Bangarang February 2014 Backgrounder1

Hydroacoustics (Using sound to see nekton & plankton)

Eric Keen

Abstract

This Backgrounder reviews the basic principles of hydroacoustics – using the echoes of transmitted high- frequency sounds to generate acoustic maps of the water column and the biota swimming within it. This branch of oceanography is increasingly sophisticated and rigorous, something I do not do justice to here. I limit my focus to the basic concept, design considerations for hydroacoustic surveys and how echograms can be interpreted.

Contents

Principles Time-Varied Gain Beam Choices Transducer Depth Data Reduction Survey Design Other Design Concerns Observation Range

Scatterers Frequency-dependence Orientation Buncha littles or a single big? Avoidance Swim Speed Density Internal Waves

Taxa Differentiation Δ MVBS Multi-Beam Systems Consideration Examples

Literature Cited

1 Bangarang Backgrounders are imperfect but rigorous reviews – written in haste, not peer-reviewed – in an effort to organize and 1 Principles

Hydoacoustics have been used to survey fish at sea since 1935 (Sund 1935) 2. “Hydroacoustics is the use of transmitted sound to detect fish. Sound is transmitted as a pulse and travels quickly and efficiently through water. As the sound pulse travels through water it encounters objects that are of different density than the surrounding medium, such as fish, that reflect sound back toward the sound source. These echoes provide information on fish size, location, and abundance. The basic components of the acoustic hardware function to transmit the sound, receive, filter and amplify, record, and analyze the echoes. All quantitative hydroacoustic analyses require that measurements that are made with a scientific-quality echo sounders, having high signal to noise ratios, and ability for easy calibration”3

“Hydroacoustics provides a repeatable, non-invasive method of collecting high-resolution (sub-meter scale), continuous data along transects in three dimensions4. MacLennan and Simmonds (1992) as well as Brandt (1996) give a thorough introduction in the use of hydroacoustics for measuring fish abundances and distributions.” 5

Hydroacoutic transducers convert electric energy into pressure waves, and conversely, incoming pressure waves to voltages6. They both send and receive the pings used in hydroacoustics. The pulse emitted from an underwater transducer propagates down the water column in an expanding cone. As it does its sound intensity decreases due to geometrical spreading and absorption 7 . Density differences in the water (caused by physiography, bubbles or biota) absorb some of this sound energy and scatters another portion of it a variety of directions. Part of the signal is reflected back to the surface. As it travels back up the water column, its signal strength continues to be attenuated by absorption and spreading loss. The echoed signal eventually reaches the transducer in a much reduced form. The transducer measures the pressure of the returned echo, translates it to voltage and sends the signal up the transducer cable. The echo sounder processer converts this voltage to a digital signal8 that is sent to a computer.

The time-delay between transmission and the return of echoes indicates how deep the reflective object was. The strength of the echo depends on how far it travelled in the water, how absorptive the water was, and how much of the signal was reflected perfectly back to the transducer (which has to do with both the reflectivity of the struck object and the beam patterns it induces in reflected signals at a specific orientation at a given frequency).

Time-Varied Gain To compensate for the signal attenuation that comes with propagation, the returning intensity is amplified digitally9 by the computer with a time-varied gain (TVG) function10 according to when the echo was received. The gain applied increases with time delay (which is indicative of how deep the signal travelled before being reflected). A 20 log R will compensate for a one-way spreading loss, or the loss from transducer to target, while a 40 log R compensates for a two-way spreading loss, or the entire loss from transducer to target and back11. Ten years ago, TVG was only a feature on expensive sounders. 20log TVG is more commonplace now, but 40logR (which compensates for spreading lost in both directions) is usually only found in large expensive instrumentation12. Some studies have not applied TVG to shallow surveys with 38kHz, since attenuation is relatively negligible13.

Beam Choices Some frequencies are absorbed better than others. In general higher-frequency sounds are attenuated more quickly than lower-frequency sounds. The width of the beam of sound emitted from the transducer will determine

2 Madureira et al. 1993. 3 Maxwell et al. Year Unknown. 4 MacLennan and Simmonds 1992 5 Maxwell et al. Year Unknown. 6 Mathiesen 2003. 7 Misund 1997 8 Mathiesen 2003. 9 Cochrane et al. 1991. 10 Misund 1997 11 Mathiesen 2003. 12 Mathiesen 2003. 13 Madureira et al. 1993. 2 the rate of geometric spreading loss. Therefore, “sonars constructed for detecting targets at long-range operate at low frequency (from around 20 kHz up to about 50 kHz), and have a beam width of around 10 degrees” 14. High-frequency sonars operate from about 150 kHz to about 200 kHz and have a narrower beam width of about 5 degrees”15.

Beam width influences spreading loss and the horizontal area ensonified and (along with ping rate) the horizontal resolution of the returned echoes. A wider beam covers a greater horizontal area but the returned echoes are very coarse. A narrow beam combats geometric spreading loss in well-attenuated high-frequency signals and provides much better horizontal resolution, but at the cost of reduced horizontal coverage. Trade offs! In my brief review of the literature I found the following published beam widths: 4 degree (200kHz)16, 10 degree (200kHz)17, 3 degree (104kHz)r18, 7 degree (200kHz) 19, 5 degrees (200 kHz), 15 degrees (200kHz)20, and 7 degrees (200kHz) 21.

Another factor is pulse duration. Shorter pulse duration can provide better vertical resolution of backscatter in the water column. In my cursory look at the literature, I found reported pulse durations of .13ms22, .3ms23 and 1ms24. See this figure:

25

To get the best of both worlds, some echosounder employ two transducers at once, each with a different frequency (usually a low one around 50 kHz and a high one around 200 kHz26). Experienced fishers and scientist use this feature to distinguish between species, because the backscattering properties of some species are frequency dependent.” (See below for much more on this) 27. Many transducers are now a split-beam design, allowing the determination of fish locations in three-dimensional space28. (See figure below.)

14 Misund 1997 15 Misund 1997 16 Rowe 1993. 17 Benoit-Bird et al. 2001. 18 Romaine et al. 2002. 19 Trevorrow 2005. 20 Yule 2000. 21 Gomez-Guitierrez et al. 1999. 22 Benoit-Bird et al. 2001. 23 Gomez-Guitierrez et al. 1999. 24 Romaine et al. 2002. 25 Mathiesen 2003. 26 Maxwell et al. Year Unknown. 27 Misund 1997 28 Maxwell et al. Year Unknown. 3 “The need for a more quantitative method led to the invention of the echo integrator29, in which the voltages generated by the returned echo signals are squared and summed over intervals of depth and distance sailed30.” “By calibrating the echo integrator unit using metal spheres with known backscattering strength31, the recording properties of the instruments can be measured. If the backscattering strength of the recorded fish is known, the echo integrator output can be converted to units of fish density3233. Calibration procedures are precise, difficult and often expensive34, but working alternatives have been developed – some involving Dunlop long-life ping pong balls.3536 High frequency transducers have been calibrated using the reflection off the floor of an enclosed pool37.

38

Transducer depth “The quality of recordings from hull-mounted transducers is weather dependent because wind-induced air- bubbles may attenuate and even block the echosounder transmissions39. Transducers need to be mounted sufficiently below the surface to avoid boundary-layer effects from the sea surface and the boat. Depending on

29 Dragesund and Olsen, 1965 30 Misund 1997 31 Foote et al., 1987 32 MacLennan and Simmonds, 1992 33 Misund 1997 34 Foote et al. 1987. 35 Welsby and Hudson 1972, Cochrane et al. 1991. 36 Yule 2000. 37 Cochrane et al. 1991. 38 Macaulay 1994. 39 Dalen and Løvik, 1981; Novarini and Bruno, 1982 4 the nature of your study area, this tow depth may need to be fairly deep. The large oceanographic vessels use a “fish” towed behind and to the side of the vessel, well below the vessel’s wave and the bubble layer caused by rough open seas. Reported depths have included 6-7m40, 5m41, 10m42, 4m43, 7m44, 6m45, and 3–4 m4647.

Small boats working in protected waters are able to keep their transducer face nearer the surface. Such published studies report mounting their transducer “directly to the transom”48, “20cm below the water line on a stanchion, fixed amidships, but away from the side of the boat… and echograms were only recorded in relatively calm conditions (Beaufort 2 or less) 49”, by pole “to a depth of 0.5m on the port side of a 6m boat50”. All studies tend to cull the top 1m or so of their echograms51, as well as the 1-3m above the seafloor, where boundary conditions can muddle echo-integration.

Survey Design “Critical to the success of any fisheries assessment program, an efficient survey design must incorporate all available knowledge of the stock in question. Increased survey effort is no substitute for a properly designed survey based on a thorough understanding of the biology of the target species to answer clearly defined objectives”52

“For any stock assessment survey, there is a trade-off between the amount of data collected and the precision of the estimate. Increasing the number of data points collected, as shown here with sub and full transects, will ultimately reduce biomass errors with any method of interpolation.”53

There are several possible design approaches: parallel transects, random placement of transects with random orientations, and zig-zag transects. The latter is of most interest to me because it is the design I need to use in the Bangarang Project. The method is common, but like all methods it comes with trade offs.

“Proponents of a systematic zig-zag track design cite a more efficient use of track time as the reason to a zig- zag grid over a parallel one. For a parallel grid with transects extending to the fish distribution boundary (or beyond), the time spent travelling from one transect to the next is “wasted”….Arguments in support of a zig-zag track appear to be more geometric or logistic than statistical.”54

“Two important limitations of a zig-zag track pattern are: the non-independence of transects and a higher local sampling intensity per unit area at the turns compared with other portions of the track. Proponents of zig-zag tracks suggest that these limitations can be addressed by using a ‘zig-zag/parallel hybrid’ – ie at the end of one transect the vessel steams a per-determine distance before starting the next transect of the zig-zag grid. Jolly and Hampton (1990) note that the advantage of parallel designs in removing variation from density gradients in the direction of the transects is lost with a zig-zag design.”55

But then these authors consider a “’narrow’ geographic area to be surveys (e.g., fjord, narrow off-shelf region) with a significant density gradient along the short axis of the region. For this type of spatial distribution and area, a zig-zag track design may be the most appropriate. However, survey planners must exercise caution when using this type of design because of the increased, and thus uneven, sampling intensity at the vertices (or turns of the grid. This poses a major problem if, for example, high densities are found at the boundaries of the survey area. …A zig-zag design has to be recognize as a poor alternative to the parallel sampling strategy and should

40 Cochrane et al. 1991. 41 Coyle and Cooney 1992. 42 Cochrane et al. 2000. 43 Gomez-Guitierrez et al. 1999. 44 Pieper 1979. 45 Sandstrom et al. 1989. 46 Ona, 1994 47 Misund 1997 48 Benoit-Bird et al. 2001. 49 Rowe 1993. 50 Yule 2000. 51 Gomez-Guitierrez et al. 1999. 52 Simmonds et al. 1992. 53 Romaine et al. 2002. 54 Simmonds et al. 1992. 55 Simmonds et al. 1992. 5 only be used if considerable survey effort would be lsot due to geometry or major navigational considerations.”56 They conclude that a systematic zig-zag is the recommended track design for a narrow shelf/fjord situation.57

58

Romaine et al. (2002) wrote: “The best design of a survey transect must therefore be weighted among expected distributions, time and required information59. Hence, zig-zag patterns have been suggested as the best method of acoustic data collection60. Zig-zag transects have been previously employed for studies involving both zooplankton61 and fish62. The major disadvantage of zig-zag transects is that the expected degree of statistical independence from other adjoining legs varies with the position along the leg.”63

Romaine et al. (2002)’s “zig-zag transects…had approximately equal spacing between parallel legs to maximize coverage during daylight hours and to account for topographic irregularities found within each inlet.”64 “Our zig- zag transect designs yielded dense coverage of along- and cross-inlet variability, while maximizing the total area covered within a limited time period.”65

56 Simmonds et al. 1992. 57 Simmonds et al. 1992. 58 Yule 2000. 59 MacLenna and Simmonds 1992 60 Nickerson and Dowd 1977; Kimura and Lemberg 1981; zig-zag also used in Wiebe et al. 1997. 61 e.g. Simard et al. 1992, Macaulay et al. 1995 62 e.g. Sullivan 1991 63 Romaine et al. 2002. 64 Romaine et al. 2002. 65 Romaine et al. 2002. 6

Other Design Concerns “Night echo sounding is undesirable because euphausiids disperse in the presence of deck lighting, they may be above the nominal depth of the transducer, and target resolution complications occur within close proximity to the transducer face (MacLennan and Simmons 1992)”66. It is generally recommended that echo sounders have two or more frequencies and if possible the beam widths of the frequencies should be the same67. “The power supply should be separate or otherwise isolated from that used by the vessel engine as electrical interference can cause noise on the acoustic signal.”68

69. 70.

Observation Range Because echosounder signals are attenuated with depth, there is a limit to the range they can ensonify and accurately represent on an echogram. As mentioned above, higher frequencies attenuate more quickly and therefore have a more limited “observation range”. Observation range is also a function of the Target Strength (TS, i.e., reflectivity) of the animal you are trying to detect (see “Scatterers” section below)71.

What are the expected observation ranges of difference frequencies? One published study with a 102kHz sounder identified schools down to 280m72, but it has been written elsewhere that “the effect of noise is seen at depths deeper than about 200m in the 120kHz echogram”73. One 200-kHz study in Saanich Inlet only looked at the upper 100m74, as did another75, while another with the same frequency showed column features down to 200m76.

When comparing echograms of different frequencies, a common observation range must be taken into account. The comparison must be conducted over a common observation range77 -- this is especially important when calculating difference of Mean Volume Backscatter Strength (see section below)78. Target Strength plays another role here. “In general, the smaller the TS value, the smaller the observation range for both frequencies

66 Romaine et al. 2002. 67 Kang et al. 2002. 68 Maxwell et al. Year Unknown.

69 Romaine et al. 2002. 70 Romaine et al. 2002. 71 Kang et al. 2002. 72 Pieper 1979. 73 Kang et al. 2002. 74 Sato et a. 2013. 75 Benoit-Bird et al. 2001. 76 Cochrane et al. 1991. 77 Kang et al. 2002. 78 Kang et al. 2002. 7 and the smaller the difference between frequencies. [For 38- and 120-kHz sounders,] both frequencies have a common observation range up to a water depth of 150m regardless of TS values”79. See the figure below.

Also important: In order to produce a large common observation range the sounder specifications for different frequencies should be as similar as possible and, above all, the beam widths should be the same80. For localized scatter concentrations, the 50- and 200-kHz spatial patterns differ slightly due to the wider 50kHz transducer beam width. This may be detected as localized variation in the shade of blue or green “fringing” around a more bluish core81.

82

Data Reduction After hydroacoustic data are collected, they need to be processed (“reduced”) and made comprehensible for meaningful analysis. There a hundreds of published ways of doing this, but all involve at least the cleaning up of data, the binning of data into rectified units for comparison, and visualization. Data sets are visually “screened to eliminate observations with excessive noise, acoustic interference, or obvious instrumental malfunction”83. Surface (down to 5m below it84) and seafloor data (up to 2.5m up from it85) need to be deleted because they are often noisy and may accidentally be incorporating reflections of the boundaries and not of the biota. Echosounders cannot assess swarms at shallow depths above the depth of the saturated outgoing signal, hence the proportion of swarm occupying this upper layer cannot be accurately evaluated86. Also, if data will be integrated into bins or “cells”, it is important to use a small integration cell for classification purposes87.

79 Kang et al. 2002. 80 Kang et al. 2002. 81 Cochrane et al. 1991. 82 Kang et al. 2002. 83 Cochrane et al. 2000. 84 Coyle and Cooney 1992. 85 Coyle and Cooney 1992. 86 Nemoto 1983. 87 Kang et al. 2002. 8 Scatterers

“Marine organisms are not the only cause of the frequency characteristics of echoes: the echosounder system, noise, and acoustic propagation have frequency characteristics and they give frequency dependent echoes.”88

“Acoustic echo levels from zooplankton are strongly dependent upon the acoustic frequency and size, shape, orientation and material properties of the animals.”89

The goal in hydroacoustics (at least here) is to detect animals remotely by receiving echoes of the backscatter they create in the water ensonified under our boat. Often a secondary goal is to identify – to some level of specificity – who the animals are. To achieve either end, we must consider the reflectivity of the targeted taxa.

In sonar equations Target Strength, TS, is the parameter that describes the reflecting properties of the target. “Target strength is the most important and the most difficult parameter to measure directly. It can also be determined indirectly from test fishing or from oscilloscope voltage measurements in low density situations.”90 However, applying laboratory measurements of an animal’s target strength to data collected in the field is difficult for many reasons. Biota are not the only scatterers in the water column. Suspended sediment91, bubbles near the surface from storm wave action, and density differences in stratified layers of water can produce scatter. Even if these variables were absent, the animals themselves introduce a flurry of confounding issues. As a result, substantial error can be associated with acoustic biomass estimates92.

Frequency dependence Even in laboratory conditions, the Target Strength of an animal is a function of the frequency of the incident sound wave. The frequency dependence of an organism is influenced by both its overall size93 and its material properties. Three categories of scatterers, represented by theoretical scattering models, have been identified by Stanton et al (1994): gas-bearing (e.g. siphonophores), fluid-like (e.g. euphausiids), and hard elastic-shelled (e.g. pteropods)94. Animals within these categories reflect certain frequencies sound more thoroughly than others. Furthermore, within each group scattering properties can be species-specific95.

96 Because the density difference between air and water is so great, gas-bearing plankton (e.g. siphonophores) and nekton (e.g. most fish, incl. walleye pollock and salmon) tend to have strong target strengths at nearly all frequencies. They do not show sharp frequency dependence. “The air-filled swim bladder accounts for about

88 Kang et al. 2002, Furusawa et al. 1999 89 Stanton et al. 1996. 90 Mathiesen 2003. 91 Sato et a. 2013. 92 Romaine et al. 2002. 93 Cochrane et al. 1991. 94 Martin et al. 1996 95 Misund 1997 96 Martin et al. 1996 9 90–95% of the backscattering cross section of fish97”, and air-bladdered fish are detected at frequencies ranging from 12kHz to above 200kHz. “Fishes that lack this organ, such as the Atlantic mackerel [or the sand lance98], consequently have a backscattering cross section that is only about 1/10 that of comparable swimbladdered species99”.

Their frequency response may be flat, but these gas-bearing taxa are best surveyed with lower frequencies (38kHz or lower) because 1) low frequencies can sample deeper (less attenuation) and 2) higher frequencies will backscatter off other organisms, confounding results (see below), and 3) some gas-bearing species like herring have been shown to exhibit a lower backscattering cross-section at frequencies higher than 38kHz100.

101

Unlike air-bladdered fish, iso-osmotic centimeter-sized zooplankton have much higher frequency dependence. “For example, the plot for euphausiids when ensonified at broadside incidence contained a series of broadly spaced deep nulls. The nulls from the euphausiid data were sometimes as deep as 30 dB below surrounding levels. The patterns are linked to the physics of the scattering process.”102

The periodic nulls in their frequency response notwithstanding, zooplankton and other fluid-like objects are generally more reflective at higher frequencies. Small zooplankton are only detected at 50 and 200 kHz103. For bladderless mackerel, “Edwards et al. (1984) found a 50% higher backscattering cross section at 120 kHz compared with that at 38 kHz”104. This holds true for Euphausia pacifica, which “exhibits an increasing acoustic target strength with frequency (the 38 kHz signal is much weaker), whereas larger animals such as fish have a roughly constant acoustic target strength across these three frequencies”105.

Euphausiid patches are usually recorded at frequencies between 79 and 200kHz, though dense patches of Meganyctiphanes norvegica have been detected at 50 kHz 106 . Some published analyses assume that

97 Foote, 1980b 98 Robards and Piatt. 1999. 99 Foote, 1980b Whole sound scattering layer (SSL) was investigated using a 200 kHz Simrad EY-200. They found latitudinal changes in the euphausiids assemblages using this method100.

100 Misund 1997, Edwards et al. (1984) and Degnbol et al. (1985) 101 Stanton et al. 1996. 102 Stanton et al. 1996. 103 Cochrane et al. 1991. 104 Misund 1997 105 Ianson et al 2011 106 Cochrane et al. 2000. 10 euphausiids abundances are proportional to backscatter levels for 50kHz and above107. Swarms of Antarctic krill, E. superba, have been successfully detected with 100-200kHz echo sounders108. Eddie (1977), working in the Antarctic, suggested that 100 to 120kHz sounders were the most effective in detecting krill layers and aggregations. 120 kHz echo sounders have been used to monitor euphausiids densities and distributions109. Dolphin (1987, 1988) used a 120kHz echo sounder to investigate both fish and euphausiids relative densities110. Many studies have used a single–beam 200-kHz echo sounder, many for euphausiid biomass estimation111112113114115 or general sound scattering layer characterization (including euphausiids)116. Others have used single 200 kHz echo sounders for characterizing internal waves117 (see above). Less conventional frequencies have been published: 197 kHz for euphausiids vertical migration studies 118 , a 104 kHz for euphausiid biomass estimation in southern BC fjords119, 420 kHz up-sounding dual-beam echosounder for target strength measurements120,

121 Buncha littles or a single big? Acousticians attempt to identify the species present based on characteristics of the observed backscatter. This is not easy because a group of low-target-strength animals might cumulatively reflect the same amount of sound as a single individual of a reflective species. It can be impossible to distinguish between the two possibilities in an echogram, especially if spatial resolution is poor. “For example, at 200 kHz, the 2-mm-long gastropods scatter sound approximately 19 000 times more efficiently (on an echo energy per unit biomass scale) than the 30-mm-long salps. As a result of this difference in scattering efficiency, it only takes about 14 m3 of these small gastropods to produce a level of volume scattering strength of 70 dB at 200 kHz, while it would take about 190

107 Cochrane et al. 2000. 108 Nemoto 1983. 109 in Sameoto (1976), Brodie et al. (1978), Hopkins et al. (1978) 110 Dolphin (1987, 1988) 111 Benoit-Bird et al. 2001. 112 Romaine et al. 2002. 113 Rowe 1993. 114 Sato et a. 2013. 115 Yule 2000. 116 Gomez-Guitierrez et al. 1999. 117 Sandstrom et al. 1989. 118 Bary and Pieper (1971) 119 Romaine et al. 2002. 120 Wiebe et ak, 1990. 121 Macaulay 1994. 11 salps to produce that same level (Table 2). This difference changes dramatically at 38 kHz, where the 2-mm- long gastropods are in the Rayleigh scattering region and 6250 are required to produce the 70 dB volume scattering strength.”122

This confusion points to another: group size and density affect detectability. “High euphausiids densities make detection possible and the known behavioral patterns aid in discriminating the euphausiids from other scatterers. In some areas, however, population densities are low, the euphausiids are deep in the water column, and some species do not migrate. Detection of these populations by acoustical methods is unlikely with conventional acoustical equipment. Similarly, quantification of euphausiids layers using commercial echo sounders operated at or near the surface is not possible when stronger targets (e.g., fishes) dominate the recorded scattering.” 123

124

Orientation Changes in the animal’s orientation during ensonification may lead to ping-to-ping variability in the acoustic returns from a single target125. This is because the orientation of the animal determines the surface exposed to the echosounder’s ping (its “backscattering cross section”). Sound pulses from echo sounders typically ensonify targets on their dorsal aspect. “A change in vertical orientation with the body tilted slightly upwards or downwards may easily result in a reduction of the backscattering cross section by a factor of 100126, in extreme cases by a factor of 10 000127. Changes in the roll angle of the fish also affect the backscattering cross-section, but not to such a dramatic extent as do changes in tilt angle128129. The effect of orientation is also frequency- dependent. “Generally, at higher frequency the tilt angle dependence becomes more variable130131”132.

Swim speed of the animal also influences target strength133.

Avoidance Target species may be avoiding the boat, which is annoying. On the bright side it is doubtful that they are reacting to the emitted frequencies. There is certainty in the literature that “the frequency band used in scientific sonars (typically 38 to 200 kHz) is not detectable by most fishes”134.

Internal Waves Because internal waves are oscillating interfaces between stratified layers of different densities, they tend to create backscatter on echosounders. This can be thought of as a hassle or a really cool opportunity. “The acoustic backscatter levels in the turbulent patches approach -50dB at 200kHz under typical oceanographic

122 Stanton et al. 1996. 123 Pieper 1983. 124 Stanton et al. 1996. 125 Martin et al. 1996 126 Nakken and Olsen, 1977; Foote, 1980a 127 Foote and Nakken, 1978 128 Love, 1977 129 Misund 1997 130 Nakken and Olsen, 1977 131 Misund 1997 132 Kang et al. 2002. 133 Mathiesen 2003. 134 except see Mann et al. 2001, Gregory and Clabburn, 2003 12 conditions, providing a rapid and convenient survey tool for estimating mixing structure and levels by internal waves and internal tides”135. Studies using 120kHz136 and 200kHz137138139 echo sounders have detected and monitored internal waves. Echo sounders have detected pycnocline displacements of 5 to 14m140. “The source of scattering in the internal waves is probably due to a combination of both animals and sound-speed microstructure141”.

142.

143 144

135 Sandstrom et al. 1989. 136 Wiebe et al. 1997 137 Sandstrom et al. 1989. 138 Trevorrow 1998. 139 Sandstrom et al. 1989. 140 Trevorrow 1998. 141 Wiebe et al. 1997 142 Sandstrom et al. 1989. 143 Sandstrom et al. 1989. 144 Trevorrow 2005. 13 Taxon Differentiation145

“Despite these uncertainties, hydroacoustic techniques are useful because they measure fine scale distributions of zooplankton biomass in both vertical and horizontal dimensions, allowing estimation of the size, relative density and distribution of zooplankton patches. When compared with hydrographic information, ADB data may help elucidate the physical and biological processes affecting distribution and abundance of zooplankton and their predators”146.

Δ MVBS

The frequency dependence of zooplankton can be a confounding factor, but it can also help to separate size classes147 or identify the taxa present148149. Quantitatively discerning between taxa requires the design of classification algorithms that are robust to the confounding variables mentioned above150, but general inferences can be drawn if the right data are collected. Because “the echoes from planktom are more highly dependent on frequencies than the echoes from fish”,151 the taxonomic content of echograms can be inferred by looking at the difference of Mean Volume Backscatter Strengths (MVBS) among frequencies. This has also been called “dB differencing152…The technique has been used to separate fish with gas-filled swimbladders from fish with no swimbladder153 and swimbladder-bearing fish from zooplankton154”. This can be done with qualitative visual scrutiny or with the actual overlay or subtraction of one frequency’s ping data from the other and examining what remains155 (see examples below).

Fishermen tend to be adroit at discerning taxa this way. “For example, in the North Sea, herring (Clupea harengus, Clupeidae) and Atlantic mackerel (Scomber scombrus, Scombridae) may frequently occur on the same fishing grounds, but fishers can distinguish their acoustic images because herring shoals appear as strong (red) recordings both at high and at low frequency while mackerel shoals give strong (red) echoes on high frequency but weak (green) echoes on low frequency156.

Echograms from 38kHz sounds or lower detect mainly fish157 or physonectid siphonophores158. Herring and young hake are the principal species associated with scattering layers in BC mainland inlets159 160. These taxa are picked up on higher frequencies as well, but the advantage of using lower frequencies is that you can separate high-frequency reflectors from the low. Soundscatter peaks on both frequencies are attribute to either gelatinous zooplankton like siphonophores or air-bladdered fish161.

Peaks that occur on 200 kHz echograms and not low-frequency echograms are attributed to euphausiids swarms162. Krill exhibit very large differences in sound-scattering strength between 38 [or lower] and 120kHz, the two most commonly used frequencies in fisheries research163 . At 12 kHz, for example, euphausiids backscatter at 25-30dB below 200-kHz levels164. The difference between 38kHz and 120kHz is also very large

145 Or, “Turning Acoustic Lemons into Fucking Delicious Lemonade.” 146 Coyle and Cooney 1992. 147 McNaught 1969, Holliday 1977 148 Anderson 1950, Haslett 1965, Zakharia and Sessarego 1982 149 Jech et al. 2006. 150 Martin et al. 1996 151 Kang et al. 2002. 152 Higgenbottom et al. 2000 153 Kirkegaard and Lassen 1990 154 Saetersdal et al. 1982; Cochrane et al. 1991, Kang et al. 2002 155 Kang et al. 2002. 156 Misund 1997 157 Cochrane et al. 2000. 158 Farquar, 1971; Andersen and Zahuranec, 1977 159 Bary 1966 160 Sato et a. 2013. 161 Coyle and Cooney 1992. 162 Coyle and Cooney 1992. 163 Kang et al. 2002. 164 Cochrane et al. 2000. 14 and offers a robust means of classifying165. Using frequencies lower than 120kHz is risky because euphausiid reflectivity degrades and fish echo contamination can be more confounding166. Compared to 50 and 150kHz, 200kHz has been considered preferable for euphausiid biomass estimation167.

The issue with the 200kHz frequency is that copepods begin to become reflective. Large and dense aggregations of large-bodied copepods have registered scantly on 120kHz echograms168169, but their presence is more of a factor in even higher frequencies. Some studies have successfully detected copepods near-surface with a 200kHz system, and others have found success with larger calanoid species170171. Other studies, including one in Saanich Inlet172, considered the contribution of copepods to their 200 kHz echogram to be negligible. 200 kHz is also on the lower end of the appropriate frequencies for pteropod detection. 445 kHz is the preferred frequency for detecting these zooplankters, and their contribution at 200 kHz is not significant173.

Multi-Beam Acoustics

Obviously, MBVS Difference relies on the simultaneous collection of acoustic data at two frequencies. This is done best by using two frequencies simultaneously, typically a high and a low. “A combination of 38 and 200 kHz [for example] has proven effective for separation of fish and zooplankton174. The 38- and 200-kHz dual- beam setup is among the most common in surveys for both fish and euphausiids175176. 38- and 120-kHz is another common duo for the same purpose177. “Surveys of 120kHz can provide good estimates of biomass over a large size range, while concurrent observations at 38kHz provide additional information that can be used to identify echo traces caused by different scatterers”178. 120- and 420-kHz duo’s have been used for scattering layer characterization179. 50- and 200-kHz has also been used180. Multi-beam systems are extremely expensive but increasingly used. Croll et al. (1998) used a Simrad EK-500 operating at 38-, 120- and 200-kHz181 for an integrative ecological study of blue whale foraging ecology. Other published multi-beam combinations include 12-50-200-kHz182 off the Scotian Shelf (for hake and euphausiids and general “taxon differentiation”), 25-50-100- 100-kHz for sound scattering layer characterization in Japan183, 11-42-107-200-kHz for scattering layer studies in Saanich Inlet184, 12-18-38-120-kHz on a Simrad EK500185, and 38-120-200-lHz in Knight Inlet, BC186.

Considerations

In order to perform dB differencing well, a few rules must be followed. MVBS output is sometimes contaminated by frequency-dependent noise, especially in deeper layers. “This is why we must determine the observation range when we discuss the frequency characteristics of scattering...The comparison between frequency outputs must be done over a common observation range [see section above]. In order to produce a large common observation range the sounder specifications for different frequencies should be as similar as possible and, above all, the beam widths should be the same”187. If beam patterns differ, precaution must be taken. “For

165 Kang et al. 2002. 166 Cochrane et al. 2000. 167 Cochrane et al. 2000. 168 Macaulay et al. 1995. 169 Macaulay et al. 1995. 170 Macaulay et al. 1995, Barraclogh et al. 1969. 171 Macaulay et al. 1995. 172 Sato et a. 2013. 173 Sato et a. 2013, Stanton et al. 1994 174 Simrad EK60 Scientific Echosounder pamphlet 175 Wiebe et al. 1997 176 Coyle and Cooney 1992. 177 Kang et al. 2002. 178 Madureira et al. 1993. 179 Wiebe et al. 1997 180 Cochrane et al. 1991. 181 Croll et al 1998 182 Cochrane et al. 1991. 183 Iida et al. 1996 184 Pieper 1971. 185 Jech et al. 2006. 186 Trevorrow 2005. 187 Kang et al. 2002. 15 localized scatter concentrations, the 50- and 200-kHz spatial patterns differ slightly due to the wider 50kHz transducer beam width. This may be detected as localized variation in the shade of blue or green “fringing” around a more bluish core”188.

“Using a color echogram to display the absolute value of the MVBS provides important information rather easily.189”

Examples

Scrutinizing echograms visually based on human experience is rather subjective190 but it is still an excellent tool. Learning how to do so correctly and with precaution is a critical skill for anyone using hydroacoustics in their study.

191

192.

188 Cochrane et al. 1991. 189 Kang et al. 2002. 190 Kang et al. 2002, Reid et al. 1998 191 Simrad EK60 Scientific Echosounder pamphlet 192 Kang et al. 2002. 16

193.

193 Cochrane et al. 2000. 17

194

194 Jech et al. 2006. 18

195

196 .

195 Jech et al. 2006. 196 Rowe 1993. 19

197

197 Trevorrow 2005. 20 Literature Cited

Andersen, N. R., and B. J. Zahuranec (eds.), 1977. Oceanic Sound Scattering Prediction. Plenum Press, New York: 859 pp. Anderson, VC. 1950. Sound scattering from a fluid sphere. J. Acoust. Soc. Am. 22:426-431. Bary BM (1966) Backscattering at 12 kc/s in relation to biomass and numbers of zooplanktonic organisms in Saanich Inlet, British Columbia. Deep-Sea Res 13: 655−666 Bary BM (1966) Backscattering at 12 kc/s in relation to biomass and numbers of zooplanktonic organisms in Saanich Inlet, British Columbia. Deep-Sea Res 13: 655−666 Bary BM, Barraclough WE, Herlinveaux R (1962) Scattering of underwater sound in Saanich Inlet, British Columbia. Nature 194: 36−37 Bary, B. McK., and R. E. Pieper, 1971. Sonic-scattering studies in Saanich Inlet, British Columbia: a preliminary report. In: G. B. Farquhar (ed.). Proceedings of an International Symposium on Biological Sound Scattering in the Ocean, Maury Center for Ocean Science, Washington, D. C.: 601-611. Beauchamp, D.A., C. Luecke, W.A. Wurtsbaugh, H.G. Gross, P.E. Budy, S. Spaulding, R. Dillenger, and C.P. Gubala. 1997. Hydroacoustic assessment of abundance and diel distribution of sockeye salmon and kokanee in the Sawtooth Valley Lakes, Idaho. North American Journal of Fisheries Management 17:253-267. Benoit-Bird, KJ, WL Au, RE Brainard, MO Lammers. 2001. Diel horizontal migration of the Hawaiian mesopelagic boundary community observed acoustically. 217:1-14. Blaxter, J.H.S. and Batty, R.S. (1990) Swimbladder behaviour and target strength. Rapp. P.-v. Re´un. Cons. Int. Explor. Mer 189, 233–44. Blaxter, J.H.S. and Tytler, P. (1978) Physiology and function of the swimbladder. Adv. Comp. Physiol. Biochem. 7, 311–67. Brandt, S.B. 1996. Acoustic assessment of fish abundance. Pages 385-419 in B.R. Murphy and D.W. Willis, editors, Fisheries techniques, 2nd edition. American Fisheries Society, Bethesda, Maryland. Brandt, S.B., D.M. Mason, E.V. Patrick, R.L. Argyle, L. Wells, P.A. Unger, and D.J. Stewart. 1991. Acoustic measures of the abundance and size of pelagic planktivores in Lake Michigan. Canadian Journal of Fisheries and Aquatic Sciences 48:894-908. Brawn, V.M. (1962) Physical properties and hydrostatic function of the swimbladder of herring (Clupea harengus L.). J. Fish. Res. Bd Can. 19, 635–56. Burczynski, J.J., and R.L. Johnson. 1986. Application of dual-beam acoustic survey techniques to limnetic populations of juvenile sockeye salmon (Oncorhynchus nerka). Canadian Journal of Fisheries and Aquatic Sciences 43:1776-1788. Cochrane, N. A., Sameoto, D. D., and Herman, A. W. 2000. Scotian Shelf euphausiids and silver hake population changes during 1984–1996 measured by multi-frequency acoustics. – ICES Journal of Marine Science, 57: 122–132 Cochrane, N. Pa., D. Sarneoto, A. W. Herman, and J. Neilson. 1991. Multiple-frequency acoustic backscattering and zooplankton aggregations in the inner Scstian Shelf basins. Can. 8. Fish. Aquat. Sci. 48: 340-355. Cochrane, NA ,D Sameoto, AW Herman, J Neilson. 1991. Multiple-frequency acoustic backscattering and zooplankton aggregations in the inner Scotian shelf basins. Can. J. Fish. Aquat. Sci. 48:340-355. Coyle, KO and RT Cooney. 1992. Water column sound scattering and hydrography around the Pribilof Islands, Bering Sea. Croll, D. A., Tershy, B. R., Hewitt, R. P., Demer, D. A., Fiedler, P. C., Smith, S. E., Armstrong, W., Popp, J. M., Kiekhefer, T., Lopez, V. R. et al. 1998. An integrated approach to the foraging ecology of marine birds and mammals. Deep Sea Res. Part II-Top. Stud. Oceanogr. 45, 1353-1371. Cyterski, M., J. Ney, and M. Duval. 2003. Estimation of surplus biomass of clupeids in Smith Mountain Lake, Virginia. Transactions of the American Fisheries Society 132:361-370. Dalen, J. and Løvik, A. (1981) The influence of wind-induced bubbles on echo-integration surveys. J. Acoust. Soc. Am. 69, 1653–9. De Robertis A (2002) Small-scale spatial distribution of the euphausiid Euphausia pacifica and overlap with planktivorous fishes. J Plankton Res 24: 1207−1220 De Robertis A (2002) Small-scale spatial distribution of the euphausiid Euphausia pacifica and overlap with planktivorous fishes. J Plankton Res 24: 1207−1220

21 Degan, D.J. and W. Wilson. 1995. Comparison of four hydroacoustic frequencies for sampling pelagic fish populations in Lake Texoma. North American Journal of Fisheries Management 15:924-932. Degnbol, P., Lassen, H. and Staer, K.J. (1985) In-situ determination of target strength of herring and sprat at 38 and 120 kHz. Dana 5, 45–54. Dolphin, WF. 1988. Foraging dive patterns of humpback whales, Megaptera novaeangliae, in southeast Alaska: a cost-benefit analysis. Can. J. Zool. 66: 2432-2441. Dragesund, O. and Olsen, S. (1965) On the possibility of estimating year-class strength by measuring echo- abundance of O-group fish. FiskDir. Skr. Ser. Havunders. 13, 47–75. Eddie, G. 0., 1977. The harvesting of krill. Food and Agriculture Organization of the United Nations, GLO/S0/77/2: 76 pp. Edwards, J.I., Armstrong, F., Magurran, A.E. and Pitcher, T.J. (1984) Herring, mackerel and sprat target strength experiments with behavioural observations. ICES CM 1984/B:34, 21 pp. Farquhar, G. B. (ed.), 1971. Proceedings of an International Symposium on Biological Sound Scattering in the Ocean, Maury Center for Ocean Science, Washington, D. C.: 629 pp. Foote, K.G. (1980a) Effects of fish behaviour on echo energy: the need for measurements of orientation distributions. J. Cons. Int. Explor. Mer 39, 193–201. Foote, K.G. (1980b) Importance of the swimbladder in acoustic scattering by fish: a comparison of gadoid and mackerel target strengths. J. Acoust. Soc. Am. 67, 2084–9. Foote, K.G. (1987) Fish target strengths for use in echo integrator surveys. J. Acoust. Soc. Am. 82, 981–7. Foote, KG, HP Knudsen, G Vestnes. 1987. Calibration of acoustic instruments for fish density estimation: a practical guide. Cooperative Research Report. No. 144. Foote, K.G. and Nakken, O. (1978) Dorsal-aspect target strength functions of six fishes at two ultrasonic frequencies. Fisken og Havet. Ser. B, 1978, Institute of Marine Research, Bergen, 95 pp. Gomez-Gutierrez, J, G Gonzalez-Chavez, CJ Robinson and V Arenas-Fuentes. 1999. Latitudinal changes of euphausiids assemblages related to the morphological variability of the sound scattering layer along Baja California, October 1994. Sci. Mar. 63(1):79-91. Gregory J., and Clabburn, P. 2003. Avoidance behaviour of Alosa fallax fallax to pulsed ultrasound and its potential as a technique for monitoring clupeid spawning migration in a shallow river. Aquatic Living Resources, 16, 313 – 316. Griffiths, G, JI Diaz. 1996. Comparison of acoustic backscatter measurements from a ship-mounted Acoustic Doppler Current Profiler and an EK500 scientific echo-sounder. ICES Journal of Marine Science 53:487- 491. Harden Jones, F.R. and Scholes, P. (1981) The swimbladder, vertical movements and the target strength of fish. In Soumala, J.B., ed. Meeting on Hydroacoustical Methods for the Estimation of Marine Fish Populations, 25–29 June 1979, Vol. 2. Cambridge, MA: Charles Stark Draper Laboratory, pp. 157–82. Haslett, RWG. 1965. Acoustic backscattering cross sections of fish at three frequencies and their representation on a universal graph. Br. J. Appl. Phys. 16: 1143-1150. Higginbottom, IR, TJ Pauly, DC Heatly. 2000. Virtual echosgrams for visualization and post-processing of multiple-frequency echosounder data. In Proceedings of the Fifth European Conference on Underwater Acoustics, ECUA 2000, 10-13 July 2000, Villeurbanne, France. Office for the Official Publications of the European Communities, Luxembourg. Pp. 1497-1502. Holliday, DV. 1977. Extracting bio-physical information from the acoustic signature of marine organisms. In Oceanic sound scattering prediction. Edited by NR Anderson and BJ Zahuranec. Plenum Press, New York, pp619-624. Hopkins, C. C. E., S. Falk-Petersen, K. Tande, and H. C. Eilertsen, 1978. A preliminary study of zooplankton sound scattering layers in Balsfjorden: structure, energetics, and migrations. Sarsia. 63:255-264. Iida, K, T Mukai, and Hwang. 1996. Relationship between acoustic backscattering strength and density of zooplankton in the sound-scattering layer. ICES Journal of Marine Science 53:507-512. Jech, J Michael and WL Michaels. 2006. A multifrequency method to classify and evaluate fisheries acoustics data. Can. J. Fish. Aquat. Sci. 63:2225-2235. Kang, M, M. Furusawa, and K Miyashita. 2002. Effective and accurate use of difference in mean volume backscattering strength to identify fish and plankton. ICES Journal of Marine Science 59:794-804. Kimura, D.K. and Lemberg, N.A. (1981) Variability of line intercept density estimates (a simulation study of hydroacoustic biomass estimates). Can. J. Fish. Aquat. Sci. 38:1141±1152. Kirkegaard, E and LH Lassen. 1990. Mean volume backscattering strength at 38kHz and 120kHz and echogram classification. Rapp. P-V. Reun.Cons.Int.Explor.Mer, 189:73-81.

22 Levy, D.A., B. Ransom, and J. Burczynski. 1991. Hydroacoustic estimation of sockeye salmon abundance and distribution in the Strait of Georgia, 1986. Pacific Salmon Commission, Technical Report 2, Vancouver, British Columbia. Love, R.H. (1977) Target strength of an individual fish at any aspect. J. Acoust. Soc. Am. 62, 1397–403. Macaulay, M.C., Wishner, K.F., Daly, K.L., 1995.Acoustic scattering from zooplankton and micronekton in relation to a whale feeding site near Georges Bank and Cape Cod. Cont. Self. Res. 15, 509_537. Macaulay, MC, KF Wishner, KL Daly. 1995. Acoustic scattering from zooplankton and micronekton in relation to a whale feeding site near Georges Bank and Cape Copd. Continental Shelf Research 15(4/5):509-537. Macaulay, MC. 1994. Applications of hydroacoustics in marine ecological studies: a perspective on the present status and future directions. Proc. NIPR Symp. Polar Biol. 7:118-132. MacCartney, B.S. and Stubbs, A.R. (1971) Measurements of the acoustic target strength of fish in dorsal aspect, including swimbladder resonance. J. Sound Vib. 15, 397–420. Mackas, D.L. (1992) Seasonal cycle of zooplankton off southwestern British Columbia: 1979±89. Can. J. Fish. Aquat. Sci. 49:903±921. Mackas, D.L. and Fulton, J.D. (1989) Distribution and aggregation of zooplankton in the Strait of Georgia and their potential availability to marine birds. In: The Ecology and Status of Marine and Shoreline Birds in the Strait of Georgia, British Columbia. K. Vermeer and R.W. Butler (eds). Ottawa, ON: Can Wildlife Serv. Spec. Publication. Mackas, D.L., Saunders, M., Keiser, R., Brown, R.M., Yelland, D.R. and Moore, D.F. (1997) Aggregation of euphausiids and hake along the outer continental shelf off Vancouver Island. Can. J. Fish. Aquat. Sci. 54:2080±2096. MacLennan, D.N. and Simmonds, E.J. (1992) Fisheries acoustics. Fish and Fisheries Series, 5. New York: Chapman & Hall,p. 325. MacLennan, D.N., and E.J. Simmonds. 1992. Fisheries acoustics. Chapman and Hall, London. Madureira, LSP, I Everson, EJ Muprhy. 1993. Interpretation of acoustic data at two frequencies to discriminate between Antarctic krill (Euphausia superba Dana) and other scatterers. Journal of Plankton Research 15(7):787-802. Mann, DA; Higgs, DM; Tavolga, WN; Souza, MJ; and Popper, AN. 2001. Ultrasound detection by clupeiform fishes. Journal of the Acoustical Society of America, 109(6):3048-3054. Martin, LV, TK Stanton, PH Wiebe, and JF Lynch. 1996. Acoustic classification of zooplankton. ICES Journal of Marine Science 53:217-224. Mathiesen, Ola A. 2003. Acoustic Stock Assessment. FAO Corporate Document Repository. Maxwell, SL, DH Johnson, and JC Taylor. Year unknown. Hydroacoustic Protocol – Lakes, Reservoirs and Lowland Rivers. McNaught, DC. 1969. Developments in acoustic plankton sampling. Proc. Conf. Gt. Lakes res. 12:61-68. Misund, OA. 1997. Underwater acoustics in marine fisheres and fisheries research. Reviews in Fish Biology and Fishers 7, 1-34. Mulligan, T.J., and R. Kieser. 1986. Comparison of acoustic population estimates of salmon in a lake with a weir count. Canadian Journal of Fisheries and Aquatic Sciences 43:1373-1385. Nakken, O. and Olsen, K. (1977) Target strength measurements of fish. Rapp. P.-v. Re´un. Cons. Int. Explor. Mer 170, 52–69. Nakken, O. and Olsen, K. (1977) Target strength measurements of fish. Rapp. P.-v. Re´un. Cons. Int. Explor. Mer 170, 52–69. Nemoto, Takahisa. 1983. Net Sampling and Abundance Assessment of Euphausiids, Biological Oceanography, 2:2-4, 211-226 Nickerson, T.B. and Dowd, R.G. (1977) Design and operation of survey patterns for demersal ®sh using the computerized echo sounding system. Rapp. P.-V. Reun. Cons. Int. Explor. Mer. 170:232±236. Novarini, J.C. and Bruno, D.R. (1982) Effects of the sub-surface bubble layer on sound propagation. J. Acoust. Soc. Am. 72, 501–14. Ona, E. (1994) Recent development of acoustic instrumentation in connection with fish capture and abundance estimation. In Ferno¨, A. and Olsen, S., eds. Marine Fish Behaviour in Capture and Abundance Estimation. Oxford: Fishing News Books, pp. 200–16. Parkinson, E.A., B.E. Rieman, and L.G. Rudstam. 1994. Comparison of acoustic and trawl methods of estimating density and age composition of kokanee. Transactions of the American Fisheries Society 123:841-854.

23 Pieper, RE. 1979. Euphausiid distribution and biomass determined acoustically at 102 kHz. Deep-Sea Research 26(6A):687-702. Pieper, RE. 1983. Quantitative estimates of euphausiids biomass determined by high-frequency acoustics. Biological Oceanography 2(2-4). Pieper, RW. 1971. A study of the relationship between zooplankton and high-frequency scattering of underwater sound. PhD Tehsis, University of British Columbia. Robards, M.D.; Piatt, J.F.; Rose, G.A. 1999. Maturation, fecundity, and intertidal spawning of Pacific sand lance (Ammodytes hexapterus) in the northern Gulf of Alaska. Journal of Fish Biology 54: 1050-1068. Romaine, SJ, DL Mackas, and MC MacAulay. 2002. Comparison of euphausiids population size estimates obtained using replicated acoustic surveys of coastal inlets and block average vs. geostatistical spatial interpolation methods. Fisheries Oceanography 11:2, 102-115. Rowe, DK. 1993. Identification of fish responsible for five layers of echoes recorded by high-frequency (200kHz) echosounding in Lake Rotoiti, north Island, New Zealand. New Zealand Journal of Marine and Freshwater Research. Saetersdal, G, T Stromme, B Bakken and L Piekutowski. 1982. Some observations on frequency dependent back scattering strength. In Symposium on fisheries acoustics. Edited by O. Nakken and SC Venema. FAO Fisheries Report No. 300. Pp. 150-156. Sameoto, D. D., 1976. Distribution of sound scattering layers caused by euphausiids and their relationship to chlorophyll a concentrations in the Gulf of St. Lawrence estuary. J. Fish. Res. Bd., Canada. 33:681--687. Sandstrom, H, JA Elliott and NA Cochrane. 1989. Observing groups of solitary internal waves and turbulence with BATFISH and Echo-Sounder. Journal of Physical Oceanography 19: 987. Sato M, Jumars PA (2008) Seasonal and vertical variations in emergence behaviors of Neomysis americana. Limnol Oceanogr 53: 1665−1677 Sato, M., JF Dower, E Kunze, R Dewey. 2013. Second-order seasonal variability in diel vertical migration timing of euphausiids in a costal inlet. Marine Ecology Progress Series. Vol. 480: 39-56. Schael, D.M., J.A. Rice, and D.J. Degan. 1995. Spatial and temporal distribution of Threadfin Shad in a southeastern reservoir. Transactions of the American Fisheries Society 124:804-812. Schael, D.M., J.A. Rice, and D.J. Degan. 1995. Spatial and temporal distribution of Threadfin Shad in a southeastern reservoir. Transactions of the American Fisheries Society 124:804-812. Simard, Y., Legendre, P., Lavoie, G. and Marcotte, D. (1992) Mapping, estimating biomass, and optimizing sampling programs for spatially autocorrelated data: case study of the northern shrimp (Pandalus borealis). Can. J. Fish. Aquat. Sci. 49:32±45. Simrad EK60 Scientific Echosounder pamphlet Simmons, EJ, NJ Williamson, F Gerlotto, A Algen. 1992. Acoustic survey design and analysis procedure: a comprehensive review of current practice. ICES Cooperative Research Report. No. 187. Stanton, TK, D Chu, and PH Wiebe. 1996. ICES Journal of Marine Science. 53:289-295. Sund, Oscar. 1935. Echo sounding in fishery research. Nature 135:3423. Sullivan, P.J. (1991) Stock abundance estimation using depthdependent trends and spatially correlated variation. Can. J. Fish. Aquat. Sci. 48:1691±1703. Taylor, J.C., J.S. Thompson, P.S. Rand, and M. Fuentes. (2005). Sampling and statistical considerations for hydroacoustic surveys used in estimating abundance of forage fishes in reservoirs. North American Journal of Fisheries Management. In press. Thorne, R.E. 1971. Investigations into the relations between integrated echo voltage and fish density. Journal of the Fisheries Research Board of Canada 28:1269-1273. Thorne, R.E. 1979. Hydroacoustic estimates of adult sockeye salmon (Oncorhynchus nerka) in Lake Washington 1972-1975. Journal of the Fisheries Research Board of Canada 36:1145-1149. Thorne, R.E. 1983. Application of hydroacoustic assessment techniques to three lakes with contrasting fish distributions. FAO (Food and Agricultural Organization of the United Nations) Fisheries Report 300:269- 277. Thorne, R.E. and Thomas, G.L. (1990) Acoustic observations of gas bubble release by Pacific herring (Clupea harengus pallasi). Can. J. Fish. Aquat. Sci. 47, 1920–8. Trevorrow MV (2005) The use of moored inverted echo sounders for monitoring meso-zooplankton and fish near the ocean surface. Can J Fish Aquat Sci 62: 1004−1018 Trevorrow, MV. 1998. Observations of internal solitary waves near the Oregon coast with an inverted echo sounder. Journal of Geophyiscal Research 103(4):7671-7680.

24 Trevorrow, MV. 2005. Volumetric multibeam sonar measurements of fish, zooplankton and turbulence. Proceedings of the International Conference “Underwater Acoustic Measurements: Technologies and Results”, Heraklion, Crete, Greece. Vondracek, B. and D.J. Degan. 1995. Among- and within-transect variability in estimates of shad abundance made with hydroacoustics. North American Journal of Fisheries Management 15:933-939. Wanzenbock, J. T. Mehner, M. Shulz, H. Gassner, I. Winfield. 2003. Quality assurance of hydroacoustic surveys: the repeatability of fish-abundance and biomass estimates in lakes within and between hydroacoustic systems. ICES Journal of Marine Science 60, 486-492. Welsby, VG and JE Hudson. 1972. Standard small targets for calibrating underwater sonars. J. Sound. Vib. 20:399-406. Wiebe, PH, CH Greene, TK Stanton, J Burczynski. 1990. Sound scattering by live zooplankton and micronekton: empirical studies with a dual-beam acoustical system. J Acoust. Soc. Am. 88(5):2346. Wiebe, PH, TK Stanton, MC Benfield, DG Mountain, CH Greene. 1997. High-frequency acoustic volume backscattering in the Georges Bank Coastal Region and its interpretation using scattering models. IEEE Journal of Oceanic Engineering. 22(3). Yule, D. 1992. Investigations of forage fish and lake trout Salvelinus namaycush interactions in Flaming Gorge Reservoir, Wyoming-Utah. Master’s thesis. Utah State University, Logan. Yule, D.L. 2000. Comparison of horizontal acoustic and purse-seine estimates of salmonid densities and sizes in eleven Wyoming waters. North American Journal of Fisheries Management 20:759-775. Yule, DL. 2000. Comparison of horizontal acoustic and purse-sein esitmates of salmonid densities and sizes in eleven Wyoming Waters. North American Journal of Fisheries Management 20:3, 759 – 775. Zakharia, M, and JP Sessagrego. 1982. Sonar target classification using a coherent echo processing. In Proceedings of the IEE International Conference on Acoustics, Speech and Signal Processing, Vol. 7, 3- 5 May 1982, Paris, Frane, the Institute of Electrical and Electronics Engineers, Inc, Piscataway, NJ. Pp. 331-334.

25