Tracking herring schools with a high resolution sonar. Variations in horizontal area and relative echo intensity

ICES Journal of Marine Science, 55: 58 66. 1998 Tracking herring schools with a high resolution sonar. Variations in horizontal area and relative echo intensity Ole Arve Misund, Anders Fernö, Tony Pitcher, and Bjørn Totland Misund, O. A., Fernö, A., Pitcher, T., and Totland, B. 1998. Tracking herring schools with a high resolution sonar. Variations in horizontal area and relative echo intensity. ICES Journal of Marine Science, 55: 58 66. Fourteen herring schools off northern Norway were tracked for about 1 hour each by the 95 khz Simrad SA950 sonar onboard R/V G.O. Sars in May 1994. The sonar was connected to a work station that contained software for reading the echo telegrams of the sonar, printing of an echogram, automatic detection and measurement of schools, and logging of the sonar data. The horizontal area and relative echo intensity of the schools were recorded ping by ping as well as swimming depth and distance and bearing to the vessel. The position, speed and heading of the vessel were also recorded. Inter- and intra-school events as interpreted from the sonar display were recorded in a separate protocol during the school tracking. The recorded horizontal area and relative echo intensity of the schools varied considerably. Linear models with school area or relative echo intensity as dependent variables, and with range, tilt, speed and swimming angle relative to the sonar beam as continuous effects, did not explain more than 15% and 30% of the observed variations for most schools, respectively. There was a negative correlation between relative echo intensity and range for all schools. Inter- and intra-school events occurred at average rates of about 14 minutes, and inter-school events such as split and joint influenced school size. The sound absorption and the degree to which the sonar beam insonifies the schools in the vertical plane are proposed as the major sources of variation for recorded horizontal area and relative echo intensity of the schools. 1998 International Council for the Exploration of the Sea Key words: sonar, schools, school area, echo intensity, herring. Received 7 May 1996; accepted 1 March 1997. O. A. Misund and B. Totland: Institute of Marine Research, P.O. Box 1870, Bergen N-5024, Norway. A. Fernö: Department of Fisheries and Marine Biology, University of Bergen, Bergen N-5020, Norway. T. Pitcher: Fisheries Centre, University of British Columbia, 2204 Main Mall, Vancouver, BC V6T 1Z4, Canada. Corresponding author: O. A. Misund, tel: +47 55 23 85 00; fax: +47 22 23 68 30; email: ole.misund@imr.no Introduction Abundance estimation of pelagic fish stocks with high resolution sonar is under development (Misund, 1993). Acoustic abundance estimation using sonar has two advantages compared with traditional methods using echosounders; the sonar covers a much greater volume, and errors in connection with avoidance of the vessel by pelagic fish schools close to the surface are negligible. All acoustic methods are, however, subject to considerable variations in the echo of fish (MacLennan and Simmonds, 1992). If we are to use sonar as a standard method in abundance estimation, it is crucial that the variations be investigated in detail and that the most important errors are corrected for. The variations in backscattered echo intensity are connected both to the properties of sound transmission and reflection and by variations in fish behaviour. The variation can be divided into three sources (Fig. 1). The first possible source of error is connected to acoustics. There exists an inverse relationship between density and horizontal area of a school and the sonar equation assumes a certain relationship between fish density and echo intensity. The sonar equation also compensates for an acoustic target generating less echo with increasing distance. To what extent the applied compensation is correct for a sonar beam guided nearly horizontally has, however, not been systematically studied. Another source of variation in the back scattered echo intensity of schools is connected to changes in aspect angle of the 1054 3139/98/010058+09 $25.00/0/jm970228 1998 International Council for the Exploration of the Sea

Tracking herring schools with a high resolution sonar 59 fish relative to the sonar beam. According to previous investigations, the backscattered echo intensity of fish in lateral aspects should peak when the fish move normal to the sonar beam and decrease drastically when fish move head on or tail on relative to the sonar beam (Mitson, 1983; MacLennan and Simmons, 1992). As the sonar beam usually is emitted at a slight angle from the horizontal, the influence of aspect angle on the backscattered echo intensity of schools may be a rather complicated function that involves both lateral and dorsal aspect angles of the individual fish in schools (Love, 1980). A second possible source of error is variations in backscattered echo intensity caused by intraschool behaviour (Pitcher et al., 1996). The swimming speed of schools can influence the echo by its effect on fish density (Pitcher and Partridge, 1979; Partridge et al., 1980) and degree of polarization (Foote, 1980; MacLennan et al., 1990). Vertical migrations can influence echo intensity by changes in swimbladder volume (Ona, 1990). Changes in school form, in response for instance to predatory attacks, could also have effects (Fréon et al., 1992, 1993). At present, we have virtually no information about the effect of intraschool behaviour on backscattered echo intensity, and there is no compensation of such behavioural events in the sonar equations. We could expect that the behaviour of schools has stronger effect on relative echo intensity than on horizontal area, as the area is probably not influenced by variations above a certain threshold level. Up to now we have dealt with variations in backscattered echo intensity from schools assumed to have constant biomass. During interschool events (Pitcher et al., 1996), constituting the third possible source of error, the situation is different. When a school splits or joins with another school, actual changes in biomass take place. The question is whether such events can be recorded as changes in echo intensity. Interschool behaviour thus constitutes a direct test on the accuracy of the sonar method. The aim of this study was to examine the different kinds of variations in backscattered echo intensity with a high resolution sonar by following individual fish schools and continuously recording echo intensity and behavioural events. Materials and methods A total of 14 herring schools were tracked for approximately 1 hour each during daytime by the 95 khz Simrad SA950 sonar onboard R/V G.O. Sars within an area 68 North, 10 East (approximately 60 nautical miles west of Lofoten, Norway) in the period 3 5 May 1994. When a suitable school for tracking was detected, the vessel was halted at a distance of about 150 m from the school, and then manoeuvred carefully within a distance interval of about 100 to 300 m during tracking. The sonar was tilted and trained manually by an experienced operator to have best possible control of the recording trial. For identification of species and fish length, sampling with a medium-sized pelagic trawl (Valdemarsen and Misund, 1994) was conducted on selected schools. The Simrad SA950 is a high resolution sonar (Misund et al., 1995) that transmits pulses in a horizontal sector of 45, and that receives with 32 beams of 1.7 each (between 3 db points). The vertical beam width is 10 (between 3 db points). The sonar was operated with full transmission power, frequency-modulated pulse, gainstep 7, and the AGC, PP, and normalization filters set to step weak. The time-varied gain function was set to 20 log R. Special software for computer-based detection and measurements of schools by this sonar has been developed and implemented on an HP9000/720 work station connected to the LAN communication in the sonar (Misund et al., 1994). The software reads the echo telegrams from the processor to the display of the sonar, and organizes an echo table with 32 columns and 512 rows (one for each distance ring of the sonar). The table contains the colour code values (a number from 0 to 63) for each pixel that is the basis for procedures searching for schools. Targets above a certain threshold and horizontal extent that occur within a minimum number of succeeding pings are identified as schools. During the school recordings, the detection system was operated with a colour code threshold of 15, and minimum lengthwise and crosswise extents (Misund et al., 1994) of 5 and 10 m, respectively. For each ping the horizontal area, range and bearing of the school, together with data on date, time, vessel position (from GPS), heading and speed as well as tilt angle of the sonar were written to a file. The data for each school tracked was logged to a separate file. The colour code is a scaled value based on point sampling of the echo envelope of each pixel. The scaling is done by the formula: Colour code= [64*log (echo envelope)/(327.8)]+6.4*display gain Colour code values above 63 are truncated, but still the colour code is linearly related to echo intensity within a substantial interval. For each ping, the detection software calculates the coloursum for a school recording by adding the colour code values above the detection threshold of all pixels that constitute the school projection. The coloursum can thereby be considered as an expression of the relative echo intensity of the schools. During the school recordings, intraschool and interschool events (Fig. 1) as interpreted by continuously watching the sonar display, were recorded in a separate protocol. Intraschool events were related to vertical

60 O. A. Misund et al. Fish abundance Sonar equation Fish behaviour Packing density Distance vessel to school Backscattering cross section Intraschool "Split and join" Horizontal area Tilt angle (dorsal aspect angle) Swimming angle rel. beam (lateral aspect angle) Swimming speed Vertical migration Split School shape Join Approach Leave Aspect angle Dive Vacuole Packing density Surface Elongate Pseudopodium Reorganization Figure 1. Diagram of factors that may influence recording of fish abundance in schools by sonar. migration (dive, surface) or changes in shape (elongate, reorganization, pseudopodium and vacuole). School splitting, and approaching, leaving or joining of smaller subgroups were scored as interschool events. Postprocessing and statistical analysis of the sonar data were conducted by aid of the SAS software (SAS, 1988). Due to shortcomings in the detection software, schools could temporarily be detected as several units, and the schoolnumber could change during tracking. These shortcomings were corrected by adjusting the enumeration and summing multiple units that belonged to a tracked school. Additional schools or targets detected during trackings were allocated successive school numbers. The speed of the schools was calculated ping by ping on the basis of the GPS position of the vessel, the heading of the vessel and the direction of bearing and range vessel-to-school. To avoid a large fraction of zero speed estimates because of no change in position and time between succeeding pings, which occurred rather frequently, the calculations were made with a lag of 30 pings between succeeding positions. However, the random GPS error will induce a substantial uncertainty in the positions of the vessel and thereby the speed of the schools. We therefore applied simple filtering of the GPS recordings to improve the reliability of estimates of school speed. This was done by restricting the ping-toping calculation of school speed to GPS recordings that did not exceed certain limits. In this procedure, the speed calculation was restricted to positions in which the north and east movements of succeeding GPS recordings were within the 95% and 90% percentiles, and then within 30 and 20 m. With this filtering, the average speed of schools fell from 1.55 m s 1 for the unfiltered data, to 0.90 m s 1 for the 20 m percentile restriction (Fig. 2). The corresponding number of accepted recordings dropped by about 60% on average. Another possibility for reducing the influence of the random GPS error is to smooth the GPS recordings. This was done by calculating the speed on the basis of succeeding positions that were averaged for 50 pings. By this procedure the average speed of the schools was reduced by about 30% to 1.05 m s 1 (Fig. 2). Similar estimates of school speed have been obtained by the authors when tracking herring schools in the Norwegian Sea in spring 1996 with the same sonar system, but using differential GPS position with an accuracy of about 2 m (unpublished data). The smoothing procedure was therefore applied in the further analysis, both to obtain more reliable speed estimates and to smooth transient ping-to-ping variations in horizontal area and relative echo intensity (coloursum) of the school. The swimming angle of the school relative to the sonar beam was calculated by assuming that individuals in schools were swimming

Tracking herring schools with a high resolution sonar 61 3.00 6000 2.75 2.50 5000 Average swimming speed (m s 1 ) 2.25 2.00 1.75 1.50 1.25 1.00 0.75 0.50 4000 3000 2000 1000 Observations (n) 0.25 0.00 Data 95% 90% 30 m 20 m Category 0 Aver. Figure 2. Average speed (full line) and number of observations (stippled line) for the recorded herring schools as functions of various filtering and smoothing procedures. 95% calculations limited to recordings within 95 percentile; 90% calculations limited to recordings within 90 percentile; 30 m calculations limited to recordings with less than 30 m movement in north or east direction between succeeding pings; 20 m calculations limited to recordings with less than 20 m movement in north or east direction between succeeding pings; aver. calculations based on GPS positions averaged over 50 pings. polarized, and that the swimming angle will be equal to the lateral aspect angle of the fish relative to the sonar beam. To simplify the analysis, lateral aspect angles >90 were transformed to the first quadrant. Results Both horizontal area and relative echo intensity as expressed through the coloursum varied substantially during the school recordings (Fig. 3). Typical periodic fluctuations with temporary maximum and minimum values in horizontal area and coloursum occurred during all trackings. In most cases the amplitudes of the fluctuations were larger for coloursum than for horizontal area. During tracking of school no. 4 (Fig. 3), there were about 10 major fluctuations that peaked at a rate varying from about 4.8 min to 11.4 min (6.6 min on average). The ratios between maximum and minimum values in the fluctuations were from about 1.5 to 5.0 for horizontal area and from 1.5 to 7 for the coloursum. Similar fluctuations were recorded for most school trackings. The average area of the schools varied from 100 to 889 m 2, and the coefficient of variation of the area from 0.29 to 0.81 (Table 1). The coefficient of variation of the coloursum was in most cases more than 20% higher than that of the area. The average speed of the schools varied from 0.40 up to 1.79 m s 1 with coefficients of variations ranging from 0.46 to 2.23 (Table 1). There were strong relationships between the area and coloursum of the schools (Fig. 3) with significant correlations between 0.3 and 0.9 (Table 2). The average colour value at the pixel level varied between 20 and 45 for most schools, and the level of saturation (63) was not recorded. The area of the schools was not systematically correlated to range, tilt, speed or relative direction of the schools, although a few negative or positive correlations between the area and these parameters were found for individual schools (Table 2). For most schools there was a significant, negative correlation between coloursum and range. Coloursum and tilt also seemed to be negatively correlated, while speed and relative direction was not systematically correlated to coloursum. A linear model with school area as the dependent variable and range, tilt, speed and relative direction as continuous effects was significant and explained more than 10% of the recorded variation for most schools (Table 2). A similar model with coloursum as dependent variable was significant, and explained more than 30% of the recorded variation for most schools. Interschool events occurred at an average rate of 14 min (Pitcher et al., 1996), and as expected, these

62 O. A. Misund et al. 1200 16000 1000 14000 12000 School area (m 2 ) 800 600 400 10000 8000 6000 Coloursum 200 4000 2000 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Time (h) 1.0 1.1 Figure 3. Variations in school area (solid curve) and relative echo intensity (coloursum, broken curve) during recording of school no. 4 offlofoten, northern Norway, May 1994. 0 1.2 Table 1. Average area, coloursum, speed, depth and heading of the herring schools. School Area Speed Depth (m 2 ) CV A Coloursum CV C (m s 1 ) CV S (m) Heading ( ) n 1 270 37 2806 57 1.15 73 44 203 106 3 255 56 2856 70 0.99 89 56 209 67 4 360 45 4877 56 0.87 92 38 246 114 5 889 48 16 549 46 0.40 118 21 139 115 6 100 59 1266 70 0.71 87 45 261 96 7 303 29 4427 38 0.94 46 44 256 82 8 573 60 7782 68 0.56 223 34 203 111 9 489 70 7727 80 1.65 68 31 206 103 10 437 75 7265 95 1.01 82 29 216 116 11 288 48 5350 89 1.26 98 30 173 93 12 177 81 1915 69 1.23 72 19 177 66 13 379 46 5417 59 1.05 73 42 143 86 14 529 33 10 611 48 0.84 70 26 200 109 15 137 47 1607 107 1.79 197 34 172 46 CV A : coefficient of variation for the school area; CV C : coefficient of variation for the coloursum; CV S : coefficient of variation for the speed of the herring schools; n: number of observations. events influenced the size of tracked schools. There were four clear cases of joining of two schools with an increase in horizontal area of 5% to 230% (mean about 90%) when comparing the 6 min before and after the event. In three clear cases of split and leave there was a decrease in horizontal area of 10% to 40% (mean about 20%). No certain effects on school area were found by intraschool events that also occurred at an average rate of about 14 min (Pitcher et al., 1996). Discussion Both horizontal area and relative echo intensity as expressed through the coloursum of the schools varied

Tracking herring schools with a high resolution sonar 63 Table 2. Correlation coefficients between school area, coloursum, range, tilt, swimming speed, and relative direction of movement (α). The determination coefficients for linear models with school area (r 2 A) or coloursum (r 2 C) as dependent variables, and range tilt, speed, and α as continuous effects are also given. School area correlated to Coloursum correlated to Linear models School Coloursum Range Tilt α Speed Range Tilt α Speed r 2 A r 2 C n 1 0.88* 0.15 0.25 0.10 0.30 0.44 0.54 0.06 0.27 0.15* 0.22* 106 3 0.90* 0.13 0.13 0.09 0.07 0.21 0.03 0.19 0.1 0.07 0.07 67 4 0.83* 0.40* 0.11* 0.29 0.26 0.62 0.48 0.26 0.19 0.22 0.43 113 5 0.27* 0.61* 0.06 0.17 0.13 0.38* 0.03 0.04 0.14 0.50* 0.19* 116 6 0.88* 0.10* 0.07 0.09 0.12 0.21 0.04 0.09 0.02 0.04 0.07 92 7 0.88* 0.33 0.01 0.09 0.14 0.57* 0.17 0.10 0.10 0.12 0.34* 82 8 0.80* 0.06 0.19* 0.11 0.27* 0.53* 0.04 0.21* 0.24* 0.14 0.38* 111 9 0.76* 0.21* 0.08 0.38* 0.23* 0.25* 0.01 0.18 0.05 0.18* 0.14* 103 10 0.77* 0.12 0.07 0.20* 0.08 0.56* 0.36* 0.01 0.33* 0.10* 0.42* 116 11 0.69* 0.02* 0.11 0.10 0.34* 0.58* 0.40 0.07 0.35* 0.14* 0.43* 93 12 0.88* 0.40* 0.30* 0.21 0.72* 0.03 0.42* 0.01 0.57 0.53* 0.43* 66 13 0.81* 0.13 0.01 0.12 0.16 0.35* 0.28* 0.01 0.17 0.06 0.16* 87 14 0.54* 0.02 0.01 0.18 0.18 0.76* 0.25* 0.11 0.65* 0.07 0.60 109 15 0.83* 0.39* 0.11 0.30* 0.26 0.62 0.48 0.27* 0.16 0.29* 0.45* 46 n, number of observations. *p<0.05.

64 O. A. Misund et al. A max A rec 0 m 50 m 100 m 150 m 10 Figure 4. Recording of a fish school by sonar. A max : maximum area of school projection if the horizontal diameter of the school is insonified by the sonar beam. A rec : area of school projection when the school is only partially insonified by the sonar beam. considerably. However, there were strong correlations between these parameters for all schools tracked. This indicates that the larger the school area, the greater the relative echo intensity. Since the biomass of the schools is assumed to be fairly constant throughout the recordings, the variations in both area and relative echo intensity should have been caused by variations in the backscattered echo intensity of the schools. At the pixel level, the average colour code value was below the level of saturation, and the backscattered echo intensity of the schools was thus within the dynamic range of the sonar for the actual settings of the gain functions. The schools were recorded at varying horizontal range and aspect angle. According to the theory of fisheries acoustics (MacLennan and Simmonds, 1992), the backscattered echo intensity of schools will be directly influenced by these parameters. However, for most schools the horizontal area appeared fairly independent of range. If the schools were properly insonified, the beam geometry should result in larger projections of schools at greater range. Nevertheless, the coloursum of most schools decreased with increasing range. According to the sonar equation, the back scattering intensity of a target will decrease both due to geometrical spread and sound absorption, but this reduction should be compensated by using an appropriate time-varied gain function. If a recorded school covers the whole beam, the applied 20 log R time-varied gain function is correct, but if the school covers only a small part of the beam, the time-varied gain function should have been 40 log R. The SIMRAD SA950 sonar transmits in a 45 sector horizontally, but has a multibeam reception mode based on 33 adjacent beams of 1.7 horizontally. Most schools recorded filled only a small part of the 45 sector, but extended over several of the 1.7 beams. A 30 log R time-varied gain function might therefore have been appropriate. However, when using the Simrad SA950 with 30 log R time-varied gain amplification during recordings of herring schools in the Norwegian Sea in spring 1996, similar range decrease of coloursum as for the 1994 recordings was apparent (unpublished data). This leaves sound absorption as the most probable cause of the range dependent decrease of coloursum. The sound absorption is frequency dependent, and amounts to about 30 db km 1 for 95 khz which is the operating frequency of the Simrad SA950 sonar (MacLennan and Simmonds, 1992). Such strong absorption will reduce the energy of a plane wave by about 50% over 100 m of the propagation path (MacLennan and Simmonds, 1992). Even if the absorption is compensated for by the time-varied gain function applied, it will therefore gradually mask the school echo in the background noise. To illustrate the influence of the aspect angle in the horizontal and vertical plane, the area and relative echo intensity were related to the tilt angle and angle of movement relative to the sonar beam. Contrary to expectations, horizontal area and relative echo intensity were uncorrelated to the aspect angle, in both the vertical and horizontal plane. A slight tendency to increased relative echo intensity with greater tilt angle was present for most schools, but this may have been an effect of range, because greater tilt angles are normally applied with decreasing range. A major uncertainty during the recordings was the degree to which the beam insonifies the school in the vertical plane. The sonar beam is 10 wide (between 3 db points) in the vertical plane, which means that the beam covers a vertical extent of about 23 m at 150 m range at a tilt angle of 5. The insonification of the schools in the vertical plane may therefore have varied substantially. In particular, the backscattered echo intensity, but also the horizontal area or projection of the school, will depend on the insonification in the vertical plane (Fig. 4). If just the upper or lower part of

Tracking herring schools with a high resolution sonar 65 a school is insonified, both the horizontal projection and backscattered echo intensity will be less than if the whole school is within the sonar beam. Assuming a circular school with radius r, and that the school is recorded marginally by the sonar beam insonifying just a slice with radius r/2 of the upper part of the school. The area of the horizontal projection of such a marginal recording will be expressed by: A MARGINAL π(r/2) 2 cos(α 1 +φ/2) where α 1 is the tilt angle of the sonar beam and φ is the vertical beam width ( 3 db points). The maximum area of the school projection obtained by proper insonification of the school is expressed by: A MAXIMUM π(r) 2 cos(α 2 +φ/2) where α 2 is the tilt angle of the sonar beam. Thus, in this case the maximum recording will be approximately four times the marginal recording. The periodic fluctuations with maximum-to-minimum proportions of about 1.5 to 4 for horizontal school area and 1.5 to 6 for coloursum were therefore probably caused by varying degree of insonification of the schools in the vertical plane. Even higher maximum-to-minimum proportions may have been caused by temporary loss of the school echo due for instance to pitch and roll movements of the vessel for which the sonar beam is not stabilized. In addition to improper tilting, varying degree of insonification of the schools may also have been caused by bending or refraction of the acoustic beam due to vertical gradients in the sound speed. The sea temperature influences sound speed, and vertical gradients in the sea temperature will thus induce proportional gradients in the sound speed. If the sea temperature decreases with increasing depth, a slightly downwards tilted sonar beam will bend downwards, while the beam will bend upwards if the sea temperature increases with increasing depth (Mitson, 1983). In extreme cases with sharp vertical gradients in the sound speed and internal waves, the detection range of schools by a horizontal guided sonar may vary five-fold (Smith, 1977). However, even such conditions will induce maximally about 4 db variation in measurements of reflected echo intensity of schools at shallow depth and at range less than 250 m. As the reflected echo intensity of schools measured by sonar at a range less than 250 m may vary by about 30 db, the variation caused by refraction will be of minor importance (Smith, 1977). In our case, the recordings were done at sea temperatures of 4.5 6.5 C at 5 m depth, which decreased by maximally 1 C to the average depth of the schools (19 56 m, Table 1). Because of this weak temperature gradients, and the relative short range vessel-to-school (100 300 m), our recordings were therefore probably influenced negligibly by refraction of the sonar beam. The varying degree of insonification of the schools in the vertical plane is a general problem when using horizontal guided sonar with a plane beam fan to record schools. An elegant solution is an additional vertical beam fan as on the Simrad SR240 sonar (Ona, 1994), which can display a vertical section through a school recording. The horizontal beam fan can then be adjusted according to the vertical section to ensure that a maximum horizontal projection of the school recording is obtained. Another solution is stepwise tilting of the sonar beam in search of the maximum horizontal school projection, but according to experience, a school may easily be lost by such a procedure. The best solution for proper recording of schools would thus be a sonar with both a horizontal and a vertical beam fan and with high resolution on both. The large variations in horizontal area and relative echo intensity due to physical reasons concealed in many cases any effects of the behavioural events. However, horizontal school area changed in the expected direction in every clear case of interschool events with splitting and joining of schools. In addition, approach and leave of small school units as well as intraschool events could be quite clearly identified on the sonar display without causing any distinct increase or decrease in the recorded school area or relative echo intensity. The conclusion of our empirical study is that varying degree of insonification of the schools in the vertical plane and probably sound absorption are the major causes of the large variations in horizontal area and relative echo intensity of the recorded schools. Further substantiation of the relative roles of the different physical factors and behavioural events in recordings of horizontal area and backscattered echo intensity of schools could possibly be obtained by a modelling exercise. Absolute abundance estimation of schools by sonar will depend on a proper understanding of the physical parameters influencing sound propagation, the reflecting properties of the fish and the behavioural elements that may influence the backscattered echo intensity of schools. Modern sonars like the instrument used in this study can provide estimates of horizontal extent and relative echo intensity of schools. If the various gain and filter functions of the sonar are taken account of, and the sonar is calibrated, it should be possible to let the sonar measure absolute volume back scattering strength. By a realistic model that compensates for the physical factors influencing sound propagation, that take account of the reflecting properties of the fish, and the behavioural aspects that may influence the backscattered echo intensity of schools, absolute abundance estimation of schools should then be possible. Acknowledgements We acknowledge the skipper and crew on board R/V G.O. Sars for good cooperation and proper

66 O. A. Misund et al. manoeuvring during the school recordings, and Chuck Hollingworth for improving the manuscript. The comments of two anonymous referees helped improve the manuscript significantly. TJP gratefully thanks University of Bergen and Institute of Marine Research, Bergen, for making his participation in this project possible. References Foote, K. G. 1980. Effect of fish behaviour on echo energy: the need for measurements of orientation distributions. J. Cons. Perm. Int. Explor. Mer, 39: 193 201. Fréon, P., Soria, M., and Gerlotto, F. 1992. Changes in school structure according to external stimuli: description and influence on acoustic assessment. Fish Research, 15: 45 66. Fréon, P., Gerlotto, F., and Soria, M. 1993. Variability of Harengula spp. school reactions to boats or predators in shallow water. ICES mar. Sci. Symp., 196: 30 35. Love, R. 1980. A model for estimating distributions of fish school target strengths. Deep-Sea Res., 28A(7): 705 725. MacLennan, D. N. and Simmonds, E. J. 1992. Fisheries acoustics. Chapman & Hall, London. 325 pp. MacLennan, D. N., Magurran, A. E., Pitcher, T. J., and Hollingworth, C. E. 1990. Behavioural determinants of target strength. Rapp. P.-v. Réun. Cons. int. Explor. Mer, 189: 245 253. Misund, O. A. 1993. Abundance estimation of fish schools based on a relationship between school area and school biomass. Aquat. Living Resour., 6: 235 241. Misund, O. A., Totland, B., Floen, S., and Aglen, A. 1994. Computer-based detection of schools by multi-beam sonar. In Proceedings of the 2nd European conference on underwater acoustics, pp. 815 820. Ed. by L. Bjørnø. Elsevier, Amsterdam. 1099 pp. Misund, O. A., Aglen, A., and Frønæs, E. 1995. Mapping the shape, size and density of fish schools by echo integration and a high-resolution sonar. ICES Journal of Marine Science, 52: 11 20. Mitson, R. B. 1983. Fisheries sonar. Fishing News Books, London. 287 pp. Ona, E. 1990. Physiological factors causing natural variations in acoustic target strength of fish. J. Mar. Biol. Ass. U.K., 70: 107 121. Ona, E. 1994. Recent developments of acoustic instrumentation in connection with fish capture and abundance estimation. In Marine fish behaviour in capture and abundance estimation, pp. 200 216. Ed. by A. Fernö and S. Olsen. Fishing News Books, Oxford. 221 pp. Partridge, B. L., Pitcher, T. J., Cullen, J. M., and Wilson, L. 1980. The three-dimensional structure of fish schools. Behav. Ecol. Sociobiol., 6(4): 277 288. Pitcher, T. J. and Partridge, B. L. 1979. Fish school density and volume. Marine Biology, 54: 383 394. Pitcher, T. J., Misund, O. A., Fernö, A., Totland, B., and Melle, V. 1996. Adaptive behaviour of herring schools in the Norwegian Sea as revealed by high resolution sonar. ICES Journal of Marine Science, 53: 449 452. SAS. 1988. SAS Institute Inc. SAS/STAT User s Guide, Release 6.03 edition. Cary, NC, SAS Institute Inc. 1028 pp. Smith, P. E. 1977. The effects of internal waves on fish school mapping with sonar in the California current area. Rapp. P.-v. Reun. Cons. int. Explor. Mer, 170: 223 231. Valdemarsen, J. W. and Misund, O. A. 1994. Trawl designs and techniques used by Norwegian research vessels to sample fish in the pelagic zone. The sixth Norwegian-Russian Symposium, Precision and relevance of pre-recruit studies for fishery management related to fish stocks in the Barents Sea and adjacent waters, Bergen, 14 17 June 1994. Paper 3.1. 17 pp.