Abstract Many migratory animals use spatial variation in the Earth's magnetic field for orientation and navigation. This raises the possibility of exploiting these same cues to geolocate and track migratory animals throughout their annual journeys. Magnetic‐based geolocation could be particularly valuable for small aerial and aquatic species, for which the most precise pressure‐based geolocation cannot be applied. We developed a novel geolocation method, implemented in the R package GeoMagR (https://geopressure.org/GeoMagR/) that uses three‐axis magnetic field measurements from lightweight multi‐sensor tags. The workflow consists of: (i) tilt compensation and magnetic calibration; (ii) extraction of time series of magnetic intensity and inclination; and (iii) generation of spatial likelihood maps using the World Magnetic Model (WMM). We evaluated the method using field data to assess achievable spatial precision and potential complementarity with other geolocation techniques. Magnetic geolocation achieved a typical spatial accuracy of ~150 km in latitude but provided little constraint in longitude. When combined with light‐based geolocation, which offers high longitudinal accuracy but poor latitudinal resolution, the integration markedly improved overall position estimates. Magnetic geolocation is a viable complementary tool for tracking small avian species, particularly in contexts where pressure‐based methods cannot be used. By independently resolving latitude, it enhances spatial inference when integrated with other geolocation data sources. This processing of 3D magnetic and acceleration data from geolocators also extends their use beyond positioning, enabling applications in studies of behaviour and navigation.

Most bird species are diurnal but drastically change their diel cycle of activity to migrate at night. Nocturnal migration has been documented using different methods (e.g., experiments, radar and radio tracking, and acoustic monitoring), but accurately quantifying the proportion of nocturnal versus diurnal flight at the individual and species levels, and understanding how this behavior evolved across the avian tree, has remained methodologically challenging.1,2,3 Such uncertainty is not only of theoretical importance but also limits our ability to mitigate conservation threats, particularly from light pollution and building collisions.4,5,6 With multi-sensor geolocators recording light, barometric pressure, and activity,7,8 we reconstructed high-resolution migratory trajectories9,10 for 411 individuals from 56 small- or medium-sized landbird species across four continents and measured the proportion of each flight that occurred during night or day. Our species-level quantification confirmed nocturnal migration as the dominant strategy among small landbirds, while also providing precise flight proportion estimates across a broad taxonomic sample and refining the classification of several species previously described as partial or facultative diurnal migrants. We found that birds initiated and ended migratory flights near civil dusk and dawn, thereby maximizing nocturnal travel. The phylogenetic signal we detected indicates that nocturnal migration is largely conserved within lineages. While nocturnal migration confers multiple advantages, the relative importance of the proposed drivers remains to be determined.11,12 Our study provides species-specific quantification of nocturnal migration, highlights tracking gaps across taxa and regions, and opens new avenues for studying the evolutionary, ecological, and sensory drivers of nocturnal migratory flights.

The main features of long-distance migration are derived from landbirds breeding in the Northern Hemisphere. Little is known about migration within the tropics, presumably because tropical species typically move opportunistically and over shorter distances. However, such generalizations are weakened by a lack of solid data on spatial, temporal and behavioural patterns of intra-tropical migrations. To start filling the research gap, we provide comprehensive data for small-sized intra-African migrants, woodland kingfishers. We inferred stationary locations, migration timing, flight behaviour and wind experienced en route from multi-sensor loggers recording atmospheric pressure, light and acceleration. After breeding in South Africa, all tagged individuals migrated 4000 km to South Sudan, spending their non-breeding period within 100 km of each other. Thereby, woodland kingfishers tracked their climatic niche, using two rainy seasons in open woodland across the Equator. Migratory flights were strictly nocturnal, reaching 2890 m.a.s.l. Flights were unusually short, but lengthened when crossing rainforests, a behavioural adjustment similar to barrier-crossing along well-described flyways. These results suggest that long-distance intra-tropical migration displays patterns that are surprisingly similar to other flyways. Pending confirmation in other species, intra-tropical migrations might be more extensive and less flexible than assumed, underlining the importance of further research guiding conservation efforts.

The path-breaking work of Eastwood (1967) provided comprehensive information on the use of surveillance radar for the study of bird migration, reference to initial studies applying pencil-beam radar, and a first hint to the use of tracking radar. Pencil-beam radars can provide information on the temporal and spatial distribution of migrating birds. Radars with tracking capacity yield data on the flight behavior of individually tracked day and night migrants and on wind conditions at the altitudes where the birds fly. The Swiss Ornithological Institute used the military tracking radar “Superfledermaus” continuously from 1968 till 2010: a) to quantify migratory passage and vertical distribution, and b) to study migratory behavior by tracking single targets. In the early 1990s, the radar was adapted to become a dedicated bird radar, and the geographic range of studies was extended far beyond the boundaries of Switzerland, from Israel to Spain and from the Baltic Sea to the Sahara (Bruderer, Vogelwarte 58:255–272, 2020). Over a period of 42 years, more than 400,000 tracks of migrating birds were electronically recorded and are now available for further investigations. Positioning mobile radars at sites with challenging environmental conditions allows studying the response of migrating birds to particular requirements, such as flights across large water surfaces, mountain ranges or deserts under varying influence of meteorological factors. Covering the relevant parts of migratory seasons in spring and autumn, the available data sets comprise ample variation for the study of specific questions on in-flight behavior of migratory birds. In comparison with long-range individual tracking devices, the radar data comprise larger numbers of individuals from restricted areas, i.e. half-spheres of about 5 km radius. The available data offer possibilities for studies on the geographic, topographic, and meteorological particularities of bird migration at the various radar stations. They also cover a wide range of atmospheric conditions and wing-beat patterns of birds, allowing studies on the variation of flight behavior of selected bird types in varying environments.

Might the flight call of a Green heron during migration provide relevant information for an Ovenbird en route? An extensive quantitative analysis of flight calls of migrating birds reveals evidence that social interactions across species boundaries occurs during sustained flight at night.

Many insects depend on high-altitude, migratory movements during part of their life cycle. The daily timing of these migratory movements is not random, e.g. many insect species show peak migratory flight activity at dawn, noon or dusk. These insects provide essential ecosystem services such as pollination but also contribute to crop damage. Quantifying the diel timing of their migratory flight and its geographical and seasonal variation, are hence key towards effective conservation and pest management. Vertical-looking radars provide continuous and automated measurements of insect migration, but large-scale application has not been possible because of limited availability of suitable devices. Here, we quantify patterns in diel flight periodicity of migratory insects between 50 and 500 m above ground level during March-October 2021 using a network of 17 vertical-looking radars across Europe. Independent of the overall daily migratory movements and location, peak migratory movements occur around noon, during crepuscular evening and occasionally the morning. Relative daily proportions of insect migration intensity and traffic during the diel phases of crepuscular-morning, day, crepuscular-evening and night remain largely equal throughout May-September and across Europe. These findings highlight, extend, and generalize previous regional-scale findings on diel migratory insect movement patterns to the whole of temperate Europe. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Birds breeding in high-Alpine habitats must select a suitable breeding site and achieve successful reproduction within a restricted time. During four breeding seasons, we monitored nest sites of the Northern Wheatear (Oenanthe oenanthe), a high-Alpine long-distance migrant. We investigated how ecological factors predicted the selection of a site for nesting within the home range, using conditional logistic regression. Birds preferred south-exposed productive pastures on gentle slopes, interspersed with non-vegetated ground and human-made rockpiles. The direct vicinity of conspecific nests was avoided, as were shrubby or north-exposed areas. We investigated if habitat also influenced breeding success. We analysed the impact of environmental factors on breeding success, which was primarily driven by predation. The probability of the brood fledging successfully decreased on north-exposed slopes or on areas with low coverage of non-vegetated ground. The vicinity of conspecific nests did not have a clear effect. Further, we describe how breeding success varied within and between years. Within years, replacement broods had a higher breeding success. The apparent absence of variation in breeding success between years and a delay of the breeding period in the year with late spring onset suggest a high level of tolerance with respect to inter-annual variation of meteorological conditions. Since the preferred habitat is still widely available in the Alps and given the negative population trends in Western Europe, the Alpine range might serve as a refuge for the Northern Wheatear, as long as low-intensity management and heterogenous habitats are maintained.

Abstract Background Migrating birds fly non-stop for hours or even for days. They rely mainly on fat as fuel complemented by a certain amount of protein. Studies on homing pigeons and birds flying in a wind-tunnel suggest that the shares of fat and protein on total energy expenditure vary with flight duration and body fat stores. Also, flight behaviour, such as descending flight, is expected to affect metabolism. However, studies on free flying migrant birds under natural conditions are lacking. Methods On a Swiss Alpine pass, we caught three species of nocturnal migrant passerines out of their natural migratory flight. Since most night migrants start soon after dusk, we used time since dusk as a measure of flight duration. We used plasma concentrations of metabolites of the fat, protein, and carbohydrate metabolism as indicators of relative fuel use. We used flight altitudes of birds tracked with radar and with atmospheric pressure loggers to characterize flight behaviour. Results The indicators of fat catabolism (triglycerides, very low-density lipoproteins, glycerol) were positively correlated with body energy stores, supporting earlier findings that birds with high fat stores have a higher fat catabolism. As expected, plasma levels of triglycerides, very low-density lipoproteins, glycerol and ß-hydroxy-butyrate increased at the beginning of the night, indicating that nocturnal migrants increased their fat metabolism directly after take-off. Surprisingly, fat catabolism as well as glucose levels decreased in the second half of the night. Data from radar observations showed that the number of birds aloft, their mean height above ground and vertical flight speed decreased after midnight. Together with the findings from atmospheric pressure-loggers put on three species, this shows that nocturnal migrants migrating over continental Europe descend slowly during about 1.5 h before final landfall at night, which results in 11–30% energy savings according to current flight models. Conclusions We suggest that this slow descent reduces energy demands to an extent which is noticeable in the plasma concentration of lipid, protein, and carbohydrate metabolites. The slow descent may facilitate the search for a suitable resting habitat and serve to refill glycogen stores needed for foraging and predator escape when landed.

Birds and bats are prone to collisions with wind turbines. To reduce the number of bat collisions, weather variables are commonly used to shut down wind turbines when a certain constellation of weather variables occurs. Such a general approach might also be interesting to mitigate raptor collisions. Studies on the relationship between flight behaviour and weather variables are needed. To investigate the flight behaviour of raptors within their breeding area in relation to local weather variables, we used high resolution data of flight tracks of Red Kites collected on a wind energy test site (Germany). Birds were tracked with a laser range finder (LRF) or with Global Positioning System (GPS) transmitters. Weather variables were continuously registered on site. We used generalised linear mixed models to analyse the influence of weather variables and of the measurement method on different flight parameters. Furthermore, we investigated the probability of flying within a virtual rotor height range defined by three hub heights (84, 94 and 140 m; diameter: 112 m). The median flight altitude measured by LRF (52.5 m, 95% CI: 44.9-61.0, N = 2511) was on average 25 m higher than the corrected one resulting from GPS (27.8 m, 95% CI: 24.7-31.2, N = 6792). Flight speed also differed between methods (GPS: 29.2 km/h, 95% CI: 28.2-30.3 km/h; LRF: 25.1 km/h, 95% CI: 24.0-26.3 km/h). The effects of the weather variables were weak. Birds tended to fly less and lower during wet (humid, rainy or foggy) than dry weather, and lower during strong than weak winds. Probabilities of flying within a height range of virtual rotors increased with decreasing hub height, and hence ground clearance. Synthesis and applications: Flight behaviour was highly variable. Flights occurred during all weather conditions at different altitudes throughout the day over the entire season. Further research into the relationship between flight behaviour, weather variables, collisions and other factors is needed as a basis for developing shutdown regimes generally suitable for raptors. The mean flight altitude and speed differed between the measurement methods. Any values resulting from studies should be interpreted in the context of the method. V & ouml;gel und Flederm & auml;use sind anf & auml;llig f & uuml;r Kollisionen mit Windenergieanlagen (WEA). Um die Zahl der Kollisionen mit Flederm & auml;usen zu verringern, werden & uuml;blicherweise Wettervariablen verwendet, um WEA abzuschalten, wenn eine bestimmte Konstellation von Wettervariablen auftritt. Ein solcher Ansatz k & ouml;nnte auch interessant sein, um Kollisionen mit Greifv & ouml;geln zu verringern. Dazu sind Studien & uuml;ber den Zusammenhang zwischen Flugverhalten und Wettervariablen notwendig. Zur Untersuchung des Flugverhaltens von Greifv & ouml;geln in ihrem Brutgebiet in Abh & auml;ngigkeit von lokalen Wettervariablen haben wir hochaufl & ouml;sende Daten von Flugwegen von Rotmilanen verwendet, die auf einem Windenergie-Testgel & auml;nde in Deutschland gesammelt wurden. Die V & ouml;gel wurden mit einem Laser Range Finder (LRF) oder mit GPS-Sendern verfolgt. Die Wettervariablen wurden kontinuierlich vor Ort registriert. Mit Hilfe von linearen gemischte Effekte Modellen analysierten wir den Einfluss der Wettervariablen und der Messmethode auf verschiedene Flugparameter. Au ss erdem untersuchten wir die Wahrscheinlichkeit, innerhalb eines virtuellen Rotorh & ouml;henbereichs zu fliegen, der durch drei Nabenh & ouml;hen (84, 94, 140 m, Durchmesser: 112 m) definiert ist. Die mit LRF gemessene mittlere Flugh & ouml;he (52.5 m, 95% CI: 44.9-61.0, N = 2.511) war im Durchschnitt 25 m h & ouml;her als die mit GPS gemessene korrigierte H & ouml;he (27.8 m, 95% CI: 24.7-31.2, N = 6.792). Die Fluggeschwindigkeit unterschied sich ebenfalls zwischen den Methoden (GPS: 29.2 km/h, 95% CI: 28.2-30.3 km/h; LRF: 25.1 km/h, 95% CI: 24.0-26.3 km/h). Der Einfluss der Wettervariablen war schwach. Die V & ouml;gel flogen bei nassem (feuchtem, regnerischem oder nebligem) Wetter tendenziell weniger und niedriger als bei trockenem Wetter, und niedriger bei starkem als bei schwachem Wind. Die Wahrscheinlichkeit, innerhalb des H & ouml;henbereichs der virtuellen Rotoren zu fliegen, nahm mit abnehmender Nabenh & ouml;he und damit kleiner werdenden Bodenabstand zu. Synthese und Anwendungen: Das Flugverhalten war sehr variabel. Flugbewegungen traten w & auml;hrend der gesamten Saison & uuml;ber den Tag verteilt unter allen Wetterbedingungen in unterschiedlichen H & ouml;hen auf. Um eine Grundlage f & uuml;r die Entwicklung von f & uuml;r Greifv & ouml;gel geeigneten Abschaltregelungen zu schaffen, muss die Beziehung zwischen Flugverhalten, Wettervariablen, Kollisionen und anderen Faktoren weiter erforscht werden. Die mittlere Flugh & ouml;he und -geschwindigkeit war je nach Messmethode unterschiedlich. Aus Studien resultierende Werte sollten daher im Kontext der jeweiligen Messmethode interpretiert werden. Flight behaviour was highly variable. Flights occurred during all weather conditions at different altitudes throughout the day over the entire season. Further research into the relationship between flight behaviour, weather variables, collisions and other factors is needed as a basis for developing shutdown regimes generally suitable for raptors. The mean flight altitude and speed differed between the measurement methods. Any values resulting from studies should be interpreted in the context of the method.image

Abstract The Alps are a natural barrier for avian broad‐front migration in Central Europe. While most birds that approach the Alps are deflected and circumvent the mountains, some choose to make the crossing. Here, they are funnelled and channelled in valleys, leading to high bird densities. Many Alpine valleys are suitable locations for wind farms, potentially creating a conflict between wind energy production and bird conservation. Collisions can be reduced by temporarily shutting down wind turbines. This however requires timely coordination, either by locally monitoring migration intensity or by extrapolating and forecasting migratory fluxes from other sites. However, little is known about the timing and intensity of bird migration in valleys of the central Alps, especially during spring migration. This study presents a 2‐year quantification of avian migration across the Alps. We collected terrestrial radar data at three sites: two located in Alpine valleys and one in the lowland, close to the northern foothills of the Alps. We found high migration traffic rates (MTR) during both migration seasons in the Alpine valleys, with outstanding numbers of migrants during the spring season. The strong alignment of the flight directions with the main orientation of alpine valleys highlights the importance of valleys and the connected passes in channelling migratory fluxes through the Alps. However, extrapolating migration intensities and forecasting peak migration events for inner Alpine sites is difficult, likely due to how migratory patterns and activity are influenced by the complexity of the local topography and the associated dynamic wind and weather conditions. Instead, we call for year‐round on‐site monitoring of migration intensities and strategies tailored to the local context to reduce the risk of bird strikes at wind turbines in the Alps.

Over the past decades, tracking technologies have become more ubiquitous and helped uncover crucial spatiotemporal relationships in nature. In order to apply these technologies to small animals and reduce any potential adverse impact of devices, geopositioning methodologies compatible with lightweight devices are highly sought after. Measured by lightweight geolocators, atmospheric pressure provides an untapped opportunity for global geopositioning, as its natural temporal variation is unique to each location. In this study, we estimate the position of birds by comparing pressure data recorded by the geolocator with reference data from a global weather reanalysis database. The method produces a likelihood map of the position based on (1) a mask of the locations for which the ground‐level elevation matches the pressure measured by the geolocator and (2) a mismatch between the temporal time series measured by the geolocator and the reanalysis dataset. This new method is introduced step by step and applied to 16 tracks of nine long‐ and short‐distance migrant species. Using known positions of double‐tagged individuals (light and pressure data), we demonstrate that our method is almost three times more accurate than light‐based positioning with an average error of 44 km in our trials. In contrast to the traditional light‐based approach, pressure geolocation can provide useful information for short stationary periods (less than a day) and is not affected by the equinox problem nor by any shading effects due to weather or animal behaviour. To facilitate the application of the method, we developed an R package GeoPressureR , together with a user guide GeopressureManual and starting code GeoPressureTemplate . The use of pressure sensors to position animals has the potential to become widespread thanks to the combination of both affordable lightweight devices (<0.4 g) and this method to estimate position of the device precisely and accurately. In particular, such devices can now be applied to short‐distant migrants (>100 km), forest‐dwelling species, nocturnal animals and altitudinal migrants.

Insects are of increasing conservation concern as a severe decline of both biomass and biodiversity have been reported. At the same time, data on where and when they occur in the airspace is still sparse, and we currently do not know whether their density is linked to the type of landscape above which they occur. Here, we combined data of high-flying insect abundance from six locations across Switzerland representing rural, urban and mountainous landscapes, which was recorded using vertical-looking radar devices. We analysed the abundance of high-flying insects in relation to meteorological factors, daytime, and type of landscape. Air pressure was positively related to insect abundance, wind speed showed an optimum, and temperature and wind direction did not show a clear relationship. Mountainous landscapes showed a higher insect abundance than the other two landscape types. Insect abundance increased in the morning, decreased in the afternoon, had a peak after sunset, and then declined again, though the extent of this general pattern slightly differed between landscape types. We conclude that the abundance of high-flying insects is not only related to abiotic parameters, but also to the type of landscapes and its characteristics, which, on a long-term, should be taken into account for when designing conservation measures for insects.

To understand the ecology of long-distance migrant bird species, it is necessary to study their full annual cycle, including migratory routes and stopovers. This is especially important for species in high-elevation habitats that are particularly vulnerable to environmental change. Here, we investigated both local and global movements during all parts of the annual cycle in a small trans-Saharan migratory bird breeding at high elevation. Recently, multi-sensor geolocators have opened new research opportunities in small-sized migratory organisms. We tagged Northern Wheatears Oenanthe oenanthe from the central-European Alpine population with loggers recording atmospheric pressure and light intensity. We modelled migration routes and identified stopover and non-breeding sites by correlating the atmospheric pressure measured on the birds with global atmospheric pressure data. Furthermore, we compared barrier-crossing flights with other migratory flights and studied the movement behaviour throughout the annual cycle. All eight tracked individuals crossed the Mediterranean Sea, using islands for short stops, and made longer stopovers in the Atlas highlands. Single non-breeding sites were used during the entire boreal winter and were all located in the same region of the Sahel. Spring migration was recorded for four individuals with similar or slightly different routes compared to autumn. Migratory flights were typically nocturnal and characterized by fluctuating altitudes, frequently reaching 2000 to 4000 m a.s.l, with a maximum of up to 5150 m. Barrier-crossing flights, i.e., over the sea and the Sahara, were longer, higher, and faster compared to flights above favourable stopover habitat. In addition, we detected two types of altitudinal movements at the breeding site. Unexpected regular diel uphill movements were undertaken from the breeding territories towards nearby roosting sites at cliffs, while regional scale movements took place in response to local meteorological conditions during the pre-breeding period. Our data inform on both local and global scale movements, providing new insights into migratory behaviour and local movements in small songbirds. This calls for a wider use of multi-sensor loggers in songbird migration research, especially for investigating both local and global movements in the same individuals.

Tracking technologies have widely expanded our understanding of bird migration routes, destinations and underlying strategies. However, determining the entire trajectory of small birds equipped with lightweight geolocators remains a challenge. We develop a highly optimized hidden Markov model (HMM) for reconstructing bird trajectories. The observation model is defined by pressure and, optionally, light measurements, while the movement model incorporates wind data to constrain consecutive positions based on realistic airspeeds. To reduce the computational costs associated with a large state space, we prune the HMM states and transitions based on flight and observation constraints to efficiently model the entire trajectory. The approach presented is based on a mathematically exact procedure and is fast to compute. We demonstrate how to compute (1) the most likely trajectory, (2) the marginal probability map of each stationary period, (3) simulated trajectories and (4) the wind conditions (wind support/drift) encountered by the bird during each migratory flight. We construct a version of an HMM optimized for reconstructing a bird's migration trajectory based on lightweight geolocator data. To render this approach easily accessible to researchers, we designed a dedicated R package GeoPressureR ( https://raphaelnussbaumer.com/GeoPressureR/ ).

The northern wheatear Oenanthe oenanthe has an almost circumpolar breeding distribution in the Northern Hemisphere, but all populations migrate to sub‐Saharan Africa in winter. Currently, tracking data suggest two main access routes to the northern continents via the Middle East and the Iberian Peninsula. These routes would require detours for birds breeding in the European Alps. Our aim was to map the migration routes and determine annual schedules for birds breeding in Switzerland and Austria, using light level geolocators. We compared their migration patterns with birds from a lowland breeding population in Germany. Birds from the Alps cross the Mediterranean Sea directly heading straight to their non‐breeding sites. In contrast, birds from Germany travelled further west via the Iberian Peninsula. While the German population initiated autumn migration relatively early, arrival on the wintering sites was nearly synchronous across the three populations. During spring migration, German birds arrived earlier at their breeding grounds than birds from the Alps. A comparison with the literature indicated that the breeding populations in the Alps use their own route and are among the latest to arrive in spring, showing resemblance to the phenology of Arctic breeding populations. Our results indicate that the annual cycle of Alps‐breeding wheatears is influenced primarily by breeding ground conditions, and not solely by migration distance.

Abstract BackgroundUnderstanding the temporal and spatial use of habitats by wildlife is crucial to apprehend ecological relationships in nature. Tracking small birds and bats requires tags of less than 2g, therefore lightweight geolocators are currently the most affordable and widespread option. Recent multi-sensor geolocators now capture accelerometer and pressure data in addition to light, offering new potential to refine the accuracy of bird positioning. In particular, as atmospheric pressure varies with space and time, pressure timeseries at a single location have a unique signature which can be used for global positioning independent of light recordings.MethodBird positions are estimated at distinct stationary periods by comparing atmospheric pressure data recorded by the geolocator with reference data from a global weather reanalysis database. The methodology produces a probability distribution map of the position based on (1) a mask of the locations for which the ground level elevation matches the pressure measured by the geolocator and (2) a likelihood of the mismatch between the temporal timeseries measured by the geolocator and the reanalysis dataset. This new method is introduced step by step and applied to 16 tracks from 9 long- and short-distance migrant species.ResultsUsing known positions of double-tagged individuals (light and pressure data), we demonstrate that our method is almost three times more accurate than light-based positioning with an average error of 44 km in our trials. In contrast to the traditional light-based approach, pressure data can provide location information for short stationary periods (less than a day) and is not affected by the equinox-problem nor the change of habitats by the tracked animal. To facilitate the application of the method, we developed an R package featuring guidelines, examples and starting code (GeoPressureR).ConclusionPositioning birds using pressure data can help identify short stopover locations, such that tracking devices measuring pressure alone could be used for global positioning, allowing for the study of lighter species.

Thanks to their light weight and low cost relative to GPS trackers, light-level geolocators are uniquely positioned to uncover bird migration patterns across less well-financed and understudied regions of the world. A main drawback of geolocators is the need to recapture equipped birds to retrieve the data. Maximizing the recapture rate is therefore critical to the success of any geolocator study. In this paper, we present a methodology drawing on historical ringing data in order to inform the deployment of geolocators, both in terms of how many birds can be equipped, and when/which birds to equip in order to maximize retrieval. We illustrate this methodology with a geolocator study of Red-capped Robin-chats (Cossypha natalensis) on the coast of Kenya and find that it accurately estimates how many geolocators to source. It also provides insights into which classes of birds (based on age, capture history, and timing within the season) are most likely to be recaptured. Finally, the analysis of recapture rates allows minimization of geolocator use and thus potential negative impacts to a population.

To investigate the complex phenomenon of bird migration, researchers rely on sophisticated methods for tracking long‐distant migrants. While large birds can be equipped with satellite tags, these are too heavy for many species. Instead, researchers often use light‐level geolocation for tracking individual small migratory birds. Unfortunately, light‐level geolocation is often coarse and unreliable, with positioning errors of anything up to hundreds of kilometres. Recent Bayesian models try to constrain the route to plausible corridors: they couple light‐level measurements with information about the bird's likely movement. While these models improve inference, they still lack information on weather conditions, specifically the impact of wind. For example, birds might encounter tailwinds—considerably increasing their (ground) speed and making longer routes more likely, or headwinds—having the opposite effect. Miniaturised multi‐sensor tags allow monitoring not only light but also acceleration and air pressure. These measurements provide essential additional information about the exact timing of flight activity and the corresponding flight altitudes. This article proposes a Bayesian model for inferring bird migration. The model integrates air pressure to estimate flight altitudes and considers wind data to calculate the most likely flight trajectory. The model constrains the migratory routes to those likely given by the winds en route and the observed timing of flight activity. We apply the model to infer the migration of European Hoopoes Upupa epops. Adding wind data for route inference excludes flight trajectories with unrealistic high airspeeds, decreases the uncertainty of the position estimates and returns more plausible migratory routes. Faithful reconstruction of migratory routes helps unravel the influence of physiological and environmental factors on bird migration. This is crucial for habitat protection where limited resources need to be allocated to relevant areas.

Light-level geolocators have revolutionised the study of animal behaviour. However, lacking spatial precision, their usage has been primary targeted towards the analysis of large-scale movements. Recent technological developments have allowed the integration of magnetometers and accelerometers into geolocator tags in addition to barometers and thermometers, offering new behavioural insights. Here, we introduce an R toolbox for identifying behavioural patterns from multisensor geolocator tags, with functions specifically designed for data visualisation, calibration, classification and error estimation. More specifically, the package allows for the flexible analysis of any combination of sensor data using k-means clustering, expectation maximisation binary clustering, hidden Markov models and changepoint analyses. Furthermore, the package integrates tailored algorithms for identifying periods of prolonged high activity (most commonly used for identifying migratory flapping flight), and pressure changes (most commonly used for identifying dive or flight events). Finally, we highlight some of the limitations, implications and opportunities of using these methods.