Information about Yellowfin Tuna fishing grounds is needed to develop the capture fisheries sector, which could be obtained through satellite multi-sensor mapping techniques. Fishermen often have difficulty determining where the fish are and when they can be caught in abundance. Knowing this information would sufficiently reduce operating costs. Mapping the fishing ground of Yellowfin Tuna would also avoid overfishing due to the concentration of fishing boats in one particular location, thus allowing the operation to be more effective and efficient.

The long-term aim of this research is to improve the welfare of fishermen in the Wakatobi district, Southeast Sulawesi, while the short-term goal is to map the fishing ground of Yellowfin Tuna (Thunnus albacares) with the application of multi-sensor satellite technology to detect upwellings. The benefits of this research are cost savings for the fishermen and providing a reference for the arrangement of management strategies of Yellowfin Tuna (Thunnus albacares) for sustainablity and continuity.

This study indicated that the average sea surface temperature in the west was 29.79°C, in the west-east an average of 29.70°C, in the east an average of 27.40°C and the east-west an average of 29.13°C. Chlorophyll-a in both the west and the west-east averaged 0.15 mg m−3, in the east 0.27 mg m−3 and in the east-west 0.21 mg m−3. High temperatues started in December and continued until February in the Wakatobi region, which moved from west to east.

Low temperature moved from east to west from June until August. Fronts occured arround Kaledupa and Koromaha reef in December, January and February, as well as in March, April and May around Kaledupa reef and Runduma Island. In June, July, August, September, October and November fronts were observed around Kapota reef, Kaledupa reef, Koromaha reef and Koka reef. Upwelling occured in Kapota reef, Kaledupa reef and Koka reef in June, and in July and August around Runduma Island, Kapota reef, and Kaledupa reef. Furthermore, upwelling in Kapota reef, Wangi-wangi Island, and Kaledupa reef was observed in September.

Introduction

Mapping of Yellowfin Tuna fishing grounds is needed for the development of the fisheries sector in Wakatobi district, Southeast Sulawesi. Fish resources have the potential to be developed for increasing the catch (Tadjuddah, 2007). Skipjack and tuna fishing in Wakatobi Islands are estimated to yield 3–4 tons per day which is on-going throughout the year (PPT-COREMAP LIPI, 2002). If this resource is not managed properly, it could lead to negative impacts on the sustainability of fish resources in the future. Determination of the fishing ground of Yellowfin Tuna in the Wakatobi waters has been done by local fishermen by using traditional methods, such as observation of the sea birds flying and swooping nearby and the appearance of dolphins to the surface. This knowledge is acquired by generation to generation. The downside of this method can result in overfishing due to concentration of fishing activity in only certain locations. Until now, there were many constraints on fishing activity. For instance, the fisherman could not rely on high catch yield which they would be able to do using identified potential fishing grounds and thus their livelihood become uncertain. Further consequences were loss of fuel, time and labour of fishermen. Finding solutions to these problems are paramount (Zainuddin et al.,2006).

Tropical tuna movements can be observed from space; tuna distribution can be predicted based on their behavior (Stretta, 1991). Knowledge base is used for assessment of a relationship between fish species and their environmental factors. Results of this analysis will be obtained as oceanographic indicators suitable for certain fish. As an example, Thunnus albacore in the sea north of the Pacific, tend to be concentrated in the temperature range from 18.5 to 21.5°C and are associated with chl-a levels of 0.3 mgm−3 (Zainuddin et al., 2006). Furthermore, the output obtained from oceanographic indicators corresponds to the distribution and abundance of fish mapped with GIS technology. Oceanographic data indicators that are suitable for fish need to be integrated with various layers in the GIS, because the fish are very likely to respond to the various parameters that are interrelated.

Mapping of fishing ground with the application of multi-sensor satellite technology and upwelling could be used by locals precisely as a direction to avoid overfishing. Furthermore, it may formulate the sustained and sustainable management plan of Yellowfin Tuna capture. Therefore, the aims of this study were to map the fishing ground of Thunnus albacares using remote sensing and GIS technologies with indicators such as thermal fronts, upwelling and fish behavior.

Materials and methods

Research location and time

This research was conducted in Wakatobi Marine National Park, Southeast Sulawesi Province from 5°12′–6°10′ S and 123° 20′–124° 39′ E, during June until October, 2009 (Figure 1).

Materials and equipment

Materials used in this study

  • (1) Sea surface temperature (SST) data from MODIS satellite, In 2004–2008, weekly data, level 3, 4 km resolution, Source: (Ocean color) http://www.modis.gsfc.nasa.gov. Accessed 2009.

  • (2) Chlorophyll-a data from MODIS satellite, In 2004–2008, weekly data, level 3, 4 km resolution, Source: (Ocean Color) http://www.modis.gsfc.nasa.gov. Accesssed 2009.

  • (3) Sea Surface Height (SSH) data from Topex-Poseidon satellite, In 2004–2008. Source: http://www.ccar.colorado.edul

  • (4) Currents pattern data from survey Wyrtki (1961).

Tools used in this study

  1. (1) SeaDAS 4.7 by using Linux UBUNTU, the image of SST, SST contour, the image of chlorophyll-a, Arc-view 3.2 for mapping of fishing ground.

  2. (2) Map of Wakatobi waters no. 317. (Source: Dishidros TNI-AL Scale: 1:200.000 as a base map

  3. (3) Camera for documentation.

  4. (4) GPS (Garmin III Plus), to determine the position of fishing ground. For more details regarding framework of research see below (Figure 2).

Data analyzing methods

Sea surface temperature analysis

The images selected were processed by considerations cloud-free image which was weekly data collected over five years (2004–2008) in 145 images. SST image is grouped by seasonal variation, which is represented by 34 images from west season (December, January, February) west-east season 46 images (March, April, May), 34 images from east season (June, July, August) and 41 image from east-west (October, November, December).

Chl-a analysis

Chl-a data was also received from Aqua-MODIS satellite from NASA that was processed using SeaDAS 4.7 under Linux UBUNTU. MODIS image processing used level 3 courses Seadisp (General image and graphics display) contained in the SeaDAS menu. Further data processing of chl-a is also equal to the process for receiving SST Images. Chl-a images selected to be processed was weekly data collected over five years (2004–2008) in 193 images; Chl-a images were grouped then by seasonal variation. In the west, season was represented in 50 images; east-west represented in 57 images; East season represented in 53 images and the east-west season represented in 33 images (Figure 3).

Sea surface height and current pattern

Sea surface height (SSH) data was received from TOPEX/POSEIDON satellite. In this study, these data served as supporting data in analyzing the changing conditions as an indicator of upwelling. SSH is obtained from http://www.ccar.colorado.edu/ while the current pattern data was obtained from a survey by Wyrtki (1961) that described the general current pattern in the location of interest. Metode analysis used in the mapping fishing ground of Yellowfin Tuna was obtained using a geographic information system approach which overlayed each image based on the season from SST data, chl-a data from Aqua MODIS, and supported by data on average SSH from TOPEX/POSEIDON. From the overlay, waters that experienced thermal fronts, upwelling zones and divergent, convergent and eddies could be determined. Circuit pattern of this relationship was further evaluated for mapping fishing grounds at the sites.

Results

Distribution of sea surface temperature temporally and spatially

The general observation shows that the image of SST in the west is 29.79°C, approximately. Warm temperatures ranging from 33.20°C to 34.0°C were found in the western Binongko Island, Wangi-Wangi Island, Kaledupa Island and around Runduma Island, while cold temperatures ranging from 25.52°C to 25.85°C were located at the southeast Tomia Island, southern Binongko Island and southern Runduma Island. The average SST in the waters of Wakatobi in west-east season was about 29.70°C. Dominant temperature was seen on the eastern side of these Islands that averaged about 26.06°C. Warm temperatures ranging between 32.32°C to 32.79°C were in the west, north and west Wakatobi Islands, and eastern Runduma Island. Cold temperatures ranging between 25.75 to 26.22°C were both on the east and west Wakatobi Islands.

Distribution of the image of SST in May of 2005 looked to have more heat than that of May, 2006. Warmer temperatures were found in the western and eastern Tomia Island, west Wakatobi Islands, east Wangi-Wangi Island, and Kaledupa Island, while the cold temperatures were found around Wakatobi Islands and surrounding eastern Runduma Island. ST images in March, April and May showed a tendency for warmer temperatures in the east, while the cold temperatures were more likely in north and south sides of the Wakatobi Islands.

In the east season, the average SST was about 27.40°C. Warm temperatures tended to be located on the west Wakatobi with temperatures ranging between 29.19°C to 31.3°C. Cold temperatures were in the eastern part, which ranged from 23.74 to 26.25°C. In the east-west seasons SST average was about 29.13°C; warm temperatures ranging from 31.72°C to 33.35°C were obserived on the east side of Wangi-Wangi Island and the north side of Runduma Island. Cold temperatures ranging between 25.78°C to 27.15 existed in some parts of eastern Wakatobi Island.

Distribution of Chl-a temporally and spatially

Average Chl-a concentration in the west season was 0.15 mg m−3. The highest concentration of chl-a, 2.6 mg m−3, was located on the west side of Wakatobi Islands; while a small portion was observed in Tomia Island and Binongko Island. The lowest chl-a concentrations averaging 0–0.05 mg m−3 are located on the western and southern Runduma Island. During the west-east season, average concentration of chl-a was 0.15 mg m−3, while the highest concentration was in the range of 2.5 mg m−3 and was located on the west Wangi-Wangi Island, Binongko and Tomia Island. The lowest Chl-a concentration was found in Kapota reef. Average chl-a concentration in the east season was 0.27 mg m−3. The highest concentration averaged around 3.7 mg m−3 in the western and eastern section Wakatobi Islands. The lowest Chl-a concentration of 0.08 mg m−3 existed around Runduma Island and eastern Wakatobi waters. The highest Chl-a concentration observed in an image from August compared with the images in June and July.

During the east season the Wakatobi waters were very fertile and the highest chl-a concentrations were found both in the west and east; while during the west-east season, highest chl-a concentrations were seen only in the west. This condition is thought to be due to upwelling in the waters of Wakatobi during the east season. According to Wyrtki (1961), based on surface water masses and circulation pattern of winds that blow east, this condition was observed during June to August. In the Banda Sea this could also indicate upwelling.

Average Chl-a concentration in the east-west season was 0.21 mg m−3. The highest concentration of chl-a, 0.5 mg m−3, was observed both on the west and east part of Wakatobi, while the lowest concentration of 0.08 mg m−3 was located on western Kaledupa Island, Tomia Island, Binongko Island and southern Runduma Island. In the east-west season, concentration of chl-a seemed higher in September, while October compared with the image of chl-a in November.

Thermal front

In December, January and February, fronts were observed around Kaledupa reef, Koromaha reef, Runduma Island, and Kentiolo Island (east of Wakatobi Islands) at 123°22′41–124°36′27E and 5°10′57′–6°18′54S. Fronts were concentrated around Koromaha reef, Kaledupa reef and at 123°30′00–124°15′00E and 5°35′00–5°45′00S. In December, the fronts formed on the west side of Binongko Island and around Koka reef at 0.5–1.5°C. In January, the fronts looked to still survive in this region but with a different temperature gradient of about 0.5°C. Nontji (1992) stated that in the west-east season, the current pattern and wind was still quite strong. It was shown in April (Wyrtki, 1961) that the current pattern was found in the waters of Wakatobi Islands from the Java Sea into the Flores Sea with a speed of 50 cm sec−1 This met the current originating from the Maluku Sea to the Banda Sea with the same speed, right in the south side of Wakatobi Islands waters. The front position in June, July and August was found scattered at the position 123°30′00–124°35′00E and 5°10′00–6°05′00S around Kapota reef, Kaledupa reef, Koromaha and Koka reef. The high frequency of fronts in this area is believed to be because of the upwelling which occurs in the reef region. Wyrtki (1961) reported that upwelling occured in the Banda Sea during June, July and August. In November, a front still existed around the Kaledupa and Koka reefs. A front in October was likely to shift to Koka reef and then, in November, to Koromaha reef with gradient temperature of 0.5°C.

Upwelling

The phenomenon of upwelling occurs in June, July, August and September. The criteria used to predict the location of upwelling are low water temperature, high salinity and high nutrient content.

Indications of upwelling were found in June around Kapota reef, Kaledupa reef and around the Koka reef at 123°40′00–124°20′00E and 5°40′00–6°05′00S and were concentrated around the Kapota reef at 123°20′00–123°50′00E and 5°30′00–5°50′00S. In July, upwelling was still present around Kapota reef, and surrounding Kaledupa and Runduma Island. In August, upwelling occurring in the western and eastern Wakatobi Islands were indicated by high chl-a concentration (>1.0 mg m−3). The high concentration of chl-a in August was caused by a strong southeast monsoon which stirred the water layer so the nutrients (silicate, phosphate and nitrate) from the rich bottom layer rich were lifted. In September, a high concentration of chl-a as an indicator of upwelling declined. This was explained due to a decrease in intensity of the wind that drives the surface water mass. Results indicated that upwelling was concentrated around Kapota reef and surrounding Kaledupa Island at 123°20′00–123°05′00E and 5°10′00–5°55′00S, respectively.

Distribution of sea surface height spatially and temporally

Anomalies in sea surface height (SSH) were used to determine sea surface topography, where a positive value means the waters will experience a downwelling, whereas negative SSH means the waters will experience upwelling.

Conditions of one oceanographic parameter influence another. During the west season, a front occurred during the 3rd week of January 2004, 1st week of February 2004, 3rd week of February 2004, 4th week of January 2005, 3rd and 4th weeks of December 2005, 4th week of January 2006, 3rd week of February 2006, 4th week of February 2006, 3rd week of February 2007, 4th week of December 2007, 3rd week of January 2008 and the 1st week of February 2008. Based on the phenomenon of the front in the western season during the 2004–2008 period, negative SSH anomaly events occurred in December with a high intensity on the eastern Islands of Wakatobi. In the west-east season, front incidents were found during the 4th week of March 2004, 4th week of February 2005, 1st week of May 2005, 2nd week of March 2006, 1st week of May 2007 and 2nd week of April 2008. Analysis of the SSH incidents showed that a SSH movement which was relatively large with a value of −20 moving from east to west, occured in March.

In the eastern season, fronts occurred during 1st week of July 2004 and 3rd week of July 2005. It was observed that in this season a negative SSH phenomenon occured and began to weaken. Upwelling usually happened during July, and according to Nontji (1992), upwelling events in the Banda Sea only occur during the east season. In the east-west season, fronts occurred in 1st week of September 2004, 3rd week of September 2004, 1st week of November 2005, 3rd week of November 2008, 1st week of November 2007, and 1st week of November 2007.

Discussion

Distribution of sea surface temperature and chl-a temporally and spatially

The distribution of SST in the west season (December, January, February) visually indicated that warmer temperatures were seen in the eastern part of Wakatobi Island, while cold temperatures tended to be in the west. However, this condition did not show a regular pattern. In this season, distribution of SST showed that warm water and cold water masses have been mixed, presumably caused by changes in seasonal wind patterns that drive the movement of surface water mass.

Nontji (1992) stated that around April, this eastward current began to weaken and even reverse in some laces where eddies occurred. Birowo (1981) also stated that the current during April was variable and very difficult to determine.

Overall distribution of SST images in east season showed spatial movement patterns in the east to west with a mass of cold temperature water. This is consistent with Schalk (1987) which stated that the mass of cold water in large quantities in Banda Sea will be shifted to the west following the movement of surface currents and continue heading east into Flores Sea. During the east-west season, distribution of SST in most of Wakatobi Islands seemed to have hotter temperatures. This caused calm surface currents in this season, indicating solar heating is more effective to increase the temperature of surface waters.

The image showed the pattern of SST distribution in the east-west season, spatially visible from the east side of the Wakatobi Islands to the west side, with the movement tendency being from cold to warm temperatures. This was due to the exact position of the sun in the southern (Equatorial) and the intensity of radiation being that much more effective. According to Hutagalung (1988), sea water temperature, especially in the surface layer, is very dependent on the amount of heat received from the sun. At the west-east season chl-a concentration was determined to be highest in April for five years (2004–2008). Highest concentration of Chl-a was in the west of Wangi-Wangi Island, Binongko and Tomia Island. Lowest concentration of Chl-a tended to be by Runduma Island. The peak of chl-a concentration during the east season was observed in waters of east and west part of Wakatobi Islands. Low chl-a concentration was only in a little part of Runduma Island. The highest concentrations were found in most of the coral, especially in th the Kaledupa and Kapota reef and on the western waters of Wakatobi Islands. Low Chl-a concentration was seen in a small area of the eastern waters of Wakatobi Islands. Chl-a concentration in east-west season was decreased. In September, chl-a concentration was relatively high but not as high as in August. Vosjan and Nieuwland (1987) stated that there were two periods of plankton bloom in Banda Sea, the first in June and the second in August–September. The highest pattern of Chl-a movement still seems to be around Kapota and Kaledupa reef (west Wakatobi Islands). In general, concentrations of Chl-a gradually declined in November.

Prediction of Yellowfin Tuna fishing ground

There is a relationship between the region around the reef with the phenomenon of the formation of fronts. It is the convergent and divergent currents that meet and collide with the ridge which has a relatively shallow depth that causes the formation of fronts in a periodic phenomenon. From the visual analysis performed, this phenomenon also formed from pockets of cold water masses surrounded by a warmer water mass with relatively stable patterns of movement around the reef. Indications of upwelling were concentrated around the Kapota reef, because in general the area around the reef is relatively shallow and when the mass of water arrives around the reefs, the mass of waters from deeper layer is raised. Thus, the upwelling temperature is colder than the surrounding area. According to Nontji (1992), the Banda Sea upwelling events occured only in the east season, where winds pushed out the Banda Sea surface water at a greater rate than could be offset by the surrounding surface water. According to Wyrtki (1961), upwelling that occurred in the Banda Sea could be classified as the alternating type upwelling, that is upwelling and downwelling which occur alternately in one year. Upwelling occurs in one season (east monsoon) and downwelling occurs in another season (west monsoon).

Fishing ground mapping of Yellowfin Tuna potential

Based on front incidents, upwelling and SSH data, the prediction of Yellowfin Tuna fishing ground potential can be mapped. Mapping of fishing ground potential is based on the season, namely west season, west-east season, east and east-west season. Prediction of fishing ground can be seen in Figure 4.*

Conclusions

Mapping of Yellowfin Tuna fishing ground is derived from satellite data (Indirect data), with ground checks performed to verify the data. The long-term aim of this research was to improve the welfare of fishermen in the Wakatobi district, Southeast Sulawesi, while the short-term goal was to map the fishing ground of Yellowfin Tuna (Thunnus albacares) with the application of multi-sensor satellite technology to detect upwellings. The benefits of this research are cost savings for the fishermen and providing a reference for the arrangement of management strategies of Yellowfin Tuna (Thunnus albacares) for sustainablity and continuity.

Acknowledgements

We are grateful to the Directorate General of Higher Education of Republic Indonesia for funding this study. This article was presented at the First International Conference on Managing Ecosystem Health of Tropical Seas (ECOSEAS), held on 19–21 October 2010 in Putrajaya, Malaysia.

References

Birowo, S.
1981
. “
Oceanographic Properties of the Surface Layer of the Ocean
”. In
Coastal And Marine Environment in Indonesia
, Edited by: Romimohtarto, K. and Thayip, Soeminarti, S.
Jakarta
:
LON-LIPI
.
CCAR
.
2009
.
Topex-POSEIDON
.
Hutagalung, H P.
1988
.
The Effect of Water Temperature On Marine Organisms
.
Oseana Journal
,
13
(
4
):
153
164
.
Nontji, A.
1992
.
Laut Nusantara
,
Jakarta
:
P.T. Djambatan
.
Ocean Color Home Page
.
2009
.
http://www.modis.gsfc.nasa.gov. Data access from 12 November-9 December
PPT-LIPI
.
2002
.
Data Base of Social Aspects of Indonesian coral reefs
,
Southeast Sulawesi Province
:
Case study: North Mola Village, Wangi Wangi District Buton Regency
.
Schalk, P. H.
1987
.
Respiratory Electron Transport System (ETS) Activities In Zooplankton and Micronekton of the Indo-Pacific Region
.
Marine Ecology-Progress Series
,
44
:
25
35
.
Stretta, J. M.
1991
.
Forecasting Models For Tuna Fishery With Aerospatial Remote Sensing
.
Int. Journal Remote Sensing
,
12
(
4
):
771
779
.
Tadjuddah, M and Oetama, D.
2007
.
Aplication of Satellite Data to Predict Potential Fishing Ground in Wakatobi Regency Waters, Southeast Province (Research Report)
,
Kendari
:
Institute of Research UNHALU
.
Vosjan, J. H and Nieuwland, G.
1987
.
Microbial Biomass And Respiratory Activity In The Surface Waters of the East Banda Sea and Northwest Arafura Sea (Indonesia) at the time of the Southeast Monsoon
.
Limnol. Oceanogr.
,
32
(
3
):
767
775
.
Wyrtki, K.
1961
.
Physical Oceanography of the South East Asian Waters
,
La Jolla, , California
:
Scripps Institution of Oceanography, The University of California
.
Naga Report. Vol. 2
Zainuddin, M., Kiyofuji, H., Saitoh, K. and Saitoh, S.-I.
2006
.
Using Multi Sensor Satellite Remote Sensing And Catch Data To Detect Ocean Hot Spot For Albarore (Thunnus Alabacore) in The Northwestern Nort Pacific
.
Deep Sea Research Part II: Tropical Studies in Oceanograpy
,
53
(
3–4
):
419
431
.