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Bio- and Fishery Acoustics
Bio- and Fishery Acoustics
12 Ph. Blondel
Department of Physics, University of Bath, Bath, United Kingdom
12.1 INTRODUCTION Marine life is an important component of biodiversity and an increasingly accessed source of food for the world’s over seven billion population. There are 33,200 different fish species, Froese and Pauly [1], more than half of all vertebrate species now identified in the world. In 2010, fish provided more than 2.9 billion people with close to 20% of their protein intake, FAO [2]. Fish capture increases at an average annual rate of 3.2%, and 58.3 million people are actively engaged in fisheries and aquaculture, often in the poorest countries of the world. However, marine ecosystems are increasingly responding to changes in regional climates, in important and sometimes different ways, IPCC [3]. Catastrophic ecosystem collapses, for example, in the Grand Banks (Canada) during the 1990s, and regular overfishing worldwide are leading some to predict “The End of the Line,” for example, Clover [4], the advent of “Silent Seas” MCS [5], and global animal loss McCauley et al. [6]. National and international regulations now aim to monitor and manage marine ecosystems, for example, with the European Union Good Environmental Status (with Descriptors 4 “Food Webs” and 11 “Energy, including underwater noise”), European Commission [7]. To a large part all rely, if not predominantly, on the use of acoustic instruments, which are the only ones able to remotely monitor large and deep areas with accuracy. This chapter aims at presenting two connected domains: fishery acoustics (How does one detect and monitor fish and other marine life?) and bioacoustics (How does marine life use sound? how sensitive are they to other sounds, including human-made sounds?). Section 12.2 sets the scene with a synthesis of the key aspects of marine life which will be relevant to acoustic investigations. Section 12.3 aims to summarize what is known about sound scattering by marine life, based on models and on experiments with dead, captive, or free-ranging animals (using some of the results from Chapter 5). This is used by different active imaging systems, presented succinctly in Section 12.4 (building on material already covered in Chapter 10). Marine animals also produce their own sounds, including for communication and echolocation. The main results are presented in Section 12.5, and how they are used in practice, with passive acoustic monitoring, is detailed Applied Underwater Acoustics. http://dx.doi.org/10.1016/B978-0-12-811240-3.00012-6 Copyright © 2017 Elsevier Inc. All rights reserved.
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in Section 12.6. Emerging trends and upcoming challenges are finally briefly described in Section 12.7. There is a large body of supporting scientific and technical literature, and it would be beyond the scope of this chapter to do justice to all of them. Instead, only key references (e.g., for recommendations now used in practice around the world) and good illustrations of important results are presented. The reader desiring more details is invited to consult in particular the textbooks of Medwin and Clay [8], Simmonds and MacLennan [9] for fisheries, Lurton [10] for bioacoustics, and the many references therein.
12.2 MARINE LIFE: FROM WHALES TO PLANKTON Marine life varies in scale over several orders of magnitude, from small zooplankton micrometers across to 190 metric ton blue whales (Fig. 12.1). Some (e.g., marine mammals) live individually or in small groups, whereas others (e.g., anchovy) form large aggregations of up to millions of animals. Some animals will be large enough to scatter sound as point-like targets, others will only be visible when grouped into layers or schools large enough to be seen as extended targets. For some marine life, most of the scattering will come from the swim bladder (if they have one), and it will vary with depth and behavior. Conversely, other animals might show most scattering from their bodies, or parts of their bodies, varying with orientation respective to the imaging sonar.
FIGURE 12.1 Marine life varies in scale from phytoplankton (mm and larger) to whales (up to 30 m long), creating complex food webs spanning all trophic levels, EC [11]. The progresses in acoustic sensors, discussed in Chapter 10, mean they can now all be investigated, at all depths.
12.3 Acoustic Scattering by Marine Life
Table 12.1 Frequency Ranges Most Suitable to Detect Different Animal Sizes
Generic Type
Body Size
Detection Frequency (Body)
Zooplankton (small) Copepods Zooplankton (large), larvae, krill Anchovy, shrimp, etc. Cod, tuna, etc. Mammals, large fish
mm mm 2e20 mm
>12 MHz? 1.2e12 MHz 120e1200 kHz
N/A N/A 1.5e6 to 15e60 kHz
2e20 cm 20e200 cm >2 m
12e120 kHz 1.2e12 kHz <1.2 kHz
150e600 Hz to 1.5e6 kHz 15e60 to 150e600 Hz Variable (up to several kHz)
Detection Frequency (Internal Organ)
Adapted from Medwin, H., Clay, C.S., Fundamentals of Acoustic Oceanography, 712 pp., Academic Press, 1998.
The potentially confusing variety of sizes and body compositions can however be approached in a systematic way, looking, for example, at the best frequencies to image their body or their internal organs (e.g., swim bladder or lungs) (Table 12.1). These first answers can then be compared with actual measurements and with models of specific animals, which are presented in Section 12.3. The detection frequency for animal bodies is assuming their body shape can be approximated to a cylinder of radius a, and using k a ¼ 1 (using the notation of Chapter 5). The detection frequency for internal organs approximates them as spherical bubbles (appropriate for swim bladders of most fish) and is related to their resonant frequency. Both sets of frequencies leave much to be desired, partly because of their underlying assumptions, voluntarily simple, and mostly because of the huge anatomical variations between animals and changes in swim bladder sizes depending on depths and behaviors. Nevertheless, they show the main characteristics: as animals get increasingly larger, the optimal imaging frequencies to detect individuals from their bodies alone get increasingly smaller (i.e., the acoustic wavelengths follow the size variations). If animals have internal organs like swim bladders or lungs with high acoustic contrasts (e.g., if they are filled with gas), they will be easier to detect, at frequencies varying roughly from 100 Hz to several kHz.
12.3 ACOUSTIC SCATTERING BY MARINE LIFE For the purposes of acoustic scattering, marine animals can be divided into five main groups, based on their sizes and acoustic characteristics: 1. Copepods, zooplankton (small and large), and small crustaceans (e.g., euphausiids like krill), very small and usually visible as large groups or with very high frequencies [12];
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2. Fish with a swim bladder (e.g., herring, Clupea harengus or cod, Gadus morhua), in which the swim bladder can contribute as much as 90% of the backscatter [13]; 3. Fish without a swim bladder (e.g., Atlantic mackerel, Scomber scombrus), in which the body will be the main contributor to scattering; 4. Larger fish and marine mammals (e.g., seals, dolphins, and whales), for which scattering will be a combination of body, body shape, and the largest internal organs (e.g., lungs). There has been much work since the 1970s, resulting in hundreds of publications investigating field measurements of specific animals (ideally complemented with direct physical sampling, e.g., with nets), field and laboratory measurements of captive or dead animals (thus restricted to specific orientations and behaviors), as well as analytical and numerical scattering models over a large range of frequencies, for example, Jech et al. [14]. Fig. 12.2 shows a synthesis of expected volume backscattering variations with frequencies for a range of marine life.
FIGURE 12.2 Volume backscattering varies with frequency, as shown here for the major biological scatterers observed by Lavery et al. [15] in the Gulf of Mexico (the exact dB values assume here a numerical abundance of 1 organism/m3: actual measurements will scale them depending on actual density, orientation, and behavior of the animals). Reprinted with permission from Lavery, A.C., Wiebe, P.H., Stanton, T.K., Lawson, G.L., Benfield, M.C., and Copley, N., Determining dominant scatterers of sound in mixed zooplankton populations, J. Acoust. Soc. Am., 122 (6), pp. 3304e3326, 2007. Copyright 2007, Acoustic Society of America.
12.3 Acoustic Scattering by Marine Life
12.3.1 ZOOPLANKTON SCATTERING The term “zooplankton” actually covers a large variety of small marine life, including amphipods, krill (classified as euphausiids), copepods, salps, as well as most larval forms of crustaceans or fish (known as “temporary zooplankton” until they grow large enough). These different life forms are key components of marine ecosystems, as they are at the base of most marine food webs. All species have developed to float in the water column, with structural adaptions like flat bodies, lateral spines, oil droplets or gas-filled floats, and solid or gel-like sheaths [16]. Zooplankton are known to migrate to deeper waters during the day and come up at night, with strong variations in locations and seasons, as well as with the exact types of zooplankton. Because they commonly stay at or close to sharp changes in the water layers (density or temperature), it had been debated how accurately they could be detected with acoustics and distinguished from underlying changes in the water column structure. This controversy has been solved, and a nice historical description of how it was addressed, with satisfactory demonstration that zooplankton had distinct acoustic signatures, can be found in Stanton [17]. The bewildering variety of shapes and sizes of zooplankton means that their acoustic characteristics had to be reduced to simple forms, like fluid-filled spheres and cylinders, for which HelmholtzeKirchhoff formulations of scattering could be used [8]. Zooplankton can be weak scatterers, if their tissues are materially very close to the surrounding seawater, but they might also have a hard elastic shell (e.g., lateral spines) or gas inclusions (e.g., floats). Laboratory and field measurements have shown variations over four orders of magnitude [17]. Complemented with in situ observations with nets (to identify species and size/type distributions) or cameras (to measure tilt angles, i.e., the orientation of zooplankton to incident acoustic waves), these observations have steadily progressed to offer a general framework in which zooplankton can be modeled as deformed cylinders, with the distorted wave Born approximation [17]. This was validated and found to be valid for all frequencies, sizes, and orientations of weakly scattering1 zooplankton (e.g., euphausiids). The backscattering amplitude fbs (in m) (called backscattering form function in other works [14]) is then expressed, using the notation of Stanton [17], as: Z J ð2 k a cost b Þ ! k1 1 2 tilt ! fbs ¼ gk gr exp 2 i ki ! r pos a d r pos (12.1) 2 cosðbtilt Þ 4 rpos where k1 and k2 are the wave numbers of the water and zooplankton body, respectively, gk and gr are the density and sound speed contrasts of the scatterer, and btilt is the tilt angle (relative to the incident wave) of the local cross section of the
1
“Weakly scattering” is generally interpreted in the scientific literature [14] as meaning that the material properties of the target are within 5% of the surrounding fluid and there are no shear waves.
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cylinder at point rpos, position vector of the axis of the cylinder. J1 is the Bessel function of the first kind of order 1. The target strength TS (in dB, referenced to 1 m2) and the differential backscattering cross section sbs are then derived (using implicit unity normalization factors) as: TS ¼ 10 logj fbs j2 ¼ 10 log sbs
(12.2)
Models of other organisms with gas inclusions (pneumatophores) or hard shells are less well constrained, because of the extreme difficulty in acquiring sufficient measurements in realistic conditions to sufficiently validate these models. Zooplankton shells vary in shape, from nearly spherical (e.g., pteropods) to more complex and irregular (e.g., foraminifera and radiolarians) (Fig. 12.3). Lavery et al. [15] investigated different models and compared them with field measurements. A frequently used approach is that designed by Stanton and coworkers [18], with a high-pass dense fluidesphere model using an empirically derived reflection coefficient. At high ka values (where a is the external radius of the spherical shell), scattering will incorporate surface waves. At lower values, scattering will mostly depend on the shell volume. For all ka values, averaged models of idealized fluid-filled spherical shells were found to match measurements well [15].
FIGURE 12.3 Numerical and analytical models of marine life are based on high-resolution measurements of the real animals. Top: Euphausiids (e.g., krill) can be modeled as a randomly rough deformed cylinder. Bottom: CT image of the body of a fish (left) and its swim bladder (right). Adapted from Stanton, T.K., 30 years of advance in active bioacoustics: a personal perspective, Methods in Oceanogr., 1e2, pp. 49e77, 2012. Copyright 2012, with permission from Elsevier.
12.3 Acoustic Scattering by Marine Life
Some zooplankton types like siphonophores often have gelatinous bodies with gas inclusions, meaning most of their scattering will be affected by the gas (often carbon monoxide). The resonant frequencies of gas bubbles are given by their wave number k0: pffiffiffiffiffiffiffi sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 3 g P0 ð1 þ 0:1 zÞ k0 ¼ (12.3) r ac where r ¼ 1027 kg/m3, P0 ¼ 1.013 105 Pa (surface pressure, corrected for hydrostatic pressure with depth z), and g ¼ 1.4 (adiabatic constant). The backscattering cross section for ka < 0.1 was calculated by Weston (1967), referenced in Lavery et al. [15] as a function of the bubble radius a and a quality factor Q (typically 5 for fish with a swim bladder, and the same value is used here for zooplankton, in the absence of data to the contrary): sbs ¼
a2 !2
k2 1 02 k
(12.4) 1 þ 2 Q
At high ka values, this cross section will become independent of frequency and converge toward the geometrical cross section, pa2. The exact modeling of acoustic scattering by zooplankton with shells or pneumatophores is still very much an open research question, although the benchmarking of analytical versus numerical scattering models performed by Jech et al. [14] suggest that numerical representations might be often more appropriate. Values observed for zooplankton scattering in the ocean are usually very small, of the order of 140 dB to 90 dB for single animals (Fig. 12.2). As they form larger and denser aggregations, they will however become visible, forming, for example, the deep scattering layer (DSL), further discussed in a subsequent section. Field measurements combine target strengths as volume scattering strengths (e.g., Fig. 12.2), related to the mode of imaging (beam width, pulse length, etc.) and modulated by target type(s) and density. Volume scattering can be modeled with ensemble-averaging and other techniques, and measurements at several frequencies can often be used advantageously to distinguish zooplankton types. This is presented further in Section 12.3.5.
12.3.2 SWIM BLADDER SCATTERING More than 80% of fish families have swim bladders, filled with gas (often oxygen, with traces of nitrogen and carbon dioxide). The main role of this organ is to maintain buoyancy and control. Because of their acoustic contrast, swim bladders often contribute up to 90% of the scattering from an individual fish [13]. Scattering between 1 and 25 kHz is often dominated by the resonance of the swim bladder. Although they can have many shapes [17,19] (Fig. 12.3), swim bladders are often
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best approximated with equivalent spheres, and Eq. (12.3) can be used to identify the peak in scattering as a function of frequency. Fish target strengths are generally small (30 to 60 dB [10]), and the presence of a (resonant) swim bladder can increase these strengths by 10e15 dB. Marine biologists recognize three main types of swim bladdered fish: 1. Physoclistous fish, like cod (Gadus morhua) have closed swim bladders, susceptible to pressure variations with depth; these variations can sometimes be slow (e.g., over 1e2 days for a cod diving 20 m down); 2. Physostomous fish, like herring (Clupea harengus) have swim bladders connected to the alimentary canal (and thus the surrounding environment), meaning any excess pressure is vented off; this adaptation is typical of many schooling fish; 3. Very deep fish like orange roughy (Hoplostethus atlanticus) have swim bladders filled with oil or fatty tissue (hence lower-density contrasts, decreasing target strengths for a similar volume). These variations in swim bladder shape, size, and composition should therefore be kept in mind when calculating the expected target strengths of a specific fish, or trying to identify fish types from acoustic measurements. Depending on the frequency used (i.e., if far from the resonance frequency of the gas-filled swim bladder), and on the aspect of the fish relative to the imaging sonar, other parts of its body might also contribute more to scattering than the swim bladder alone (Fig. 12.4). This problem is exacerbated when different fish types are present;
FIGURE 12.4 Numerical simulation of sound scattering for an orange roughy (From Macaulay, G.J., Hart, A.C., Grimes, P.J., Coombs, R., Barr, R., and Dunford, A.J., Estimation of the target strength of oreo and associated species, Final Research Report for Ministry of Fisheries Research Project OEO2000/01A Objective 1. http://fs.fish.govt.nz/Doc/22654/OEO200001A%20Oreo%20and %20 Associated %20species%20Objective%201%20Final.pdf. ashx, 2002.), varying from blue (darkest gray in print versions) (low) to red (dark gray in print versions) (high). The swim bladder (located with an arrow) is full of wax esters and does not reflect as strongly. The digitized outline of a typical fish sample also shows that some of the scattering comes from other parts of the fish, not only the swim bladder. Copyright: The Ministry for Primary Industries, New Zealand.
12.3 Acoustic Scattering by Marine Life
Godø et al. [20] show, for example, the variations in scattering strengths for two distinct types of fish, moving between depths, and how this can be better resolved using several frequencies.
12.3.3 FISH BODY SCATTERING Swim bladders only account for a small portion of a fish body (around 5%), but they can contribute to a large part of its acoustic scattering properties. This will of course vary with the imaging frequency. As the frequency increases, the wavelengths will become closer to the scale of variation of the fish body and any surface structures or strong reflectors (e.g., backbones). Sun et al. [21] measured, for example, the acoustic responses at 220 kHz of yellow perch (Perca flavescens) (Fig. 12.5) and northern
FIGURE 12.5 High-frequency measurements of individual fish (here, a yellow perch imaged at 220 kHz) show that their acoustic response is dominated by the swim bladder (if present) but that other parts of the body also contribute to scattering. For some fish species, the swim bladder might not be the main contributor to scattering. Reprinted with permission from Sun Y, Nash R, Clay CS. Acoustic measurements of the anatomy of fish at 220 kHz. J. Acoust. Soc. Am., 78 (5), pp. 1772e1776, 1985. Copyright 1985, Acoustic Society of America.
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hog sucker (Hypenteeium nigricans). Relative contributions from the swim bladder were 79% (for the perch) and only 22% (for the hog sucker), whereas the flesh contributed 12% and 45% of the respective returns, the head 6% and 10%, and the vertebrae 3% and 23%. These two sets of results show that the contribution of the swim bladder is not always the main one, and that more information might be needed about fish morphology, aspect toward the imaging sonar (e.g., head-on or broadside), and behavior (e.g., staying at the same depth or not, as it might affect the swim bladder’s acoustic properties). Section 5.2.1.3 presented mathematical expressions of the target strengths of fish as a function of individual length and imaging frequency. Eqs. (5.20) and (5.21) are of the general form: TS ¼ a log L þ b log f þ g. Tried and tested over many decades and with many types of fish, these equations combine the responses of different parts of a fish body into a simple and useable expression. They can be used with several variations on the values of parameters a, b, and g, depending on fish type and growth stage (assuming that allometric relations hold). Many fast-moving fish such as tuna have lost their swim bladders during evolution, as the organ is not able to adjust quickly enough to rapid vertical movements. Their scattering strengths will therefore be smaller and affected by body morphology at scales commensurate with the acoustic wavelength. Observations have shown that the target strengths of different types of fish, or sometimes the same type of fish in different conditions, do not vary linearly with frequency. Gorska et al. [22] studied, for example, the scattering by Atlantic mackerel (Scomber scombrus). They were able to model the flesh and backbone with different variations of the deformed cylinder model of Stanton and coworkers [18] (and references therein), explaining the directivity pattern of fish scattering as well as resonance and antiresonance peaks at different frequencies. They also made the interesting observation that, since the swim bladder of physostomous fish compresses with depth, at some point its contribution to scattering will become low enough for their target strengths to be mainly constrained by their body shape and aspect toward the imaging sonar.
12.3.4 LARGE-BODY SCATTERING The same questions will be pertinent to acoustic scattering by marine animals larger than fish. Depending on the wavelengths used, these animals will become extended targets. Depending on their morphology (e.g., large bony or cartilage structures and sizable internal organs), their target strengths will vary with many factors, some of which have sometimes not been measured in vivo or in situ. This is, for example, true for sea snakes. Based on their morphology (3e9 m long, usually very thin), their scattering properties are expected to be similar to those of fish, but no measurements have been published so far (2016). Side-scan sonar surveys have shown that other animals like river turtles and crocodiles had strong and distinctive acoustic responses [23], but there are no published target strengths or discussions of which parts of the animals contribute most to the scattering. Marine turtles have attracted more interest, because they sometimes get entangled in fishing
12.3 Acoustic Scattering by Marine Life
nets and also because they are often endangered. Again, there are very few details of their acoustic characteristics. Mahfurdz et al. [24] published tank measurements (at 200 kHz) of sea turtles at different aspects, aiming narrow beams at their head, side, tail, carapace, and plastron (the ventral surface of the shell). Overall, the target strengths measured range between 23 and 17 dB. As expected, the hard shells of the carapace and plastron are more reflective. The tails reflect sound differently, depending on aspect. Turtle heads exhibit the most variability, presumably also because of varying aspects. Interestingly, target strengths increased with turtle age, presumably because of the larger sizes and possibly the thicker shells. Marine mammals have been much more extensively studied in the last (pre2016) decades (Fig. 12.6). They cover close to 130 distinct species, extending in size from less than a meter (for juvenile seals) to 30 m (for the blue whale, Balaenoptera musculus). These animals are large (relative to the acoustic wavelengths traditionally used to study them) and their relevant characteristics will include the presence of flesh or blubber, through which sound penetrates but is attenuated; large bones, scattering sound and potentially inducing shear waves; internal organs, like lungs or stomachs, filled with mixed gas and/or fluids, introducing strong acoustic discontinuities; and (for some animals and at the highest acoustic resolutions) teeth or tusks. General morphology, from “rounder” to thin and elongated, and the presence of external appendages or flukes, will also affect variations of scattering depending on the aspect of the animal relative to the imaging sound, coming from the side or from head or tail. Because of their larger sizes, variations within animals of one species will be more evident acoustically. These complex contributions to
FIGURE 12.6 Acoustic scattering from large animals like dolphins is a complex combination of reflections from their body and internal organs. Adapted from Au, W.W.L., Acoustic reflectivity of a dolphin, J. Acoust. Soc. Am., 99 (6), pp. 3844e3848, 1996. Reprinted with permission. Copyright 1996, Acoustic Society of America.
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acoustic scattering are compounded by the large variety of behaviors these animals can exhibit (from breaching whales to rapidly moving dolphins on a group hunt). Scattering by large animals has been studied in open-water experiments (ocean or close to shore), in tanks/swimming pools, or by measuring dead animals. Some experiments have used wild animals, whereas others have used trained subjects. The growing body of scientific results points to some common features, associated to the aspect of animals relative to the imaging beam, their body morphology, and the effects of greater hydrostatic pressures. Scattering from animals varies greatly with aspect, being larger when the animals present their broadside to the acoustic beams and lower at tail aspect (by 21 dB for dolphins, as measured by Au [25]). The relative target strength decreases more rapidly toward the tail aspect than toward the head aspect, with echo levels at the head aspect 5 dB lower for dolphins [25]. Similar results were found for fin whales (Balaenoptera physalus) [26], gray whales (Eschrichtius robustus) [27], humpback whales (Megaptera novaeangliae) [28], and killer whales (Orcinus orca) [29], inter alia. A compilation of target strengths found in the literature is given in Table 12.2 (Banda, personal communication). Several studies also investigated variations with frequency. Contrary to what has been reported in some articles or technical reports, the target strengths do not follow Love’s curve for fish (Section 5.2.1.3). Target strength seems to decrease (by up to 5e10 dB in some cases) as imaging frequency increases, before leveling off after a certain frequency, at least from measurements on dolphins [25] and humpback whales [30]. Table 12.2 Selection of Typical Target Strengths Reported in the Scientific Literature Species
TS (Aspect, if Known)
Bottlenose dolphin (Tursiops truncatus)
11 to 24 dB (broadside) 21 dB below broadside values (tail) 5 dB below broadside values (head) 28 dB (broadside) 5 to 10 dB (broadside) 20 to 40 dB 2.9 (tail) to þ12.8 (broadside) 4 to þ7.2 dB (broadside) 3 to þ4 dB (head) 50 to 20 dB (head) 50 to 10 dB (broadside) 40 to 10 dB (tail) 39 to 46 dB 12 to 1 dB 9 to þ10 dB
Dusky dolphin (Lagenorhynchus obscurus) Fin whale (Balaenoptera physalus) Florida manatee (Trichechus manatus latirostris) Gray whale (Eschrichtius robustus) Humpback whale (Megaptera novaeangliae) Killer whale (Orcinus orca)
Manatee (Trichechus spp.) Northern right whale (Eubalaena glacialis) Sperm whale (Physeter microcephalus) From Banda, personal communication.
12.3 Acoustic Scattering by Marine Life
Blubber (fat-storage layers used in particular for buoyancy) and tissues contribute significantly to acoustic scattering, as they are distributed around the entire animal body. Blubber thickness varies, from 30 cm for fin whales to a few centimeters for small odontocetes like harbor porpoises (Phocoena phocoena) [30]. As these layers become thicker, sound attenuation will increase, and there are some indications that this might increase with frequency (e.g., Au [25]). Bones and similar structures are other sound scatterers, distributed differently according to the species. Detailed measurements of sound velocity and density at different parts of the body were performed for different animals, for example, Cuvier’s beaked whale (Ziphius cavirostris) [31], bottlenose dolphin (Tursiops truncatus) [32], and Yangtze finless porpoise (Neophocaena asiaeorientalis) [33]. These values seem to decrease as sound goes further into the body and to change with maturity of the animals, but there are not enough measurements, covering enough species, to draw authoritative conclusions. Because these detailed measurements were often performed on dead animals, McKenna et al. [32] addressed the question of postmortem changes in geometry, density, and sound speed within organs and tissues (melon, bone, blubber, and mandibular fat). They concluded there were no significant changes with time from death, except possibly for blubber. Lungs are important contributors to acoustic scattering (up to 95%, according to Au [25]), as they are filled with gas. As an example, experimentally measured resonant frequencies of white whale and dolphin lungs were 30 and 36 Hz, respectively. These values were highly damped and far less intense than those predicted using a free spherical air bubble model [34]. Hyperbaric tests on animal bodies revealed that internal organs do not change shape linearly with increasing depths, and also that supersaturation of some gases might occur in the lungs, affecting their acoustic characteristics [35]. Ocean measurements by Bernasconi et al. [26] indicate that, for large whales at least, target strengths decrease with depth, and they decrease faster at the lower frequencies. Lung compression follows Boyle’s law down to 170 m but becomes nonlinear or leads to collapse deeper, i.e., at higher surrounding pressures [35]. To complicate matters, for some animals, a greater percentage of the air compressed during a dive will move from the lungs to the nasal and tracheal regions, affecting their acoustic properties. Bernasconi et al. [30] used field observations of diving humpback whales to derive an empirical relation between the target strength TS at the surface and at depth z: z 0:57 TSðzÞ ¼ TSðz ¼ 0 mÞ 1 þ (12.5) 10
12.3.5 MANY-BODY SCATTERING Large aggregations of marine life are particularly spectacular when considering zooplankton (Section 12.3.1). Individual animals are weak scatterers, with volume backscattering strengths usually 50 dB lower than fish (e.g., Fig. 12.2). Combining their individual echoes is straightforward if there is no attenuation or multiple
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scattering, and ensemble-averaging can be used to calculate volume backscattering coefficients. Lavery et al. [15] express them generally as: SV ðf ; zk Þ ¼
Nk X Mk D E 1 X f ; z ; T si;j i;j k Vk i¼1 j¼1 bs
(12.6)
where f is the frequency considered, Vk is the volume of water sampled in depth range zk, Nk is the number of zooplankton of a particular type in this depth range, Mk is the number of zooplankton taxa, and the averaging term considers the backscattering cross section of each individual of size i and taxon j in this range, averaged over angular orientations. The parameter Ti,j is related to the physical characteristics of the zooplankton type considered. Their combination results in a sonar-reflective region known as the DSL, discovered during World War II. These strong reflections, sometimes with individual reflections from predators (e.g., fish) show diel vertical movement and are often clearly identifiable (Fig. 12.7). At lower frequencies (<20 kHz), the DSL is caused by the resonance of swim bladders and scattering strengths are highly variable. The resonant frequencies vary during the day, as fish follow the diel migrations of their prey and hydrostatic pressure changes their scattering [10,20]. At higher frequencies (>20 kHz), the DSL visibility depends mostly on population statistics.
FIGURE 12.7 Dense aggregations of zooplankton can give rise to large regions with distinctive scattering, much higher than that of individual targets. The deep scattering layer (DSL) and a shallow scattering layer (SSL) are presented here at three different frequencies. The measurements were taken in the early morning offshore Hawaii [36], in water 800 m deep. Black horizontal lines are spaced every 200 m down, starting from the sea surface. Volume backscattering strengths are color-coded from 44 dB re 1 m1[brown (dark gray in print versions)] to 80 dB re 1 m1 (gray). Redrawn from Domokos, R., Acoustic surveys study abundance and movements of bigeye tuna and their micronektonic forage on the Cross Seamount, NOAA Pacific Islands Fisheries Science Center Quarterly Research Bulletin, https://pifsc-www.irc.noaa.gov/qrb/2009_2/eod2.php, March 2009. Courtesy: NOAA Fisheries.
12.3 Acoustic Scattering by Marine Life
Fish schools vary greatly in shapes and sizes, typically a few meters vertically and a few tens of meters horizontally, although larger schools can be seen (e.g., Colbo et al. [52]). Section 5.2.2.1 presented the basics of scattering by fish schools, with Eq. (5.24) giving the correspondence between volume density of fish and target strengths. This volume backscatter strength decreases as fish size increases, because the number density has more influence than the individual size. In most cases, though, the fish type or its average target strength (at the frequency or set of frequencies used) is not known. Medwin and Clay [8] recommend addressing this problem by considering the scattered signal as a combination of a fish scattering component sf and a random noise sn. Because this is analogous to the complex sum of a sinusoidal signal and narrow-band random noise, they recommend addressing it with a Rician probability density function (PDF) of the peak e of the echo envelope: pffiffiffiffiffi 2 e sf e 2 þ sf 2e PDFRice ðeÞ ¼ exp I0 (12.7) s sn s n n
I0 ðxÞ ¼ J0 ði xÞ (J0 being the modified Bessel function). with I0 ð0Þ ¼ 1 The ratios g ¼ sf /sn (equivalent to a signal-to-noise ratio) and the average
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12.4 ACTIVE IMAGING SYSTEMS 12.4.1 SINGLE-BEAM ECHO SOUNDERS Single-beam echo sounders were presented in Section 10.3. They have been the fundamental tool of fisheries for close to a century now, with the first models (also called fathometers) commercialized in the early 1920s, for example, Balls [38]. The first scientific fishery applications are reported on the German research vessel Meteor in 1926, for example, J.B. [39] and the field has greatly progressed since that time, for example, Medwin and Clay [8] and Lurton [10]. Frequencies depend on the exact applications, and typically range between 12 kHz for deepwater models to up to 200 kHz for shallow-water models with 38 kHz being the most common, Lurton [10]. Fig. 5.2 showed the typical application of echo sounders to detect fish schools. These echo sounders typically transmit short signals (1e10 ms) along a narrow beam (5e15 degrees) and they measure the volume backscattering strength of mid-water targets. Individual echo levels EL are related to the source level SL, the range R to the target, the absorption coefficient a of water at this frequency and its sound speed c, the solid angle of the imaging beam j, its signal duration T, and the backscattering strength BS of fish by the equation, Lurton [10]: 2 jR c T EL ¼ SL 40 log R 2 a R þ 10 log þ BS (12.9) 2 The combination of 40 log R þ 2 a R corresponds to the time-varying gain. The backscattering component BS can relate to a single fish with the target strength defined, for example, in Eqs. (5.20) and (5.21) or to a fish school given by Eq. (5.24). Measurements are integrated along the ship’s path, creating a two-dimensional view of mid-water targets immediately below the ship (known as echo trace or echogram). Depending on the size of a target relative to the imaging beam, this integration might create the crescent or boomerang shapes well known of early sonars and recreational fishermen. It is an artifact created by the acquisition: as the echo sounder moves from position 1 to 2 to 3 (Fig. 12.8), the target will be imaged at slightly different angles. At position x1 along the track, it will be at a higher angle from the vertical, as the fish is at the edge of the beam, and its depth will be slightly overestimated. At position x2, immediately above, the fish will be in the center of the imaging beam, and its depth z2 will be the correct one. As the ship moves away, the fish, if large enough, will be at the edge of the next beam(s). The crescent shape z(x) follows a simple equation linked to the closest range of the fish: z ¼ z1 þ
ðx x2 Þ2 2 z2
(12.10)
This effect will vary with the echo sounder’s settings, the vessel’s speed and the range: higher ping repetitions, associated with slower speeds and lower frequencies, are more likely to create larger crescent shapes than higher frequencies
12.4 Active Imaging Systems
FIGURE 12.8 Targets large enough to be imaged several times, as the sensor moves relative to it, are extremely likely to be at slightly different ranges. This is particularly visible for single-beam echo sounders, resulting in the characteristic crescent shape seen in raw measurements (see text for explanations). Ship outline taken from Fonteneau, A., Diouf, T., and Mensah, M., Tuna Fisheries in the Eastern Tropical Atlantic, FAO Corporate Document Repository, 2016; http://www.fao.org/docrep/005/t0081e/T0081E04.htm, Copyright FAO.
(e.g., Fig. 12.9). These variations should be corrected during processing. Echo integration is a topic frequently discussed in the processing of fisheries echo sounder measurements. Earlier systems were separate electronic instruments, connected to the output of the echo sounders: they are now assimilated into the software. Echo integrators sum the energy in different parts of the echogram, for example, preselected depth channels or areas specified by an operator, over a specified number of transmissions. The reader interested in the exact details of how this is done in practice, and the physical assumptions behind it, is referred to textbooks, such as Simmonds and MacLennan [9]. The interest of echo integration is well shown in Fig. 12.9, where the water layers closer to the sea surface are strongly affected by turbulence, and those closer to the seabed might be affected by bathymetry, gas-venting, or vegetation (in the shallower areas). For point-like targets like individual fish, the echo sounder must possess a high enough spatial resolution to detect each of them. The measurement of one such target inside a single beam strongly depends on its angular position (due to beam directivity) and additional techniques are available to better resolve them [10]. Splitbeam sounders use different parts of the transducer as interferometers, to determine the angular position relative to the beam axis and compensate for beam directivity at this angle. Dual-beam sounders use two coaxial receiving beams with different
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FIGURE 12.9 Single-beam echo sounder measurements of single fish next to a dense school. Left: the lower frequencies show the traditional crescent shapes and overestimate the sizes of the different targets. Right: the higher frequencies show better accuracies (because of the smaller wavelengths), revealing the vertical structure of the fish school and separating distinct groups closer to the seabed. Note also the higher definition of the seabed itself (see Chapter 5 for theoretical justification). Image from FURUNO, Furuno FISH FINDER Model FCV-1900 technical documentation, http://www.furuno. com/en/products/fishfinder/FCV-1900#Screenshots, 2016.
apertures, and echo level differences are used to estimate the angular position of the target. These two approaches, along with echo integration, rely on accurate calibration of the echo sounders, in transmission and in reception. The equations presented in Section 10.8 are used to measure the reflections from known metal spheres, using the methods of Foote et al. [42], Tomich et al. [43], and Demer et al. [44]. The main interest of calibration, ideally before each survey, is of course the provision of reliable values for the echoes. It is also fundamental to the accuracy of echo integration for fish stock monitoring and biomass quantification. Lurton [10] advises, for example, that transmission and reception sensitivities, or beamwidth patterns, must be accurate to 1 dB (a 3-dB bias in level estimations leading to an error by a factor of 2 in biomass estimations). Typical frequencies used by single-beam echo sounders for fisheries applications are 38, 120, 200, and 420 kHz, as shown by the variety of commercially available
12.4 Active Imaging Systems
sounders using these exact frequencies. Section 12.3 showed the role of frequencies in estimating individual and group backscattering strengths. It is therefore logical to think about using several frequencies to better identify different fish types. Much work has been done in the field, and echograms of the same fish at different frequencies can show striking differences (Fig. 12.5). The different strands of work have been summarized by Korneliussen et al. [45] and implemented in software like EchoView (www.echoview.com). The many applications spawned by this approach are very attractive, but require meticulous preparation of both the sounders to be used and the collection of the measurements. The recommendations of Korneliussen et al. [23], prioritize the following (Fig. 12.10): •
•
Selection of frequencies with no harmonic interference (e.g., 18, 38, 70, 120, 200, 333, 555, 926, 1543, and 2572 kHz) (Simrad’s EK60 uses, for example, seven frequencies simultaneously between 18 and 710 kHz); Selection of transducers with similar beam widths, mounted as close as possible with the smaller ones in the center;
FIGURE 12.10 Marine life echograms at 18, 120, and 200 kHz in the Gulf of Alaska. Note how the definition of fish schools near the seabed and zooplankton and foraging fish at lower depths vary with the imaging frequencies. Reprinted with permission from Anderson, C.I.K., Horne, J.K., and Boyle, J., Classifying multi-frequency fisheries acoustic data using a robust probabilistic technique, J. Acoust. Soc. Am. Express Letters, 121 (6), pp. EL230-EL237, 2007. Copyright 2007, Acoustic Society of America.
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• • •
Synchronized transmissions, time-stamped to <10 ms, at power levels without nonlinear effects; Use of similar pulse duration and ping rate, digitized sample lengths for all frequencies, and the lowest possible thresholds for data collection; “Before and after” calibration for each survey (keeping in mind the earlier caveat of Lurton [10] about keeping accuracies below 1 dB).
These different approaches have been developed to high degrees, providing good estimates of fish densities and biomass and, using multiple frequencies, even potentially identifying the type of fish or the stage of development. But, for physical reasons, the use of a single beam immediately below the surveying vessel will always induce some limitations. The first one is the relatively large beam spread, especially at larger ranges, which limits the resolution of changes within fish schools and also the detection of fish close to the seabed (Fig. 12.8, left, implies that seabed returns will be shaped like an upward crescent, meaning fish sizes and densities might be biased). Second, the monodimensional echo return means measurements must be made at several positions relative to the fish schools, to get accurate ideas of their overall shapes and dimensions. Third, fish are sensitive to the lower-frequency noise of both ships and single-beam echo sounders, and are known to avoid the path of moving vessels, for example, Olsen et al. [47], potentially biasing fish observations close to the vessel, although there are, of course, interspecies differences in avoidance ability/behavior, for example, Colbo et al. [52], and the use of quieter platforms like “silent vessels” or autonomous underwater vehicles, which strongly reduces these biases [48].
12.4.2 SIDE-SCAN SONARS Single-beam echo sounders provide accurate and very useful measurements of fish and other targets immediately below the surveying vessel, but they do not offer instantaneous coverage athwarthship. Side-scan sonars, conversely, scan the seabed at distances up to 30 km from the ship (for the old GLORIA system, using a frequency of 6.5 kHz, yielding 60-m resolutions useless for fisheries), but generally in the range of a kilometer or less (for frequencies of a few hundreds of kHz, closer to the spatial resolutions of use for fish studies). Side-scan systems are described in detail in Section 10.5, and modern systems can achieve resolutions down to millimeter or centimeter in all environments [49]. They have regularly been used to detect fish and other marine life, either as a by-product of the seabed survey or on purpose. Fig. 12.11 shows two typical examples: a dense school of small targets (fish) and a large, single target (identified as a shark). The images are unprocessed and show the nadir (thick white line) and the water column (black, i.e., with low to nil acoustic returns), with the seabed exhibiting different reflectivities as range from the sonar increases. Fig. 12.11 (left) already shows some returns in the water column: they are small and fuzzy, leading to mottled patterns and bright (reflective) patches as fish density increases. The narrow beam width along track means the
12.4 Active Imaging Systems
FIGURE 12.11 Side-scan sonar images of a 20-m wide fish school (left) and a hammerhead shark (right), with basic interpretations (bottom sketches). Arrows indicate the respective directions of ensonification. Note the role of the shadows in describing the target shapes. Images courtesy of the Search for the Lost French Fleet of 1565 Expedition, NOAA-OER/St. Augustine Lighthouse and Museum (http://oceanexplorer.noaa.gov/explorations/14lostfleet/logs/july19/media/baitball. html, left; http://oceanexplorer.noaa.gov/explorations/14lostfleet/logs/july19/media/hammerhead.html, right).
fish school creates acoustic shadows at further ranges. From the ranges and lengths of these shadows, it is possible to infer the overall size and height of the fish school, at least in the bottom part of the sonar image. If fish density is not large enough, individual fish or small groupings can be detected, as in the upper part of the image, but it is impossible to identify the exact distribution of fish sizes, the type(s) of fish, or how high they are above the seabed. Fig. 12.11 (right) shows a single target, unequivocally in the water column and associated with a distinct shadow on the seabed. Based on its size, and the morphology of its shadow, it was identified as a hammerhead shark. It is however doubtful that similarly large targets could be detected if closer to the seabed, or at further ranges, as their acoustic returns would be mixed with those of the geological features below. Side-scan sonars are extremely useful for many tasks (see Ref. [49], for examples), but the limited information they provide about fish means that other tools are often preferable.
12.4.3 MULTIBEAM ECHO SOUNDERS Multibeam echo sounders are versatile instruments, providing bathymetry and seabed reflectivity (Section 10.4.2.1), “snippets” (Section 10.4.2.2), and pseudo-side-scan
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imagery of the seabed (Section 10.4.2.3). Snippets record portions of the individual waveforms reflected in each beam sector and increasingly contain water column data, meaning they can be used for imaging of mid-water targets. A wide-ranging review by Colbo et al. [52] shows the many applications of multibeam echo sounders to fisheries, as they directly address the limitations of single-beam echo sounders: higher frequencies and narrower beams, offering higher resolutions, wider coverage across-track, detecting fish some distance away from the surveying vessel, and much improved definition of fish school shapes and distributions. Fig. 12.12 shows a typical multibeam “ping,” acquired by the author in an Arctic fjord using an Imagenex sonar with 260 beams. The raw image shows the seabed as a thicker line 12e14 m deep. Highly backscattering targets in the water column can be seen in close-up, and based on concurrent visual observations in the very clear waters, they are associated to small fish aggregations. A fisheries multibeam survey would cover very large transects, often in much deeper water and therefore covering very large volumes of water. Many studies, summarized in Colbo et al. [52], show that multibeam sounders can determine with confidence school shape parameters (e.g., length, width, height, surface area, volume, and their evolution with time or space as surveys progress), external parameters (depth and distance to thermocline or to seabed), etc.
FIGURE 12.12 Raw multibeam image of small groups of fish in a shallow Arctic fjord. The seabed is 12 m deep and picked up as a line of thickness increasing with the outer beams (slightly noisier, owing to the mode of acquisition). The fish show up as clear targets and it is possible to identify distinct reflectors (color coded by increasing reflectivity, from black to red (gray in print versions), scattering as much as the underlying seabed.
12.4 Active Imaging Systems
FIGURE 12.13 The wider cover across track of multibeam measurements of a herring school [red cloud (gray in print versions)] can be advantageously compared with single-beam measurements along a single transect [blue segment (dark gray in print versions)]. Reprinted from Colbo, K., Ross, T., Brown, C., and Weber, T., A review of oceanographic applications of water column data from multibeam echosounders, Est. Coast. Shelf Sci., 145, pp. 41e56, 2014, Copyright 2014, with permission from Elsevier.
Fig. 12.13 shows advantageously the additional information brought by multibeam echo sounders. Repeated single-beam measurements below the survey vessel produced the blue segment, in which the fish school can be recognized as a red “patch” of higher backscatter strengths, but there is no information about the exact shape of this school. Shape is known to evolve with school dimension, but it is also affected by external constraints, from school movement to food availability and predator interaction, and it is of course highly species dependent. Because they cover a large section across track, and have higher resolutions, repeated multibeam measurements show the exact shape of the fish school (red “cloud,” extending from the red “patch”).
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The 3-D measurement of fish schools and densities can ideally be used to estimate the fish biomass through its volume backscattering. The first obstacle is the calibration of the multibeam sonar, often requiring facilities beyond easy and regular reach of survey teams, although some simple approaches using calibration spheres are proposed by Foote et al. [50] and recommended by the ICES for both single-beam and multibeam sounders [[44] (more details about sensor calibration are provided in Section 10.8)]. It should be noted, however, that the absence of such system calibration in the field does not preclude obtaining meaningful results, as shown, for example, in Parsons et al. [51]. The second obstacle is that fish backscatter strongly depends on the orientation of the fish relative to the imaging wave (see Section 12.3). Generally, fish swimming across fan will have reduced scattering volume in the far beams compared to the center beams, but the opposite is true for diving fish, for example, Colbo et al. [52]. Larger targets, like marine mammals, will exhibit stronger returns from their lungs, and smaller targets, like zooplankton, will show backscatter variations associated with internal movements within their aggregations, leading to similar effects. Some authors investigated the difference between multibeam and other measurements, for example, Gurshin et al. [53] with multibeam and split-beam echo sounders for captive cods, Weber et al. [54] with multibeam and single-beam echo sounders, and other references in Colbo et al. [52]. Other effects are linked to the oceanographic setting: Melvin and Cochrane [55] noted, for example, the difficulty of integrating measurements in dynamic and complex environments such as tidal sites.
12.4.4 COMBINING SENSORS The previous sections showed the relative advantages and limitations of each type of instrument. Modern applications often combine them to address potential data gaps. For example, catch monitoring now often supplements fisheries single-beam echo sounders, to monitor where the fish is in the water column, with additional sensors next to the trawl or seine nets. Along with the useful measurements of water temperature (also used for velocity corrections of acoustic sensors), weight trawl, or flow, high-frequency sounders can be used to monitor the amount of fish closer to the nets (Fig. 12.14). This enables direct imaging closer to the seabed, where fish can be missed during deep trawling because of the higher seabed returns, and in general imaging the amounts and types of fish entering the nets, as they can sometimes be smaller than the resolution achievable with the ship’s echo-sounder. Smaller targets like zooplankton are often at the limit of resolution. Comparisons of acoustic measurements with traditional net sampling and camera observations were, for example, conducted by De Robertis [57], observing euphausiids in Canada and leading to useful observations as to how zooplankton behavior and 3-D organization could influence multibeam measurements. Similar approaches were used by Nichol and Brierley [58] and Cox et al. [59] to look at krill swarms.
12.4 Active Imaging Systems
FIGURE 12.14 Additional acoustic sensors can be installed closer to the fish, for example, on the trawl itself. Scanmar TrawlEye system, Scanmar, Advanced catch systems for increased efficiency and financial gain, report, http://www.scanmar.no/wp-content/uploads/2016/04/Scanmar-Info Booklet_2011-2012_English.pdf, 2012.
Multibeam measurements show that swarms cluster, depending on environmental characteristics such as bathymetry and water conditions, and that future surveys may require a stratified design to better measure krill biomass and swarm volumes. More dynamic environments offer additional challenges, as noted by Melvin and Cochrane [31]. Tidal sites are increasingly used for human activities, including the siting of marine renewable energy structures, and acoustic monitoring of fish and other biological activity is hampered by the rapid changes in the water structure. In the more energetic sites, kolks (vortices within the water column) burst at the surface as “boils,” which are short lived (minutes) and of sizes comparable to the water depth. The high currents also affect the deployment of instruments. Williamson et al. [60] showed, however, that it was possible to accurately and reliably monitor these areas by combining multibeam and multifrequency single-beam echo sounders (Fig. 12.15), installed on a platform moored on the seabed. Their studies investigated fish, marine mammals, and diving seabirds, at the same time, comparing acoustic measurements with radar and visual observations from the shore.
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FIGURE 12.15 Different sensor types can be integrated, for example, multibeam with multifrequency single-beam echo sounders. This example shows an innovative approach, with sensors on an autonomous subsea platform imaging the environment around a tidal turbine from the seabed up. From Williamson, B.J., Blondel, Ph., Armstrong, E., Bell, P.S., Hall, C., Waggitt, J.J., and Scott, B.E., A self-contained subsea platform for acoustic monitoring of the environment around Marine Renewable Energy Devices eField deployments at wave and tidal energy sites in Orkney, Scotland, IEEE J. Oceanic. Eng., 41 (1), pp. 67e81, 2015. Creative Commons Attribution 3.0 License.
12.5 Marine Life and Sound
12.5 MARINE LIFE AND SOUND 12.5.1 GENERAL POINTS Sounds are essential to the transmission of information underwater, and as such they are heavily used by all forms of marine life. Even those species not known to produce sound will still use it, or be sensitive to it. The relevant body of literature is vast and constantly updated with new measurements, either on live animals in the field or in the laboratory, and with new observations of behaviors best explained with auditory senses (e.g., flight or avoidance reactions). The masterful synthesis of De Ruiter [61] is recommended to the reader wanting to know the consensus on sound emission by all types of marine animals, and the many different mechanisms by which they receive and can be sensitive to sounds. Backed with considerable references and 25 pages of data about exact frequencies, source levels (SLs), and modes of measurements, this is an essential summary of the key points of sound emission and reception by marine life. The Discovery of Sound in the Sea project (DOSITS) also provides a high-quality educational resource, with multimedia presentations of particular animals (www.dosits.org). The following sections will focus on key points. The hearing sensitivity of marine animals is measured with audiograms. These are collected either by behavioral analyses, in which trained animals indicate whether they have detected particular signals, or electrophysiological techniques, in which potential differences between electrodes on the subject’s body show neural activity for different signals (it can be measured directly as the auditory brainstem response, ABR). Both techniques have inherent biases, insofar as they rely on a few animals that can be trained (behavioral analyses) or animals susceptible of being captured and analyzed. Intraspecific variations are also a concern, therefore, values found in the literature need to be interpreted in view of how many animals of each kind were studied, and how representative they might be. Finally, some animals (like sea otters, turtles, snakes, or polar bears) are amphibious and their auditory systems will be functional both in air and underwater, but with different sensitivities. Frequency discrimination, directional hearing, and source location abilities will vary with species, and within species. The hearing threshold is the lowest level of sound at a particular frequency that an animal can detect. Depending on how loud the sound is, how long it is, and its frequency content, animals might be adversely affected. Temporary threshold shift (TTS) is when animals can only detect louder sounds, but this damage is reversed after some time (like a human affected by loud occupational noise or a rock festival). If this threshold does not return to normal levels, this is a permanent threshold shift (PTS). To pursue the human analogy, PTS can result from repeated TTS (e.g., listening to loud bands every weekend) or single exposure to a very intense sound (e.g., a close explosion). Noise exposure will also affect animals directly, for example, through injury to the ear and associated structures, or even nonauditory tissues. These injuries can lead to death or equally deleterious long-term effects (e.g., degradation of the ability to echolocate, communicate, or detect predators and preys).
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12.5.2 MARINE MAMMALS Marine mammals can be divided into four main groups: (1) Cetaceans (whales, dolphins, and porpoises), divided into odontocetes (toothed whales) and mysticetes (baleen whales); (2) Pinnipeds (phoceids, like the true seals, otariids, like the eared seals and walruses); (3) Sirenians (e.g., manatees and dugongs); and (4) amphibious mammals like sea otters and polar bears. Toothed whales produce click sounds (understood as primarily related to echolocation, as their repetition rate increases with proximity to a prey, finishing with a high-rate buzz, similar to that of bats), click-based sounds or pulsed calls, tonal sounds, and other sounds associated with communications, like codas (short rhythmic series of clicks). A wide variety of whistles and other tonal sounds have also been documented (see Ref. [61], for in-depth review). Odontocetes are thought to produce sound using pressurized air, as potentially confirmed by some observations of frequency shifts when some animals go deeper (e.g., reduction of air volume available for sound production). Toothed whales can also produce percussive sounds by beating body parts against the sea surface, for example, when feeding and presumably to affect the prey. Sound levels are generally high, for example, 210e225 dB re 1 mPa at 1 m for broadband echolocation clicks (delphinids) or narrowband, highfrequency clicks at 155e190 dB re 1 mPa at 1 m (harbor porpoises). Baleen whales can also produce sounds by beating body parts against the water surface (or other objects) but other mechanisms of sound production are less well understood [61]. Most vocalizations are thought to be associated with reproduction or communication. They have low frequencies and are repetitive (often stereotypical) and frequency modulated. Local and cultural variations have led to their qualification as “singing,” and there have been many studies of how they can be related to specific animal activities. These sounds are loud too, for example, 178e186 dB re 1 mPa at 1 m for 10e100 Hz calls by blue whales (over durations of up to tens of seconds). Pinniped sounds are equally varied, described as barks, buzzes, grunts, roars, or yelps [62]. Levels range about 135e193 dB re 1 mPa at 1 m, over frequency ranges of tens of hertz to tens of kilohertz. Fig. 12.16 shows how they compare with cetacean calls. Vocalizations by manatees and dugongs are referred to as whistle-squeaks, chirps, squeaks, chirp squeaks, barks, and trills, again reflecting a high variety. They are made at lower frequencies (<10 kHz), with lower SLs (<150 dB re 1 mPa at 1 m). Amphibious mammals exhibit a large variety of vocalizations too, but there have been very few measurements of SLs or sensitivity, either in air or underwater (more difficult experimentally). For example, polar bears are known from ABR studies to be sensitive between 11 and 23 kHz (Nachtigall et al., 2007, in Ref. [61]) but there are no measurements of the sound levels they produce (apart from measurements near cubs and mothers in controlled situations). Sea otters are known to vocalize at levels up to 50e113 dB re 20 mPa (up to 7 kHz) in air but there are no reported measurements in water [63]. Measurements of sound emission and reception in amphibious mammals also need to account for the difference between dB levels measured in air (for a reference value of 20 mPa) and those measured in water (for a reference value of 1 mPa), as well as the properties of air versus water and how sound
12.5 Marine Life and Sound
FIGURE 12.16 Marine mammal vocalizations can be quite complex, as shown in this collection of spectrograms collated by NOAA (http://www.nefsc.noaa.gov/psb/acoustics/sounds.html). From top to bottom: humpback whale (Megaptera novaeangliae), for 32 s and displayed from 0 to 5 kHz; bottlenose dolphin (Tursiops truncatus) (for 12 s and from 0 to 16 kHz); and harbor seal (Phoca vitulina) (for 0.6 s only, and from 0 to 4.5 kHz). Brighter colors indicate louder sound levels. Courtesy: NOAA Fisheries.
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levels (e.g.) are calculated (see the simple steps outlined in Ref. [64] for in-depth discussion). The mechanisms of sound reception by marine mammals are still not fully understood [61] and there is sometimes controversy about the exact pathways or combination of mechanisms (e.g., for dolphin hearing), or no information at all (e.g., for polar bears). But the key characteristics of the different species are now known with a higher degree of certainty [61]. For example, toothed whales hear best frequencies between 10 and 100 kHz. Baleen whales can hear frequencies ranging from infrasounds to about 20 kHz. Pinnipeds hear best at 2e40 kHz, manatees at 0.4e20 kHz, and polar bears at 11e23 kHz (in air, but no data is available underwater). Frequency-weighted functions (known as M-level weightings) can be used to account for these distinct hearing sensitivities [65]. Based on a synthesis of field observations (e.g., strandings and postmortems) and PTS and TTS data, the following injury criteria have been proposed by Southall et al. [65] and are now widely regarded as the basis for sound environmental regulations: • •
Peak exposure levels should not exceed 230 dB re 1 mPa for cetaceans, 218 dB re 1 mPa (underwater) and 149 dB re 1 mPa (in air) for pinnipeds. M-weighted Sound Exposure Levels (SELs, explained in Section 12.6) should not exceed 198 dB re 1 mPa2 s for cetaceans exposed to pulsed sounds (defined as >3 dB in a 35-ms interval than in a 125-ms interval) and 186 dB re 1 mPa2 s (in water) for pinnipeds, compared to 215 dB re 1 mPa2 s for cetaceans exposed to nonpulsed sounds and 203 dB re 1 mPa2 s for pinnipeds. For pinnipeds in air, these thresholds would be 144 dB re 1 mPa2 s (pulsed sounds) and 144.5 dB re 1 mPa2 s (other sounds).
12.5.3 FISH, TURTLES, AND INVERTEBRATES Other animal groups known to produce and use sounds include fish (with increasing numbers of measurements being reported in the scientific literature), sea turtles and snakes (for which extremely little is known), and invertebrates (like the infamous snapping shrimp, loud enough to affect acoustic communications). Sounds produced by fish show lower frequencies, mostly below 1 kHz (Fig. 12.17, top). They consist in tonal and pulsed sounds, varyingly called grunts, growls, croaks, chirps, squeals, etc. They are generated by stridulation (friction between hard structures of the fish anatomy), drumming (usually by rapid contraction of muscles near the swim bladder), percussion and involuntary mechanisms (e.g., air movements within the swim bladder of digestion), as well as breathing, feeding, and swimming. Some of these sounds have been demonstrated to be voluntary and associated to fish behaviors like communication. They often vary during the day, with strong variations associated with day or night activities. The New Zealand bigeye (Pempheris adspersa) produces short-duration (<8 ms) popping sounds with a peak frequency of 405 Hz and SLs around 115 dB re 1 mPa at 1 m [66]. Fish calls recorded by McCauley and Cato [67] were louder, with “pops” at
12.5 Marine Life and Sound
FIGURE 12.17 Top: Vocalization of haddock (Melanogrammus aeglefinus), showing a 17-s segment with frequencies between 0 and 800 Hz (From http://www.nefsc.noaa.gov/psb/acoustics/ sounds.html. Courtesy NOAA Fisheries.). Bottom: Laboratory measurements of sound emission by snapping shrimps, showing loud, broadband pulses (up to 140 kHz), with typical durations of 0.3 ms [68].
157 dB re 1 mPa at 1 m, “trumpet calls” at 150 dB re 1 mPa at 1 m, and “banging” noises at 144 dB re 1 mPa at 1 m. Based on hearing mechanisms, fish are usually divided into generalists and specialists [61]. The generalists only receive sound directly, mostly through particle motion, and hear best between tens of hertz and about 1 kHz. Specialists evolved other means of hearing, enabling them to hear better at frequencies of 100 Hz to 2e10 kHz (but up to 100 kHz for some species like the American shad and the gulf menhaden). Some of the specialist species use sound propagation through the swim bladder, meaning their sensitivities would change with depth (depending on how the swim bladder reacts to changes in hydrostatic pressure). Documented changes in hearing sensitivity also occur at specific times, for example, during the breeding season for female midshipman fish (Sisneros and Bass, 2003, in Ref. [61]). There are very few measurements of sea turtle’s hearing, and it seems they hear best at frequencies below 1 kHz [61]. Sea turtles were long thought not to vocalize, but recent research showed the long-necked freshwater turtle (Chelodina oblonga) had a variety of underwater vocalizations between 0.1 and 3.5 kHz [69]. For
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comparison, the giant South American river turtle (Podocnemis expansa) can vocalize between 0.03 and 4.5 kHz [70]. No SLs have been documented, but vocalizations from sea turtles are much richer than originally thought, and the range of frequencies might suggest they are also adapted to hearing at frequencies slightly higher than 1 kHz. Based on the data available, sound exposure guidelines for fishes and sea turtles were developed [71], on the line of the injury criteria presented earlier for marine mammals. Marine invertebrates produce sounds, in particular crustaceans [61]. Some are intentional and others are by-products of other activities (e.g., mussels torn loose from their substrate). Stridulation is the most common mechanism, as is percussion. For American lobster, buzz-like sounds with mean frequency 180 Hz and mean duration of 227 ms have been reported (Henninger and Watson, 2005, in Ref. [61]). Snapping shrimps can be the dominant source of noise in shallow tropical waters, especially in summer and at dusk, and climate change has led them to be noticeable at higher latitudes, e.g., close to UK shores. Sound is produced by cavitation when its large snapper claw is closed extremely rapidly during predation or other encounters. Laboratory measurements by Kim et al. [68] investigated individual snapping shrimps, revealing very loud SLs of 204e219 dB re 1 mPa at 1 m (Fig. 12.17, bottom). These “snaps” are broadband, expanding to 140 kHz in these measurements, and lasting for up to 0.3 ms at a time. Although colonies are small (several tens of animals, up to 300 at most), the combination of individual “snaps,” closely spaced, follows Gaussian statistics and is known by submariners as the noise of “frying fat.” Crustaceans are thought to only perceive particle motion, not sound pressure itself, and they are harder of hearing than most generalist fish species. Bottomdwelling species are also susceptible to vibrations from their substrate [72], below 100 Hz. Cephalopods are sensitive up to 600 Hz. ABR measurements of octopus and cuttlefish showed upper limits of 1 and 1.5 kHz respectively (Hu et al., 2009 in Ref. [61]).
12.6 PASSIVE ACOUSTIC MONITORING Section 12.5 showed the diversity of sounds produced by marine animals, and passive acoustic monitoring (PAM) can be used to monitor for the presence of certain animals [73,74]. The different approaches are now very well developed [75], and there is a large body of supporting literature, only a few of which can be presented here (the thousands of other references not presented can prove as interesting, and the present selection does not imply any ranking or priority). Further analyses, for example, looking at specific frequencies, can investigate the numbers of animals involved, for each species identified [76], thus quantifying an aspect of biodiversity. PAM can be used to understand specific behaviors, like echolocation clicks of dolphins hunting prey, or use of habitats by particular species [77]. In the most challenging applications, PAM can also monitor acoustic repertoires of particular
12.6 Passive Acoustic Monitoring
species [78,79], paving the way to developing automated call detectors (e.g., CPODs and T-PODs, see later for details). Section 12.5 summarized the broad sensitivity of marine animals to acoustic sounds. PAM can therefore also be used to monitor potential impacts of different types of noise on animal behavior and health [80e82]. The simplest embodiment of a PAM system consists in the deployment of a single hydrophone, deployed from the side of a boat or other platform [83]. Moored hydrophones can be deployed for longer periods, offering the benefit of higher stability and lesser susceptibility to movements induced by weather at the sea surface [84]. The recent and ongoing development of cabled seafloor observatories around the world also offers the possibility of continuous, very long-term, measurements [85]. C-PODs [77] and T-PODs [86] reduce these very large datasets to the desired animal vocalizations, for example, click repetitions. They have often been used in groups, either moored or freely drifting. Directional frequency analysis and recording (DIFAR) sonobuoys have also been used in several studies [87]. Using several hydrophones, at different locations or in arrays, allows the estimation of range and bearing of acoustic sources (Chapter 10). These sources can be animals naturally emitting sounds (e.g., whales or fish), other background sources (Chapter 6), or, in some cases, purpose-built transmitters tagged onto fish or other animals [88]. Metrics and full reporting of all parameters relevant to the analyses and interpretations of the measurements are paramount to PAM (as they are to other types of acoustic measurements, of course). Robinson et al. [89] summarize best practice for underwater noise measurements, and Merchant et al. [90] show how this can be used in PAM reporting. The conversion of raw pressure measurements (often as a voltage or a normalized value in a .wav audio file) to actual pressures has sometimes led to confusion (if some acquisition parameters were not known) and/or reporting of pressures or sound levels with arbitrary units (making intercomparison difficult). The open-source software provided by Merchant et al. [90] (as supplementary information on the publisher’s website) addresses this gap, by clearly laying out all acquisition information necessary, and how to translate any measurements into actual pressures and sound levels. Industry and research efforts also routinely include PAMGUARD (www.pamguard.org), an open-source software infrastructure for PAM, with a strong emphasis on cetaceans. Robinson et al. [89] recommend sound pressure level (SPL) as the best measure of both continuous and pulsed sounds. It is expressed as a ratio of the rms squared sound pressure
(over a stated time interval) and the standard reference pressure p0 ¼ 1 mPa used in underwater acoustics: h pi SPL ¼ 20 log10 (12.11) p0 Its units are therefore dB re 1 mPa. For pulsed sounds, the other recommended metrics are the peak SPL, the peakto-peak SPL, the sound exposure level (SEL) for a single pulse, and the cumulative SEL for several pulses, stating clearly how many pulses are considered, how long
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this is considered for (times t1 and t2 in the integral), and the duty cycle of any sampling. Using the same reference pressure of 1 mPa, they can be expressed mathematically as: ppeak SPLpeak ¼ 20 log10 (12.12) p0 ppp SPLpp ¼ 20 log10 (12.13) p0 R t2 SEL ¼ 10 log10
t1
p2 ðtÞdt
1 mPa2 s
! (12.14)
The frequency distribution of animal and background sounds can amount to large ranges (e.g., up to 200 kHz or beyond), and it is often not feasible to consider the measurements at a 1-Hz accuracy. Instead, third-octave and (sometimes and very rarely) twelfth-octave bands are used. Third-octave bands are defined (ANSI, 2009, in Ref. [90]) by their center frequencies fc (referred to f0 ¼ 1 kHz) and their lower and upper bounds, respectively, f and fþ: 8 ( i1 > i 1 for fc f0 > > > > fc ¼ f0 10 10 ; i˛ℕ and > > > i < 1 for fc < f0 > > < 1 (12.15) > > 20 > f ¼ f 10 þ c > > > > > 1 > > : f ¼ fc 10 20 Measurements over third-octave bands (or any frequency band) are expressed as spectral density levels: the amplitude values are divided by the frequency bandwidth, resulting in units of dB re 1 mPa2/Hz (sometimes seen as dB re 1 mPa/Hz1/2). These different metrics can then be used to assess the contributions from the background (using the Wenz curves, seen in Chapter 6, for natural sources) and to compare different sources of noise (e.g., animals vs. shipping or other offshore activities). All sound levels measured in PAM systems are received levels (RL); some applications might require knowledge of the actual SLs, generally at a reference distance of 1 m. Other applications might require understanding of how RL at the range measured would change if measured at another location (e.g., assessing risks to marine mammals at different ranges from a loud source). SL can be obtained by measuring closer to the source, although this is not possible for larger sources (whose contributions cannot be reduced to a single point source at short ranges) or if the survey has already been completed. In most cases, one needs to backpropagate RLs to a generic SL, using the results from Chapters 2 and 3, with those of Chapter 7 as appropriate. Again, clear reporting of the parameters used in
12.7 Selected Practical Applications
modeling acoustic propagation is essential for intercomparison of the final results. This modeling generally requires knowledge of other environmental conditions [91], including bathymetry and seabed types, and information about other loud sources in the vicinity, for example, ships monitored with automatic identification system (AIS) transponders.
12.7 SELECTED PRACTICAL APPLICATIONS 12.7.1 ACTIVE ACOUSTICS: FISH SURVEY The most common application of fishery acoustics is the surveying of commercial fish stocks [9]. This requires measuring the abundance of the species of interest, locating the largest concentrations of fish and how they vary with seasons and weather, and to determine the age/sex/maturity distribution of these species, to assess commercial viability [92]. These aims have considerable challenges. Measurements of fish numbers is often estimated from surveying along lines, keeping in mind that fish are sensitive to noise and are reputed to swim away from ships. Not all seasons are suitable for surveys, meaning that variations in fish abundance with time and weather need to be accounted. And although the exact type of fish and their maturity/size can be estimated from their acoustic scattering (Section 12.3), these need to be calibrated with trawls or optical imaging. There are many models of survey design, depending on platform(s) and instrument(s) available and on costs, which can quickly escalate. Optimization of the survey design can now make use of geographical information systems; a workshop convened by ICES in 2005 [93] published a decision tree to adapt a potential survey to measure the abundance of a single fish species2. Logistics can sometimes result in one survey being achieved with several vessels, potentially with different instruments. The acoustic measurements are then averaged along specific lengths of the survey track, called the elementary distance sampling unit (EDSU). It should be small enough to capture the key spatial elements of the species of interest, but large enough that intrinsic variability does not obscure statistical analyses. This results in typical EDSU values in the range 1e5 km, with extremes at 0.1 km (for dense schools in tight spaces like a fjord) and 9 km (for sparse deep-sea species) [92]. Water-column echoes from the fish species are isolated through different means (see Ref. [94] for a good illustration), and volume backscattering strengths SV (Section 12.3) are integrated over depths z to produce a nautical area scattering coefficient (NASC), expressed in m2/nmi2: Z Zmax 10SV =10 dz (12.16) NASC ¼ 4 pð1852Þ2 Zmin
2
www.ices.dk/sites/pub/Publication%20Reports/Expert%20Group%20Report/ftc/2005/wksad05.pdf (Figure 11).
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This can then be converted to estimated fish densities r by dividing by the expected backscattering cross-section
NASC 4 phsbs i
(12.17)
Multiplying by the survey area (in square nautical miles) should therefore give an estimate of the abundance. These estimates need to be tempered with several factors. Although fish tend to avoid larger/noisier ships, recent research shows they do not avoid more silent survey vessels [48]. Gimona and Fernandes [95] discussed how to put error bars on sounder biomass estimates, given the spatial patchiness and other unknowns. Acoustic scattering can be difficult to relate to a single fish species, but multifrequency approaches [45] can resolve ambiguities, especially if associated with in situ sampling. D’Elia et al. [96] illustrated this potential by combining results from eight acoustic surveys in the Central Mediterranean, to estimate abundances of sardine, anchovy, horse mackerel, and other species. These surveys took place over 9 years, using different instruments working at 38, 120, and 200 kHz, some of which were not regularly calibrated. They were ground truthed with daytime pelagic trawls at specific times. Volume backscattering strengths SV and NASC values at 38 and 120 kHz were compared, but the three main species could not be distinguished from their acoustic properties alone (as their swim bladders are very similar in shape and size). Further processing with classification trees [94] and bathymetry parameters (e.g., school depths) improved discrimination between these groups to 85% overall. This thorough examination of multiple, carefully designed surveys shows the steps needed to better estimate fish abundance and compare surveys. Research in mid2010s [97] investigated how to incorporate multiple sources of uncertainty in a stock assessment, validating their approach with ICES measurements of the Iberian hake stock.
12.7.2 PASSIVE ACOUSTICS: AMBIENT NOISE MONITORING Accurate knowledge of underwater noise is increasingly required by regulators before approval of offshore projects, from construction of harbor extensions to installation of marine structures, seismic surveying, or new shipping patterns. Understanding baseline noise (before any change in human activity) and how it might evolve later forms a large part of the consenting. Any method that can reliably demonstrate these changes will therefore be welcome. A recent collaboration between the University of Bath and the University of Aberdeen showed how standard PAM could be integrated with automatic identification system (AIS) shipping data, time-lapse video, and meteorological and tide data. This methodology was first presented in Merchant [98], expanded in Pirotta et al. [99] and Merchant et al. [100]. The study site in the Moray Forth (Scotland) is a marine protected area (MPA), with a resident population of bottlenose dolphins (Tursiops truncates) and other protected marine mammal species, such as harbor seal (Phoca vitulina), harbor porpoise
12.7 Selected Practical Applications
(Phocoena phocoena), and gray seal (Halichoerus grypus). The entire area is expected to see developments in shipping density and the expansion of fabrication yards within the MPA, associated to the expansion of the Scottish marine renewable energy industry. Two sites were selected for closer investigation. They were both deep, narrow channels with steep gradients and strong tidal currents. Single PAM devices were deployed for 101 days overall, recording ambient noise at 384 kHz sampling rate, with a duty cycling of 1 min every 10 min. This was synchronized with a time resolution of the AIS data (also recorded every 10 min), provided by third-party network www.shipais.com. Time-lapse footage was recorded from shore, with PAM locations within the field of view of the digital cameras. This allowed identification of vessels with or without AIS, as it is compulsory only for vessels more than 300 GT (gross tons). In two instances, it also identified rigs being moored or towed past (by vessels using dynamic positioning, which produces loud broadband noise). By comparing AIS and acoustic data, it was possible to identify the closest point of approach from a particular vessel to the recording hydrophones, assigning peaks in underwater noise to these vessels (this was possible in about 65% of cases). PAM data was used to calculate 24-h SELs (total SEL, SELs associated to AIS-tracked vessels, and SELs from unidentified sources). Acoustic data (processed with PAMGuard) was also used to detect dolphin clicks and quantify population densities [99]). Additional data used in the analyses included local meteorological data about precipitation and wind speed every 5 min, from the open-access Weather Underground database (www.wunderground. com), and POLPRED tidal computations (at 10 min intervals, to match the acoustic duty cycling). A C-POD was also deployed independently at these two sites, providing additional information about dolphin activity. The methodology (detailed in Merchant [98]) shows the interest of combining different sources of information, acoustic and nonacoustic. This was aided in this case by the proximity to shore, but recent developments in autonomous surface vehicle technology and station-keeping mean that similar information (from time-lapse footage to environmental conditions) can now be acquired further offshore. The main result of this study was that AIS-operating vessels accounted for the total cumulative sound exposure at 0.1e10 kHz, meaning that noise can be modeled using AIS data alone, and that expected noise levels can be calculated using planned increases in shipping patterns (in time and in space). The European Marine Strategy Framework Directive, European Commission [7], recommends the use of the third-octave bands centered on 63 and 125 Hz to assess shipping impacts on noise pollution. Merchant et al. found that the relationship between shipping and noise was stronger at 125 than at 63 Hz, possibly because of tidal flow noise or low-frequency propagation effects in the shallow waters, presented in Chapter 7. Pirotta et al. [99] also found a direct correlation between the presence of moving vessels and the buzzing activity of bottlenose dolphins, suggesting that dolphins perceive shipping as a clear risk as well as an acoustic masker of their own echolocation signals.
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12.7.3 ACOUSTIC TELEMETRY: FISH BEHAVIOR Acoustic tags have been used in many studies of fish behavior [101] and movements of whales [102], and the study selected here looks at the behavior of a relatively large number of fish for a long duration (close to 1 year). MPAs are set up to protect and restore overexploited fish populations. Fish movements occur across different spatial and temporal scales, and they must be understood to assess medium-to long-term MPA efficiency and assist in its management. Aspillaga et al. [103] looked at the white seabream (Diplodus sargus) in a northwest Mediterranean MPA. This is a commercially important fish, highly sedentary and known to shape rocky marine ecosystems. Aspillaga’s study was one of the longest experiments conducted with this type of fish, and it provided a wealth of new, quantitative information. MPA is located around the Medes Islands (NE Spain) and is divided into two zones: no-take, established in 1983 and shown in Fig. 12.18, surrounded by a partial reserve buffer, where very limited fishing is allowed. The seabed habitats are varied and white seabream is known to be more abundant in the no-take zone. Water depths vary between 25 and 65 m, and a particularly severe storm (waves up to 14.4 m high) occurred during the study. Forty-one individual fish were caught and tagged; the acoustic tags were very small and surgically inserted inside the animals (using the best ethical procedure available), and they transmitted at 153 dB. The acoustic monitoring network comprised 27 receivers, most of which are shown in Fig. 12.18. Receivers were moored and placed 8 m below the sea surface: 17 of them within the no-take zone, covering the entire perimeter, and 10 receivers were placed on the mainland shore a few kilometers away. Signal range tests using an acoustic tag as transmitter showed signals could be detected with >90% probability as far as 150 m, after which this dropped to 50%. During the entire monitoring period, 816,250 valid receptions were recorded by the array. Fish in the no-take zone could be tracked for long periods (329 65 days). The residence index of each fish was calculated as the ratio of the number of days it was detected and the total number of monitoring days. All fish proved to be highly territorial, moving within small home ranges (<1 km2), with an average residence index of 0.95 0.0. They displayed repetitive diel activity patterns with 95% of all receptions corresponding to depths of 0.4e11 m below the sea surface. Extraordinary movements beyond the ordinary home range were observed for two occasions: (1) during stormy events, fish quickly sheltered to more protected places; (2) during the spawning season, they moved (up to 400 m away) and aggregated in deep areas (>50 m). These results clearly show the potential of acoustic telemetry with a welldesigned receiver array: individual animals could be tracked over long periods (close to a year) with high (submetric) horizontal and vertical accuracy. The data analysis methodology (fully presented in Aspillaga et al. [103] and supplementary material) provides a robust framework for understanding individual behaviors of any type of fish and population dynamics in baseline and extraordinary (e.g., storm) circumstances. These measurements can also later be used in models of how the effects
12.8 Conclusions: Future Developments
FIGURE 12.18 Marine protected area (MPA) and acoustic receiver array used by Aspillaga et al. [103] to study fish behavior with acoustic telemetry (Reproduced under Creative Commons Attribution License.). The numbers refer to some of the 27 acoustic receivers (numbers not shown were positioned near the mainland, outside the no-take zone and around 1 km away).
of disturbance relate to animal condition/health, environmental variability, bioenergetics, vital rates, and reproductive success (PCoD model: Population Consequences of Disturbance).
12.8 CONCLUSIONS: FUTURE DEVELOPMENTS This chapter aimed to present, through simple concepts and examples, the two connected domains of fishery acoustics and bioacoustics. It started with a simple definition of the different types of marine life (Section 12.2), suitable for
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acousticians, and highlighting the main parameters of interest. Chronologically, the first question faced was how does one detect and monitor fish and other marine life? Section 12.3 looked at acoustic scattering by different animals, from zooplankton to whales, individually and in combination. The different instruments available to detect these animals were presented briefly in Section 12.4, giving only brief examples. How does marine life use sound? How sensitive are animals to other sounds, including man-made? Differences in physiology led to the separate examination of marine mammals, fish, turtles, and invertebrates in Section 12.5. Guidelines for protection of marine animals were introduced. Monitoring of underwater sound, as well as compliance of human activities with existing (and future) regulations are achieved with passive acoustic monitoring (PAM), presented in Section 12.6 Finally, an arbitrary choice of practical applications was presented in Section 12.7, showing the current trends in the use of fishery acoustics (Section 12.7.1), how traditional PAM can be augmented with suitably chosen additional measurements (Section 12.7.2), and how active acoustics (fish tags) and passive acoustics (widely scattered receivers) can be elegantly used to monitor fish behavior over large temporal and spatial scales while still maintaining a very high resolution (Section 12.7.3). The extensive bibliography at the end of this chapter is but a short sample of the very high number of peer-reviewed publications, reports, and opinion pieces written about fishery acoustics and bioacoustics. Search engines indicate both subjects have seen a strong linear growth in publications over the last decades, associated with an exponential increase in citation rates, showing how dynamic these two fields are. It is impossible to do justice to all these interesting studies, but it is worth looking at some future developments, and the questions they pose as of 2016: •
•
• •
•
Acoustic scattering by marine animals is better constrained, for a wide range of frequencies, but there is still significant work to do in benchmarking analytical and numerical models for different species, and variations within each species, as well as making these models computationally fast and approachable by nonspecialists. Target strengths have been measured for many animals in the wild and in the laboratory, but there are still many unknowns, from variations with aspect (e.g., for large animals or even some fish species) to simply any measurement for animals like crocodiles or sea otters. Auditory sensitivity of many animals still needs to be measured, in particular for invertebrates and sea turtles. Identifying scattering by animals close to the sea surface or to the seabed is still a challenge, and so is the identification of multiple species sharing the same space. Accurate tracking of targets of interest across acoustic beams and quantifying the risks of occlusion of one target by a closer one are also open processing problems (other bioacoustics issues are presented in Ref. [104]). New instruments are coming to the fore, from panoramic sonars to multiangle sonars, and coupled with the increased accessibility of autonomous platforms
References
•
•
like autonomous underwater vehicles [105], gliders, and autonomous surface vehicles, new approaches are likely to emerge within the next decade. PAM technology has matured but improvements (e.g., for towed arrays, source localization in complex environments, and transformation of RLs into SLs) are still needed. National and international policies are developing, with the development of marine protected areas (and similarly protected areas), regulations like the European NATURA-2000 or the Marine Strategy Framework Directive, calibration, operation, and analysis standards (e.g., ISO, MEDIN, and JNCC). How much will they be informed by current measurements, and how much will they shape future capabilities and research efforts?
REFERENCES [1] R. Froese and D. Pauly (Eds.), FishBase. World Wide Web electronic publication. www.fishbase.org, version (10/2015), 2015. [2] FAO (Food and Agriculture Organization of the United Nations), “The State of World Fisheries and Aquaculture (SOFIA) - 2014”, Rome, 223 pp., 2014. [3] IPCC; “Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change”, [V.R. Barros, C.B. Field, D.J. Dokken, M.D. Mastrandrea, K.J. Mach, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (Eds.)]. Cambridge University Press, pp. 688, 2014. [4] Clover, C., The End of the Line: How Overfishing is Changing the World and What We Eat, Ebury Press (UK), 2004. [5] MCS (Marine Conservation Society), Silent Seas, 34 pp., also Available at: http:// www.mcsuk.org/information.php/AboutþMCS/Silentþseasþreport, 2008. [6] McCauley, D.J., M.L. Pinsky, S.R. Palumbi, J.A. Estes, F.H. Joyce, Warner, R.R., Marine defaunation: Animal loss in the global ocean, Science 347 (6219):1255641: http://dx.doi.org/10.1126/science.1255641, 2015. [7] European Commission, Directive 2008/56/EC of the European Parliament and of the Council of 17 June 2008 establishing a framework for community action in the field of marine environmental policy (Marine Strategy Framework Directive), http://eur-lex. europa.eu/legal-content/EN/TXT/PDF/?uri¼CELEX:32008L0056&from¼EN, 2008. [8] Medwin, H., Clay, C.S., Fundamentals of Acoustic Oceanography, 712 pp., Academic Press, 1998. [9] Simmonds, E.J., and MacLennan, D.N. Fisheries Acoustics: Theory and Practice, Second Edition, Blackwell Publishing, Oxford. 456 pp., 2005. [10] Lurton, X., An Introduction to Underwater Acoustics: Principles and Applications, 680 pp., Springer-Praxis, 2010. [11] EC, 2016; Good Environmental Status e Descriptor 4: Food Webs, http://ec.europa.eu/ environment/marine/good-environmental-status/descriptor-4/index_en.htm. [12] Stanton, T.K., Chu, D., Reeder, D.B., Non-Rayleigh acoustic scattering characteristics of individual fish and zooplankton. IEEE J. Oceanic. Eng., 29, pp. 260e268, 2004.
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