The extraordinary adaptations of birds to contend with atmospheric conditions during their migratory flights have captivated ecologists for decades. During the 21st century technological advances have sparked a revival of research into the influence of weather on migrating birds. Using biologging technology, flight behaviour is measured across entire flyways, weather radar networks quantify large-scale migratory fluxes, citizen scientists gather observations of migrant birds and mechanistic models are used to simulate migration in dynamic aerial environments. In this review, we first introduce the most relevant microscale, mesoscale and synoptic scale atmospheric phenomena from the point of view of a migrating bird. We then provide an overview of the individual responses of migrant birds (when, where and how to fly) in relation to these phenomena. We explore the cumulative impact of individual responses to weather during migration, and the consequences thereof for populations and migratory systems. In general, individual birds seem to have a much more flexible response to weather than previously thought, but we also note similarities in migratory behaviour across taxa. We propose various avenues for future research through which we expect to derive more fundamental insights into the influence of weather on the evolution of migratory behaviour and the life-history, population dynamics and species distributions of migrant birds.

Given that soaring birds travel faster with supportive winds or in good thermal soaring conditions, we expect weather conditions en route of migration to explain commonly observed regional and seasonal patterns in the performance of soaring migrants. We used GPS-loggers to track 13 honey buzzards and four Montagu's harriers for two to six migrations each. We determined how tailwinds, crosswinds, boundary layer height (a proxy for thermal convection) and precipitation aff ected hourly speeds, daily distances and daily mean speeds with linear regression models. Honey buzzards mostly travel by soaring while Montagu's harriers supplement soaring with fl apping. Th erefore, we expect that performance of harriers will be less aff ected by weather than for buzzards. Weather conditions explained between 30 and 50% of variation in migration performance of both species. Tailwind had the largest eff ect on hourly speeds, daily mean speeds and daily travel distances. Honey buzzards travelled signifi cantly faster and farther, and Montagu ' s harriers non-signifi cantly faster, under better convective conditions. Honey buzzards travelled at slower speeds and shorter distances in crosswinds, whereas harriers maintained high speeds in crosswinds. Weather conditions varied between regions and seasons, and this variation accounted for nearly all regional and seasonal variation in fl ight performance. Hourly performance was higher than predicted at times when we suspect birds had switched to intermittent or continuous fl apping fl ight, for example during sea-crossings. Th e daily travel distance of Montagu ' s harriers was determined to a signifi cant extent by their daily travel time, which diff ered between regions, possibly also due to weather conditions. We conclude with the implications of our work for studies on migration phenology and we suggest an important role for high-resolution telemetry in understanding migratory behavior across entire migratory journeys.

Summary1. Avian migrants often make substantial detours between their seasonal destinations. It is likely some species do this to make the most of predictable wind regimes along their respective flyways. We test this hypothesis by studying orientation behaviour of a long-distance soaring migrant in relation to prevailing winds along the East Atlantic Flyway. 2. We tracked 62 migratory journeys of 12 adult European Honey Buzzards Pernis apivorus with GPS loggers. Hourly fixes were annotated with local wind vectors from a global atmospheric model to determine orientation behaviours with respect to the buzzards' seasonal goal destinations. This enabled us to determine hot spots where buzzards overdrifted and overcompensated for side winds. We then determined whether winds along the buzzards' detours differed from winds prevailing elsewhere in the flyway. 3. Honey Buzzards cross western Africa using different routes in autumn and spring. In autumn, they overcompensated for westward winds to circumvent the Atlas Mountains on the eastern side and then overdrifted with south-westward winds while crossing the Sahara. In spring, however, they frequently overcompensated for eastward winds to initiate a westward detour at the start of their journey. They later overdrifted with side winds north-westward over the Sahel and north-eastward over the Sahara, avoiding adverse winds over the central Sahara. 4. We conclude that Honey Buzzards make seasonal detours to utilize more supportive winds further en route and thereby expend less energy while crossing the desert. Lifelong tracking studies will be helpful to elucidate how honey buzzards and other migrants learn complex routes to exploit atmospheric circulation patterns from local to synoptic scales.

Contemporary tracking studies reveal that low migratory connectivity between breeding and non-breeding ranges is common in migrant landbirds. It is unclear, however, how internal factors and early-life experiences of individual migrants shape the development of their migration routes and concomitant population-level non-breeding distributions. Stochastic wind conditions and geography may determine whether and where migrants end up by the end of their journey. We tested this hypothesis by satellite-tagging 31 fledgling honey buzzards Pernis apivorus from southern Finland and used a global atmospheric reanalysis model to estimate the wind conditions they encountered on their first outbound migration. Migration routes diverged rapidly upon departure and the birds eventually spread out across 3340 km of longitude. Using linear regression models, we show that the birds' longitudinal speeds were strongly affected by zonal wind speed, and negatively affected by latitudinal wind, with significant but minor differences between individuals. Eventually, 49% of variability in the birds' total longitudinal displacements was accounted for by wind conditions on migration. Some birds circumvented the Baltic Sea via Scandinavia or engaged in unusual downwind movements over the Mediterranean, which also affected the longitude at which these individuals arrived in sub-Saharan Africa. To understand why adult migrants use the migration routes and non-breeding sites they use, we must take into account the way in which wind conditions moulded their very first journeys. Our results present some of the first evidence into the mechanisms through which low migratory connectivity emerges.

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The ontogeny of migration routines used by wild birds remains unresolved. Here we investigated the migratory orientation of juvenile lesser spotted eagles (LSE; Clanga pomarina) based on translocation and satellite tracking. Between 2004 and 2016, 85 second-hatched juveniles (Abels) were reared in captivity for release into the declining German population, including 50 birds that were translocated 940 km from Latvia. In 2009, we tracked 12 translocated juveniles, as well as eight native juveniles and nine native adults, to determine how inexperienced birds come to use strategic migration routes. Native juveniles departed around the same time as the adults and six of eight used the eastern flyway around the Mediterranean, which was used by all adults. In contrast, translocated juveniles departed on average 6 days before native LSEs, and five travelled southward and died in the central Mediterranean region. Consequently, fewer translocated juveniles (4/12) than native juveniles (7/8) reached Africa. We conclude that juvenile LSEs have a much better chance of learning the strategic southeastern flyway if they leave at an appropriate time to connect with experienced elders upon departure. It is not clear why translocated juveniles departed so early. Regardless, by the end of the year, most juveniles had perished, whether they were translocated (10/12) or not (6/8). The small number of surviving translocated juveniles thus still represents a significant increase in the annual productivity of the German LSE population in 2009.

Every autumn, large numbers of raptors migrate through geographical convergence zones to avoid crossing large bodies of water. At coastal convergence zones, raptors may aggregate along coastlines because of convective or wind conditions. However, the effect of wind and thermal convection on migrating raptors may vary depending on local landscapes and weather, and on the flight strategies of different raptors. From 20 August to 14 October 2008 and 2009, we studied the effect of cloud development and crosswinds on the flight paths of raptors migrating through the eastern Black Sea convergence zone, where coastal lowlands at the foothills of the Pontic Mountains form a geographical bottleneck 5‐km‐wide near Batumi, the capital of the Independent Republic of Ajaria in southwestern Georgia. To identify key correlates of local aggregation, we examined diurnal variation in migration intensity and coastal aggregation of 11 species of raptors categorized based on size and flight strategies. As reported at other convergence zones, migration intensity of large obligate‐soaring species peaked during the core period of thermal activity at mid‐day. When clouds developed over interior mountains and limited thermal convection, these large obligate‐soaring species aggregated near the coast. However, medium‐sized soaring migrants that occasionally use flapping flight did not aggregate at the coast when clouds over the mountains weakened thermal convection. Numbers of alternate soaring‐flapping harriers (Circus spp.) peaked during early morning, with these raptors depending more on flapping flight during a time of day with poor thermal convection. Small sparrowhawks (Accipiter spp.) aggregated at the coast during periods when winds blew offshore, suggesting aggregation caused by wind drift. Thus, weather conditions, including cloud cover and wind speed and direction, can influence the daily rhythm and flight paths of migrating raptors and, therefore, should be accounted for before inferring population trends from migration counts.

Thermal soaring birds reduce flight-energy costs by alternatingly gaining altitude in thermals and gliding across the earth's surface. To find out how soaring migrants adjust their flight behaviour to dynamic atmospheric conditions across entire migration routes, we combined optimal soaring migration theory with high-resolution GPS tracking data of migrating honey buzzards Pernis apivorus and wind data from a global numerical atmospheric model.We compared measurements of gliding air speeds to predictions based on two distinct behavioural benchmarks for thermal soaring flight. The first being a time-optimal strategy whereby birds alter their gliding air speeds as a function of climb rates to maximize cross-country air speed over a full climb-glide cycle (V opt ). The second a risk-averse energy-efficient strategy at which birds alter their gliding air speed in response to tailwinds/headwinds to maximize the distance travelled in the intended direction during each glide phase (V bgw ).Honey buzzards were gliding on average 2.05 ms -1 slower than V opt and 3.42 ms -1 faster than V bgw while they increased air speeds with climb rates and reduced air speeds in tailwinds. They adopted flexible flight strategies gliding mostly near V bgw under poor soaring conditions and closer to V opt in good soaring conditions.Honey buzzards most adopted a time-optimal strategy when crossing the Sahara, and at the onset of spring migration, where and when they met with the best soaring conditions. The buzzards nevertheless glided slower than V opt during most of their journeys, probably taking time to navigate, orientate and locate suitable thermals, especially in areas with poor thermal convection.Linking novel tracking techniques with optimal migration models clarifies the way birds balance different tradeoffs during migration. List of symbols and abbreviationsb Angle between heading and track direction over full climb-glide cycle. V a Gliding air speed. V ac Horizontal air speed during the climb phase. V bg Theoretical best-gliding air speed for maximizing gliding range relative to the air. V bgw Theoretical bestgliding air speed for maximizing gliding range relative to the ground. V c Climb rate. V cc Cross-country speed relative to the air. V g Gliding ground speed. V h Ground speed during the climb phase (mostly due to advection by wind). V ms Theoretical minimum-sink speed. V opt Theoretical optimal air speed for maximizing V cc . V s Sink rate. V xc Cross-country speed relative to the ground. TEA Thermal exit altitude.