Volume Reverberation 

 Bottom Echo 



School Echo via 

 Bottom Reflection 



Surface Echo via 



Bottom Reflection 



FHU'RK 1. — Illustration of bottom bounce technique geometry and typical time-amplitude graph of 



sonar echo. 



either mud or mud and sand in the operating areas , 

 (Revelle and Shepard 1939:247), but no bottom 

 samples were taken. Relative to that over a flat 

 bottom, performance appeared to be slightly im- 

 proved in areas with a gentle slope, presumably 

 because of a change in bottom composition or 

 roughness. Schools were easily detected when sur- 

 face waves were <3-5 ft, but acoustic measure- 

 ments became more difficult when the wind in- 

 creased in strength and whitecaps were formed. 

 This was partly due to uncertainties in the precise 

 location of the surface reflection which is used as a 

 reference in determining target depth. The sur- 

 face reflection was substantially more diffuse 

 when moderate numbers of whitecaps were visi- 

 ble. This effect may have been due to increased 

 surface scattering and absorption by small air 

 bubbles entrained by wave action near the sur- 

 face. Although we made no direct measurements 

 of school target strengths, our best estimates 

 range between -5 dB and +10 dB for side aspect 

 target strengths of the schools studied. These es- 

 timates are based on earlier measurements made 

 for schools similar in size and suspected composi- 

 tion ( Larsen' ). Ventral aspect target strengths are 

 possibly 3-6 dB less (Love 1977) based on mea- 

 surements for individuals rather than schools. 



'Larsen, H. 1974. Distributions of target strengths and 

 horizontal dimensions for aggregations and schools of marine 

 organisms. Tracor Doc No T74-SD-1054-U. 66 p. 



Results antl Discussion 



Examination of the bottom bounce data for the 

 depth distribution of schools (Figure 2) revealed 

 an apparent preference of the schools for depths 

 near the seasonal thermocline. The accumulation 

 of the number of observations per depth interval, 

 when normalized to achieve a display with a unit 

 area under the curve, is one means of estimating 

 the probability density function (p.d.f.) for a quan- 

 tity such as school mean depth (Feller 1971:36). 

 The most probable value (depth, thickness) of a 

 random variable is defined as the value of the 

 quantity at the largest peak in its p.d.f. (Papoulis 

 1965:140). Though the thermocline was less well 

 defined in May than in December and September, 

 the most probable depth at which a school was 

 found in each survey generally coincided with the 

 ma.ximum thermal gradient (Table 1; Figure 2a, f, 

 k). In order to quantify the apparent relation of 

 fish school distribution and the thermal profile, 

 the mean depth of each school was determined. 

 The data were sorted into 10 m depth intervals. 

 Because of the sonar's beam shape, the volume 

 searched by the bottom bounce procedure varied 

 for a given school depth interval as the bottom 

 depth changed. For a bottom depth of 300 m, about 

 40'/^ more water was searched for schools at 5 m 

 depth than for schools at 150 m. The number of 

 schools observed during each survey in a particu- 

 lar depth interval (Figure 2a, f, k) was normalized 



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