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21.
The acoustic behaviour of Eptesicus serotinus was investigated in the field using a 13.5-m vertical, linear microphone array that allowed for simultaneous recordings at
three different heights and for the calculation of flight altitude and distance from the array. Recordings were made at two
locations that differed in bat species diversity. E. serotinus hunted on average at an altitude of 10.7 m (±2.7) at one location and 6.8 m (±3.6) at the other location. Search signals
were 5–17 ms long depending on flight altitude, and consisted of two to three frequency-modulated harmonics. For bats flying
below 8–10 m altitude, signal duration decreased with decreasing flight altitude, whereas signal interval, terminal frequency,
peak frequency and frequency range of the first harmonic increased. Above 8–10 m flight altitude, the signal parameters were
fairly constant. The –10 dB bandwidth and duty cycle did not change with flight altitude. Source levels were calculated to
between 121 and 125 dB peSPL re 20 μPa at 10 cm. For bats flying higher than 9 m, the microphone placed 1.5 m above the ground
recorded significantly reduced signal durations and frequency ranges of the first harmonic compared to the same signals recorded
with the microphones at heights of 7 or 15 m. We caution the use of ground recordings to fully describe the echolocation signals
of high-flying bats. We demonstrate that flight altitude significantly influences the structure of sonar signals from E. serotinus.
Received: 17 May 1999 / Received in revised form: 20 September 1999 / Accepted: 25 September 1999 相似文献
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David R. Brillinger 《Journal of the American Water Resources Association》1985,21(5):743-756
Fourier inference is a collection of analytic techniques and philosophic attitudes, for the analysis of data, wherein essential use is made of empirical Fourier transforms. This paper sets down some basic results concerning the finite Fourier transforms of stationary process data and then, to illustrate the approach, uses those results to develop procedures for: 1) estimating cloud and storm motion, 2) passive sonar and 3) fitting finite parameter models to nonGaussian time series via bispectral fitting. This last procedure is illustrated by an analysis of a stretch of Mississippi River runoff data. Examples 1), 2) refer to data having the form Y(xj, yj, t) for j = 1, …, J and t = 0, …, T-l say, and view that data as part of a realization of a spatial-temporal process. Such data has become common in geophysics generally and in hydrology particularly. The goal of this paper is to present some new statistical procedures pertinent to problems in the water sciences, equally it is to illustrate the genesis of those procedures and how their properties may be approximated. 相似文献
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