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Predicting spatial patterns of eagle migration using a mesoscale atmospheric model: a case study associated with a mountain-ridge wind development

Overview of attention for article published in International Journal of Biometeorology, January 2013
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Title
Predicting spatial patterns of eagle migration using a mesoscale atmospheric model: a case study associated with a mountain-ridge wind development
Published in
International Journal of Biometeorology, January 2013
DOI 10.1007/s00484-012-0620-0
Pubmed ID
Authors

B. Ainslie, N. Alexander, N. Johnston, J. Bradley, A. C. Pomeroy, P. L. Jackson, K. A. Otter

Abstract

High resolution numerical atmospheric modeling around a mountain ridge in Northeastern British Columbia (BC), Canada was performed in order to examine the influence of meteorology and topography on Golden Eagle migration pathways at the meso-scale (tens of km). During three eagle fall migration periods (2007-2009), local meteorological conditions on the day of peak bird counts were modeled using the Regional Atmospheric Modeling System (RAMS) mesoscale model. Hourly local surface wind speed, wind direction, temperature, pressure and relative humidity were also monitored during these migration periods. Eagle migration flight paths were observed from the ground and converted to three-dimensional tracks using ArcGIS. The observed eagle migration flight paths were compared with the modeled vertical velocity wind fields. Flight tracks across the study area were also simulated using the modeled vertical velocity field in a migration model based on a fluid-flow analogy. It was found that both the large-scale weather conditions and the horizontal wind fields across the study area were broadly similar on each of the modeled migration days. Nonetheless, the location and density of flight tracks across the domain varied between days, with the 2007 event producing more tracks to the southwest of the observation location than the other 2 days. The modeled wind fields suggest that it is not possible for the eagles to traverse the study area without leaving updraft regions, but birds do converge on the locations of updrafts as they move through the area. Statistical associations between observed eagles positions and the vertical velocity field suggest that to the northwest (and to a lesser extent the southwest) of the main study ridge (Johnson col), eagles can always find updrafts but that they must pass through downdraft regions in the NE and SE as they make their way across the study area. Finally, the simulated flight tracks based on the fluid-flow model and the vertical velocity fields are in general agreement with the observed flight track patterns. Our results suggest that use of high resolution meteorological fields to locate the occurrence of updrafts in proposed ridge-line wind installations could aid in predicting, and mitigating for, convergence points in raptor migrations.

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Geographical breakdown

Country Count As %
United States 2 4%
Israel 1 2%
Mexico 1 2%
Germany 1 2%
Unknown 43 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 27%
Student > Ph. D. Student 10 21%
Other 6 13%
Student > Master 6 13%
Professor 2 4%
Other 3 6%
Unknown 8 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 44%
Environmental Science 11 23%
Unspecified 1 2%
Earth and Planetary Sciences 1 2%
Sports and Recreations 1 2%
Other 4 8%
Unknown 9 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 February 2014.
All research outputs
#15,294,762
of 22,745,803 outputs
Outputs from International Journal of Biometeorology
#979
of 1,292 outputs
Outputs of similar age
#184,030
of 284,783 outputs
Outputs of similar age from International Journal of Biometeorology
#18
of 21 outputs
Altmetric has tracked 22,745,803 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,292 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.