Migration by soaring or flapping: numerical atmospheric simulations reveal that turbulence kinetic energy dictates bee-eater flight mode

Abstract

Aerial migrants commonly face atmospheric dynamics that may affect their movement and behaviour. Specifically, bird flight mode has been suggested to depend on convective updraught availability and tailwind assistance. However, this has not been tested thus far since both bird tracks and meteorological conditions are difficult to measure in detail throughout extended migratory flyways. Here, we applied, to our knowledge, the first comprehensive numerical atmospheric simulations by mean of the Regional Atmospheric Modeling System (RAMS) to study how meteorological processes affect the flight behaviour of migrating birds. We followed European bee-eaters (Merops apiaster) over southern Israel using radio telemetry and contrasted bird flight mode (flapping, soaring -gliding or mixed flight) against explanatory meteorological variables estimated by RAMS simulations at a spatial grid resolution of 250 Â 250 m 2 . We found that temperature and especially turbulence kinetic energy (TKE) determine bee-eater flight mode, whereas, unexpectedly, no effect of tailwind assistance was found. TKE during soaring -gliding was significantly higher and distinct from TKE during flapping. We propose that applying detailed atmospheric simulations over extended migratory flyways can elucidate the highly dynamic behaviour of air-borne organisms, help predict the abundance and distribution of migrating birds, and aid in mitigating hazardous implications of bird migration.

Commuting fruit bats beneficially modulate their flight in relation to wind

“…Recently, high-resolution atmospheric simulations have been applied to study how meteorological conditions may shape the soaring behaviour of migrating birds [10,15]. Our study demonstrates the advantages of using detailed atmospheric modelling and rigorously tests predictions related to the effects of external factors (wind vectors) on commuting flyers.…”

“…Model steps were calculated every minute, and modelled wind data were spatially and temporally matched to each bat's location and averaged over every 5 min of the bat's commuting flight. Because no wind data were available from the study area, we report error estimates from a different application of RAMS [15]. Based on these error estimates, 95% of the wind data estimates are within 0.7 m s 21 of their actual value, with up to 2.4 m s 21 difference under strong (8 m s 21 ) but rare winds.…”

“…In addition, we calculated the relationship between bat ground speed and the crosswind and tailwind velocities to assess whether strong crosswinds and headwinds incurred slower progress towards the destination. To correct for the unequal sample size from different individuals, the data from each bat were weighted based on the inverse proportion of that bat's sample size from the total data from all the bats [15,34,35]. We additionally report the results of the unweighted regression.…”

“…The ability to correctly determine wind direction and speed is critical for inferring animal flight performance, because optimal movement in relation to wind may involve changes in airspeed (speed relative to air), and modulation of this response when the wind is blowing from different directions relative to the heading [13]. Consequently, wind must be estimated at high spatial and temporal resolution to match the relevant scales affecting the flying organisms [14], as has been successfully done in recent studies of bird migration [10,15].…”

Use of multiple modes of flight subsidy by a soaring terrestrial bird, the golden eagleAquila chrysaetos, when on migration

“…[10][11][12]; but see [13] for an exception). However, it is long established that many species use multiple modes of subsidized flight [14].…”