad de luz solar durante el verano favorece especialmente a las especies que migran a lo largo de un gradiente latitudinal. Sin embargo, el efecto de la duración del día (es decir, la disponibilidad de luz solar) en los patrones de actividad de las especies que migran latitudinalmente largas distancias, aún no es claro. Aquí nos preguntamos si un aumento de la disponibilidad de luz solar representa un beneficio para los animales que migran largas distancias, al prolongar el periodo de actividad diurna. Para responder a esta pregunta, investigamos si cuatro especies diferentes de aves migratorias de larga distancia, dos migrantes árticos y dos migrantes de latitudes medias, pueden ajustar su actividad diaria y aprovechar los cambios en la duración del día. Cuantificamos la relación entre la actividad diaria (medida con datos de acelerómetro) y la duración del día, y estimamos los patrones de actividad de cada especie. Además, evaluamos el papel de la duración del día como mecanismo último subyacente a la migración de las aves. Las cuatro especies mostraron períodos de actividad más largos durante los días con más horas de luz, mostrando una fuerte relación positiva entre la actividad diaria total y la duración del día. Esta relación varió entre las especies evaluadas. La actividad aumentó en promedio 1.5 veces durante la migración desde las áreas de invernada a las áreas de reproducción. Los mecanismos subyacentes a estas relaciones revelan dos patrones de actividad diaria. Las especies que forrajean en vuelo mostraron un aumento en su patrón de actividad. En este caso, la actividad diurna aumentó uniformemente hasta el mediodía y disminuyó hasta el atardecer, mostrando una pendiente de actividad específica para la estación. De otro lado, las especies que forrajean en tierra mostraron un patrón de actividad constante. Según este patrón, la actividad diurna aumenta hasta un determinado nivel, a partir del cual se mantiene durante el resto del día. Nuestro estudio revela que el aumento en la longitud del día le permite a las aves prolongar su actividad e incrementar su actividad diaria total. Estos resultados señalan que la disponibilidad de luz diurna podría ser otro mecanismo último subyacente a la migración de las aves y puede actuar como un factor de selección en la evolución de la migración.

Author Correction: Stochastic simulations reveal few green wave surfing populations among spring migrating herbivorous waterfowl.

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

Stochastic simulations reveal few green wave surfing populations among spring migrating herbivorous waterfowl.

Tracking seasonally changing resources is regarded as a widespread proximate mechanism underpinning animal migration. Migrating herbivores, for example, are hypothesized to track seasonal foliage dynamics over large spatial scales. Previous investigations of this green wave hypothesis involved few species and limited geographical extent, and used conventional correlation that cannot disentangle alternative correlated effects. Here, we introduce stochastic simulations to test this hypothesis using 222 individual spring migration episodes of 14 populations of ten species of geese, swans and dabbling ducks throughout Europe, East Asia, and North America. We find that the green wave cannot be considered a ubiquitous driver of herbivorous waterfowl spring migration, as it explains observed migration patterns of only a few grazing populations in specific regions. We suggest that ecological barriers and particularly human disturbance likely constrain the capacity of herbivorous waterfowl to track the green wave in some regions, highlighting key challenges in conserving migratory birds.

A periodic Markov model to formalize animal migration on a network.

Regular, long-distance migrations of thousands of animal species have consequences for the ecosystems that they visit, modifying trophic interactions and transporting many non-pathogenic and pathogenic organisms. The spatial structure and dynamic properties of animal migrations and population flyways largely determine those trophic and transport effects, but are yet poorly studied. As a basis, we propose a periodic Markov model on the spatial migration network of breeding, stopover and wintering sites to formally describe the process of animal migration on the population level. From seasonally changing transition rates we derived stable, seasonal densities of animals at the network nodes. We parametrized the model with high-quality GPS and satellite telemetry tracks of white storks (Ciconia ciconia) and greater white-fronted geese (Anser a. albifrons). Topological and network flow properties of the two derived networks conform to migration properties like seasonally changing connectivity and shared, directed movement. Thus, the model realistically describes the migration movement of complete populations and can become an important tool to study the effects of climate and habitat change and pathogen spread on migratory animals. Furthermore, the property of periodically changing transition rates makes it a new type of complex model and we need to understand its dynamic properties.

Signatures of chaos in animal search patterns.

One key objective of the emerging discipline of movement ecology is to link animal movement patterns to underlying biological processes, including those operating at the neurobiological level. Nonetheless, little is known about the physiological basis of animal movement patterns, and the underlying search behaviour. Here we demonstrate the hallmarks of chaotic dynamics in the movement patterns of mud snails (Hydrobia ulvae) moving in controlled experimental conditions, observed in the temporal dynamics of turning behaviour. Chaotic temporal dynamics are known to occur in pacemaker neurons in molluscs, but there have been no studies reporting on whether chaotic properties are manifest in the movement patterns of molluscs. Our results suggest that complex search patterns, like the Lévy walks made by mud snails, can have their mechanistic origins in chaotic neuronal processes. This possibility calls for new research on the coupling between neurobiology and motor properties.

Deriving Animal Behaviour from High-Frequency GPS: Tracking Cows in Open and Forested Habitat.

The increasing spatiotemporal accuracy of Global Navigation Satellite Systems (GNSS) tracking systems opens the possibility to infer animal behaviour from tracking data. We studied the relationship between high-frequency GNSS data and behaviour, aimed at developing an easily interpretable classification method to infer behaviour from location data. Behavioural observations were carried out during tracking of cows (Bos Taurus) fitted with high-frequency GPS (Global Positioning System) receivers. Data were obtained in an open field and forested area, and movement metrics were calculated for 1 min, 12 s and 2 s intervals. We observed four behaviour types (Foraging, Lying, Standing and Walking). We subsequently used Classification and Regression Trees to classify the simultaneously obtained GPS data as these behaviour types, based on distances and turning angles between fixes. GPS data with a 1 min interval from the open field was classified correctly for more than 70% of the samples. Data from the 12 s and 2 s interval could not be classified successfully, emphasizing that the interval should be long enough for the behaviour to be defined by its characteristic movement metrics. Data obtained in the forested area were classified with a lower accuracy (57%) than the data from the open field, due to a larger positional error of GPS locations and differences in behavioural performance influenced by the habitat type. This demonstrates the importance of understanding the relationship between behaviour and movement metrics, derived from GNSS fixes at different frequencies and in different habitats, in order to successfully infer behaviour. When spatially accurate location data can be obtained, behaviour can be inferred from high-frequency GNSS fixes by calculating simple movement metrics and using easily interpretable decision trees. This allows for the combined study of animal behaviour and habitat use based on location data, and might make it possible to detect deviations in behaviour at the individual level.

Experimental evidence for inherent Lévy search behaviour in foraging animals.

Recently, Lévy walks have been put forward as a new paradigm for animal search and many cases have been made for its presence in nature. However, it remains debated whether Lévy walks are an inherent behavioural strategy or emerge from the animal reacting to its habitat. Here, we demonstrate signatures of Lévy behaviour in the search movement of mud snails (Hydrobia ulvae) based on a novel, direct assessment of movement properties in an experimental set-up using different food distributions. Our experimental data uncovered clusters of small movement steps alternating with long moves independent of food encounter and landscape complexity. Moreover, size distributions of these clusters followed truncated power laws. These two findings are characteristic signatures of mechanisms underlying inherent Lévy-like movement. Thus, our study provides clear experimental evidence that such multi-scale movement is an inherent behaviour rather than resulting from the animal interacting with its environment.

Forecasting spring from afar? Timing of migration and predictability of phenology along different migration routes of an avian herbivore.

Herbivorous birds are hypothesized to migrate in spring along a seasonal gradient of plant profitability towards their breeding grounds (green wave hypothesis). For Arctic breeding species in particular, following highly profitable food is important, so that they can replenish resources along the way and arrive in optimal body condition to start breeding early. We compared the timing of migratory movements of Arctic breeding geese on different flyways to examine whether flyways differed in the predictability of spring conditions at stopovers and whether this was reflected in the degree to which birds were following the green wave. Barnacle geese (Branta leucopsis) were tracked with solar GPS/ARGOS PTTs from their wintering grounds to breeding sites in Greenland (N = 7), Svalbard (N = 21) and the Barents Sea (N = 12). The numerous stopover sites of all birds were combined into a set of 16 general stopover regions. The predictability of climatic conditions along the flyways was calculated as the correlation and slope between onsets of spring at consecutive stopovers. These values differed between sites, mainly because of the presence or absence of ecological barriers. Goose arrival at stopovers was more closely tied to the local onset of spring when predictability was higher and when geese attempted breeding that year. All birds arrived at early stopovers after the onset of spring and arrived at the breeding grounds before the onset of spring, thus overtaking the green wave. This is in accordance with patterns expected for capital breeders: first, they must come into condition; at intermediate stopovers, arrival with the food quality peak is important to stay in condition, and at the breeding grounds, early arrival is favoured so that hatching of young can coincide with the peak of food quality. Our results suggest that a chain of correlations between climatic conditions at subsequent stopovers enables geese to closely track the green wave. However, the birds' precision of migratory timing seems uninfluenced by ecological barriers, indicating partly fixed migration schedules. These might become non-optimal due to climate warming and preclude accurate timing of long-distance migrants in the future.

Migratory herbivorous waterfowl track satellite-derived green wave index.

Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI) time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI), has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7). Data were collected over three years (2008-2010). Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%), while the Greenland geese followed an earlier stage (GWI 20-40%). Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration), thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

How superdiffusion gets arrested: ecological encounters explain shift from Lévy to Brownian movement.

Ecological theory uses Brownian motion as a default template for describing ecological movement, despite limited mechanistic underpinning. The generality of Brownian motion has recently been challenged by empirical studies that highlight alternative movement patterns of animals, especially when foraging in resource-poor environments. Yet, empirical studies reveal animals moving in a Brownian fashion when resources are abundant. We demonstrate that Einstein's original theory of collision-induced Brownian motion in physics provides a parsimonious, mechanistic explanation for these observations. Here, Brownian motion results from frequent encounters between organisms in dense environments. In density-controlled experiments, movement patterns of mussels shifted from Lévy towards Brownian motion with increasing density. When the analysis was restricted to moves not truncated by encounters, this shift did not occur. Using a theoretical argument, we explain that any movement pattern approximates Brownian motion at high-resource densities, provided that movement is interrupted upon encounters. Hence, the observed shift to Brownian motion does not indicate a density-dependent change in movement strategy but rather results from frequent collisions. Our results emphasize the need for a more mechanistic use of Brownian motion in ecology, highlighting that especially in rich environments, Brownian motion emerges from ecological interactions, rather than being a default movement pattern.

The complex network of global cargo ship movements.

Transportation networks play a crucial role in human mobility, the exchange of goods and the spread of invasive species. With 90 per cent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 16 363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features that set it apart from other transportation networks. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analysed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.

Population fluctuations and regulation in great snipe: a time-series analysis.

1. During the last centuries, the breeding range of the great snipe Gallinago media has declined dramatically in the western part of its distribution. To examine present population dynamics in the Scandinavian mountains, we collected and analysed a 19-year time series of counts of great snipe males at leks in central Norway, 1987-2005. 2. The population showed large annual fluctuations in the number of males displaying at lek sites (range 45-90 males at the peak of the mating season), but no overall trend. 3. We detected presence of direct density-dependent mechanisms regulating this population. Inclusion of the density-dependent term in a Ricker-type model significantly improved the fit with observed data (evaluated with Parametric Bootstrap Likelihood Ratio tests and Akaike's Information Criterion for small sample size). 4. An analysis of (a number of a priori likely) environmental covariates suggests that the population dynamics were affected by conditions influencing reproduction and survival of offspring during the summer, but not by conditions influencing survival at the wintering grounds in Africa. This is in contrast to many altricial birds breeding in the northern hemisphere, and supports the idea that population dynamics of migratory nidifugous birds are more influenced by conditions during reproduction. 5. Inclusion of these external factors into our model improved the detectability of density dependence. This illustrates that allowing for external effects may increase statistical power of density dependence tests and thus be of particular importance in relatively short time series. 6. In our best model of the population dynamics, two likely density-independent offspring survival covariates explained 47.3% of the variance in great snipe numbers (predation pressure estimated by willow grouse reproductive success and food availability estimated by the amount of precipitation in June), whereas density dependence explained 35.5%. Demographic stochasticity and unidentified environmental stochasticity may account for the remaining 17.2%.