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In this technique, a 3D estimation area is considered where vocalizing fish and mammals produce acoustic signals as a consequence of their acoustic activities. Transmitted acoustic signals from N fish and mammals are received by two acous- tic sensors at different delay differences and summed at each sensor location forming composite signals. These two com- posite signals are then cross-correlated to formulate Cross- correlation function (CCF) that results a series of delta func- tions stated in [167-168]. Such an acquisition of CCF is shown below for 100 fish and mammals.

Figure 11 In this technique, a 3D estimation area is considered where vocalizing fish and mammals produce acoustic signals as a consequence of their acoustic activities. Transmitted acoustic signals from N fish and mammals are received by two acous- tic sensors at different delay differences and summed at each sensor location forming composite signals. These two com- posite signals are then cross-correlated to formulate Cross- correlation function (CCF) that results a series of delta func- tions stated in [167-168]. Such an acquisition of CCF is shown below for 100 fish and mammals.

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Abstract: In marine biodiversity conservation, population size estimation of marine species is the most significant challenge. Many top-notch researches have been conducted for estimating the population size of fish and mammals. Most of the researches followed mainly two methods namely non-acoustics and acoustics techniques to estimate fish population. The non-acoustic technique is an old terminology and a number of mechanical instruments are required to implement this technique. Consequently, acoustic methods for estimating fish population become popular. Acoustic techniques can be classified in to two ways, i.e., active acoustic techniques, and passive acoustic techniques. In this paper, we have reviewed the major non-acoustic and acoustic techniques for estimating the population size of fish and mammals. At the same time, performance analysis among these techniques has been discussed in this study. An introduction to the diversity in fish population estimation techniques is the aim of this investigation.
Abstract: In marine biodiversity conservation, population size estimation of marine species is the most significant challenge. Many top-notch researches have been conducted for estimating the population size of fish and mammals. Most of the researches followed mainly two methods namely non-acoustics and acoustics techniques to estimate fish population. The non-acoustic technique is an old terminology and a number of mechanical instruments are required to implement this technique. Consequently, acoustic methods for estimating fish population become popular. Acoustic techniques can be classified in to two ways, i.e., active acoustic techniques, and passive acoustic techniques. In this paper, we have reviewed the major non-acoustic and acoustic techniques for estimating the population size of fish and mammals. At the same time, performance analysis among these techniques has been discussed in this study. An introduction to the diversity in fish population estimation techniques is the aim of this investigation.
Because of their small size, minnow traps can also be set amongst complex habitat and in very small and shallow pools of water [30]. Fyke nets are essentially a type of cylindrical fish trap which contain a series of funnel-shaped openings which make it easy for fish to enter the trap but very difficult to for them to make their way out.
Because of their small size, minnow traps can also be set amongst complex habitat and in very small and shallow pools of water [30]. Fyke nets are essentially a type of cylindrical fish trap which contain a series of funnel-shaped openings which make it easy for fish to enter the trap but very difficult to for them to make their way out.
To overcome the limitation of echo counting technique, echo integration technique was introduced to estimate fish population [67-70]. Echo-integration uses the total backscat- tered acoustic energy, divided by a previously determined volume backscattering coefficient in order to estimate fish population [71]. An echo-integrator equation relates fish population to echo energy integrated over a time gate corre- sponding to the depth channel of interest. Parameters include the equivalent beam angle, the expected backscattering cross section per fish, equipment sensitivity, and a time-varied-gain correction factor [72]. However, the choice of frequency plays the most important role in this technique [73].
To overcome the limitation of echo counting technique, echo integration technique was introduced to estimate fish population [67-70]. Echo-integration uses the total backscat- tered acoustic energy, divided by a previously determined volume backscattering coefficient in order to estimate fish population [71]. An echo-integrator equation relates fish population to echo energy integrated over a time gate corre- sponding to the depth channel of interest. Parameters include the equivalent beam angle, the expected backscattering cross section per fish, equipment sensitivity, and a time-varied-gain correction factor [72]. However, the choice of frequency plays the most important role in this technique [73].
Fig. 6: Analysis pathways implemented in echo-view (version 4.1). Four parallel processes are presented that provide similar outcomes even though they are used to optimize analyses under various conditions [75]
Fig. 6: Analysis pathways implemented in echo-view (version 4.1). Four parallel processes are presented that provide similar outcomes even though they are used to optimize analyses under various conditions [75]
in which fish produce sounds is by stridulating [102]; a process in which hard body parts like bones or teeth hit each other. Body movements that create water currents or splashes are also used to create sounds for communication [103]. Cavita- tions sounds are produced during the feeding of the fish with a piece of food. A rapid drop of the pressure inside of the oral cavity can lead to the appearance of small cavitations bubbles. Reduction of their volume occurs for a short time, and it is ac- companied by a sound pulse [104]. Fig. 7: Diversity of sound generating mechanisms in fish and sono- grams of sounds produced by these mechanisms with acronyms (right part) (a) SMi attached to both SL in the Lusitanian toadfish Halobatrachus didactylus, (b) SMe originating at the 2R and in- serting on a BT ventrally of the swim bladder in the black piranha Serrasalmus rhombeus, (c) in the stimulatory mechanism in cat- fish a ridged DP of the PS rubs in a groove of the SG, (d) ETs are plucked similar to guitar strings in the croaking gourami Trichop- sisvittata, (e) PT stridulating in damselfish, sunfish, among others, and pectoral girdle vibration in sculpins by a SM originating at the skull and inserting at the dorsal part of the pectoral girdle. All sonograms show sounds produced in agonistic contexts
in which fish produce sounds is by stridulating [102]; a process in which hard body parts like bones or teeth hit each other. Body movements that create water currents or splashes are also used to create sounds for communication [103]. Cavita- tions sounds are produced during the feeding of the fish with a piece of food. A rapid drop of the pressure inside of the oral cavity can lead to the appearance of small cavitations bubbles. Reduction of their volume occurs for a short time, and it is ac- companied by a sound pulse [104]. Fig. 7: Diversity of sound generating mechanisms in fish and sono- grams of sounds produced by these mechanisms with acronyms (right part) (a) SMi attached to both SL in the Lusitanian toadfish Halobatrachus didactylus, (b) SMe originating at the 2R and in- serting on a BT ventrally of the swim bladder in the black piranha Serrasalmus rhombeus, (c) in the stimulatory mechanism in cat- fish a ridged DP of the PS rubs in a groove of the SG, (d) ETs are plucked similar to guitar strings in the croaking gourami Trichop- sisvittata, (e) PT stridulating in damselfish, sunfish, among others, and pectoral girdle vibration in sculpins by a SM originating at the skull and inserting at the dorsal part of the pectoral girdle. All sonograms show sounds produced in agonistic contexts
their generated chirps consisted of trains of 12-42 short puls- es of three to six cycles, with a duration from 0-6 to 1-27 ms; and the peak frequency varied from 3400 to 4100 Hz [110]. Northern searobin (Prionotus carolinus), Southern striped searobin (P. evolans) [111-114], Black Sea gurnard [115], etc., can produce cluck like sound. The cluck, generated by Northern searobin (Prionotus carolinus) has a frequency range of 40-2400 Hz with duration of 100 ms [111-114]. Japanese gurnard (Chelidonichthys kumu) [116], Grey gur- nard (Eutrigla gurnardus) [117], the oyster toadfish Op- sanus tau [118-119], gulf toadfish (O. beta) [120-121], Porichthys notatus nesting males [122], etc., species can pro- duce grunt like sound. The haddocks emit grunts lasted less than 75 ms and comprised 3-4 pulses whereas the grunts pro- duced by codfish had durations were typically smaller than 150 ms and consisted of around 9 pulses. Grunts are broad- band (up to 3 kHz) pulsed sounds which have a lasting of 300 ms approximately. Pollimyrus adspersus, Cichlasoma cen- trarchu [123], etc., produce a growl like sound. The growls are broadband (100 Hz - 2 kHz) pulsed sounds, variable in duration, and with the typical pulse repetition rate of 25 pps (pulses per second) [124]. Hoots and pops are sounds heard exclusively in aggressive interactions. Hoots are made by P. isidori [125], P. ballayi [126], P. adspersus [127], etc., and are relatively short sounds (30 ms), with frequencies lower than 1 kHz, and made up of nearly sinusoidal waveforms. Pops are made by species of Chromis chromis [128], Pollimyrus Gnatho- nemus petersii [128], etc., and consist of a series of pulse emis- sions with focal energies up to 2-3 kHz. Cod (Gadus morhua) can produce click like sound with peak frequency 55.95 2.22 kHz; peak-to-peak duration 50.70 60.45 ms [129-130]. Beluga (Delphinapterus leucas), bottlenose dolphin (Tursiops truncatus) [131], Sperm whale [132], etc., fish and mammals can produce similar sound-signal. Whistle is common in Killer whale (Orcinus orca) [133], some species of dolphin like (tur- siops truncatus) [134] and various species of mammals.
their generated chirps consisted of trains of 12-42 short puls- es of three to six cycles, with a duration from 0-6 to 1-27 ms; and the peak frequency varied from 3400 to 4100 Hz [110]. Northern searobin (Prionotus carolinus), Southern striped searobin (P. evolans) [111-114], Black Sea gurnard [115], etc., can produce cluck like sound. The cluck, generated by Northern searobin (Prionotus carolinus) has a frequency range of 40-2400 Hz with duration of 100 ms [111-114]. Japanese gurnard (Chelidonichthys kumu) [116], Grey gur- nard (Eutrigla gurnardus) [117], the oyster toadfish Op- sanus tau [118-119], gulf toadfish (O. beta) [120-121], Porichthys notatus nesting males [122], etc., species can pro- duce grunt like sound. The haddocks emit grunts lasted less than 75 ms and comprised 3-4 pulses whereas the grunts pro- duced by codfish had durations were typically smaller than 150 ms and consisted of around 9 pulses. Grunts are broad- band (up to 3 kHz) pulsed sounds which have a lasting of 300 ms approximately. Pollimyrus adspersus, Cichlasoma cen- trarchu [123], etc., produce a growl like sound. The growls are broadband (100 Hz - 2 kHz) pulsed sounds, variable in duration, and with the typical pulse repetition rate of 25 pps (pulses per second) [124]. Hoots and pops are sounds heard exclusively in aggressive interactions. Hoots are made by P. isidori [125], P. ballayi [126], P. adspersus [127], etc., and are relatively short sounds (30 ms), with frequencies lower than 1 kHz, and made up of nearly sinusoidal waveforms. Pops are made by species of Chromis chromis [128], Pollimyrus Gnatho- nemus petersii [128], etc., and consist of a series of pulse emis- sions with focal energies up to 2-3 kHz. Cod (Gadus morhua) can produce click like sound with peak frequency 55.95 2.22 kHz; peak-to-peak duration 50.70 60.45 ms [129-130]. Beluga (Delphinapterus leucas), bottlenose dolphin (Tursiops truncatus) [131], Sperm whale [132], etc., fish and mammals can produce similar sound-signal. Whistle is common in Killer whale (Orcinus orca) [133], some species of dolphin like (tur- siops truncatus) [134] and various species of mammals.
deviation Fig. 8 shows simulated form of fish chirp in which Fig. 8(a) represents a simple form of chirp with duration of 1s and Fig. 8(b) represents a chirp with linear instantaneous frequency deviation where the chirp is sampled at 1 kHz for 2 seconds. The instantaneous frequency is 0 at t= 0 and crosses 200 Hz at t= 1 second. Fig. 9: Pulse train representation of a 10 kHz fish signal with 10 ms duration
deviation Fig. 8 shows simulated form of fish chirp in which Fig. 8(a) represents a simple form of chirp with duration of 1s and Fig. 8(b) represents a chirp with linear instantaneous frequency deviation where the chirp is sampled at 1 kHz for 2 seconds. The instantaneous frequency is 0 at t= 0 and crosses 200 Hz at t= 1 second. Fig. 9: Pulse train representation of a 10 kHz fish signal with 10 ms duration
Thus, from equations (7) or (8), we can calculate N since we know 6 and R or can be calculated from CCF. Fig. 12: Simplified block diagram of cross-correlation based fish population estimation technique
Thus, from equations (7) or (8), we can calculate N since we know 6 and R or can be calculated from CCF. Fig. 12: Simplified block diagram of cross-correlation based fish population estimation technique
A tabular representation of the estimation for exponential dis- tribution of damselfish using this technique is illustrated bel- low [167, 183]: Tab. 1: Experimental & theoretical data of CCF and percentage of error for exponential distribution
A tabular representation of the estimation for exponential dis- tribution of damselfish using this technique is illustrated bel- low [167, 183]: Tab. 1: Experimental & theoretical data of CCF and percentage of error for exponential distribution
Tab. 2: Features of non-acoustic, active acoustic and passive acoustic techniques ine Narsnness of underwater environment | loU-lol} ninaers the fish population estimation greatly. However, to satisfy necessity of ecological conservation and commercial fishery management, diverse fish population estimation techniques were introduced. Mechanical equipment based non-acoustic methods of fish population estimations were suffered from various drawbacks like poor accuracy, mechanical complexity, mostly human interaction, low efficiency, etc. Hence, after ar- rival of acoustic techniques of fish population estimation, the researchers and modern commercial fishery managers began to use these. While active sonar’s have been widely adopted in the past 20 years for estimating fish population, passive acous- tics has not seen widespread adoption. The reason can be a paucity of commercial passive acoustic technologies in the market [182]. Similarly, vast researches on passive acoustics- based fish population estimation are underway. Auspiciously, it is expected that diverse commercial passive acoustic tech- niques will be available in the near future. A relative features and analysis of non-acoustic, active acoustic and passive acoustic techniques is illustrated in Tab. 2.
Tab. 2: Features of non-acoustic, active acoustic and passive acoustic techniques ine Narsnness of underwater environment | loU-lol} ninaers the fish population estimation greatly. However, to satisfy necessity of ecological conservation and commercial fishery management, diverse fish population estimation techniques were introduced. Mechanical equipment based non-acoustic methods of fish population estimations were suffered from various drawbacks like poor accuracy, mechanical complexity, mostly human interaction, low efficiency, etc. Hence, after ar- rival of acoustic techniques of fish population estimation, the researchers and modern commercial fishery managers began to use these. While active sonar’s have been widely adopted in the past 20 years for estimating fish population, passive acous- tics has not seen widespread adoption. The reason can be a paucity of commercial passive acoustic technologies in the market [182]. Similarly, vast researches on passive acoustics- based fish population estimation are underway. Auspiciously, it is expected that diverse commercial passive acoustic tech- niques will be available in the near future. A relative features and analysis of non-acoustic, active acoustic and passive acoustic techniques is illustrated in Tab. 2.
Fig. 13: Corresponding estimation results ~— from Hossain et al. (2018) for exponential distribution of Damselfish, (a) Number of damselfish vs. mean of CCF, and (b) Variation of estimated number of damselfish from the actual quantity [167]
Fig. 13: Corresponding estimation results ~— from Hossain et al. (2018) for exponential distribution of Damselfish, (a) Number of damselfish vs. mean of CCF, and (b) Variation of estimated number of damselfish from the actual quantity [167]
Related topics:
Marine ConservationUnderwater AcousticsFishery Stock Assessment and ManagementPassive Acoustic MonitoringActive Acoustics
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