© 2006 International Council for the Exploration of the Sea
Age characteristics of walleye pollock school echoes
a Tokyo University of Marine Science and Technology Tokyo, Japan
b Hokkaido National Fisheries Research Institute 116, Katsurakoi, Kushiro, Hokkaido 085-0802, Japan
c Marine Fisheries Research and Development Department of Fisheries Research Agency 2-3-3 Minato-mirai, Nishi, Yokohama, Kanagawa 220-6115, Japan
*Correspondence to M. Kang: tel: +61 3 6231 5588; fax: +61 3 6234 1822. e-mail: kang{at}sonardata.com; size100{at}hotmail.com.
The purpose of this study was to investigate the possibility of identifying the age of walleye pollock (Theragra chalcogramma) using acoustic information. Acoustic data targeting walleye pollock were collected at 38 and 120 kHz from 16 June to 12 July 2000 in the Pacific, off Hokkaido, Japan. To complement these data 33 trawl hauls were made and the species and age of the sample fish were accurately examined. The echoes of walleye pollock schools according to age were used to determine the morphological and bathymetric characteristics such as mean height, maximum length, centre depth, seabed depth, and distance from the seabed, as well as the frequency characteristics, this latter being the difference of mean volume backscattering strengths at 38 and 120 kHz, respectively (
MVBS). The MVBS method is elaborated using MVBS (mean volume backscattering strength) from an integration cell of optimal size, the cell being examined by means of various integration periods to highlight the characteristics of the walleye pollock schools resulting in 20 pings (120 m), and by applying this method only in a common observation range for two frequencies. The ages of the schools are identified by a combination of morphological and bathymetric characteristics, and MVBS characteristics. Age-0 groups are easy to distinguish from other age groups because they exist in distinct, small schools, are close to the coast, and have a narrow range of MVBS regardless of time of day. Age-1 schools are low in height and very long, are distributed close to the sea floor, and have an MVBS range of –1 to 8 dB, with most between 3 and 5 dB. These characteristics of age-1 schools are distinct from other age groups. As age-2 and age-5 schools have similar maximum length and distribution depth, it is almost impossible to identify these two by just morphological and bathymetric characteristics. However, the MVBS of age-2 and age-5 schools show characteristic patterns that can be used as a means of identification. The pattern of MVBS, which reflects an internal structure (swimming angles) of a school, is different for each age class, and is essential in the identification of the age of a walleye pollock school.
Keywords: age identification, common observation range, morphology and bathymetry, optimal size of an integration cell, pattern of MVBS
Received 18 November 2004; accepted 8 June 2006.
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Introduction |
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Four acoustic methods are used in identifying fish species. The first is the frequency characteristics method, which is based on the difference in the frequency characteristics of fish school scattering by means of a wideband echosounder (Simmonds et al., 1996; Zakharia et al., 1996) or multiple frequencies (Conti and Demer, 2002; Kang et al., 2002; Korneliussen and Ona, 2002). The second is the distribution characteristics method in which morphological, bathymetric, and energetic characteristics are extracted from school echoes on the echogram. ICES (2000) gives a comprehensive overview of this method by defining acoustic school echoes, raising issues of acoustic school images, and suggesting correction algorithms that use simulated school echoes. Many software packages have applied this method, including Echoview (Higginbottom et al., 2000), EIPS (Lu and Lee, 1995), FASIT (LeFeuvre et al., 2000), MOVIES (Weill et al., 1993; Masse et al., 1996; Scalabrin et al., 1996), SHAPES (Coetzee, 2000), TSAN (Sawada, 2000), SCHOOLS, and SCHOOLBASE (ICES, 2000). It seems that it is a very common method and easy to apply for species classification. However, if several species are present together it becomes less effective. The third method is that of signal characteristics. While the distribution characteristics method relies on the geometric features of school echoes on the echogram, this approach deals with the echo signal itself, and in particular the characteristics of the echo envelope. Rose and Leggett (1988) found that the distance between the peak and the trough of the envelope, and the distance between two peaks were important for identification, whereas Scalabrin et al. (1996) pointed out that a short echo length restricted the use of a complicated spectrum analysis. This finding suggested that further investigation was required. The fourth is the acoustic result method, which is based on data produced from an echosounder, including the volume backscattering strength (SV), target strength (TS), and swimming speed by echo trace analysis (Richards et al., 1991; Sawada, 2000). Moreover, environmental information by non-acoustic methods has been employed. The relationship between species and environmental characteristics such as water temperature, current, and seabed geography has been studied widely (Cooke et al., 2002).
Although several species have been accurately identified using the above methods, the methods have not yet been adopted at a practical level over a wide range of times and areas (Scalabrin et al., 1996). Moreover, even if the methods are utilized, acoustic species identification is not easy because characteristics of echoes within the same species may be different because of school formations, distribution patterns, and age composition (Misund, 1993; Coetzee, 2000). Factors causing a variety of characteristics of echoes within the same species must be examined for species identification. However, if the characteristics of the echo per se vary with fish age, it is feasible to identify an age of the species by acoustic methods. This can be useful for estimating individual stock sizes by age.
In this study we examine the age characteristics of echoes of walleye pollock (Theragra chalcogramma) schools to identify the representative ages of the schools. When more information of this type has been collected and the results verified, it will be easier to identify the species of marine organisms acoustically (MacLennan and Holliday, 1996; Horne, 2000); this is just a first step. For age identification, a wealth of information is created by combining the frequency characteristics approach (MVBS characteristics) and the distribution characteristics method (morphological and bathymetric characteristics). Species were confirmed by trawl sampling, and ages were measured via a precise experiment. In this study, the advanced MVBS method discussed in Kang et al. (2002) is further improved. The advanced MVBS method was applied over a common observation range to compare the frequency characteristics of only the target marine organisms at two frequencies. In this case, the method of calculating observation range has been enhanced by using measured noise. By applying a small integration cell, it was possible to reduce the contamination of multiple species, but hitherto the most appropriate size of the integration cell has not been investigated sufficiently. One purpose of this study is to determine an optimal size of integration cell that can best highlight the characteristics of schools. Finally, age identification using two characteristics is attempted for echoes from walleye pollock schools collected from the Pacific Ocean off Hokkaido, Japan.
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Methods |
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Acoustic and trawl survey
An acoustic survey targeting walleye pollock schools was conducted from 16 June to 12 July 2000 in the Pacific Ocean off Hokkaido, Japan, using the RV "Kaiyo-maru #3" (460 grt), a vessel originally built for fishing but now used for research. In all, 19 parallel transects were covered on the east side of Cape Erimo and ten transects on the west, as shown in Figure 1. Survey data were collected from the calibrated 38 and 120 kHz channels of a SIMRAD EK500 echosounder. Table 1 shows the specifications of the echosounder and the parameters of the calibration. Two transducers were mounted at the same depth, on the bottom of a protruding instrument keel, with the 38-kHz transducer in front of the 120-kHz transducer. The beam widths of both transducers were close to 7°. Simultaneous transmission of pulse was used. The calibration was carried out on 18 June 2000, and two calibration spheres made from tungsten were used at 38 and 120 kHz. The water temperature was 4.6°C, salinity was 32.3, and sound speed was 1465 m s–1.
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Figure 1 also shows the trawl survey stations where the age and species of walleye pollock were confirmed. To examine differences between day and night echoes, the vessel covered the same survey line by both day and night of the same day, when possible. Trawl positions were determined by daytime echograms, but taking into consideration the night-time ones. Samples were collected by trawling during daylight. In all, 33 trawls were used to ground-truth the acoustic data. A dual purpose, midwater/bottom trawl net (JAMARC-98, Nichimo Co. Ltd, Tokyo, Japan), made up of four panels, was designed to sample rather diversely distributed fish schools. The main purpose of using a new trawl net was to catch walleye pollock schools regardless of various distribution patterns by time and season. The net was 63.2 m long, with 11-mm stretched mesh in the codend. When a midwater trawl was used, the size of the mouth opening was approximately 25 m vertically and 18 m horizontally, and for bottom trawls, the measurements were 20 m vertically and 23 m horizontally. Bottom trawling was used in most cases.
The samples caught by the trawls were classified by species onboard. A double-checking method for samples was applied in order to obtain accurate age and size. At every trawl station, fork lengths of 300 fish were measured, and 100 fish were randomly selected, for age, length, and weight to be determined. The age of a fish was accurately determined by counting the yearly translucent zones on a vertical section of an otolith embedded in black resin.
Observation range
The observation range of an echosounder is derived by finding the border of an acceptable signal-to-noise ratio; this is related to the insonified marine organisms, instrument parameters, vessel noise, and acoustic propagation. The MVBS method makes use of the frequency characteristics of the scattering of marine organisms. It is essential for this method to be used within a common observation range across multiple frequencies, in which the effects of the frequency difference by noise and directivity of the echosounder are minimal, in order to obtain pure frequency characteristics of scattering of the target marine organisms. The concept of a common observation range was introduced by Furusawa et al. (1999) and applied to the MVBS method by Kang et al. (2002).
In Kang et al.'s (2002) paper, the noise spectrum level, an essential parameter for obtaining the common observation range, was calculated using an experimental equation by Nishimura (1969). However, during the current study, noise was measured from the echo-integrator output (Takao and Furusawa, 1995). The noise spectrum level was accurately calculated for each frequency using noise measurements from the EK500 echosounder and the RV "Kaiyo-maru #3". Takao and Furusawa (1995) showed that when the SV corresponding to noise was measured at echo-integrator output, it was related directly to the mean power of the noise. This is a practical method, because the noise component of SV, the so-called noise SV, is measured in the same way as normal SV. The noise spectrum level can be directly calculated from
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the pulse width, 
the equivalent beam angle, f the bandwidth of the receiver, r the range, 
the absorption attenuation coefficient, g the coefficient caused by the integration process, and 
SV
N is the mean noise SV. The coefficient g is calculated as follows:
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1 when r is large and rw is small. When there was no echo of marine organisms, the noise SV was measured in an integration cell 10 min long in the horizontal and 150–170 m in the vertical. The SVN was –83.3 dB at 38 kHz and –69.0 dB at 120 kHz. Calculations using Equations (1), (3), and (4) of Kang et al. (2002) were utilized to find values of P0 and DI.
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There was regrettably an error in Equation (6) of Kang et al. (2002). The parameter
(the density of seawater) in the numerator was erroneously displayed as P. The following corrected equation should be used to calculate observation ranges:
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It is difficult to assume B, because there can be diverse types and sizes of fish or schools or, indeed, both parameters together, present when carrying out an acoustic survey. Moreover, some part of a large school insonified at the edge of a beam can appear to be a small weak school. Therefore, if a relatively small value is used for B, there will not be an issue when calculating an observation range. The TS of the smallest single fish is calculated as –49.2 dB using the reduced TS (TScm = –66 dB), and the average body length (6.9 cm) confirmed at trawl station 2. Therefore, we examine a common observation range for a range of B from –50 to –20 dB.
Optimal size of an integration cell
Acoustic data from multiple frequencies should physically and spatially be as similar as possible in order for them to be compared (Korneliussen and Ona, 2002). In this study, the acoustic parameters at 38 and 120 kHz are almost the same except for pulse length. Although the pulse lengths were different (1 ms at 38 kHz, 0.3 ms at 120 kHz), SV data have been processed by correcting pulse lengths at different frequencies and can be used for comparison. The size of the integration (averaging) cell should be considered as an essential parameter in comparing multi-frequency data, especially for the purpose of highlighting the characteristics of a fish school. There has not been any study on cell size with this in mind. As it is very likely that there would be a mixture of different body lengths, ages, and species in a large integration cell (Kang et al., 2002), a small cell would seem to be preferable. However, if a cell is too small, the averaging process within the cell does not serve to represent adequately the mean backscatter on respective frequencies. Further details of this issue will be explained later, in the Discussion section.
Consequently, for highlighting school characteristics, an optimal size of an integration cell is necessary, so that the dominant age of a school can be ascertained. To select the optimal size of the integration period, i.e. the horizontal interval of a cell, it should be, first, small enough to retain the shape of a school, second, small enough to distinguish the boundary between the target school and others, and third, large enough to be able to read the MVBS pattern, i.e. a change of MVBS. The first two points are related to the exterior characteristics of a school, and the last bears on its interior characteristics. To help decide the minimum threshold of horizontal cell size, rough parts of the perimeter of a school can be calculated by distance or by the number of pings. If integration was conducted on a cell of larger size than the parts, the boundary of the school becomes too smooth to retain the shape of a school. Simple investigation of the horizontal lengths of schools of different species, and the distance between a targeted school and a school of another species, provides an idea to assist with understanding the second point. The relationship between a target school and other species should be clear after processing integration. Regarding the third point, the MVBS characteristics of a school should be readily apparent. If a cell is too small, the range of MVBS becomes too large, and if a cell is too large, the range of MVBS becomes too small for a specific MVBS range for a school to be obtained.
Several integration periods, such as 1, 6, 10, 20, 30, and 50 pings, i.e. 5.2, 31.2, 52, 104, 156, and 260 m, were used to investigate the optimal size of a cell for school of age-0 walleye pollock sampled at trawl station 1.
MVBS characteristics
The improved MVBS method attempts to discriminate walleye pollock schools by age. First, MVBS values from an optimal size of integration cell are obtained at 38 and 120 kHz. The MVBS characteristics of walleye pollock schools are examined up to the common observation range on the MVBS echograms. As schools were distributed very close to the sea floor by day, data suitable for the MVBS method were rarely collected. Therefore, only data collected at night were used.
To understand MVBS characteristics in a school, we take the example as follows. Consider the TS directivities (change of TS according to fish tilt angle) and MVBS of two fish which have different body lengths (short and long) and are swimming at different angles (horizontally and some other direction) at different frequencies (low and high). When a fish is swimming horizontally, the maximum TS at two frequencies is the same regardless of body length, so MVBS does not appear. However, when a fish is swimming in another direction, the TS directivity of fish with the longer body length will change relative to the small fish. TS directivity is sharp and fluctuating with body length especially at high frequency (Sawada, 2000). Therefore, if fish with longer body length are swimming in many directions, various MVBS will be observed easily. If a school comprises fish of the same species and similar body lengths, MVBS in a cell can represent information on the swimming angles of fish. Therefore, characteristics of MVBS (or patterns of MVBS) in schools provide characteristics of swimming angle within schools. Even if a part of the MVBS range overlaps between schools of different ages, the MVBS patterns within schools may be different and can provide unique information to identify the internal distribution of the schools at each age. Hence, it is necessary for the MVBS echogram to have the same scales in the horizontal and vertical dimensions for the purpose of viewing and comparing the MVBS ranges and patterns of schools.
Morphological and bathymetric characteristics
Mean height, maximum length, centre depth, seabed depth, and distance from the seabed of the echoes of walleye pollock schools were examined to obtain the morphological and bathymetric characteristics of the schools by age. Figure 2 shows these school descriptors. Echoview software was utilized to extract the characteristics. First, echoes of a targeted school on the echogram were selected manually. Mean height was calculated for each ping in the enclosed region. The depths from the surface to the centre of the school at each ping in the region were averaged, and the average was referred to as the centre depth. Seabed depth is the average depth from the water surface to the seabed in the region where walleye pollock schools were distributed. Distance from the seabed is the distance from the centre depth to the seabed. Maximum length is calculated by multiplying the average distance between two continuous pings by the number of pings within the enclosed region. As the ping distance depended on vessel speed, several ping distances were selected and averaged at 6 m.
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Composition of age and body length
Figure 3 shows the age composition of the walleye pollock schools and the ratio of the number at each age to the total numbers of samples at each trawl station. The data from trawl stations when fewer than 100 samples were taken were not included. The data in which a specific age group is the most prominent were used as target age school. The coloured rectangles under the trawl number show the prominent ages that correspond to the colour of the trawl stations in Figure 1. Age-0 schools comprised almost completely fish of that age, and age-1 schools were 53–99% 1 year olds. From age-2, fish tend to mix with schools of older age. Age-2 and age-5 schools have been labelled as such because they comprise 50% or more of that age group.
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Figure 4 shows the composition of the body length of walleye pollock at the trawl stations. The body length of walleye pollock is divided into five groups according to average body length, based on grouped trawl stations by age. Figures 3 and 4 show that age composition is strongly related to body length. In general, walleye pollock schools seem to contain fish of similar size, but the longer the body length, the more diversity of body length there tends to be within a school.
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Observation range
The noise spectrum levels using the measured noise in Equation (1) were 68.8 dB re µPa Hz–1/2 at 38 kHz, and 61.0 dB re µPa Hz–1/2 at 120 kHz, for the calculation of the observation range.
Figure 5 shows that the observation ranges at 38 and 120 kHz are dependent on the backscattering strength of the insonified marine organisms, such as –20, –30, –40, and –50 dB. As the backscattering strength of scatterer(s) B becomes smaller, the observation ranges at both frequencies and the difference between the observation ranges become smaller. The observation breadths at two frequencies are similar due to the similar beam widths. When B is –50 dB, the maximum observable depth is about 169 m at 38 kHz and 120 m at 120 kHz, and the maximum observable breadth is approximately 17 and 14 m. Clearly, the observation range is identical up to a depth of 100 m for 38 and 120 kHz, even when B is small. In other words, even though only a single fish with a body length of approximately 10 cm is insonified at both frequencies, observation ranges at the two frequencies are the same up to a depth of 100 m. Therefore, the minimum common observation range is approximately 100 m at both frequencies for the various sizes of fish schools.
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The common observation range at two frequencies becomes larger as school size increases. For example, B of the school confirmed age-1 at trawl station 16 results in –26.6 dB using SV, TS, and reverberation volume. In Figure 5, when B is –20 dB, the observable depth shown as an overlapped maximum depth between two frequencies is about 300 m, and when B is –30 dB, the depth is about 220 m. As the B of the school is about –25 dB, a common observation range can be used at 200 m. Therefore, for the age-1 school at trawl station 16, the
MVBS method can be used up to a depth of 200 m. Finally, an observation range is dependent on the backscattering strength of scatterer(s) at a similar condition of the acoustic system. However, a common observation range at multiple frequencies should be decided by considering the approximate backscattering strength of a target school. A depth of 100 m is the safest common observation range regardless of size of fish school and will be used in this study, though occasionally modified to suit the backscattering strength of a school.
Optimal size of an integration cell
To find the optimal size of an integration cell, a change in MVBS (Figure 6) compares the characteristics of the school with various integration periods in ping number or distance, or both parameters. In the echogram with a one-ping integration period, the MVBS range is approximately –3 to 14 dB, with noticeable patches from 10 to 14 dB (Figure 6a). When the number of pings in one integration period increases from 6 to 20 (31.2–104 m) the range of MVBS decreases to –3 to 6 dB (Figure 6b–d). The blue (–13 to –10 dB of MVBS) and orange (10–12 dB of MVBS) colours in the upper part of the school may indicate different species, perhaps planktonic organisms, because plankton has a variety of frequency characteristics according to the physiology of its constituent species, and it often comprises different species, even if their taxon cannot be confirmed. The state of a mixture of multiple species in the case of >30 pings is difficult to observe (Figure 6e, f). When the integration period is as large as 50 pings (260.4 m), the edge of the school is not clear, and its inner portion has a very narrow range of MVBS, approximately –1 to 1 dB. When a cell is too large, all the MVBS of a school become nearly one value. There is no value in averaging echoes in such a large integration cell to describe the frequency characteristics of the school (Figure 6f). Therefore, the optimal integration period for the walleye pollock school should be set at 6–20 pings (31–104 m).
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We found the optimal integration period to be about 20 pings (124 m calculated at 6.2 m of ping distance between two pings) for the school of age-5 fish at trawl station 33 during daylight. In this study, therefore, an integration period of 20 pings (120 m) is used as the optimum size of an integration cell for walleye pollock schools.
Morphological and bathymetric characteristics
To illustrate the distribution characteristics of walleye pollock schools based on age, a typical example of a night-time echogram for each school by age is shown in Figure 7a–d, and for daylight in Figure 7e–h. Daylight echograms were obtained at the same locations as those recorded at night.
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In the night-time echogram the school of age-0 is widely distributed in depth from the surface down to approximately 100 m, mainly at a distance from the seabed, but parts do reach the seabed. The age-1 school is distributed through a height of some 40 m at a depth of 180–190 m over the continental shelf. The age-2 school has a height of 40–60 m, is distributed approximately 25 m above the seabed, and is located at the edge of the continental shelf. The age-5 school starts at a depth of approximately 140 m on the upper continental slope, and has a height of 40–120 m.
In the daylight echogram, the age-0 school is distributed more densely in the centre of the school than is observed at night. In general although the sizes of age-0 schools vary greatly by day, they have a tendency to cluster, which makes them easily distinguishable from other age groups. The age-1 schools, indicated by a brown arrow in Figure 7f, are very small, and are located near the sea floor. The age-2 school observed by day has different distribution characteristics from those observed at night: it is largely scattered and forms only a few small clusters. The age-5 school is distributed close to the seabed, so it is hard to discriminate between seabed and fish.
The number of schools analysed during this study is shown in Table 3. In all, 23 small schools of age-0 were observed by day, but just two schools of the same age at night. Most age-1 schools could barely be distinguished from seabed echoes by day (e.g. Figure 7f), so these daytime schools have not been included for further analysis (Table 3, Figure 8).
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In order to understand the general distribution characteristics of walleye pollock schools based on this survey, school descriptors by age are illustrated in Figure 8. This shows that age-0 fish are small and live in shallow water, so it is easy to distinguish their schools from schools of different age. The age-1 schools are distributed in relatively deep water at about 180 m, and have little height but great length, e.g. 7770 m. When comparing the age-2 schools with those of age-5, their distribution characteristics are very similar, especially their maximum length, the centre depth, and the seabed depth, even though the schools of age-5 fish show a greater change of mean height between day and night and are distributed near the seabed by day.
MVBS characteristics
Figure 9 presents the MVBS echograms of walleye pollock schools according to age. Each echogram has a vertical axis of 300-m depth and a horizontal axis of 6000 m. The optimal cell size of 20 pings is used as the integration period. The safest common observation depth of 100 m (shown as a white dotted line) is necessary when observing the MVBS echograms, regardless of the size of the fish school. The common observation depth expands to some 200 m in Figure 9b because of the strong backscatter (–26.6 dB). The age-0 school has a narrow range (–3 to 2 dB) of MVBS (Figure 9a), which means similar scattering strengths at 38 and 120 kHz. The age-1 school has MVBS distributed from –1 to 8 dB (Figure 9b). Most MVBS is between 3 and 5 dB (yellow) and 0 dB (light green spots). The school of age-2 fish has MVBS between –3 and 8 dB (Figure 9c). A mixture of MVBS is shown mainly between 3 and 4 dB (yellow) throughout the school, and some MVBS of –3 dB (green) at the upper edge and at the middle of the school. The school of age-5 fish has a wide range of MVBS, from 0 to 12 dB (Figure 9d). A section of MVBS between 6 and 12 dB in orange is shown at the centre of the school.
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Not all school groups can be easily identified using the range of
MVBS, because parts overlap. However, the pattern of MVBS, shown as a range of colours, is distinctive between age groups. When looking at all echograms, it is very easy to see that the school of each age has its own particular characteristic in terms of a pattern of MVBS. The pattern of MVBS is crucial information in identifying the age of schools, and can be assumed to be a reflection of the character of the movements of the fish.
A great variation in MVBS values in schools of older age might be due to distributed tilt angles. When fish in an integration cell are distributed randomly, fish tilt angles (or TS directivity) are averaged in the cell. Hence, there is little effect of fish tilt angle on the MVBS of the cell. If fish in a school uniformly face a certain direction in an integration cell, as can be supposed for older walleye pollock schools, TS will not be appropriately averaged across a large and random distribution of tilt angles. A specific tilt angle affects MVBS differently at different frequencies, and causes fluctuating MVBS. Therefore, if there are several subgroups of fish with various orientations in a school, a diversity of MVBS can be seen. If a school of a certain age has a particular swimming direction, then that characteristic appears in the pattern of MVBS. It can be concluded that MVBS indicates the internal distribution structure of a school.
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Discussion |
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Observation range
When the acoustic signals of a school or single fish are not more than a given threshold, the weak echoes do not contribute to the received signals, and so the sampled volume effectively becomes smaller. To calculate this volume an equivalent beam angle is often used, and the term given to the end result is often called the acoustic sample volume (Aglen, 1982; Foote, 1991; Reynisson, 1996). The tilt angle of fish is known to be a more important factor than transducer directivity and threshold in this situation (Foote, 1991; Reynisson, 1996). However, this method did not consider the acoustic system and the noise of the vessel. The "observation range", which gives the detectable range of an echosounder, does consider both, as well as the backscattering strength of a school, and so provides a better measure of the various underwater conditions.
Diverse MVBS
A diverse range of MVBS was apparent when the integration cell was very small, for example with an integration period of one ping. If a cell is too small, no averaging in the cell can be carried out effectively. Two possible reasons can be assumed. The first may be frequency difference in TS directivity. It is well known that TS directivity is narrower and more complicated with a long body length (i.e. body length is large compared with wavelength) (Sawada, 2000). If a cell is too small to have a large number of fish, the tilt angles of the fish cannot be considered to be effectively random. Hence, the effect of TS directivities is different at different frequencies, which results in a diverse MVBS. The second reason may be the frequency difference caused by the interference of multiple echoes. Multiple echoes are generated when single echoes with a carrier signal overlap. The amplitude of multiple echoes comprises the basic component and the interference. When the number of echoes is small, variations of both components are large. Moreover, in some cases the interference becomes complicated, and may occur at two frequencies (Furusawa, 1991). If the data set is large, a variation of the basic component becomes even, and interference can be considered to be uniformly distributed and ignored. If many echoes in an integration cell are averaged, the frequency difference attributable to interferences will become smaller. Therefore, the size of the cell should be large enough for it not to be affected by interference and TS directivity.
TS characteristics by age
TS characteristics by age were investigated using single targets detected at the boundaries of schools recorded at trawl stations. Only the average TS, such as approximately –46 dB, the assumed age-0, is clearly distinguishable from that of other groups, and the body length deduced from this average TS and that from trawls are quite similar. However, in groups older than age-1, average TS can be similar while the body lengths from each average TS do not correspond with that of specimens found in the trawls. Therefore, it is difficult to discriminate the age of walleye pollock among older age groups using TS. The study of Sadayasu (2005) on the TS of walleye pollock used measurements of suspension and free swimming, and a Kirchhoff ray-mode model. The relationship between TS and body length differed beyond a body length of 10 cm. This can be explained by the fact that the relative growth ratio of the swimbladder (strongly affecting TS) changed greatly at that body length. Therefore, to demonstrate satisfactorily whether age can be discriminated by TS characteristics, data from in situ TS measurement of targets close to a transducer may be required, and further study of fish behaviour will be needed.
It is imperative when using the MVBS method that MVBS be measured with negligible noise. The ICES report on the underwater noise of research vessels (ICES, 1995) suggested that noise spectrum levels of a research vessel should be 47.6 and 42.1 dB at 38 and 120 kHz, respectively. As the vessel used in this study was not designed for acoustic research, its noise spectrum was higher than that of the ICES recommendation. However, the noise of the vessel was measured accurately and used to calculate the observation ranges.
Many morphological, bathymetric, and energetic characteristics are used in fish species identification (Weill et al., 1993; Lu and Lee, 1995; Scalabrin et al., 1996; Coetzee, 2000; Lawson et al., 2001). Of the three, morphological characteristics tend to provide the best predictor of species. Even if descriptors of height, area, length, and perimeter of school have proven more effective, the contributions of those parameters varied slightly between studies. It is important to use many school descriptors, however, in order to ascertain those that are most effective. One study used distribution characteristics along with MVBS between three frequencies to identify Antarctic krill from other plankton (Woodd-Walker et al., 2002). If a pattern of MVBS among frequencies in that study had been examined, the results may have been interesting.
It is well known that age-0 and age-1 schools contain pre-recruitment walleye pollock, and these age groups should be managed for sustainability (Honda, 2004). The results presented here are therefore relevant to fisheries resource management, because they can be used to discriminate age-0 and age-1 schools from other older age groups in order to estimate the biomass of younger age groups individually. Also, for commercial fisheries, the method can be applied to prevent younger fish from being inadvertently caught.
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Acknowledgements |
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The study was supported by grants from the Fisheries Agency of Japan. We thank cruise members of RV "Kaiyo-maru #3" at Nippon Kaiyo for assistance, and two anonymous reviewers for pertinent comments on an earlier draft. We also thank Matthew Wilson of SonarData for smoothing the English in this paper.
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References |
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