Flying with the wind: scale dependency of speed and direction measurements in modelling wind support in avian flight

Movement Ecology

Gil Bohrer⁹  Martin Wikelski⁴  Roland Kays¹  Daniel Bengtsson⁶  Jonas Waldenström⁶  Scott H Newman⁵  John Y Takekawa⁸  Carolina Proaño⁴  Sebastian Cruz⁴  David Cabot⁷  Eileen C Rees²  Larry Griffin²  Rolf Weinzierl³  Bart Kranstauber⁴  Kamran Safi⁴ 

[1] School of Natural Resources, North Carolina State University, 3118 Jordan Hall, Raleigh, NC, 27695, USA;Wildfowl & Wetlands Trust, Slimbridge, Gloucestershire, GL2 7BT, UK; , Am Fügsee 29, Seehausen am Staffelsee, 82418, Germany;Department of Biology, University of Konstanz, Konstanz, 78464, Germany;Emergency Center for Transboundary Animal Diseases, Animal Production and Health Division, Food & Agriculture Organization of the United Nations, Rome, 00153, Italy;Centre for Ecology and Evolution in Microbial Model Systems (EEMiS), Linnaeus University, Kalmar, SE-391 82, Sweden;Environmental Consultancy Services, White Strand, Killadoon, Louisburgh, Westport, Co. Mayo, Ireland;U.S. Geological Survey, Western Ecological Research Center, 505 Azuar Drive, Vallejo, CA, 94592, USA;Department of Civil, Environmental & Geodetic Engineering, The Ohio State University, Columbus, OH, 43210, USA

关键词: Flight speed;    Flight direction;    Measurement error;    Scaling;    Doppler-shift;    Aves;    GPS;    ECMWF;    NOAA;   

Others  :  803025
DOI  :  10.1186/2051-3933-1-4

 received in 2013-01-07, accepted in 2013-05-22,  发布年份 2013

【 摘 要 】

Background

Understanding how environmental conditions, especially wind, influence birds' flight speeds is a prerequisite for understanding many important aspects of bird flight, including optimal migration strategies, navigation, and compensation for wind drift. Recent developments in tracking technology and the increased availability of data on large-scale weather patterns have made it possible to use path annotation to link the location of animals to environmental conditions such as wind speed and direction. However, there are various measures available for describing not only wind conditions but also the bird's flight direction and ground speed, and it is unclear which is best for determining the amount of wind support (the length of the wind vector in a bird’s flight direction) and the influence of cross-winds (the length of the wind vector perpendicular to a bird’s direction) throughout a bird's journey.

Results

We compared relationships between cross-wind, wind support and bird movements, using path annotation derived from two different global weather reanalysis datasets and three different measures of direction and speed calculation for 288 individuals of nine bird species. Wind was a strong predictor of bird ground speed, explaining 10-66% of the variance, depending on species. Models using data from different weather sources gave qualitatively similar results; however, determining flight direction and speed from successive locations, even at short (15 min intervals), was inferior to using instantaneous GPS-based measures of speed and direction. Use of successive location data significantly underestimated the birds' ground and airspeed, and also resulted in mistaken associations between cross-winds, wind support, and their interactive effects, in relation to the birds' onward flight.

Conclusions

Wind has strong effects on bird flight, and combining GPS technology with path annotation of weather variables allows us to quantify these effects for understanding flight behaviour. The potentially strong influence of scaling effects must be considered and implemented in developing sampling regimes and data analysis.

【 授权许可】

   
2013 Safi et al.; licensee BioMed Central Ltd.

【 图 表 】

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