Flight speeds of swifts (Apus apus): seasonal differences smaller than expected

We have studied the nocturnal flight behaviour of the common swift (Apus apus L.), by the use of a tracking radar. Birds were tracked from Lund University in southern Sweden during spring migration, summer roosting flights and autumn migration. Flight speeds were compared with predictions from flight mechanical and optimal migration theories. During spring, flight speeds were predicted to be higher than during both summer and autumn due to time restriction. In such cases, birds fly at a flight speed that maximizes the overall speed of migration. For summer roosting flights, speeds were predicted to be lower than during both spring and autumn since the predicted flight speed is the minimum power speed that involves the lowest energy consumption per unit time. During autumn, we expected flight speeds to be higher than during summer but lower than during spring since the expected flight speed is the maximum range speed, which involves the lowest energy consumption per unit distance. Flight speeds during spring were indeed higher than during both summer and autumn, which indicates time-selected spring migration. Speeds during autumn migration were very similar to those recorded during summer roosting flights. The general result shows that swifts change their flight speed between different flight behaviours to a smaller extent than expected. Furthermore, the difference between flight speeds during migration and roosting among swifts was found to be less pronounced than previously recorded.     

How swift are swifts Apus apus?

Swifts Apus apus are renowned for their fast flight manner which has fascinated people in all times. However, previous studies of swifts in flight during migration and roosting flights have shown that the birds operate over a narrow range of flight speeds compared with most other birds studied. In this study we have focused on the special flight behavior often called 'screaming parties'. During these flights the birds appear to reach very high speeds and therefore we used a stereo high speed camera setup to measure the flight speeds of the birds during this behavior with high accuracy. The birds were found to fly at much higher speeds during 'screaming parties' than during migration or roosting, on average twice as fast, 20.9  ms⁻¹ (±5.1  ms⁻¹) in horizontal speed. The highest record was 31.1  ms⁻¹ which is the highest measured yet for a swift in self powered flight. Furthermore, the birds were performing steep climbing flights, on average 4.0  ms⁻¹ (±2.8  ms⁻¹) in vertical velocity. A clear trade-off between horizontal speed and vertical speed was found, suggesting that the birds are operating at their maximum.     

Wing kinematics of avian flight across speeds

To test whether wing shape affects the kinematics of wing motion during bird flight, we recorded high-speed video (250 Hz) of four species flying in a variable-speed wind tunnel. The birds flew at intervals of 2 m s⁻¹, ranging from 1 m s⁻¹ up to their respective maximum flight speed, which varied from 14 to 17 m s⁻¹ depending on the species. Kinematic data obtained from two synchronized, high-speed video cameras were analyzed using 3D reconstruction. Three species with relatively pointed, high-aspect ratio wings changed wingbeat styles according to flight speed (budgerigar, Melopsittacus undulatus ; cockatiel, Nymphicus hollandicus ; ringed turtle dove, Streptopelia risoria ). These species used a wing-tip reversal upstroke, characterized by supination of the distal wing at mid-upstroke, at equivalent airspeeds ≤7 to 9 m s⁻¹. In faster flight, they used a swept-wing upstroke, without distal wing supination. At mid-upstroke at any speed, wingspan in these species was greater than wrist span. In contrast, at all steady flight speeds, the black-billed magpie Pica hudsonia with relatively broad, low-aspect ratio wings, used a flexed-wing, feathered upstroke in which wrist spans were equal to or greater than wingspans. Our results demonstrate that wing kinematics vary gradually as a function of flight speed, and that the patterns of variation are strongly influenced by external wing shape.     

Can wind help explain seasonal differences in avian migration speed?

A bird's ground speed is influenced by the wind conditions it encounters. Wind conditions, although variable, are not entirely random. Instead, wind exhibits persistent spatial and temporal dynamics described by the general circulation of the atmosphere. As such, in certain geographical areas wind's assistance (or hindrance) on migratory flight is also persistent, being dependent upon the bird's migratory direction in relation to prevailing wind conditions. We propose that, considering the western migration route of nocturnal migrants through Europe, winds should be more supportive in spring than in autumn. Thus, we expect higher ground speeds, contributing to higher overall migration speeds, in spring. To test whether winds were more supportive in spring than autumn, we quantified monthly wind conditions within western Europe relative to the seasonal direction of migration using 30 years (1978–2008) of wind data from the NCEP/NCAR Reanalysis dataset. We found that supporting winds were significantly more frequent for spring migration compared to autumn and up to twice as frequent at higher altitudes. We then analyzed three years (2006–2008) of nocturnal migratory ground speeds measured with radar in the Netherlands which confirmed higher ground speeds in spring than autumn. This seasonal difference in ground speed suggests a 16.9% increase in migration speed from autumn to spring. These results stress the importance of considering the specific wind conditions experienced by birds when interpreting migration speed. We provide a simple methodological approach enabling researchers to quantify regional wind conditions for any geographic area and time period of interest.     

Hydroacoustic measurement of swimming speed of North Sea saithe in the field

Saithe Pollachius virens , tracked diurnally with a split-beam echosounder, showed no relationship between size and swimming speed. The average and the median swimming speeds were 1·05 m s⁻¹(±0·09 m s⁻¹) and 0·93 m s⁻¹, respectively. However, ping-to-ping speeds up to 3·34 m s⁻¹ were measured for 25–29 cm fish, whose swimming speeds were significantly higher at night (1·08 m s⁻¹) than during the day (0·72 m s⁻¹). The high average swimming speed could be related to the foraging or streaming part of the population and not to potential weakness of the methodology. However, the uncertainty of target location increased with depth and resulted in calculated average swimming speeds of 0·15 m s⁻¹ even for a stationary target. With increasing swimming speed the average error decreased to 0 m s⁻¹ for speeds >0·34 m s⁻¹. Species identity was verified by trawling in a pelagic layer and on the bottom.     

Towards a new understanding of migration timing: slower spring than autumn migration in geese reflects different decision rules for stopover use and departure

According to migration theory and several empirical studies, long‐distance migrants are more time‐limited during spring migration and should therefore migrate faster in spring than in autumn. Competition for the best breeding sites is supposed to be the main driver, but timing of migration is often also influenced by environmental factors such as food availability and wind conditions. Using GPS tags, we tracked 65 greater white‐fronted geese Anser albifrons migrating between western Europe and the Russian Arctic during spring and autumn migration over six different years. Contrary to theory, our birds took considerably longer for spring migration (83 days) than autumn migration (42 days). This difference in duration was mainly determined by time spent at stopovers. Timing and space use during migration suggest that the birds were using different strategies in the two seasons: In spring they spread out in a wide front to acquire extra energy stores in many successive stopover sites (to fuel capital breeding), which is in accordance with previous results that white‐fronted geese follow the green wave of spring growth. In autumn they filled up their stores close to the breeding grounds and waited for supportive wind conditions to quickly move to their wintering grounds. Selection for supportive winds was stronger in autumn, when general wind conditions were less favourable than in spring, leading to similar flight speeds in the two seasons. In combination with less stopover time in autumn this led to faster autumn than spring migration. White‐fronted geese thus differ from theory that spring migration is faster than autumn migration. We expect our findings of different decision rules between the two migratory seasons to apply more generally, in particular in large birds in which capital breeding is common, and in birds that meet other environmental conditions along their migration route in autumn than in spring.     

Causes and characteristics of reverse bird migration: an analysis based on radar,radio tracking and ringing at Falsterbo,Sweden

That birds migrate in the reverse direction of the expected is a phenomenon of regular occurrence which has been observed at many sites. Here we use three different methods; tracking radar, radiotelemetry and ringing, to characterize the flights of these reverse migrants and investigate possible causes of reverse migration of nocturnally migrating passerines during autumn migration at Falsterbo peninsula, Sweden. Using these different methods we investigated both internal factors, such as age and fuel load, and external factors such as weather variables, competition and predation risk. Birds flying in the reverse direction were more likely to be lean and to be juveniles. Reverse migration was also more common with overcast skies and winds with north and east components. We did not find any effect of temperature, visibility, number of migrating sparrowhawks, or the total number of ringed birds at the site on the day of departure. We found that reverse migration is characterized by slower flight speeds (airspeed) at high altitudes and that it takes place later in the night than forward migration.     

Nocturnal autumn bird migration at Falsterbo, South Sweden

We investigated the patterns of nocturnal bird migration in autumn 1998 at a coastal site on the Falsterbo peninsula in south-western Sweden, by means of a passive infrared device. In total 17 411 flight paths, including track direction and altitude, of migrating birds were recorded for 68 nights from August to October. Mean migratory traffic rate per night varied between 6 and 6618 birds km⁻¹ h⁻¹, with an average of 1319 birds km⁻¹ h⁻¹. Migration at Falsterbo showed a similar seasonal pattern to that reported for central Europe, with pronounced peaks of migration and intermittent periods with relatively low migratory intensities. Weather factors explained two thirds of the variance in the intensity of bird migration. During nights with intense migration, associated with weak winds, the mean track direction was close to that in central western Europe (225°). Birds usually maintained a constant heading independent of wind directions and, in consequence, were drifted by the wind. The mean orientation clearly differed from that of the nearest coastline, suggesting that the birds did not use the topography below to compensate for wind drift.     

Swimming performance of European eel (Anguilla anguilla (L.)) elvers

To determine the relation between swimming endurance time and burst swimming speed, elvers of the European eel, Anguilla anguilla (L.), were made to swim at speeds from 3.6 to 7.2 L (body lengths) s⁻¹ in both fresh and sea water. Swimming endurance time of elvers averaging 7.2 cm total length decreased logarithmically with increased swimming speed from 3.0 min at 3.5 L s⁻¹ to 0.7 min at 5.0 L s⁻¹, and again logarithmically but with a lesser slope to 0.27 min at 7.5 L s⁻¹. No differences were found between fresh and sea water elvers. In still water, elvers could swim at high speeds for about 10–45m before exhaustion, depending upon speed. Elvers would be able to make virtually no progress against water currents >50 cm s⁻¹. Drift in coastal water currents and selective tidal transport probably involve swimming speeds below those tested in this study. Migration into freshwater streams undoubtedly involves avoidance of free stream speeds and a combination of burst and sustained swimming.     

Endurance swimming of diploid and triploid Atlantic salmon

When groups of diploid (mean ±  s . e . fork length, L _F) 33·0 ± 1·4 cm and triploid (35·3 ± 0·5 cm) Atlantic salmon Salmo salar were forced to swim at controlled speeds in a carefully monitored 10 m diameter 'annular' tank no significant difference was found between the maximum sustained swimming speeds ( U _ms, maintainable for 200 min) where the fish swam at the limit of their aerobic capability. Diploids achieved 2·99 body lengths per second (bl s⁻¹)(0·96 m s⁻¹) and triploids sustained 2·91 bl s⁻¹(1·02 m s⁻¹). The selection of fish for the trials was based on their ability to swim with a moving pattern projected from a gantry rotating at the radius of the tank and the selection procedure did not prove to be significant by ploidy. A significant difference was found between the anaerobic capabilities of the fish measured as endurance times at their prolonged swimming speeds. During the course of the experimentation the voluntary swimming speed selected by the fish increased and the schooling behaviour improved. The effect of the curvature of the tank on the fish speeds was calculated (removing the curved effect of the tank increased the speed in either ploidy by 5·5%). Implications of the endurance times and speeds are discussed with reference to the aquaculture of triploid Atlantic salmon.     

Is tilting behaviour at low swimming speeds unique to negatively buoyant fish? Observations on steelhead trout,Oncorhynchus mykiss,and bluegill,Lepomis macrochirus

When swimming at low speeds, steelhead trout and bluegill sunfish tilted the body at an angle to the mean swimming direction. Trout swam using continuous body/caudal fin undulation, with a positive (head-up) tilt angle ( 0 , degrees) that decreased with swimming speed ( u , cm s⁻¹) according to: 0 =(164±96).u^{(−1.14±0.41)} (regression coefficients; mean±2 s.e. ). Bluegill swimming gaits were more diverse and negative (head down) tilt angles were usual. Tilt angle was −3·0 ± 0.9° in pectoral fin swimming at speeds of approximately 0.2–1.7 body length s⁻¹ (Ls⁻¹; 3–24 cm s⁻¹), −4.5 ±2.6° during pectoral fin plus body/caudal fin swimming at 1·2–1·7 L s⁻¹ (17–24cm s⁻¹), and −5.0± 1.0° during continuous body/caudal fin swimming at 1.6 and 2.5 L s⁻¹ (22 and 35cm s⁻¹). At higher speeds, bluegill used burst-and-coast swimming for which the tilt angle was 0.1±0.6°. These observations suggest that tilting is a general phenomenon of low speed swimming at which stabilizers lose their effectiveness. Tilting is interpreted as an active compensatory mechanism associated with increased drag and concomitant increased propulsor velocities to provide better stabilizing forces. Increased drag associated with trimming also explains the well-known observation that the relationship between tail-beat frequency and swimming speed does not pass through the origin. Energy dissipated because of the drag increases at low swimming speeds is presumably smaller than that which would occur with unstable swimming.     

Spring migration strategies of two populations of bar-tailed godwits,Limosa lapponica,in the Wadden Sea: time minimizers or energy minimizers?

Birds can optimize their migration either by minimizing time of transport, energy expenditure, or predation risk during migration. For each of these optimization criteria different fattening and stopover strategies are predicted. The first two of these optimization criteria are examined here for the bar-tailed godwit ( Limosa lapponica ). In the European Wadden Sea two populations of bar-tailed godwits stop over during spring migration between their wintering and breeding areas. The European population winters mainly in Great Britain and the western part of the Wadden Sea and breeds in Fennoscandia. The Afro-Siberian population winters in West Africa and breeds in Siberia. The European wintering population migrates to the eastern parts of Wadden Sea in March where it stays until early May. During this time birds gain 1.9 g d⁻¹ in body mass for a 1500–2000-km non-stop flight to the breeding areas. Afro-Siberian birds stay only for one month in May in the Wadden Sea where they gain on average 9.4 g d⁻¹ in mass for a 4000-km non-stop flight. Intake rates in April/May did not differ between the two populations (1.5 kJ min⁻¹ and 1.8 kJ min⁻¹ for Siberian and European migrants, respectively) but total energy intake was higher for the Siberian migrants, since they spend 50% of the day foraging vs 30% in the European birds. In contrast to European migrants, Afro-Siberian birds start to moult into breeding plumage already in their winter quarters. During their stopover in the Wadden Sea thermostatic costs are lower than at times when European birds are present. Thus, the higher energy demands of the Afro-Siberian birds seem to be fulfilled by a combination of physiological adaptations and a high working level. European birds seem to adopt an energy-minimized migration strategy whereas Afro-Siberian birds appear to follow a time-minimized migration.     

Effects of host-odour plume altitude and changing wind velocity on upwind flight manoeuvres of a specialist braconid parasitoid

Abstract. Females of the specialist parasitoid, Microplitis croceipes (Cresson) (Hymenoptera: Braconidae), were released in a wind tunnel into host-odour plumes dispersed by winds of three velocities and winds whose speed was changed while the wasps were engaged in upwind flight. In steady winds of 61, 122 and 183 cms-^-1, wasps maintained similar 'preferred' ground speeds by adjusting their airspeed, while turning to a lesser degree as wind velocity increased. In winds of changing velocity (either increasing or decreasing within a 60–100 cm s-¹ range), wasps lowered their rate of upwind progress, leading to more tortuous tracks. During changing wind speeds longitudinal image flow decreased. Wasps flying in host-odour plumes 10 cm and 20 cm above the flight tunnel floor in a 122 cm s-¹ wind had similar ground speeds; thus their rate of ventral visual image flow varied two-fold. M.croceipes may 'aim' upwind by comparing how changes in the course angle vary with the direction of visual image flow. During changing wind velocities the relationship between changes in visual and flight muscle generated torque is ambiguous. Under these conditions most wasps cast, a manoeuvre characterized by wide lateral excursions across the wind without upwind progress. Once wind speed stabilizes, flight straightens out and upwind flight resumes.     

Favorable winds speed up bird migration in spring but not in autumn

Wind has a significant yet complex effect on bird migration speed. With prevailing south wind, overall migration is generally faster in spring than in autumn. However, studies on the difference in airspeed between seasons have shown contrasting results so far, in part due to their limited geographical or temporal coverage. Using the first full‐year weather radar data set of nocturnal bird migration across western Europe together with wind speed from reanalysis data, we investigate variation of airspeed across season. We additionally expand our analysis of ground speed, airspeed, wind speed, and wind profit variation across time (seasonal and daily) and space (geographical and altitudinal). Our result confirms that wind plays a major role in explaining both temporal and spatial variabilities in ground speed. The resulting airspeed remains relatively constant at all scales (daily, seasonal, geographically and altitudinally). We found that spring airspeed is overall 5% faster in Spring than autumn, but we argue that this number is not significant compared to the biases and limitation of weather radar data. The results of the analysis can be used to further investigate birds'' migratory strategies across space and time, as well as their energy use.     

The swimming endurance of threespine sticklebacks, Gasterosteus aculeatus L., from the Afon Rheidol, Wales

The endurance of threespine sticklebacks, Gasterosteus aculeatus , swimming with pectoral fin locomotion at 20° C in a laboratory flume was measured. Each trial lasted a maximum of 480 min. At a speed of 4 body lengths per sec (L s⁻¹) all fish were still swimming at the end of the trial, but endurance decreased at higher speeds. At speeds of 5 or 6 L s⁻¹ (20–30 cm s⁻¹) a few fish still maintained labriform locomotion for the 480 min. However, at a speed of 7 L s⁻¹ all fish furled their pectoral fins and used body and caudal fin propulsion but fatigued rapidly. During sustained swimming, fish could cover distances of 6 km or more. No significant differences between males and females were found.     

Sustained swimming speeds and myotomal muscle function in the trout, Salmo gairdneri

Rainbow trout were trained for 3–4 weeks in a flume at swimming speeds of 1, 2 and 3 l s⁻¹. For each experiment growth rates were estimated and by measuring the hypertrophy of red and mosaic skeletal muscle fibres their function was described at particular swimming speeds and compared with earlier experiments on coalfish using the same technique.
Maximum growth, compared with controls in still water, occurred at swimming speeds of 1 l s⁻¹. At this speed the trout mosaic muscle fibres hypertrophied by 40% but the red muscle fibres showed only a 25% hypertrophy. It is suggested that natural swimming speeds are close to 1Ls^−l and the trout mosaic fibres are better adapted for use at this speed in comparison with coalfish white muscle fibres.     

Flight characteristics of birds:

This is the first part of a study on flight characteristics of birds and presents an annotated list of flight speeds of 139 western Palearctic species. All measurements were taken with the same tracking radar and corrected for wind influence according to radar-tracked wind-measuring balloons. Graphical presentation of the birds' air speeds emphasizes the wide variation of speeds within species and allows easy comparison between taxonomic groups, species, and types of flight. Unlike theoretical predictions, speeds increase only slightly with size. The larger species seem to be increasingly limited to speeds close to their speed of minimum power consumption V_mp',. Released birds, apparently reluctant to depart with migratory speed, fly at considerably lower speeds than migrating conspecifics. While large birds seem to be limited to speeds around V _mp', smaller birds seem to be capable of selecting between various speeds, approaching predicted V _mp, when tending to remain airborne at low cost, but flying at much higher speeds when tending to make best progress at low cost (around predicted speed of maximum range V _mr,). Predictions of air speeds by aerodynamic models proved to be too low for small birds because the models do not account for the gain in speed attained by the reduction in profile drag during bounding flight of small passerines. The models predict excessive speeds for large birds because the power output available for flight seems to decline much more with size than previously assumed.     

Faster migration in autumn than in spring: seasonal migration patterns and non‐breeding distribution of Icelandic whimbrels Numenius phaeopus islandicus

Migration is fundamental in the life of many birds and entails significant energetic and time investments. Given the importance of arrival time in the breeding area and the relatively short period available to reproduce (particularly at high latitudes), it is expected that birds reduce spring migration duration to a greater extent than autumn migration, assuming that pressure to arrive into the wintering area might be relaxed. This has previously been shown for several avian groups, but recent evidence from four tracked Icelandic whimbrels Numenius phaeopus islandicus, a long distance migratory wader, suggests that this subspecies tends to migrate faster in autumn than in spring. Here, we 1) investigate differences in seasonal migration duration, migration speed and ground speed of whimbrels using 56 migrations from 19 individuals tracked with geolocators and 2) map the migration routes, wintering and stopover areas for this population. Tracking methods only provide temporal information on the migration period between departure and arrival. However, migration starts with the fuelling that takes place ahead of departure. Here we estimate the period of first fuelling using published fuel deposition rates and thus explore migration speed using tracking data. We found that migration duration was shorter in autumn than in spring. Migration speed was higher in autumn, with all individuals undertaking a direct flight to the wintering areas, while in spring most made a stopover. Wind patterns could drive whimbrels to stop in spring, but be more favourable during autumn migration and allow a direct flight. Additionally, the stopover might allow the appraisal of weather conditions closer to the breeding areas and/or improve body condition in order to arrive at the breeding sites with reserves.     

Testing an emerging paradigm in migration ecology shows surprising differences in efficiency between flight modes

To maximize fitness, flying animals should maximize flight speed while minimizing energetic expenditure. Soaring speeds of large-bodied birds are determined by flight routes and tradeoffs between minimizing time and energetic costs. Large raptors migrating in eastern North America predominantly glide between thermals that provide lift or soar along slopes or ridgelines using orographic lift (slope soaring). It is usually assumed that slope soaring is faster than thermal gliding because forward progress is constant compared to interrupted progress when birds pause to regain altitude in thermals. We tested this slope-soaring hypothesis using high-frequency GPS-GSM telemetry devices to track golden eagles during northbound migration. In contrast to expectations, flight speed was slower when slope soaring and eagles also were diverted from their migratory path, incurring possible energetic costs and reducing speed of progress towards a migratory endpoint. When gliding between thermals, eagles stayed on track and fast gliding speeds compensated for lack of progress during thermal soaring. When thermals were not available, eagles minimized migration time, not energy, by choosing energetically expensive slope soaring instead of waiting for thermals to develop. Sites suited to slope soaring include ridges preferred for wind-energy generation, thus avian risk of collision with wind turbines is associated with evolutionary trade-offs required to maximize fitness of time-minimizing migratory raptors.     

Skylark optimal flight speeds for flying nowhere and somewhere

Flight is energetically very costly. For birds the mechanicalpower in relation to airspeed is characterized by a U-shapedfunction. From this function we can derive optimal flight speedsassociated with minimum power (V_mp), minimum cost of transport(V_mr) and minimum overall time of migration (V_mt). Since flightis energetically so costly, aerial displays and song flightcan potentially serve as signals reliably indicating the individualquality or resource potential of the signaler. In order to maximizethe amount of song flight produced, we expect V_mp during songflight, while during migration we rather expect V_mr or V_mv Wecompared flight speeds of skylarks (Alauda arvensis) duringsong flight and migration flight, respectively. In this speciespredicted V_mp = 5.5 m/s, V_mr = 10.5 m/s, and V_mt = 12.1 m/s.The preferred airspeed during song flight did not differ significantlyfrom the predicted V_mp, while airspeed during migration wassignificantly higher than V_mr and Vmp indicating that flightspeed is a flexible trait that birds adjust to different situations.Why the skylarks speed up so much on migration is still unclear,but it may be that due to the shape of the predicted power curve,variation in cost of transport at high speeds is relativelysmall.