Data from: Soaring across continents: decision-making of a soaring migrant under changing atmospheric conditions along an entire flyway

Vansteelant W, Shamoun-Baranes J, McLaren JD, van Diermen J, Bouten W

Date Published: December 7, 2016

DOI: http://dx.doi.org/10.5061/dryad.bp70s

 

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Title Flight measurements, wind data and theoretical speeds for thermal-soaring Honey Buzzards
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Description Honey Buzzards were tracked with high-resolution GPS-loggers, measuring 3D positions every 10 seconds during two cycles of 30 minutes each on every day spent on migration during autumn 2012 and spring 2013. Based on running average of vertical speeds we distinguished climbing from gliding events. We then extracted the location, altitude and time at which birds started/ended each climb and each glide, and created one record for every climbing-gliding cycle that was completely covered by high-resolution measurements. Based on these data we calculated distances travelled, track direction, altitude gained/lost, duration, ground speeds, climb/sink rates from the start to the end of every climb, of every glide and across every full climbing-gliding cycle. We then determined wind conditions to the start of each glide by linearly interpolating wind estimates from the ECMWF deterministic forecast model (2.5x2.5 degrees, 3 hour resolution). By combining tracking data with wind data we could determine determine the heading and air speed achieved during every climb, glide and climbing-gliding cycle. Finally, we generated an aerodynamic model of a Honey Buzzard in thermal-soaring flight based following Pennycuick 2008 (see also original paper) to compute the theoretical minimum-sink speed (Vms), optimal air speed (Vopt), best-gliding air speed (Vbg) and best-gliding air speed in head-/tailwinds (Vbgw) for a Honey Buzzard (assuming mass = 1kg, wing span = 1.3m, wing area = 0.26m-squared, other parametrizations see Vansteelant et al. 2016). By comparing real gliding air speeds (Va) with theoretical benchmarks for time-optimal (Vopt) and risk-averse (Vbgw) flight, we calculated a measure of risk-averison (RAFI). All calculations were implemented in R version 3.1. Detailed descriptions of all columns are provided in the readme.txt file. Note that all distance are measured in meters, time differences in seconds and speeds are noted in meters per second.
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When using this data, please cite the original publication:

Vansteelant WMG, Shamoun-Baranes J, McLaren J, van Diermen J, Bouten W (2017) Soaring across continents: decision-making of a soaring migrant under changing atmospheric conditions along an entire flyway. Journal of Avian Biology 48(6): 887-896. http://dx.doi.org/10.1111/jav.01298

Additionally, please cite the Dryad data package:

Vansteelant W, Shamoun-Baranes J, McLaren JD, van Diermen J, Bouten W (2017) Data from: Soaring across continents: decision-making of a soaring migrant under changing atmospheric conditions along an entire flyway. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.bp70s
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