the estimation of bigeye tuna (thunnus obesus, (lowe, 1839 ... · the catch in benoa port mainly...
TRANSCRIPT
Available online at www.worldscientificnews.com
( Received 30 October 2018; Accepted 18 November 2018; Date of Publication 30 November 2018 )
WSN 115 (2019) 1-14 EISSN 2392-2192
The estimation of bigeye tuna (Thunnus obesus, (Lowe, 1839)) fishing season in the East Indies
Ocean which is disembarked in Benoa Port, Bali
Arsa Dipanoto*, Mega L. Syamsuddin, Zuzy Anna, Izza Mahdiana A.
Faculty of Fisheries and Marine Sciences, Universitas Padjadjaran, Indonesia
*E-mail address: [email protected]
ABSTRACT
Prediction about fishing season is needed for fishing operation, so it can help fisherman to catch
a big number of fish with effective and efficient. This study was started on May – June 2018. This study
aimed to analize fishing season pattern of big eye tuna in Indian Ocean. Historical data about fish
production and fishing effort of long line vessel for 5 years (2013-2017) collected from Indonesia Tuna
Longline Asociation (ATLI) in Benoa Port, was used to calculate monthly CPUEs which were then
analyzed using average percentage methods to obtain fishing season index for each month and sea
surface temperature (SST) data collected from satellite. The result shows that big eye tuna can be caught
along the year, but there was a pattern that fishing season occurs from June – September, December,
and April with the peak season in east season. Optimum distribution of sea surface temperature base on
big eye tuna’s fishing ground ranged from 27-27.5 °C.
Keywords: Bigeye Tuna, Fishing Season, SST, Indian Ocean, Thunnus obesus
1. INTRODUCTION
Indonesian waters, particularly the Indies ocean, have great potential because of its vast
oceanic wealth, especially with its big pelagic fishes (Amandè et al., 2012). Benoa Port is the
World Scientific News 115 (2019) 1-14
-2-
biggest port in Bali province, which is directly connected to the Indies Ocean. Benoa Port has
fishing areas which is also a place for tuna debarkation in Indonesia.
Tuna, specifically the bigeye tuna, is a big pelagic species commercial target and a
valuable species in the longline tuna fishing that operates in the Eastern Indies Ocean (ISSF
2012 in Nurdin 2012). Indonesia’s Bigeye tuna production reached 34,259 tons in 2013 (Indies
Ocean Tuna Commission, 2015). The bigeye tuna deployment follows the fish migration path,
one of which is affected by temperature. The migration path that is based on the temperature
includes South Sumatera waters, Southern Java, Bali, Nusa Tenggara, and Banda Ocean.
Bigeye tuna fishing rate is still below the amount of the allowed potential. Therefore, it
is necessary to increase effort so that the fishing rate will increase. The knowledge of fishing
season patterns is needed in order to increase bigeye tuna productivity. This is also a way in an
effort of sustained fishing so that the bigeye tuna potential lasts and its utilization will not
exceed the allowed fishing rate. Information about bigeye tuna fishing season is not common
in research. Therefore, it is deemed necessary to estimate the bigeye tuna fishing season in the
Eastern Indies Ocean based on the amount of catch that is disembarked in Benoa Port and ocean
surface temperature distribution.
Photo 1. Thunnus obesus (Lowe, 1839)
2. MATERIALS AND METHODS
This research was conducted in the waters of Indian Ocean with fishing base in Benoa
Port, Bali which will be carried out in April – May 2018. Benoa port is a location to take
production of big eye tuna and catching effort data. This research is conducted in 2 phases,
which is data gathering and data processing, respectively. This research used survey with
descriptive analysis which includes direct data gathering (in-situ) and visual analysis of satellite
images (ex-situ). The in-situ data includes the bigeye tuna fishing rate and the fishing trip rate
of Benoa port, while the ex-situ data includes the image of ocean surface temperature (OST)
from MODIS image detection satellite using Aqua sensor (MODIS-Aqua)
World Scientific News 115 (2019) 1-14
-3-
Figure 1. The Research Site Map
The obtained data was analyzed using the catch per unit effort (CPUE) (Gulland, 1983,
in Edmond, 2017), and the fishing season patterns. The fishing pattern is obtained by calculating
the average percentage based on the time series analysis (Spiegel, 2016), and both of the
analysis are connected. According to Purwasasmita (1983), the fishing season analysis used the
following procedure:
1. Calculate the CPUE value per month
CPUEi = 𝐶(𝑖)
𝑓(𝑖)
2. Calculate the monthly average of CPUE in a year
m
i
iUm
U1
1
where: Ū = CPUE monthly average in a year
Ui = CPUE per month (ton/trip)
m = 12 (the number of months in a year)
World Scientific News 115 (2019) 1-14
-4-
3. Calculate the ratio of Ui to Ū
U
UU i
p × 100%
where: Up = Ratio of Ui to Ū
4. Calculate the season index
IMi =
t
i
pUt 1
1
where: IMi = ith Season Index
t = the sum of year from the data
5. If the IMi is not 1200% (12 month × 100%), then an adjustment is required by using
the following formula:
IMSi =
m
i
iIM1
1200× IM
where: IMSi = The Adjusted ith Season Index
6. While calculating, if the Up has an extreme value, then the Up value is discarded from
the Season Index (IM) calculation, and the IM median (Md) will be used as a substitute. If the
Md is not 1200%, then an adjustment is required by using the following formula:
IMMdSi =
m
i
iMd1
1200 × Mdi
where: IMMdSi = The Adjusted ith Season Index median
7. If the IM is more than 1 (>100%) or greater than the average value, then it is fish season,
and if the IM is less than 1(<100), then it is not. Lastly, If the IM is equal to 1
(= 100%), then it is in a normal or balanced state.
The monthly sea surface temperature data that has the same period with the bigeye tuna
fishing period is obtained from MODIS Aqua sensor with a spatial resolution of 4 km. The data
are then combined (overlay) with the fishing ground coordinates from the fishing logbook. The
results of the data are analyzed descriptively to identify the correlation between temperature
distribution with bigeye tuna productivity in the Eastern Indies Ocean.
World Scientific News 115 (2019) 1-14
-5-
3. RESULTS
3. 1. Temperature Distribution Analysis in The Indies Ocean
Temperature is an oceanographic factor that affects fishing rate. Weilan (2013) stated that
a low or high temperature will affect the fishing productivity. Every fish will adjust with the
temperature that is ideal to its metabolism.
In this research, the temperature distribution is divided into each season, this is done to
identify the best season that has the ideal temperature to fish bigeye tuna. Indonesian waters are
highly related with ENSO and affected by the west monsoon or wet season which occur from
December to February, followed by the transitional season I from March to May, whilst the east
monsoon or dry season occur from June to August followed by the transitional season II from
September to November (McBride and Nicholls 1983; Haylock and McBride 2003; Hendon
2003).
Overall, the temperature distribution of Indies Ocean surface is within the range of 24-30
°C. In the east monsoon (June-August) from 2013 to 2017, the temperature is relatively warm
in the western offshore ranging between 28-29 °C. Upwelling occurs at the coastal area in east
monsoon, such as the one that occurred in 2015. Therefore, the temperature tends to be colder
and ranging between 24-25 °C (Pictured in Figure 2). East monsoon has a colder Ocean Surface
Temperature (OST), this is due to the water current from Eastern Australian waters flows into
Indonesian waters. Based on these, the season indicates that it is the ideal season for tuna
distribution because of the temperature distribution that tends to be low offshore.
The OST in the early transitional season II is seen to be affected by the east monsoon,
and as the transitional season II approaches the end (November), the temperature gradually
increases. The warm temperature in transitional season II ranges between 29-31 °C, which
generally distributed in the eastern offshore (Pictured in Figure 3), and in coastal area, it tends
to be colder with the temperature ranging between 25-28 °C. This is due to the upwelling, as
stated in a research by Goela (2016), that is, upwelling causes the ocean surface having lower
temperature.
In the west monsoon from 2013 to 2017, the OST in Indies Ocean ranges between 24-35
°C. The OST distribution of west monsoon is relatively warmer. This warmer temperature
spreads across the eastern offshore and ranging between 28-32 °C, and the lower temperature
spreads across the western waters and ranging between 25-27 °C (Pictured in Figure 4). The
warmer OST in the western season could be caused by the effect of the west monsoon which
moves to southeast and bringing warmer current temperature. The uneven low temperature is
affected by the South Equatorial Current (SEC) which then causes upwelling.
Entering the transitional season I, that is the transition from west monsoon to east
monsoon, causes the OST starting to decrease. The current moving from the west near the
equator, that occurred in this season, causes the water temperature to be warm although the
degree keeps decreasing.
The temperature in this season ranges between 26-34 °C (pictured in Figure 5). The warm
temperature in this season spreads more on the eastern offshore (28-30 °C), and colder
temperature spreads on the western waters, with the exception in May of 2005 and 2017 which
is indicated to have upwelling in the coastal area.
World Scientific News 115 (2019) 1-14
-6-
Figure 2. The Ocean Surface Temperature (OST) Distribution in East Monsoon in 2013-2017
World Scientific News 115 (2019) 1-14
-7-
Figure 3. The Ocean Surface Temperature (OST) Distribution in Transitional Season II
in 2013-2017
World Scientific News 115 (2019) 1-14
-8-
Figure 4. The Ocean Surface Temperature (OST) Distribution in West Monsoon
in 2013-2017
World Scientific News 115 (2019) 1-14
-9-
Figure 5. The Ocean Surface Temperature (OST) Distribution in Transitional Season I
in 2013-2017
World Scientific News 115 (2019) 1-14
-10-
3. 2. Bigeye Tuna Production Analysis in Benoa Port, Bali
The catch in Benoa Port mainly consists of tuna, one of which is the bigeye tuna.
swordfish, cakalang (skipjack tuna), escolar and squid are other types of catch in Benoa Port.
The catch of bigeye tuna in Benoa Port for 5 year period (2013-2017) based on the data below
showed a fluctuating result every month (Pictured Below).
Figure 6. The Fluctuating Pattern of Monthly Bigeye Tuna Catch from 2013-2017
in Benoa Port
The highest bigeye tuna catch is in July 2013, with the total of 318 tons, whilst December
2017 has the least bigeye tuna catch with the total of 31 tons. Syamsuddin (2016) stated that
the highest fishing rate occurred between June – August, which meant that the catch rate is also
the highest in those months. The fluctuation of the bigeye tuna production is caused by a few
factor which include the fish availability, the fishing effort, the fishing success rate, the number
of manpower, the duration of fishing, and climate changes (Cheung 2010). The bigeye tuna
production tends to be higher at mid-year (east monsoon), this indicates that the mid-year has
suitable temperature for the tuna’s metabolism.
From the data shown above, the year 2013 has the highest catch rate of 2,214,126 kg and
2017 has the lowest catch rate of 755,888 kg. This decreasing trend could be caused by the trip
rate that also decreases each year. This is because the fishing effort affects the results of catch
rate as stated before.
The bigeye tuna fishing effort by the fishermen in Benoa Area include using the ship with
an array of long line. The size of the ship used in Benoa is between 30 GT (Gross Tonage) to
200 GT. From 2013-2017, the total fishing effort in Benoa is 9097 trip. As the catch rate, the
highest fishing effort occurred in July 2013 with the total of 383 trips and the lowest fishing
effort occurred in December 2017 with the total trip of 29 trips.
The fishing effort fluctuation is affected by a few factor such as the increasingly further
fishing ground potential, and climate changes affected the fishermen decision to make a trip.
-
50 000
100 000
150 000
200 000
250 000
300 000
350 000
BIG
EYE
TU
NA
CA
TCH
(KG
)
2013 2014 2015 2016 2017
World Scientific News 115 (2019) 1-14
-11-
In addition, according to The Association of Tuna Longline Indonesia (ATLI), the
number of longline fleet decreases each year in the 5-year period. This, in turn, also decreases
the fishermen fishing effort.
The bigeye tuna catch and effort catch data is used as the reference data to determine the
Catch Per Unit Effort (CPUE) per month (kg/trip) in the 5-year period. The CPUE Analysis
showed that there is a correlation between the increase and decrease of the catch with the fishing
effort. The highest CPUE is in April 2016 with the rate of 2013 kg/trip and the lowest is in
March 2014 with the rate of 441 kg/trip. This is because in 2016, the fishing effort rate tends to
be low which increases CPUE, and vice versa in 2014, which has a pretty high fishing effort
rate which decreases the catch per trip.
Potier and Boely (1990, in Apriliani, 2018) stated that fishing is affected by season and
the water environmental conditions. In this research, the highest CPUE occurred in eastern
season (east monsoon). This confirms by Rochman et al. (2017) that stated eastern season has
the highest CPUE for bigeye tuna because the climate changes causes relatively low tide and
currents, which in turn causes the longline fleet to operate more often.
3. 3. The Bigeye Tuna Fishing Season Pattern
The estimation of bigeye tuna fishing season in Eastern Indies waters was based on the
average of monthly fishing effort (2013-2017). The obtained season pattern will refer to the
catching season index (IMP) calculation. Based on the IMP, it can be seen that bigeye tuna
fishing can be done throughout the year. However, fishing season mostly occurred in eastern
season. The seasonal pattern can be seen in Figure 7.
Pictured below, the fishing season occurred in April, June, July, August, September, and
December. The non-fishing season, occurred when the IMP is less than 100%, is in January,
February, March, May, October, and November.
Figure 7. Bigeye Tuna Fishing Season Index Pattern in Indies Ocean Waters
The graph above indicates that the indices are higher in the eastern season, this confirms
Nurani et al. (2012) research that showed the tuna fishing season peak in the southern waters
106,77 107,22
114,8
107,58
115,45
107,22
80
90
100
110
120
1 2 3 4 5 6 7 8 9 10 11 12
SEA
SON
IND
EX
MONTH
THE FISHING SEASON INDEX
IMP IMP = 1
World Scientific News 115 (2019) 1-14
-12-
of Indian Ocean occurred in June and July, which is in the eastern season as evidence by the
large number of catches. The results obtained from this research is consistent, this is shown by
the highest CPUE is in the eastern season and fishing season mostly occurred in the eastern
season, as well.
Based on the calculation of bigeye tuna catch data, fishing season mostly occurred in the
eastern season. The temperature distribution in said season is relatively low and ranging
between 24-30 °C. Based on the fishing location which are 30 coordinates obtained from the
fishing logbook, with August to November 2016 came from KM Surya Terbit – 169 and KM
Sari Dewata – 1 which is based in Benoa Port Bali (Pictured in Figure 8), the ideal temperature
distribution to fish bigeye tuna ranges between 27-27.5 °C. This temperature range confirms
Syamsuddin et al. (2013) research that showed bigeye tuna is mostly fished in waters with a
temperature between 24-27.5 °C (Pictured in Figure 9). The logbook data showed that the
bigeye tuna fishing are is wider in August with the average temperature distribution of 27 °C.
Figure 8. The Bigeye Tuna Fishing Map in August (a), September (b), October (c), and
November (d) 2016 in the Eastern Indies Ocean Waters
World Scientific News 115 (2019) 1-14
-13-
Figure 9. The Ideal Temperature Distribution from August to November 2016 in the Eastern
Indies Ocean Waters
4. CONCLUSION
The bigeye tuna fishing activity in the Indies Ocean peaks at eastern season, specifically
in July and September. The ideal ocean surface temperature distribution in the Eastern Indies
Ocean based on the location of bigeye tuna fishing ranges between 27-28°C, this range is also
the temperature distribution in bigeye tuna fishing season.
ACKNOWLEDGEMENT
The authors would like to thank the NASA for the SST data and Benoa Port for catching of big eye tuna data.
References
[1] Amandè, M. J., Chassot, E., Chavance, P., Murua, H., de Molina, A. D., & Bez, N.
2012. Precision in bycatch estimates: the case of tuna purse-seine fisheries in the Indian
Ocean. ICES Journal of Marine Science, 69(8), 1501-1510.
[2] Apriliani I. M., Nurrahman Y. A., Dewanti L.P., Herawati H., 2018. Determination of
Potential fishing ground for hairtail (Trichiurus sp.) fishing based on chlorophyll-a
distribution and sea surface temperature in Pangandaran waters, West Java, Indonesia.
AACL Bioflux. 11(4): 1047-1054.
[3] Cheung, W.W.L., Lam, V W.Y., Sarmiento, K.L., Kearney K., Watson, R., Zeller, D.
2010. Large Scale Redistributium of Maximum Fisheries Catch Potential in The Global
Ocean Under Climate Change. Global Change Biology. 16(1): 24-35
0
5
10
15
20
25
27 - 28 °C 28.5 - 29 °C 29.5 - 30 °C
Tem
per
ature
Ideal Temperature Distribution
World Scientific News 115 (2019) 1-14
-14-
[4] Edmond, S., Azonningbo, S. H. W., Fiogbe, E. D. 2017. Growth, Mortality Parameters
and Exploitation Rate of West African Ilisha (Ilisha africana Bloch, 1795, Clupeidae)
off Benin Coastal Waters (West Africa): Implications for Management and
Conservation. Open Journal of Marine Science, 7(3): 327-342.
[5] Goela, P.C., Alice, N. 2016. Time Series Analysis of Data for Sea Surface Temperature
and Upwelling Component from The Southwest Coast of Portugal. Journal of Marine
System Vol. 163, 12-22
[6] Haylock M., McBride J.L. 2003. Spatial Coherence and Predictability of Indonesian
Wet Season Rainfall. Journal of Climate 14, 3882-3887.
[7] Hendon H. 2003. Indonesian rainfall variability: impacts of ENSO and local air-sea
interaction. Journal of Climate 16: 1775-1790.
[8] [ISSF]. International Seafood Sustainability Foundation. 2012. ISSF stock status
ratings-2012; status of the world fisheries for tuna. Technical Report 2012-04, United
Stated of America.
[9] [IOTC]. Indian Ocean Tuna Commission. 2015. Indonesia National Report to The
Scientific Committe IOTC [Internet]. Victoria (SC): IOTC
[10] Nurdin, E., Muhamad F. A. S., Roza Y., Mulyono S.B. 2016. Growth and mortality
parameters of yellowfin tuna (Thunnus albacares) in Palabuhanratu waters, west Java
(eastern Indian Ocean). AACL Bioflux. Vo. 9(3): 741-747
[11] Nurani, T. W., Prihatin, I. W., Sugeng H. W., Risti E. A., Soraya G. 2016. The
Dynamics of Fishing Season and Tuna Fishing in The Indian Ocean (FMA 573).
International Journal of Development Research. Vol. 6 No. 7: 8288-8294
[12] Rochman, F., Bram S., Arief W. 2017. Standardizing CPUE of Albacore Tuna on Tuna
Longline Fishery in Eastern Indian Ocean. Indonesia Fisheries Research Journal Vol
23(1): 29-38.
[13] Spiegel, L. A. 1961. Diorder and Consolidation in Adolescence. ICES Journal of the
American Psychoanalytic Association, 9 (3): 406-416
[14] Syamsuddin, M. L., Saitoh, S. I., Hirawake, T., Bachri, S., & Harto, A. B. (2013).
Effects Of El Nin͂o-Southern Oscillation Events On Catches Of Bigeye Tuna (Thunnus
Obesus) in the Eastern Indian Ocean off Java. Fishery Bulletin NOAA , 111: 175-188,
doi 10.755/FB.111.2.5
[15] Syamsuddin, M., S. Saitoh, T. Hirawake, F. Syamsudin, M. Zainuddin. 2016.
Interannual variation og bigeye tuna (Thunnus obesus) hotspot in the eastern Indian
Ocean off Java. International Journal of Remote Sensing, 1-14 p, DOI:
10.1080/01431161.2015.1136451
[16] Weilan, K., Karen, E., Ming-an, L. 2013. Effect of climate variabilitiy on the
distribution and fishing conditions of yellow tuna (Thunnus albacares) in The Western
Indian Ocean. Journal Climate Change 19: 63-77