Numerical simulation of dispersal patterns of red sea bream juveniles, Pagrus major, in Nyuzu Bay, Japan

Journal of Marine Systems, 3 (1992) 477-487

477

Elsevier Science Publishers B.V., Amsterdam

Numerical simulation of dispersal patterns of red sea bream juveniles, Pagrus major, in Nyuzu Bay, Japan Tetsuo Yanagi a, Shin-Ichi O k a d a b and Katsumi Tsukamoto c a Department of Ocean Engineering, Ehime University, Matsuyama 790, Japan b Japan NUS Co., Ltd., Nisso Dai-12 Bldg., 6-12 Shin-Yokohama 3, Kohoku-Ku, Yokohama 222, Japan c Ocean Research Institute, University of Tokyo, Minami-Dai 1-15-1, Nakano-ku, Tokyo 164, Japan Received March 13, 1991; revised version accepted November 5, 1991

ABSTRACT Yanagi, T., Okada, S.-I. and Tsukamoto, K., 1992. Numerical simulation of dispersal patterns of red sea bream juveniles, Pagrus major, in Nyuzu Bay, Japan. J. Mar. Syst., 3: 477-487. A numerical simulation of the experimental stocking of red sea bream, Pagrus major, was tested. Three groups of juveniles of 20-40 mm T.L. were released at two stations in Nyuzu Bay in the Bungo Channel, Japan, on 5 July 1989. At the entrance of the Bay, 78,800 of 40 mm fish (G40M) and 130,900 of 20 mm fish (G20M) were released; at the head of the Bay, 144,200 of 20 mm fish (G20H) were released. Samples were collected for three days after release. The recapture percentage of the G40M group (0.69%) was about 35 times larger than that of G20M (0.024%). Recapture of the G20H group occurred only near the point of release and its recapture rate (0.10%) was about 5 times larger than that of G20M. The numerical simulation incorporated the flow field and behavioral characteristics of red sea bream juveniles. The calculated dispersal patterns of the three fish groups were consistent with the observed patterns.

Introduction

Stocking of juvenile red sea bream (Pagrus major) has been a major program of the Sea Farming Project in the coastal sea of Japan. To ensure effective stocking, it is important to know the behavior of juveniles after the stocking. However, the factors affecting post-stocking survival of released juveniles are unknown. One important factor regulating post-stocking dispersion of weak swimming juveniles is the flow field. The relationship between the flow field and survival of juveniles is unknown. Numerical simulation has been used to investigate the relationship between the flow field and fish migration. Bartsch et al. (1989) simulated the advection of herring

larvae in the North Sea with use of the three-dimensional numerical model considering the flow field and the vertical migration of larvae. The objective of'this study was to obtain the information concerning dispersion of released juveniles and the effects of the flow field and the behavior of juveniles on dispersion. Experimental data and a three-dimensiona! numerical model were used. Methods

Field experiment Three groups of juveniles of the red sea bream,

Pagrus major, were released in Nyuzu Bay in the

Correspondence to." T. Yanagi, Department of Ocean Engineering, Ehime University, Matsuyama 790, Japan.

Bungo Channel, Japan (Fig. 1) from 5 to 7 July 1989. A total of 353,900 juveniles were released at two sites (Fig. 1). Groups G20M (20 mm Total Length) and G40M (40 mm T.L.) were released

0924-7963/92/$05.00 © 1992 - Elsevier Science Publishers B.V. All rights reserved

478

T. Y A N A G I E T A L .

at the mouth of the bay (point M, Fig. 1) and group G20H (20 mm T.L.) were released at the head of the bay (point H, Fig. 1) at the beginning of flood tide on 5 July 1989. All fish were marked by otolith-tagging (Tsukamoto, 1988) two days to two weeks before release. Juveniles were immersed in a 50-200 m g / l solution of the fluorescent substance, alizarin complex (ALC), for 24 hours at 20°C. The treatment resulted in a scarlet fluorescent ring in the otolith detectable under ultraviolet light. Kuwada and Tsukamoto (1987) reported

that marks were retained for two years and the marking procedure had no effect on growth and mortality of red sea bream juveniles. Fish groups were distinguished by the number diameter of the marks determined by the otolith size as treatment (Table 1). The behavior of red sea bream was observed in laboratory aquaria and by SCUBA diving, both in the daytime and at night. About 25,000 fish of 20 mm T.L. and 1500 fish of 40 mm T.L. were contained separately in two tanks (3 × 3 × 2.5 m : length × width × depth). They were caught by

Seto Inl

~

Kyushu~

Bay

oki

33+20'N

.+@ 4" < ~

.33°00"N <

"~7~UNGO CHANNEL t]z~oo,E

~OttN

;OcN

131 o ST;30.tE

132~'00 'r:

Fig. 1. Nyuzu Bay. Numbers show the depth in meter. Dashed line shows the open boundary of the numerical model.

,

1 km

=

i:. o

..' -..~'~,..-:~.

G20H

o

o

G20M

. r~ :~'~

"~,

G 40M

~

~ /

~:

. :::~

; :~

Fig. 2. Horizontal distributions of stocked juveniles for three days after the release. Plus mark denotes the release point.

~;:,~-

:':~::

•

•

•

0.(~1--O. 100

0.0.-0.050

0.001-0.010

Recapture (%)

t"

z

< nl

>

©

z

t-

480

T. Y A N A G I E T AL.

Dep. 0

(~)

(°C]

]7

Temp.

25

0

/

Temp.i!!i al"

[m)

200

oo/

10

2O

DO

,/ 32

i\,

i Sal.

34

21

O't

TABLE 1 Results of experimental stocking of the red sea bream juveniles in Nyuzu Bay Group

T.L. (mm)

Otolith marking

Fish stocked (xl000)

Fish recaptured

Recapture rate (%)

G20H G20M

17.8 18.7

144.2 130.9

138 31

0.10 0.024

G40H

39.5

double small single large single

78.8

547

0.69

353.9

716

Total

25

Fig. 3. Observed vertical distributions of water temperature, salinity, density and dissolved oxygen at point M on 5 July 1989.

horizontal towing of circular dip net (mouth of 40 cm diameter) at four depth strata; 0.2, 1.0, 1.8 and 2.3 m, in order to determine the diel change in vertical distribution. The observational informations obtained in the laboratory and in the field were used to determine the behavioral characteristics of juveniles in the numerical model. Released juveniles were mostly collected using a small beach seine with a mouth width of 1.5 m, wing length of 5 m and cod-end mesh of 1.8 ram. Juveniles were also collected using horizontal tows at the surface and bottom at 20 sampling loca-

tions in the bay (Fig. 1). Samples were collected on three occasions from 5 to 7 J u l y 1989. Samples were frozen at - 20°C. T o determine the group of origin of each fish, otoliths were extracted and the ALC mark was checked under a U V light microscope.

Results Distribution of recovered juveniles are shown in Fig. 2. Number of fish recaptured was 547 from G40M (0.69%), 31 from G20M (0.024%) and 138 from G20H (0.10%). G40M and G20M juveniles dispersed mainly along the shore from the release point M, although some juveniles crossed the deep central part of the bay to the ,

~:

' __

52'30"N

32°50'N

57'30"E "

132°00'E

57' 30" E

132000 ' E

0

57'30"E 2km

132°00'E

1

Fig. 4. Observed horizontal density distribution in each layer, upper: 0-2 m, middle: 2-5 m, lower: 5m-bottom.

48l

DISPERSAL PATFERNS OF RED SEA BREAM JUVENILES

opposite shore. G20H juveniles released at point H were recaptured only near the release point, however. Horizontal and vertical distributions of water temperature, salinity and dissolved oxygen were also recorded in the bay at the time of release of the juveniles fish. Water temperature, salinity and density at station M showed a clear pycnocline at about 2 m depth (Fig. 3). Dissolved oxygen is super-saturated from the sea surface to 7 m depth, but is lower than 50% below 15 m depth. Released red sea bream juveniles did not move below 15 m depth from the SCUBA diving observation. This may be due to the concentration of dissolved oxygen being lower than 50%. The upper, middle and lower layers are defined as 0 - 2 m, 2 - 5 m and 5 m - b o t t o m , respectively. Horizontal distributions of density in three layers, which are calculated from water temperature and salinity, are shown in Fig. 4. Sigma t values less than 22.0 were found at the northern head of the bay in the upper layer, while the density was essentially uniform throughout the study area in the middle and lower layers (Fig. 4).

Numerical experiment

aw --

8z

=

-

v.

u

p=pog~+po B

(2)

joB d z

Po - P - g P0

(4)

OB 02B - - + v" VB = khV2V + 3t kz 0Z 2

3v poVz-~z = & c a [ W [ W

OB

-Kz Oz

poCp

0B

at, 1 --at + (v " V ) v +fKxv = - --Vppo

a2v + vhV2v + Vz az2 (1)

at z = 0

(6)

at z = 0

(7)

at z = - H

(8)

atz=-H

(9)

gaQ

--=0 Current and density fields in Nyuzu Bay were calculated to simulate the dispersion of red sea bream juveniles directly after the release. The basic equations which govern the current and density fields in the bay are as follows (Yanagi, 1989):

(5)

where v denotes the horizontal velocity; w, vertical velocity; V, horizontal differential operator; f , Coriolis parameter; K, vertical unit vector; P0, vertical average density; p, the pressure; v h, horizontal eddy viscosity; G, vertical eddy viscosity; g, the gravitational acceralation; ~, sea level height above the mean sea surface; B, the buoyancy; k h and kz, horizontal and vertical eddy diffusivity, respectively. The boundary conditions are given on the sea surface and at the bottom as:

0v VZ~z = c 0 1 v l v

Flow and density fields

(3)

az

where Pa denotes the density of air; Ca, the drag coefficient on the sea surface; W, wind vector; c 0, the drag coefficient at the bottom; a, heat expansion coefficient; Q, heat flux through the sea surface; Cp, specific heat under the constant pressure and H, water depth. The buoyancy flux from rivers Qr at P, Q and R (Fig. 1) are given as follows, Qr = ( B r - B ) R

(10)

TABLE 2 Harmonic constants of tide at Saiki Bay

Amplitude (cm) Phase lag (degrees)

M2

S2

51.9 175.9

23.0 201.4

K2 6.3 201.4

N2 9.5 174.2

KI 20.3 192.1

O1 16.0 161.7

PI 6.8 192.1

Q1 3.3 161.7

M4 0.6 189.0

MS4 0.7 10.0

482

T. YANAGI ET AL.

TABLE 3 Parameters used in the numerical experiment Ax : At = vh = vz = kh= kz = g= f = cd = ca = P0 =

Horizontal grid scale Time step Horizontal eddy viscosity Vertical eddy viscosity Horizontal eddy diffusivity Vertical eddy diffusivity Gravitational constant Coriolis parameter Bottom frictional coefficient Surface frictional coefficient Overall mean density Atmospheric density Heat flux Specific heat Heat expansion coefficient River discharge Wind speed

(cm) 120

= 1.2 ×

Q = 300 Cp = 0.932 a = 0.2 X

(m) (s) (cm2/s) (cm2/s) (cm2/s) (cm2/s) (cm/s 2) (l/s)

(g/cm 3) (g/cm 3) (cal/cm2/day) (cal/g/°C)

10 - 3

(I/°C) (cm3/s/cm)

10 - 4

P,Q,R=70 (Ua, Ca) =

(cm/s)

(200, O) where

B r denotes the buoyancy of river water,

and R the river discharge. The non-slip condition

1989

6

60 ~ I ~

-60 -12C

200 20 5.0 x 103 10 5.0 × 103 10 980 7.8 × 10 -s 2.6 × 10 -3 1.3 × 10 -3 1.0238

V

i

7

8

t i o n is g i v e n at t h e o p e n b o u n d a r y (Fig. 5). B e c a u s e t i d a l d a t a a r e n o t a v a i l a b l e for N y u z u Bay,

l

the estimated tidal variation was calculated from ten harmonic

constants

at Saiki B a y ( T a b l e 2,

Hydrographic Department, northern

end of Nyuzu

1985) w h i c h is at t h e Bay ( s e e Fig. 1). T h e

horizontal gradient of buoyancy across the open

Fig. 5. Estimated tidal variation at Nyuzu Bay which is given at the open boundary of the numerical model. Arrow shows the time of stocking.

a}

o f v e l o c i t y is g i v e n at t h e coast. T h e t i d a l v a r i a -

...::--

boundary

is a s s u m e d to b e z e r o in this e x p e r i -

ment. E q u a t i o n s (1) to (10) a r e a p p r o x i m a t e d by t h e

b)

Fig. 6. Maximum flood tidal current in the upper layer at 17:00 on 5 July (a) and maximum ebb tidal current in the upper layer at 0:00 on 6 July (b). Plus mark denotes the release point.

483

D I S P E R S A L P A T r E R N S O F R E D SEA B R E A M J U V E N I L E S

,ES,DU^LCo, ls~ F'O,~ ~ i ~ i ....

,ESIOU^~F'OW

J.....-..."'~':::::': ~1

: .....

,ES,O0^~ ~LOW

~, . - - _

: :_:_' '."_

I

Fig. 7. Residual flowin each layer. finite difference and solved by the semi-implicit method (Oonishi, 1978). The water column in the numerical model is divided into the three layers defined from field observation (Fig. 3). The horizontal grid size is 200 m × 200 m. The parameters used in this numerical experiment are given in Table 3. The dominant current in Nyuzu Bay is the tidal current. The calculated maximum flood tidal current in the upper layer occurred at 17:00 on 5 July and maximum ebb tidal current at 0:00 on 6 July (Fig. 6). The tidal current attains a velocity of about 40 c m / s in the upper layer at the mouth of the bay because the bay mouth is shallow (7 m to 10 m). However, the tidal current does not exceed 2 c m / s at the head of the bay and in the middle and lower layers. As for the long-term

DENSITY ~ ' ~

DENc~TIY

movement of juveniles, residual flow is also important as well as the tidal current. The residual flow is obtained by averaging the calculated current over 24 hours 50 minutes. The residual flow in the Seto Inland Sea consists of tide-induced residual current, wind-driven current and densitydriven current (Yanagi, 1989). The calculated residual flow is shown in Fig. 7. An outward flow of 5 to 10 c m / s occurs in the upper layer and an inward flow of several c m / s occurs in the middle and lower layers. The calculated density distributions (Fig. 8) agree well with the observed density distributions (Fig. 4). Therefore, even though there were no direct measurements of current in Nyuzu Bay, the calculated flow field is considered to adequately represent that in Nyuzu Bay.

DEN(~ITY/

UPPER~y~R [7~23.0

Fig. 8. Calculated horizontal distribution of density in each layer.

484

T. Y A N A G 1 E T A L .

Estimated movement o f red sea bream juveniles

avoidance. Based on visual observations, 40 mm juveniles occur near the bottom both in the daytime and at night. Based on the field observations using SCUBA diving and the tank experiment, the following behavioral characteristics were established for each fish group: (1) G40M: 40 mm juveniles occur between the bottom and 1 m off the bottom, moving at a speed of 1 / 4 of the water velocity in the daytime. That is, 40 mm juveniles swim against the flow with a speed of 3 / 4 of the water velocity. They do not move at night, but hide behind rocks or in hollow shells. (2) G20M and G20H: Half of the juveniles of 20 mm size fish (G20M-up and G20H-up) are between the sea surface and 5 m depth in the daytime and between the sea surface and 3 m depth at night. They move at the speed of the water velocity in the same direction of water flow throughout the day. That is, they are passive to the water flow. The other half of 20 mm fish (G20M-bot. and G20H-bot.) occur between the bottom and 3 m off the bottom, moving at a speed of 1 / 2 of the water velocity in the same direction with the water flow in the daytime. At night, they are distinguished

The E u l e r - L a g r a n g e method was used to track juvenile movements in the model. The position of a juvenile X , + 1 at time n + 1, which was at X , at time n, can be calculated by the following equation: X , + 1 = X , + u At + ( V u ) v At 2 + ws At + R

(11) where v denotes the calculated velocity including tidal current and residual flow; ws, the swimming velocity of juveniles; and R the dispersion due to turbulence. The third term

(VV)U At 2 denotes the effect of current shear. R is given by the following equation,

(12)

R = 3,Vr2 AtO

where 7 is the normal random number whose average is zero and whose standard deviation is 1.0; D, the dispersion coefficient. Figure 9 shows the results of a tank experiment with a depth of 2.5 m. At night, half of the 20 mm juveniles are in the surface layer and half at the bottom. In the daytime, half the 20 mm juveniles are in the subsurface layer and half are in the lower layer. We could not get such information for 40 mm fish because 40 mm fish could not be taken by net tows due to a large net

40mmT,L,

20mmT,L,

depth

depth

I

156

~0,2!2

o),2 o m

,q

I

1,)

NIGHT

i I

2,ol --""""

DAY

o1,0o NIGHT

DAY 01,80

2o~2,3 f

200

I

100

0

I

I

L

100

200

100

Number

o i

0

100 Number

Fig. 9. Vertical distributions of 20mmT.L. and40mmT.L, juveniles ofthe red sea bream in the daytime and at night in the tank experiment.

485

DISPERSAL PATTERNS OF RED SEA BREAM JUVENILES

between the bottom and 1 m off the bottom, moving at a speed of 1 / 6 of the water velocity in the same direction of water flow. Juveniles cannot move below 15 m d e p t h because of the oxygen-minimum there. In the laboratory experiment or restricted narrow space, red sea b r e a m as well as other fish swim against the current showing optkinetic response. However, in a field under relatively weak flow condition lower than a sustained speed, their response to current is quite different. According to our underwater observations after being released, some fish, e.g. almost all of G40M, sink rapidly to bottom and stay at the area near point of release. Thereafter, they move slowly in a school. Current is relatively weak at bottom and optical references such as sea glass and rocks are

abundant. Fish can move free or easily stay at any point. However they were transported gradually to some extent by an influence of current during fairly long time, e.g. several hours to one day. Therefore, we estimate the coefficient as one quarter in this case of G40M. Night diving revealed that 40 m m fish sleep in a oyster shell, etc. A part of released fish stayed at the surface and did not move to the bottom. These fish (G20M & H-up) are apparently 100% influenced by environmental current since there is no reference for station holding at surface. Some fish (G20M & Hbot.) showed intermediate pattern between G40M and G 2 0 M & H - u p . The transport coefficient of juveniles used in these numerical experiments is rather arbitrary but no data is available on a long term influence of current on the transport of juveniles in a field. It will be very important to

G20H-up

D

g

G40M

"" •

" "t'.~,

I-

Fig. 10. Calculated horizontal ditributions of stocked juveniles.

;.

"

486

T. Y A N A G I E T AL.

clear quantitatively the swimming ability of juveniles in a field. We conventionally divided 20 mm fish into two groups, i.e. G20-up and G20-bot., which were originally one group because they clearly separated into a surface group and a bottom one. Such grouping is due to the difference in developmental stages such as endocrinological conditions and body sizes. These two groups show quite different typs of behavior and distribution in a field. In the numerical simulation, 100 juveniles of 40 mm T.L. (G40M) and 20 mm T.L. (G20M-up and G20M-bot.) were released at point M and 100 juveniles of 20 mm T.L. (G20H-up and G20H-bot.) were released at point H at 13:00 on July 5. The best-fit calculated dispersions of red sea bream juveniles 3 days after the release are obtained with the dispersion coefficient of 105 cm2/s (Fig. 10). The calculated dispersion patterns of the three fish groups agreed with the observed distributions (Fig. 2). Juveniles of 20 mm T.L. (G20M-up and G20H-up) which are near the sea surface are transported out of the bay due to the combined effect of tidal current and outward residual flow. The reason why the numbers of marked fish are small in G20M-up and G20H-up groups is because many of them are transported out of the bay. On the other hand, most of juveniles of 40 mm T.L. (G40M)

G40M

[~

G40M

-

,

Discussion

The arbitrary and sensitive parameter which regulates the dispersion pattern of juveniles in these numerical experiments is the dispersion coefficient. The dispersion coefficient D of l0 s cm2/s used in these numerical simulations is rather large considering the horizontal grid size

[-~

105cm 2 / sec

•

and 20 mm T.L. (G20M-bot. and G20H-bot.), which are near the bottom, remain in the bay because of the combined effect of tidal current and inward residual flow. In summary, the calculated dispersa1 area of the G40M juveniles nearly coincides with that observed in the field (Fig. 2), but that of G20H-bot. and G20M-bot. juveniles is wider than the observed. We suggest that there is more predation by other fish on 20 mm fish than on 40 mm fish. The effects of predation are suggested by the difference in recapture rates of 40 mm and 20 mm fish. If we assume that the predation pressure was much higher at surface than at bottom and all fish of G20M-up and G20H-up disappeared during the three days after release, fitness between field observation and simulation results increase significantly; i.e. the observed distributions of G20M and G20H can be explained only by the simulation G20M-bot. and G20H-bot., respectively. The effect of predation is not included in this numerical simulation.

G40M

"! i'

LT:

Fig. 11. Calculated horizontal distribution of stockedjuveniles of 40 mm T.L. (G40M) in the cases of different horizontal dispersion coefficients.

DISPERSAL PATI'ERNS OF RED SEA BREAM JUVENILES

487

of 200 m. The empirical value of horizontal dispersion coefficient is estimated by the following equation (Okubo, 1974),

D = c. 14/3

(13)

where c is numerical constant and I the horizontal scale. From Okubo (1974), the dispersion coefficient for a horizontal scale 1 of 200 m is 2 × 103 cm2/s. The value of k h in this numerical experiment, 5 × 103 cm2/s, was determined from eqn. (13) considering the irregularities of geometry of Nyuzu Bay. The discrepancy between k h and D implies that the dispersion of juveniles is greater than that of molecules in sea water, and therefore of water temperature or salinity. The results of numerical simulations for G40M juveniles using various dispersion coefficients are shown in Fig. 11. The dispersion coefficient of 10 4 c m 2 / s results in too small a dispersal area while that of 106 cm2/s is too large compared to the observed dispersal area (Fig. 2). The small discrepancy between observed (Fig. 2) and calculated (Fig. 10) dispersal patterns of the G40M juveniles can be explained by active migration of the released fish. Predation pressure on released red sea bream, especially 20 mm fish, was estimated to be significant. Marked otoliths of 20 mm fish were found in stomachs of barracuda (Sphyraena japonica), redfin velvetfish (Hypodytes rubripinnis), black rock fish (Sebastes inermis), streaked goby (Acentrogobius pflaumi), gluttonous goby (Chasmichthys gulosus) and other species which were abundant in Nyuzu Bay. Approximately 80% of the Japanese barracuda caught on the day of release at point M ate an average of 5.6 individuals of the 20 mm red sea bream.

In our study we showed the feasibility of applying the numerical simulation model to the actual field releases. However, the results are preliminary since predation mortality needs to be incorporated into the simulation model would be a future subject for the quantitative analysis of post stocking survival of red sea bream.

Acknowledgments We express our sincere thanks to the staff of the Kamiura Branch of the Japan Sea Farming Association for their kind permission to use the data in the field experiment.

References Bartsch, J., Brander, K., Hearth, M., Munk, P., Richardson, K. and Svendsen, E., 1989. Modeling the advection of herring larvae in the North Sea. Nature, 340 (24): 632-636. Kuwada, H. and Tsukamoto, K., 1987. Otolith-tagging of the red sea bream larvae by Alizarin complex - I. Saibai Giken, 16 (2): 93-104. Hydrographic Department, 1985. Table of tidal harmonic constants. Maritime Safety Agency, Tokyo, 154 pp. Okubo, A., 1974. Some speculations on oceanic diffusion diagrams. Rapp. Pc. V. Renn. Cons. Int. Explor. Mer., 167: 77-85. Oonishi, Y., 1978. Numerical simulation in the coastal sea. In: Y. Horibe (Editor), Science of Ocean Environment. Tokyo Univ. Press, pp. 246-271. Tsukamoto, K., 1988. Otolith-tagging of ayu embryo with fluorescent substances. Bull. Jap. Soc. Sci. Fish, 54: 12891295. Tsukamoto, K., Kuwada, H., Hirokawa, J., Oya, M., Sekiya, S., Fujimoto, H. and Imaizumi, K, 1989. Size-dependent mortality of red sea bream, Pagrus major, juveniles released with fluorescent otolith-tags in News Bay, Japan. J. Fish Biol., 35: 59-69. Yanagi, T., 1989. Coastal Oceanography. Koseisha-Koseikaku, Tokyo, 154 pp.