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DISTRIBUTION OF PELAGIC FISH IN SOUTH CHINA SEA USING GEOSTATISTICAL APPROACH

Jurnal Ilmu Kelautan SPERMONDE · Vol. UME (2018) · pp. 20–24

DOI
10.20956/jiks.v4i1.3800
ISSN
2614-5049, 2460-0156
Published
2018-04-03
Publisher
Hasanuddin University
Language
en
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Pelagic fish are spesies that live in water column at depth of 100 to 200 meters from surface. They migrate as a group looking for nutrient and spawning place. Potential fisheries comodities in Indonesia including pelagic fish have high economic value. Then, stock assessment of pelagic fish measurement is important to researched. The research was conducted in May – June 2016 surrounding South China Sea waters using Madidihang 02 Research Vessel operated by Marine Fisheries Affair (MFA) Republic of Indonesia. To estimate the density of pelagic fish hydro-accoustic equipment and oceanography parameters were used and measured during the campaign. The split beam echosounder was use in aim to obtain precission position and number of fish target. The highest density of fish was found around Tambelan Island and Anambas Island. Statistically pelagic fish density has correlation with chlorophyll-a, salinity, temperature, and sea current velocity. The statistical analysis between pelagic fish density and those oceanography parameters (as statistic variables) yields positive vector correlation.

Keywords

Collaboration network of the authors

19 authors · 64 co-authorship links

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  • Affiliation unknown
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Co-authorOrganisationJoint articles
Muhammad HisyamAffiliation unknown1
Riza Aitiando PasaribuIPB University1
Endang Sunarwati SrimarianaAffiliation unknown1
Dea Fauzia LestariAffiliation unknown1
Mochamad Tri HartantoAffiliation unknown1
Nyoman Metta NatihAffiliation unknown1
Rastina RastinaAffiliation unknown1
Steven SolikinAffiliation unknown1
Erwin MaulanaAffiliation unknown1
Faisal HanafiAffiliation unknown1
Hery PurwantoAffiliation unknown1
Alifah NorainiAffiliation unknown1
Kristina MarselaAffiliation unknown1
Atika Kumala DewiAffiliation unknown1
Muhammad Zainudin LubisAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/jiks/oai, first harvested 4 Nov 2026, last seen 4 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">DISTRIBUTION OF PELAGIC FISH IN SOUTH CHINA SEA USING GEOSTATISTICAL APPROACH</dc:title>
	<dc:creator xml:lang="en">Hidayat, Esa Fajar</dc:creator>
	<dc:creator xml:lang="en">Pujiyati, Sri</dc:creator>
	<dc:creator xml:lang="en">Suman, Ali</dc:creator>
	<dc:creator xml:lang="en">Hestirianoto, Totok</dc:creator>
	<dc:subject xml:lang="en">Pelagic Fish</dc:subject>
	<dc:subject xml:lang="en">South China Sea</dc:subject>
	<dc:subject xml:lang="en">Hydroacoustic</dc:subject>
	<dc:subject xml:lang="en">Fish Density</dc:subject>
	<dc:description xml:lang="en">Pelagic fish are spesies that live in water column at depth of 100 to 200 meters from surface. They migrate as a group looking for nutrient and spawning place. Potential fisheries comodities in Indonesia including pelagic fish have high economic value. Then, stock assessment of pelagic fish measurement is important to researched. The research was conducted in May – June 2016 surrounding South China Sea waters using Madidihang 02 Research Vessel operated by Marine Fisheries Affair (MFA) Republic of Indonesia. To estimate the density of pelagic fish hydro-accoustic equipment and oceanography parameters were used and measured during the campaign. The split beam echosounder was use in aim to obtain precission position and number of fish target. The highest density of fish was found around Tambelan Island and Anambas Island. Statistically pelagic fish density has correlation with chlorophyll-a, salinity, temperature, and sea current velocity. The statistical analysis between pelagic fish density and those oceanography parameters (as statistic variables) yields positive vector correlation.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2018-04-03</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/jiks/article/view/3800</dc:identifier>
	<dc:identifier>10.20956/jiks.v4i1.3800</dc:identifier>
	<dc:source xml:lang="en">Jurnal Ilmu Kelautan SPERMONDE; VOLUME 4 NUMBER 1, 2018; 20-24</dc:source>
	<dc:source>2614-5049</dc:source>
	<dc:source>2460-0156</dc:source>
	<dc:source>10.20956/jiks.v4i1</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jiks/article/view/3800/2182</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2018 Jurnal Ilmu Kelautan SPERMONDE</dc:rights>
	<dc:rights xml:lang="en">http://creativecommons.org/licenses/by-nc/4.0</dc:rights>
</oai_dc:dc>