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![Page 1: 1 The influence of fish morphological and behavioural parameters on acoustic data in algorithmic reconstruction of fish length distribution Marek Moszynski,](https://reader036.fdocuments.in/reader036/viewer/2022062515/56649ca25503460f94961093/html5/thumbnails/1.jpg)
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The influence of fish morphological and behavioural parameters on acoustic data in
algorithmic reconstruction of fish length distribution
Marek Moszynski, Andrzej Stepnowski
Gdansk University of Technology Poland
ICES ASC 17-21 September 2007, Helsinki, FinlandICES CM 2007/H:08Effects of environmental changes on the biology, physiology, and behaviour of pelagic fish
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The influence of fish morphological and behavioural parameters on acoustic data in
algorithmic reconstruction of fish length distribution
ICES ASC 17-21 September 2007, Helsinki, FinlandICES CM 2007/H:08Effects of environmental changes on the biology, physiology, and behaviour of pelagic fish
Abstract The paper investigates the algorithm for estimation the fish length distribution from acoustic target strength data. The theory of scattering from a tilted cylinder is used for modelling the fish directivity pattern of swimbladdered fish. The model allows formulating the dependence of target strength on two main components: fish maximum target strength and the fish directivity pattern. As both terms depend on fish length, the inverse technique could be used to reconstruct unknown fish length distribution from acoustic data, when morphological parameters of fish are properly assumed. However, as it is shown, the algorithmic approach is very sensitive to some of behavioural parameters of swimming fish. Thus, although the effect of unknown fish tilt angle could be partially removed by statistical processing, the mean value of fish tilt angle still may produce large errors. The method and its results are verified on actual data acquired during the survey and compared to trawl catches.
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Introduction (1)
Echo Level E
Target Strength
TS
Fish length
L
FishBiomass
Q
acoustical measures physical measures
Catchdata
Fish echo processing chain:
regression modelsmeasurements:• ex situ• in situ
Ei = SL+RS + TSi(li, i , zi,, fo ) + 2B(i ) - 2TL( Ri, α)
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Introduction (2)
Backscattering modelTilt angle statistics
INVERSE PROCESSING
Sample catchRegression relation
MEAN VALUE PROCESSING
pTSFish
lengthL
< l >
pl
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Fish length estimation
pTS plpTS0
-tilt angle statistics-backscattering model
backscattering model
problems:• unknown titl angle during ensonification• unknown fish directivity pattern
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Fish backscatter models for swimbladdered fish
• tilted cylinder - Haslett (1962)
• finite bent cylinder model - Stanton (1989)
• low resolution acoustic model - Clay (1991)
• Kirchhoff ray mode model (KRM) - Clay, Horn (1994)
• boundary element model - Foote, Francis (2002)
simple
precise
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Haslet model for swimbladdered fish
Haslett, 1962• swimbladder is approximated by a combination of: a hemisphere, a short cylinder, a cone of fixed dimensions relative to the fish fork length. • then this shape is modified to: a cylinder maintaining their geometrical cross section.
lecb=0.24L
2aecb=0.049L
0.2L0.125L
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Methods
i f z = x + y t h e n dxxzxpzp yxz ),()( ,
( i . e . E = B + T S o r T S = T S 0 + D f ) i f x y i n d e p e n d e n t r a n d o m v a r i a b l e s t h e n
dxxzpxpzp yxz )()()(
i f x y d e p e n d e n t r a n d o m v a r i a b l e s t h e n
dxxxzpxpzp xyxz ),()()( |
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Methods (2)
i f z = x + y t h e n dxxzxpzp yxz ),()( ,
( T S = T S 0 + D f ) i f x y d e p e n d e n t r a n d o m v a r i a b l e s t h e n
dxxxzpxpzp xyxz ),()()( |
f o r T S 0 a n d D f
000|0 ),()()(00
dTSTSTSTSpTSpTSp TSDTSTS f
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Backscatter theory (1)T h e a m p l i t u d e o f a c o u s t i c b a c k s c a t t e r i n g l e n g t h o f a g a s - f i l l e d
c y l i n d e r i n w a t e r m a y b e e v a l u a t e d f r o m H e l m h o l t z - K i r c h h o f f i n t e g r a l( M e d w i n a n d C l a y ) :
)cos(
)sin(
)sin(sin)( 0
0
00
ecb
ecbBSBS kl
klll ( 1 )
l B S 0 = l e c b ( a e c b / 2λ ) 1 / 2 - m a x i m u m b a c k s c a t t e r i n g l e n g t h ,a e c b , l e c b - r a d i u s / l e n g t h o f t h e e q u i v a l e n t s w i m b l a d d e r a s a c y l i n d e r ,χ - f i s h a n g u l a r c o o r d i n a t eχ 0 - t i l t a n g l e o f t h e s w i m b l a d d e rk = 2π / λ - w a v e n u m b e r
+0
lecb
aecb
k
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Backscatter theory (2) I n t h e l o g a r i t h m i c f o r m :
),,,(),,( 00 flDfalTSTS ecbfecbecb
T S = 2 0 l o g | l B S | T S 0 m a x i m u m t a r g e t s t r e n g t h
2log200
ecbecb
alTS
B f ( . ) l o g a r i t h m i c f i s h a n g u l a r p a t t e r n i n d o r s a l a s p e c t
)cos()sin(
)sin(sinlog20),,,( 0
0
00
ecb
ecbecbf kl
klflD
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Tilt angle/Angular fish position PDF
Multiple echo statistics:
moving vessel and stationary fish model
equally probable distance
from the centre to the trace of the fish
moving fish and stationary vessel model
equally probable crossing angle
rm ax
zm ax
r
Rz
t
M o d e l 2 - : U ( 0 , /2 )
r
t
1
r
t
M o d e l 1 - 1 : U ( 0 ,r )
cos = 1 / r
1: U (0,r)
1 = r u
p()=sin
p()=2 /
(0,/2)
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Tilt angle dependance (1)
)cos()sin(
)sin(sinlog20),,,( 0
0
00
ecb
ecbecbf kl
klflD
f = 38kHz0=8°lecb=L/4
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Conditional fish beam pattern PDF
Df [dB]
TS0 [dB]
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randomgenerator
pTS
TS
Statistical processing
0|ˆ TSD fp
0ˆTSp
Lp̂inversionEMS
Inversion
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Processing example
a) acoustically measured target strength TS at 200kHz b) conditional PDF of the fish directivity pattern assuming swim bladder tilt angle 5 c) estimated maximum target strength PDF
d) reconstructed fish length distribution along with the catch histogram (in cm)
a) b) c) d)
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Case study 1 • NOAA/Alaska Fisheries Science Center - summer 2002 - Bering Sea• provided by Neal Williamson (PMEL - Seattle)
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Survey data
•Simrad EK500 v.5.30 echosounder• 38kHz split beam transducer• logged w/ Sonardata's Echolog 500• 14-07-2002 8:57 – 11:22 am• 6776 pings (540MB) • 2002 tracks of walleye pollock (Theragra chalcogramma)
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Survey data analysis
30 40 50 600
10
20
30
40
pL1
14-07
30 40 50 600
10
20
30
40
50
pL2
14-07
-80 -60 -40 -200
100
200
300
400
pTS
14-07
30 40 50 600
0.2
0.4
0.6
0.8
1
pL,p'
L
f=38kHz
[dB]
[cm]
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Survey data analysis (2)
-80 -60 -40 -200
100
200
300
400
pTS
(f=38kHz) 14-07
-80 -60 -40 -200
500
1000
1500
pTS
(f=120kHz) 14-07
30 40 50 600
10
20
30
40
pL1
14-07
30 40 50 600
10
20
30
40
50
pL2
14-07[dB]
[cm]
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Survey data analysis (3)
30 40 50 600
0.5
1f=38kHz
0=5
30 40 50 60
0=6
30 40 50 60
0=7
30 40 50 60
0=8
30 40 50 60
0=9
30 40 50 60
0=10
30 40 50 600
0.5
1f=120kHz
0=5
30 40 50 60
0=6
30 40 50 60
0=7
30 40 50 60
0=8
30 40 50 60
0=9
30 40 50 60
0=10
Reconstruction of fish length PDF for different mean swimbladder tilt angle 0 along with estimate from catch data.
Upper sequence for 38kHz and lower for 120kHz. X-axis represents fish length in [cm].
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Survey data analysis (4)
5 6 7 8 9 100.1
0.2
0.3
0.4
0.5
Root mean square error function obtained from 38kHz and 120 kHz estimates versus assumed swimbladder tilt angle
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Survey data analysis (6)
Estimates of length PDF for mean swimbladder tilt angle 0=7 along with catch data
30 35 40 45 50 55 600
0.2
0.4
0.6
0.8
1
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Tilt angle dependance (3) Target strengths as a function of tilt angle for a 31.5cm pollock
at dorsal aspect at 38kHz and 120kHz Foote (1985)
Walleye pollock Theragra chalcogramma (Horne - Radiograph Gallery)
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Case study 2
• R/V “G. O. Sars” • March 17 to April 5, 2004• Lofoten 2004 survey• Lofoten islands, from 67oN to 70oN, • spawning grounds of North East Arctic Cod • shelf between 500 m to about 50 meters • sea temperature 6.8 – 7.1oC from 40–300m • 5 Simrad EK60 split beam echosounders
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Experiment
• standard sphere calibration methods CU64 (18 kHz), CU60 (38 kHz) , WC38.1 (70, 120 and 200 kHz)• transducers mounted in one of the instrument keels of the vessel • full half-power beam widths 7o, except for the 18 kHz (11o)• the transmitted pulse duration was identical on all frequencies - 1.024 ms• the Bergen Echo Integrator, BEI. • heave, roll, pitch and yaw Seatex MRU 5 -Simrad EM 1002 at 10 Hz • CTD observations (Sea-Bird SBE9).• trawling partly on fixed locations, mostly on registrations for identification of the targets and for biological sampling.• Campelen 1800 bottom survey trawl • Åkratrawl, a medium sized midwater trawl• Standard biological parameters were measured on all catch samples, • individual total length, weight, gonad and liver index, age and stomach content.
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Trawl data
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38kHz 70 kHz
120kHz 200 kHz
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Survey data • provided by Institute of Marine Research - Bergen
Norwegian cod echoes at depth range 100-160m acquired with 18kHz system
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Survey data • provided by Institute of Marine Research - Bergen
Norwegian cod echoes at depth range 100-160m acquired with 38kHz system
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Survey data • provided by Institute of Marine Research - Bergen
Norwegian cod echoes at depth range 100-160m acquired with 70kHz system
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Survey data • provided by Institute of Marine Research - Bergen
Norwegian cod echoes at depth range 100-160m acquired with 120kHz system
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Survey data • provided by Institute of Marine Research - Bergen
Norwegian cod echoes at depth range 100-160m acquired with 200kHz system
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Target strength data
-60 -40 -200
50
100
150
pTS
18kHz (20-03-2004)
-60 -40 -200
100
200
300
400
500
pTS
38kHz (20-03-2004)
-60 -40 -200
50
100
150
200
250
pTS
70kHz (20-03-2004)
-60 -40 -200
100
200
300
400
pTS
120kHz (20-03-2004)
-60 -40 -200
100
200
300
400
500
pTS
200kHz (20-03-2004)
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Results
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
40 60 80 100 1200
0.5
1
38kHz
70kHz
120kHz
200kHz
2° 5° 8°
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Tilt angle dependance (3) TS/length relationship on tilt angle for atlantic cod
TS = 20log L + B20 , McQuinn, Winger (2002)EK500 38kHz SB 7
B20
Atlantic codGadus morhua(Horne - Radiograph Gallery)
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Problems
Proposed method can be applied only for one species in the data set.
The knowledge of simplified morphological parameters of
swimbladder (aecb, lecb, χ0) are required . The statistics of fish orientation changes are also required
(normal distribution is assumed).
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Conclusions
The estimated PDF of acoustic backscattering length of fish differs from actual fish length PDF.
The transformation of physical fish length distributions is a result of combined effect of random fish length and its scattering pattern.
The process of removing fish directivity pattern effect requires application of inverse technique as fish length information is included in maximum fish target strength TS0.
The knowledge of mean fish swimbladder tilt angle (χ0) can be estimated by multifrequency approach using simple comparison of their fish length rms estimates.