| Literature DB >> 22558166 |
Adam E Duerr1, Tricia A Miller, Michael Lanzone, Dave Brandes, Jeff Cooper, Kieran O'Malley, Charles Maisonneuve, Junior Tremblay, Todd Katzner.
Abstract
To maximize fitness, flying animals should maximize flight speed while minimizing energetic expenditure. Soaring speeds of large-bodied birds are determined by flight routes and tradeoffs between minimizing time and energetic costs. Large raptors migrating in eastern North America predominantly glide between thermals that provide lift or soar along slopes or ridgelines using orographic lift (slope soaring). It is usually assumed that slope soaring is faster than thermal gliding because forward progress is constant compared to interrupted progress when birds pause to regain altitude in thermals. We tested this slope-soaring hypothesis using high-frequency GPS-GSM telemetry devices to track golden eagles during northbound migration. In contrast to expectations, flight speed was slower when slope soaring and eagles also were diverted from their migratory path, incurring possible energetic costs and reducing speed of progress towards a migratory endpoint. When gliding between thermals, eagles stayed on track and fast gliding speeds compensated for lack of progress during thermal soaring. When thermals were not available, eagles minimized migration time, not energy, by choosing energetically expensive slope soaring instead of waiting for thermals to develop. Sites suited to slope soaring include ridges preferred for wind-energy generation, thus avian risk of collision with wind turbines is associated with evolutionary trade-offs required to maximize fitness of time-minimizing migratory raptors.Entities:
Mesh:
Year: 2012 PMID: 22558166 PMCID: PMC3338847 DOI: 10.1371/journal.pone.0035548
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Energy demands of flight.
Energy demands of flapping flight increase with body mass (E = M1.17; [13]) more rapidly than do basal metabolic rate (BMR = M0.78; [16]) or energy demands of soaring/gliding (2× BMR; [14], [15]). Schematic shows these relationships, assuming constant body and wing shape, size and wing loading.
Figure 2Altitude and topography of flight types.
Flight modes were manually classified based upon flight patterns, changes in flight altitude, and underlying topography for locations of golden eagles during spring migration 2009–2010. A) Thermal soaring includes points (triangles) that are closely spaced with increasing altitude. B) Gliding points (circles) connect flight segments of thermal soaring, with points decreasing in altitude. C) Slope soaring segments include locations (squares) along ridgelines that are close to ground level (less than 200 m). The background map shows topographic relief with darkened slopes of ridgelines.
Figure 3Progress path and progress distance.
The progress path is the straight line that connects the first and last points that a satellite tag recorded for each golden eagle as it migrated from the 39.5° to the 42.5° north latitude. For each flight segment, the progress distance is the distance along the progress path defined by the latitudes of the start and end points of the segment. The progress speed is the quotient of the progress distance for the segment and the time an eagle spent traveling along the actual path of the segment.
Mean ± s.e. ground and progress speeds for flight modes used by five golden eagles migrating through Pennsylvania during spring migration, 2009–2010.
| Speed | Mean raw speed (m s−1) | Mean modeled speed (m s−1) | |
| Ground | Thermal soaring | 10.45±0.80 | 10.26±0.82 |
| Slope soaring | 10.90±0.87 | 11.49±0.95 | |
| Thermal soaring & gliding | 14.24±0.78 | 14.48±0.82 | |
| Gliding | 18.07±1.39 | 18.04±0.82 | |
| Progress | Thermal soaring | 1.87±1.54 | 4.73±0.74 |
| Slope soaring | 7.35±0.96 | 7.79±1.01 | |
| Thermal soaring & gliding | 9.59±1.08 | 11.72±0.74 | |
| Gliding | 17.32±1.44 | 17.61±0.75 |
Raw speeds are the average of speeds measured for each bird (empirical estimates). Modeled speeds are predictions from linear mixed models (see table 1). N = 5 in all cases.
Model parameters ± s.e. and statistics for effects that influence ground and progress speed (m s−1) of golden eagles as they passed through the central Appalachians during spring migration, 2009–2010.
| Speed | Intercept | Gliding | AGL | Slope soaring | |
| (m s−1) | (m) | (m s−1) | |||
| Ground | Model coefficients | 8.910±0.847 | 7.020±0.284 | 0.002±0.001 | 2.070±0.543 |
|
| - | 610.75 | 43.49 | 14.56 | |
|
| - | <0.0001 | <0.0001 | 0.0002 | |
| Progress | Model coefficients | 2.244±0.796 | 11.471±0.433 | 0.005±0.001 | 4.605±0.816 |
|
| - | 701.51 | 70.26 | 31.86 | |
|
| - | <0.0001 | <0.0001 | <0.0001 |
Intercept term includes values for thermal soaring.
Altitude above ground level.
Variance-covariance matrices for each model are given in Table S1.
Means ± se of predictor variables and time measures for flight modes used by five golden eagles that migrated through Pennsylvania during spring, 2009–2010.
| Flight mode | No. flight segments | Altitude above ground level (m) | Slope (deg) | Time per segment (s) | Proportion of total time |
| Thermal soaring | 261 | 541±76.5 | 11.4±1.05 | 158±29.4 | 0.411±0.045 |
| Slope soaring | 41 | 204±29.1 | 17.3±1.56 | 223±63.2 | 0.102±0.039 |
| Gliding | 276 | 846±118 | 10.6±0.56 | 187±33.1 | 0.487±0.041 |
For reference only, n = 5 eagles for all measures.