Data from: Soaring across continents: decision-making of a soaring migrant under changing atmospheric conditions along an entire flyway
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https://datadryad.org/dataset/doi:10.5061/dryad.bp70s
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(1) 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. (2) 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 (Vopt). 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
(Vbgw). (3) Honey Buzzards were gliding on average 2.05 ms-1 slower than
Vopt and 3.42 ms-1 faster than Vbgw while they increased air speeds with
climb rates and reduced air speeds in tailwinds. They adopted flexible
flight strategies gliding mostly near Vbgw under poor soaring conditions
and closer to Vopt in good soaring conditions. (4) 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 Vopt during most
of their journeys, probably taking time to navigate, orientate and locate
suitable thermals, especially in areas with poor thermal convection. (5)
Linking novel tracking techniques with optimal migration models clarifies
the way birds balance different trade-offs during migration.
提供机构:
Dryad
创建时间:
2016-12-07



