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16 results for “flight speed”
Fine-scale changes in speed and altitude suggest protean movements in homing pigeon flights
<p>The power curve provides a basis for predicting adjustments that animals make in flight speed, for example in relation to wind, distance, habitat foraging quality and objective. However, relatively few studies have examined how animals respond to the landscape below them, which could affect speed and power allocation through modifications in climb rate and perceived predation risk. We equipped homing pigeons (<i>Columba livia</i>) with high-frequency loggers to examine how flight speed, and hence effort, varies in relation to topography and land cover. Pigeons showed mixed evidence for an energy-saving strategy, as they minimized climb rates by starting their ascent ahead of hills, but selected rapid speeds in their ascents. Birds did not modify their speed substantially in relation to land cover, but used higher speeds during descending flight, highlighting the importance of considering the rate of change in altitude before estimating power use from speed. Finally, we document an unexpected variability in speed and altitude over fine scales; a source of substantial energetic inefficiency. We suggest this may be a form of protean behaviour adopted to reduce predation risk when flocking is not an option, and that such a strategy could be widespread.</p>
Vertical profiles and integrated time series of bird density and flight speed vector (19.09.2016-10.10.2016)
<p><strong>Description</strong></p> <p>This dataset contains the vertical profiles and integrated time series of bird density and flight speed (NS and EW) used in Nussbaumer (2019) [open access: <a href="https://www.mdpi.com/2072-4292/11/19/2233">https://www.mdpi.com/2072-4292/11/19/2233</a>]. Data are stored in a JavaScript Object Notation (JSON) file for each radar, with the following structure:</p> <pre><code>{ "name" : "bejab", //code name of the radar (http://eumetnet.eu/wp-content/themes/aeron-child/observations-programme/current-activities/opera/database/OPERA_Database/index.html) "lat" : 51.1917, //Latitude "lon" : 3.0642, //Longitude "height" : 50, //Height of the radar antenna [m] a.s.l. "maxrange" : 25, //Maximum range [km] used for profile "alt" : [100, 300,...], "time" : ["19-Sep-2016 00:00:00", "19-Sep-2016 00:05:00",...], "dens" : [[...],...], //Vertical profile of bird density [1/km3] "u" : [[...],...], //Vertical profile of bird flight speed in East(+)/West(-) [m/s] "v" : [[...],...], //Vertical profile of bird flight speed in North(+)/South(-) [m/s] "denss" : [...], //Integrated profile of bird density [1/km2] "us" : [...], //Integrated profile of bird flight speed in East(+)/West(-) [m/s] "vs" : [...], //Integrated profile of bird flight speed in North(+)/South(-) [m/s] }</code></pre> <p> </p> <p><strong>Procedure</strong></p> <p>The raw data are downloaded on the <a href="http://enram.github.io/data-repository/">ENRAM repository</a>,( see Dokter (2011) and (2019) for more details) and processed according to the procedure described below.</p> <ol> <li>Of the 84 radars contributing data during the study period, 11 radars are discarded because of their poor quality due to S-band radar type, poor processing or large gaps (temporal or altitude cut). The same radars were removed in Nilsson et al. (2019).In addition, the 4 radars from Bulgaria and Portugal were excluded because of their geographic isolation.</li> <li>The full vertical profile was discarded when rain was present at any altitude bin. A dedicated MATLAB GUI was used to visualise the data and manually set bird densities to “not-a-number” in such cases. </li> <li>Zones of high bird densities can sometimes be incorrectly eliminated in the raw data. To address this, Nilsson et al. (2019) excluded problematic time or height ranges from the data. Here, in order to keep as much data as possible, the data was manually edited to replace erroneous data either with “not-a-number”, or by cubic interpolation using the dedicated MATLAB GUI.</li> <li>Due to ground scattering,the lower altitude layers are sometimes contaminated by errors or excluded in the raw data. We vertically interpolated bird density by copying the first layer without error into to the lower ones. This approach is relatively conservative as bird migration intensity usually decreases with height in the absence of obstacles, and more so in autumn (Bruderer, 2018)</li> <li>The vertical profiles are vertically integrated from the radar altitude and up to 5000 m asl.</li> <li>The data recorded during daytime are excluded. Daytime is defined at each radar by the civil dawn and dusk (6° below horizon).</li> <li>Finally, the data of 10 radars with high temporal resolution (5-10minutes) was down-sampled to 15 minutes to preserve a balanced representation of each radar.</li> </ol> <p>The resulting cleaned vertical-integrated time series of nocturnal bird density can be viewed in vp_corrected.zip.</p> <p>More details and illustrations are available in Nussbaumer (2019) [open access: <a href="https://www.mdpi.com/2072-4292/11/19/2233">https://www.mdpi.com/2072-4292/11/19/2233</a>], </p> <p><strong>Acknowledgement</strong></p> <p>We acknowledge the <a href="http://eumetnet.eu/activities/observations-programme/current-activities/opera/">European Operational Program for Exchange of Weather Radar Information (EUMETNET/OPERA)</a> for providing access to European radar data, faciliated through a research-only license agreement between EUMETNET/OPERA members and <a href="http://enram.eu/">ENRAM</a>.</p> <p> </p> <p><strong>References</strong></p> <p>Bruderer, B.; Liechti, F. Variation in density and height distribution of nocturnal migration in the south of israel. <em>Israel Journal of Zoology</em> <strong>1995</strong>, <em>41</em>, 477–487. <a href="http://doi.org/10.1080/00212210.1995.10688815">doi:10.1080/00212210.1995.10688815</a>.</p> <p>Dokter A. M. , F. Liechti, H. Stark, L. Delobbe, P. Tabary, and I. Holleman, “Bird migration flight altitudes studied by a network of operational weather radars,” <em>J. R. Soc. Interface</em>, vol. 8, no. 54, pp. 30–43, Jan. <strong>2011</strong>. <a href="http://doi.org/10.1098/rsif.2010.0116">doi:10.1098/rsif.2010.0116</a></p> <p>Dokter A. M. , P. Desmet, J. H. Spaaks, S. van Hoey, L. Veen, L. Verlinden, C. Nilsson, G. Haase, H. Leijnse, A. Farnsworth, W. Bouten, and J. Shamoun‐Baranes, “bioRad: biological analysis and visualization of weather radar data,” <em>Ecography </em>(Cop.)., vol. 42, no. 5, pp. 852–860, May <strong>2019</strong>. <a href="http://doi.org/10.1111/ecog.04028">doi: 10.1111/ecog.04028</a></p> <p>Nilsson, C.; Dokter, A.M.; Verlinden, L.; Shamoun-Baranes, J.; Schmid, B.; Desmet, P.; Bauer, S.; Chapman, J.; Alves, J.A.; Stepanian, P.M.; Sapir, N.;Wainwright, C.; Boos, M.; Górska, A.; Menz, M.H.M.; Rodrigues, P.; Leijnse, H.; Zehtindjiev, P.; Brabant, R.; Haase, G.; Weisshaupt, N.; Ciach, M.; Liechti, F. Revealing patterns of nocturnal migration using the European weather radar network. <em>Ecography </em><strong>2019</strong>, <em>42</em>, 876–886. <a href="http://doi.org/10.1111/ecog.04003">doi:10.1111/ecog.04003</a>.</p> <p>Nussbaumer R., L. Benoit, G. Mariethoz, F. Liechti, S. Bauer, and B. Schmid, “A Geostatistical Approach to Estimate High Resolution Nocturnal Bird Migration Densities from a Weather Radar Network,” <em>Remote Sens</em>., vol. 11, no. 19, p. 2233, Sep. <strong>2019</strong>. <a href="https://www.mdpi.com/2072-4292/11/19/2233">doi: 10.3390/rs11192233</a></p> <p> </p> <p> </p>
Data for: Experimental elevated temperature affects bumblebee foraging and flight speed
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Fine-scale changes in speed and altitude suggest protean movements in homing pigeon flights
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Data from: Age dominates flight distance and duration, while body size shapes flight speed in Bombus terrestris L. (Hymenoptera: Apidae)
<p>Flight plays crucial role in the fitness of insect pollinators, such as bumble bees. Despite their relatively large body size compared to their wings, bumble bees can fly under difficult ambient conditions, such as cooler temperatures. While their body size is often positively linked to their foraging range and flight ability, the influence of age remains less explored. Here, we studied the flight performance (distance, duration, and speed) of aging bumble bee workers using tethered flight mills. Additionally, we measured their intertegular distance (ITD) and dry mass as proxies for their body size. We found that flight distance and duration was predominantly influenced by age, challenging assumptions that age does not play a key role in foraging and task allocation. From the age of 7 to 14 days, flight distance and duration increased six-fold and five-fold, respectively. Conversely, body size primarily impacted the maximum and average flight speed of workers. Our findings indicate that age substantially influences flight distance and duration in bumble bee workers, affecting foraging performance and potentially altering task allocation strategies. This underscores the importance of considering individual age and physiological changes alongside body size/mass in experiments involving bumble bee workers.</p>
Low conversion efficiency of flight power increases with speed in the migratory bat Nathusius' pipistrelle
<p>The efficiency with which flying animals convert metabolic fuel to mechanical power dictates an individual's flight behaviour and energy requirements. Despite the significance of this parameter, we lack empirical data on conversion efficiency for most species. Furthermore, the assumption that efficiency is constant across flight speeds has yet to be empirically confirmed, revealing a major outstanding question in animal flight. We show, through direct measurements of metabolic and aerodynamic power, that conversion efficiency in the migratory bat (<em>Pipistrellus nathusii</em>) increases with flight speed between 7.0 and 10.4%. Our findings suggest that peak conversion efficiency in this species occurs near maximum range speed, where the cost of transport is minimized. A meta-analysis of 16 bird and 8 bat species revealed a strong scaling relationship between estimated conversion efficiency and body mass, with no discernible differences between bats and birds. This has profound consequences for modelling flight behaviour as estimates assuming 23% efficiency underestimate flight costs for <em>P. nathusii</em> by almost 50% on average (36-62%). Our findings suggest that conversion efficiency may vary around an ecologically relevant optimum speed and provides a crucial baseline for investigating how this may drive the variation in conversion efficiency between species.</p>
Data from: Age dominates flight distance and duration, while body size shapes flight speed in Bombus terrestris L. (Hymenoptera: Apidae)
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Low conversion efficiency of flight power increases with speed in the migratory bat Nathusius’ pipistrelle
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Data from: Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction
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Data from: A global review of Procellariiform flight height, flight speed and nocturnal activity: Implications for offshore wind farm collision risk
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Data from: Carrying a logger reduces escape flight speed in a passerine bird, but relative logger mass may be a misleading measure of this flight performance detriment
1. The recent boost in bird migration studies following the development of various tracking devices raised awareness of how detrimental attaching devices can be for animals. Such effects can occur during migration, but also immediately post-release if the device impairs escape flight performance and, consequently, the bird's ability to evade predators. 2. In this study, we investigated the effect of carrying a device on the escape flight speed and aerodynamic force production in a migratory passerine. We recorded upward-directed escape flights of 15 male blackcaps. Each individual was tested without a tag, and when equipped with three different leg-loop dummy tags with masses representing around 3%, 5% and 7% of their body mass. The experiment was designed such that all individuals passed through all treatments in a randomized order. 3. We found that two factors affected flight speed in roughly equal amounts: first, tagged escape flights had lower flight speeds compared to the control flights, irrespective of tag mass. Second, we found an effect of the total mass, i.e. the sum of the masses of the individual bird and of the tag, with heavier birds being slower. In contrast, flight speed was not correlated with relative tag mass in percentage of body mass, the metric commonly used in ethical guidelines for tag attachment. Aerodynamic flight force production also depended on total mass, with heavier birds producing higher forces. But these flight forces did not differ between flights with or without a tag. 4. We conclude that, when tagging birds, it is misleading to choose heavy individuals for tagging in order to minimize the tag mass as a percentage of body mass. This is particularly relevant in species for which body mass is not necessarily related to size, like migratory birds that accumulate large fat reserves. The lower escape speed in "tagged" flights could not be explained by differences in net flight force production, because these did not differ between flights with and without a tag. This suggests that the tag also affected pre-flight take-off dynamics, possibly due to a leg harness-induced reduction in leg push-off performance.
Data from: Mechanical power curve measured in the wake of pied flycatchers indicate modulation of parasite power across flight speeds
How aerodynamic power required for animal flight varies with flight speed determines optimal speeds during foraging and migratory flight. Despite its relevance, aerodynamic power provide an elusive quantity to measure directly in animal flight. Here we determine the aerodynamic power from wake velocity fields, measured using tomographical particle image velocimetry, of pied flycatchers flying freely in a wind tunnel. We find a shallow U-shaped power curve, which is flatter than expected by theory. Based on how the birds vary body angle with speed, we speculate that the shallow curve result from increased body drag coefficient and body frontal area at lower flight speeds. Including modulation of body drag in the model results in a more reasonable fit with data than the traditional model. From the wake structure we also find a single starting vortex generated from the two wings during the downstroke across flight speeds (1-9 m/s). This is accomplished by the arm wings interacting at the beginning of the downstroke, generating a unified starting vortex above the body of the bird. We interpret this as a mechanism resulting in uniform downwash and low induced power, which can help explain the higher aerodynamic performance in birds compared to bats.
Data from: Mechanical power curve measured in the wake of pied flycatchers indicate modulation of parasite power across flight speeds
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Data from: Carrying a logger reduces escape flight speed in a passerine bird, but relative logger mass may be a misleading measure of this flight performance detriment
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Data from: Octopaminergic modulation of the visual flight speed regulator of Drosophila
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A typical result from the high-speed camera HSC for the flight trajectory of a 7 mm diameter projectile propelled from the explosion of 10 g C4 at the entrance of the explosive driven shock tube
<p>The video shows a typical result from the high-speed camera HSC for the flight trajectory of a 7 mm diameter projectile propelled from the explosion of 10 g C4 at the entrance of the explosive driven shock tube. The video depict the magnitude of the displacement which represents the distortion of the air density due to the passage of the shock wave. The displacement is shown in colors where red represents the highest values. The main features of the flow field around the supersonic freely flying projectile, such as the spherical and the detached shock wave in its front are captured with a good spatial resolution. </p>
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