SEBARAN HASIL TANGKAPAN MADIDIHANG (Thunnus albacares Bonnaterre, 1788) DI SAMUDERA HINDIA BAGIAN TIMUR

Ikan Madidihang (Thunnus albacares Bobbaterre, 1788) merupakan salah satu komoditaspenting bagi industri perikanan di Indonesia dimana hasil tangkapannya merupakan yang tertinggi dibandingkan jenis tuna lainnya. Saat ini, kondisi stok madidihang berada dalam kondisi yang baik. Namun, untuk menjaga kelangsungan pemantaatan stok ikan tuna, diperlukan upaya pengelolaan sumber daya tuna. Penelitian ini bertujuan untuk mengetahui distribusi laju tangkap madidihang di Samudera Hindia Bagian Timur. Pengumpulan data dilakukan oleh pemantau ilmiah pada kapal rawai tuna komersial yang berbasis di Benoa, Pelabuhanratu dan Bungus dari Agustus 2005 sampai Desember 2013; serta program monitoring pendaratan tuna yang berbasis di Benoa tahun 2010-2013. Hasil penelitian menunjukkan bahwa laju pancing bervariasi secara bulanan dan tahunan. Rata-rata bulanan laju pancing tertinggi terjadi pada Mei (0,17 ekor/100 pancing) dan terendah pada Februari (0,01 ekor/100 pancing), sedangkan rata-rata laju pancing tahunan tertinggi pada 2006 (0,11 ekor/100 pancing) dan terendah pada 2011 (0,06 ekor/100 pancing). Rata-rata laju pancing tahunan cenderung mengalami penurunan sebesar 29,48%/ tahun. Ikan madidihang tertangkap oleh rawai tuna Indonesia tersebar dari 0°-34° LS dan 76°-134° BT. Sebaran spasial laju pancing tertinggi berada di sekitar Kepulauan Mentawai dan selatan Jawa Timur hingga Nusa Tenggara. Yellowfin tuna (Thunnus albacares Bobbaterre, 1788) is one of the important commodity for the fishing industry in Indonesia because it has the highest catches compared with other tunas. Nowadays, the yellowfin stock is currently in good condition (not overfished and not subject to overfishing). However, management measure was required to support sustainability of tuna fishery. This study aims to determine the hook rate distribution of yellowfin tuna in the Eastern Indian Ocean. Data was obtained by scientific observers on commercial tuna longline vessels, mainly based in Benoa, Palabuhan Ratu and Bungus Fihing Port, from August 2005 to November 2013; also monitoring program of tuna catches mainly landed in Benoa during 2010 to 2013. The results showed that the hook rate of yellowfin tuna was varied monthly and yearly. The highest of monthly average CPUE occurred in May (0,17 fish/100 hooks) and the lowest were in February (0,01 fish/100 hooks), while the highest annually CPUE also occurred in 2006 (0,11 fish/100 hooks) and the lowest in 2011 (0,06 fish/100 hooks). CPUE also has declining with 29,48%/year. Distribution of yellowfin tuna caught by Indonesia tuna longline spreads from 0°-34° S dan 76°-134° E. The highest CPUE was around Mentawai islands and also in south coast of East Java to Nusa Tenggara.

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Catch per unit effort, condition factor and length-weight relationship of albacore tuna (Thunnus alalunga), yellowfin tuna (Thunnus albacares) and bigeye tuna (Thunnus obesus) in the longline tuna fishery in the Eastern Pacific Ocean

Indian Journal of Fisheries ◽

10.21077/ijf.2021.68.2.87673-04 ◽

2021 ◽

Vol 68 (2) ◽

pp. 23

Author(s):

Nyatchouba Nsangue Bruno Thierry ◽

Zhou Cheng ◽

Njomoue Pandong Achille ◽

Kindong Richard ◽

Liuxiong Xu

Keyword(s):

Condition Factor ◽

Yellowfin Tuna ◽

Thunnus Albacares ◽

Bigeye Tuna ◽

Eastern Pacific Ocean ◽

Catch Per Unit Effort ◽

Thunnus Obesus ◽

Thunnus Alalunga ◽

Relationship Of ◽

Tuna Fishery

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Stock depletion of yellowfin tuna Thunnus albacares (Bonnaterre 1788) in the Northeastern Indian Ocean

E3S Web of Conferences ◽

10.1051/e3sconf/202132205004 ◽

2021 ◽

Vol 322 ◽

pp. 05004

Author(s):

Bram Setyadji ◽

Hety Hartaty ◽

Arief Wujdi ◽

Ririk K. Sulistyaningsih

Keyword(s):

Indian Ocean ◽

Data Collection ◽

Relative Abundance ◽

Yellowfin Tuna ◽

Coastal Communities ◽

Thunnus Albacares ◽

The Indian Ocean ◽

Stock Depletion ◽

Longline Fisheries ◽

Tuna Longline

The stock of yellowfin tuna (Thunnus albacares) has been in a declining trend in the last five years. Although the noticeable decline mainly occurred in the western part of the Indian Ocean, uncertainty lingers on how this phenomenon will affect the opposite leg. The study aimed to investigate the dynamics of stock through monitoring several indicators by utilizing logbooks, scientific port sampling, and observer data available. The result showed that both relative abundance and estimated catch trend are declining in recent years, a sign that the negative global inclination also influences Indonesian tuna longline fisheries. Further studies are needed to understand whether this phenomenon also impacts other gears. Hence, mitigation on conserving the resource by reducing the catch and strengthening the data collection should be the priority to maintain the livelihood and welfare of many coastal communities.

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Estimation of overall fishing intensity of tuna longline fishery-yellowfin tuna (Thunnus albacares) fishery in the indian ocean as a case study

Journal of Applied Ichthyology ◽

10.1111/j.1439-0426.1986.tb00435.x ◽

1986 ◽

Vol 2 (3) ◽

pp. 97-102

Author(s):

P. P. Pillai ◽

M. Srinath

Keyword(s):

Indian Ocean ◽

Yellowfin Tuna ◽

Thunnus Albacares ◽

Longline Fishery ◽

The Indian Ocean ◽

Tuna Longline

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Status Pemanfaatan Perikanan Tuna Madidihang (Thunnus albacares) Berdasarkan Model Biologi Schaefer

Marine Fisheries Journal of Marine Fisheries Technology and Management ◽

10.29244/jmf.9.1.65-75 ◽

2018 ◽

Vol 9 (1) ◽

pp. 65

Author(s):

Abgusta Fajri Wiranata ◽

Budy - Wiryawan ◽

Sugeng Hari Wisudo ◽

Nimmi - Zulbainarni

Keyword(s):

Linear Regression ◽

Population Growth ◽

Growth Function ◽

Yellowfin Tuna ◽

Thunnus Albacares ◽

Quadratic Regression ◽

Maximum Production ◽

The Difference ◽

Tuna Fishery

There are two types of population growth function of the basic formulation of Schaefer’s biology model, however in this study there is a difference in form and value of “r” as one of a biology parameter. In addition to the difference in the method by calculating the process of a and b coefficient. The calculating process of a and b coefficient in Schaefer’s biology model was conducted through linear regression which has not yet been exact. This is due to the model itself which is quadratic. Therefore to provide the solution is through quadratic process. The linear regression shows the value of fmsy and Ymsy 1.40 and 1.34 times smaller than quadratic process respectively. Based on the two graphs from the calculating process of a and b coefficient, it can be concluded that the utilization of yellowfin tuna fishery was still not optimal. According to the result based on the linear and quadratic regression, the maximum production of yellowfin tuna can be increased to 664,037 and 877,340 kg.Keywords: Population growth function, Schaefer’s Biology Model, Utilization status, Yellowfin tuna ABSTRAKDua jenis fungsi pertumbuhan populasi menjadi dasar pembentukan model biologi Schaefer, namun dalam kajian ini terdapat perbedaan dalam bentuk dan nilai r sebagai parameter biologi ditambah juga berdasarkan perbedaan metode perhitungan koefisien a dan b. Metode perhitungan koefisien a dan b model biologi Schaefer melalui regresi linear masih kurang tepat, karena model biologi Schaefer berbentuk kuadratik, sehingga penyelesaiannya harus melalui proses kuadratik. Nilai fmsy dan Ymsy dari proses regresi linear memiliki nilai 1,40 dan 1,34 kali lebih rendah dari proses kuadratik. Berdasarkan kedua kurva dari kedua metode perhitungan koefisien a dan b, maka status pemanfaatan perikanan tuna madidihang diduga masih belum optimal. Sehingga berdasarkan proses regresi linear dan kuadratik, maka produksi maksimal tuna madidihang masih dapat ditingkatkan sampai dengan 664.037 dan 877.340 kg.Kata kunci: Fungsi pertumbuhan populasi, Model biologi Schaefer, Status pemanfaatan Tuna madidihang

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Genetic Variation in Yellowfin Tuna Thunnus Albacares (Bonnaterre, 1788) Along Indian Coast Using Pcr-Rflp Analysis of Mitochondrial Dna D-Loop Region

International Journal of Scientific Research ◽

10.15373/22778179/jan2014/8 ◽

2012 ◽

Vol 3 (1) ◽

pp. 25-30

Author(s):

Swaraj Priyaranjan Kunal ◽

◽

Girish Kumar Girish Kumar ◽

Maria Rosalia Menezes

Keyword(s):

Mitochondrial Dna ◽

Genetic Variation ◽

Rflp Analysis ◽

Yellowfin Tuna ◽

Thunnus Albacares ◽

Indian Coast ◽

Loop Region ◽

Pcr Rflp ◽

D Loop

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Ontogenetic change in the amount and position of slow‐oxidative myotomal muscle in relationship to regional endothermy in juvenile yellowfin tuna Thunnus albacares

Journal of Fish Biology ◽

10.1111/jfb.14092 ◽

2019 ◽

Author(s):

Juleen M. Dickson ◽

Kathryn A. Dickson

Keyword(s):

Yellowfin Tuna ◽

Thunnus Albacares ◽

Ontogenetic Change ◽

Myotomal Muscle ◽

Regional Endothermy

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Ontogenetic changes in cutaneous and branchial ionocytes and morphology in yellowfin tuna (Thunnus albacares) larvae

Journal of Comparative Physiology B ◽

10.1007/s00360-018-1187-9 ◽

2018 ◽

Vol 189 (1) ◽

pp. 81-95 ◽

Cited By ~ 5

Author(s):

Garfield T. Kwan ◽

Jeanne B. Wexler ◽

Nicholas C. Wegner ◽

Martin Tresguerres

Keyword(s):

Yellowfin Tuna ◽

Thunnus Albacares ◽

Ontogenetic Changes

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Extraction optimization and properties of collagen from yellowfin tuna (Thunnus albacares) dorsal skin

Food Hydrocolloids ◽

10.1016/j.foodhyd.2007.04.015 ◽

2008 ◽

Vol 22 (5) ◽

pp. 879-887 ◽

Cited By ~ 77

Author(s):

Jin-Wook Woo ◽

Sung-Jae Yu ◽

Seung-Mock Cho ◽

Yang-Bong Lee ◽

Seon-Bong Kim

Keyword(s):

Yellowfin Tuna ◽

Thunnus Albacares ◽

Dorsal Skin ◽

Extraction Optimization

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Exploitation and movements of yellowfin tuna (Thunnus albacares) and bigeye tuna (T. obesus) tagged in the north-western Coral Sea

Marine and Freshwater Research ◽

10.1071/mf97210 ◽

1998 ◽

Vol 49 (6) ◽

pp. 475 ◽

Cited By ~ 18

Author(s):

John Hampton ◽

John Gunn

Keyword(s):

Seasonal Pattern ◽

Yellowfin Tuna ◽

Thunnus Albacares ◽

Bigeye Tuna ◽

Catch Per Unit Effort ◽

The North ◽

Coral Sea ◽

Release Area ◽

Seasonal Signal ◽

North Western

Yellowfin tuna (Thunnus albacares) and bigeye tuna (T. obesus) were tagged and released in the north-western Coral Sea off northern Queensland in 1991 and 1992. Over the next five years, recaptures were reported by Australian longline vessels based in Cairns and fishing in the release area, and by industrial tuna fleets fishing in the adjacent western Pacific region, thus demonstrating clear links between the tuna stocks in these areas. Some southerly movements of yellowfin, in particular, further suggested links with stocks supporting the longline fishery in the south-eastern Australian Fishing Zone. Bigeye tuna tag returns and catch per unit effort by Cairns-based longliners showed a strong seasonal signal, peaking in mid year. Yellowfin tag-return data displayed a similar, but weaker, seasonal pattern. The data were analysed by use of tag-attrition models with seasonally variable catchability and with two assumptions regarding changes in targeting of the two species by longliners during the study. Under both assumptions, the local exploitation rates for yellowfin are low: about 0.07 in 1996. For bigeye, the local exploitation rate in 1996 may have been as high as 0.30, warranting a cautious approach to further fishery expansion in this area.

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