Bigeye Tuna Cath Relative to Sea Surface Height Anomaly during El Nino and Indian Ocean Dipole Event in Eastern Indian Ocean

(1)

Bigeye Tuna Cath Relative to Sea Surface Height Anomaly during

El Nino and Indian Ocean Dipole Event in Eastern Indian Ocean

1. Introduction

The E astern Indian O cean region (4ºS -16ºS and 105ºE -120ºE ) has long been considered as an im portant area for pelagic fisheries in general and tuna fisheries in particular. The productive pelagic fisheries in this area are sustained through enhanced biological production due to seasonal coastal upwelling during southeast m onsoon season occur from June to S eptem ber (W irtky, 1962; P urba, 1995; S usanto et al., 2001; G aol et al., 2003). In 1973, PSB C orp. Ltd starting operated 3 units longliner 100 G T in E IO , but after 1974 total longliner increase to becom e 17 units. The dom inant catch are yellowfin (Thunnus albacares) about 61% and bigeye (Thunnus obesus) about 30 % respectively. S ince 1992, PS B C orp. Ltd. has been changed the type of longline to becom e depth long line, with hooks set at depth between 100 and 300 m eter, m ade the dom inant catch changed to becom e 73 % bigeye and 6 % bigeye tuna.

M any scientists have been conducted research to investigate the variability of E IO . They concluded that EIO is high variability, which influenced by the m onsoon system (W irtky, 1962; B irol and M orrow, 2001; S usanto et al., 2001), Indonesian through flow (ITF) (Bray et al., 1996; Fieux et al., 1996), clim atic phenom ena such as E l N ino S outhern O scillation (E N S O ) and Indian O cean D ipole M ode (IO D M ) (M eyers, 1996; S aji et al., 1999; W ebster et al., 1999; S hinoda et al., 2004). The variability of oceanographic conditions such as tem perature, salinity and dissolve oxygen will be playing an im portant role on distribution and availability of fish (S harp & D izon., 1978; S und et al., 1981). H anam oto, 1985 found that the optim um fishing layer of bigeye tuna are closed to tem perature between 10o and 15o C , where the isodepth in E IO are varieties from 200 m to 400 m .

S ince 1982/83 the extra E N S O occurred, the scientist’s interes to its im pact on m arine ecosystem rapid growth especially in P acific O cean. They conclude that clim ate variability was im pact on com m unity com position, species ubundance and distribution, recruitm ent level, and tropics structure (A rntz & R azona, 1990; Lehodey et al., 1997; Kim ura et al., 1997; S unchez et al., 2000; S ugim oto et al., 2001; G aol et al., 2002). R ecenly, M enard et al., (2007) base on the statistic data of Japanese longline fishery found strong association between tuna and clim atic series for the 4- and 5-yr periodic m odes i.e. the periodic band of El Nino signal propagation in Indian O cean. H igh total catch anom alies associated with low sea level height. D uring E l N ino and D M event occur negative sea surface height anom alies (SS H A )

Dr. Jonson Lum ban G aol

Departm ent of Marine Science and Technology, Faculty of Fisheries and M arine Science

Bogor Agricultural University, Bogor - INDO NESIA. (jonsonrt@ yahoo.com )

Ab stract

T he stu d y is aim e d a t un de rstanding the varia bility of se a su rface heig ht a nom aly (S S H A ) of E aste rn tro pical In dian O ce an (E IO ) an d assessing its im p act on big e ye tu na catchability. A nin e-ye ar (199 3-20 01) tim e serie s of S S H A d ata set are use d in this inve stig atio n. A six-ye ar d aily tuna fish ca tch data (19 97 -1 999 , a nd 20 04 -20 06 ) a nd a eigh t-six-ye a rs (1 99 3-2 00 0) m o nthly a verag e o f tu n a h ook rate is de rive d from a tu na fishing com pan y “P erikan a n S am o dra B esa r” (P S B ) C orp. Ltd. log books of 1 5-2 0 fishing ve ssels o pe rate d in E IO . D aily an d an eight-ye ar o f m o nthly m e an S S H A d erive d from d ata base of C olora do C enter of A stro d yn am ics R ese arch a nd N A S A -P O E T -JP L resp ectively. T he S p ectrum a nalysis of S S H A an d H R a nom aly sho ws there are tw o dom in ant sig nals a re represe ntation of th e ann ual a n d inter-a nn ual varia bility. S ig nifica nt in tera nn ual va ria bility o f S S H A is influ en ced E l N in o S outhe rn O scillation (E N S O ) an d In dia n O cean D ipole m o de (IO D ). D uring E N S O a n d IO D event, S S H A n ega tive in IO D corresp on din g to sh allo w therm o cline dep th a nd e nha nching up welling stren gth . T h e M o nte C arlo a n alysis sho w s tha t the relationship be tw een o f the highe st ho ok rate an d ne gative S S H A is significan t espe cially in latitud e o f 1 3oS , wh ere tun a fishing grou nd concentrated. T h e de pth of the rm oclin e b ecom e sh allo wer an d e nh anchin g up welling m ig ht have co ntribu ted to increase the big e ye tu na catchibility b y providin g suita ble am bie nt tem perature a nd fee ding grou nd.

2. Data

Our study focused in EIO geographically 10

o

S-16

o

S and 105

o

E-120

o

. We used a nine-year (1993-2001) time series

of SSHA data set are used in this investigation. A six-year daily tuna fish catch data (1997-1999, and 2004-2006) and a

eight-years (1993-2000) monthly average of tuna hook rate is derived from a tuna fishing company “Perikanan Samodra

Besar” (PSB) Corp. Ltd. logbooks of 15-20 fishing vessels operated in EIO. Daily and an eight-year of monthly mean

SSHA derived from data base of Colorado Center of Astrodynamics Research and NASA-POET-JPL respectively. Bigeye

tuna catch index (hereafter referred to as for HR) calculated from bigeye tuna catch divided 100 hooks of long line. We

computed a catch rate (HR) which aggregated 1

o

x 1

o

grid area (Fig 1).

Indian Ocean

INDONESIA

EIO

Indian Ocean

INDONESIA

EIO

-250 -200 -150 -100 -50 0 50 100 150 200

J M M J S N J M M J S N J M M J S N J M M J S N J M M J S N J M M J S N J M M J S N J M M J S N

S

H

A

(m

m

)

-0.6 -0.4 -0.2 0 0.2 0.4 0.6

H

o

k

R

a

te

A

n

o

m

a

ly

SSHA HRA r = -0.32

-300 -200 -100 0 100 200

S

H

A

(m

m

)

-6 -4 -2 0 2 4

S

O

I

SSHA SOI r = 0.39

-6 -4 -2 0 2 4

r = 0.38

S

O

I

-0.6 -0.4 -0.2 0 0.2 0.4 0.6

H

o

k

R

a

te

A

n

o

n

a

ly

SOI HRA

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

H

o

k

R

a

te

-300 -200 -100 0 100 200

S

H

A

(m

m

)

HR SSHA

1993 1994 1995 1996 1997 1998 1999 2000

-250 -200 -150 -100 -50 0 50 100 150 200

S

H

A

(m

m

)

-0.6 -0.4 -0.2 0 0.2 0.4 0.6

H

o

k

R

a

te

A

n

o

m

a

ly

SSHA HRA r = -0.32

-300 -200 -100 0 100 200

S

H

A

(m

m

)

-6 -4 -2 0 2 4

S

O

I

SSHA SOI r = 0.39

-300 -200 -100 0 100 200

S

H

A

(m

m

)

-6 -4 -2 0 2 4

S

O

I

SSHA SOI r = 0.39

-6 -4 -2 0 2 4

r = 0.38

S

O

I

-0.6 -0.4 -0.2 0 0.2 0.4 0.6

H

o

k

R

a

te

A

n

o

n

a

ly

SOI HRA

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

H

o

k

R

a

te

-300 -200 -100 0 100 200

S

H

A

(m

m

)

HR SSHA

1993 1994 1995 1996 1997 1998 1999 2000

Fig 1. Area of study and spatial distribution of yearly average bigeye tuna HR (the biggest, medium, and small circles

shows the area with high, moderate, and low frequency of HR > 0.8 respectively).

(a)

(b)

(c)

(D)

(e)

(f)

Fig 2. (a) The time plot of monthly mean of SSHA and HR for 1993-2000, (b) SSHA and SOI, (c) SSHA and HR anomaly,

(d) SOI and HR anomaly, (e) spectral analysis of SSHA, and (f) spectral analysis of HR anomaly.

3. Result

Spectral analysis of monthly mean HR of Bigeye tuna and SSH anomaly during 1993-2000 shows two dominant

signals are represented of annual and inter-annual variability (Fig 2). Annual variability of sea level in EIO is influenced

by monsoon system, lower sea level during seasonal upwelling correspond to southeastern (SE) monsoon (Bray

et al

.,

1996; Susanto

et al

., 2001). Such SSHA extremes (negative) correspond well with the duration of intense phase of IOD

and ENSO (1996; Saji

et al

., 1999; Webster

et al.,

1999; Murtugudde

et al

., 2000; Susanto

et al.,

2001).

Bigeye tuna HR is higher during SE monsoon is corresponded to seasonal upwelling. During ENSO and IOD event

(1992, 97, and 98), HR tend to increase except in 1994. Relationship between monthly mean HR anomaly and SOI

shows negative correlation with SOI negative, HR is increased. Menard

et al

., (2007) has reported strong association’s

tuna and climate series for the 4- and 5-years mode, i.e. the periodic band of the El Nino propagation in Indian Ocean.

Since shallow thermocline and feeding ground for tuna during El Nino and IOD-induced upwelling can increase the catch

rate of bigeye using long line gear.

Hook rate > 1.5

Des-97

(a) (b)

(c) _(d)

Hook rate > 1.5 Hook rate > 1.5

Des-97 Des-97

(a) (b)

(c) _(d)

Sea level and thermocline depth are negatively correlated

over the Indian Ocean, with low sea level corresponding to

shallow thermocline depth and vice versa (Bray

et al

., 1996;

Susanto

et al

, 2001; Yu, 2003). In area where SSHA is lower,

the optimum depth for fishing is shallower so that hooks can

reach swimming layer of bigeye and catchability increased.

Upwelling processes around tuna fishing ground improves and

enhance the fertility of waters since nutrient increases. That

area has higher productivity and food is responsibility for tuna

abundance. Tuna are expected to be plentiful in upwelling

area because the micronecton, unless the waters too cool or

turbid (Sund

et al

., 1981).

HR >1.5

Fig 3. Oceanographic param eters anom aly in Eastern Indian

O cean in 1997 El Nino and IOD event. (a) chlorophyll-a

distribution, (a) overlay of tuna catch (HR) on sea surface

height anom aly, (c) XBT stations, (d) vertical section of

tem perature (Decem ber 1997).

Fig 4. Oceanographic parameters anomaly

in EIO during normal condition.

Fig. 5. Hovmuller plot of SSHA and daily

tuna hook rate (1997-1999) around of -13

o

S

4. Discussion

Bigeye tuna is a highly migratory fish. The predominant bigeye tuna daytime distribution was between 220 and 240 m, whereas the predominant nighttime depth was 70 and 90 m (Hollan et al., 1990). Temperature and thermocline depth seem to be the main environmental factors governing the vertical and horizontal distribution of bigeye tuna. Bigeye tuna were taken in waters ranging widely in temperature from 9 oC to 28 oC. However, the optimum of temperature for fishing ranges between 10oC and 15oC (Hanamoto, 1985). The depth of isotherm 10oC and 15oC (IT10o-15o) in EIO are varieties

from 150 to 400 m, whereas in fishing ground area from 200 to 400 m. The PT. PSB tuna long line gear is normally set so that the hooks reach depths of 100 to 280 m. There fore, finding the depth of IT(10o-15o) less than 280 m, the maximum

depth of hook is very important for setting longline.

Fig 3 shows an example result of overlay between SSHA and HR of bigeye tuna in EIO. The HR > 1.0 concentrated in the front between SSH positive and negative. During El Nino and IOD event, upwelling extended both in time and space in EIO (Susanto et al., 2000). Occurrence of cyclonic and anti-cyclonic eddies might also have contributed to increase of catchability by providing suitable ambient temperature and feeding grounds for bigeye. Catch rate of bigeye tend to increase around area with SSHA negative (Fig 5). The Monte Carlo analysis between SSHA and HR shows the significant correlation between SSHA negative and HR >.1.5 around area of -13oS where tuna fishing vessels concentrated.

Acknowledgements.

We thanks the Colorado Center for Astrodymanics Researh (CCAR) and my suvervisor (Dr. Robert Leben),

University of Colorado at Boulder for the research facilities for processing altimeter data. This work was undertaken during the tenure of

Partnerships Ocean Global Observation Observation (POGO) Fellowship to principal author.

5. Conclusion

Variability of SSHA in EIO influenced both of SE monsoon and El Nino and IOD. During El Nino and IOD event, upwelling

extended in time and space. Since shallow thermocline during El Nino and IOD-induced upwelling enhance the fertility of

waters can increase the catch rate of bigeye using long line gear.

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