scholarly journals Small scale tuna fisheries profiles in the Indonesia archipelagic waters

2021 ◽  
Vol 869 (1) ◽  
pp. 012017
Author(s):  
U Muawanah ◽  
F Y Arthatiani ◽  
P A Soedjarwo ◽  
N Kurniasari ◽  
Y D Sari ◽  
...  

Abstract Indonesia is one of the largest tuna producers in the world, which contributes 16% to world tuna production. The dominant tuna species catched in Indonesia are Albacore Tuna (Thunnus alalunga), Madidihang/Yellowfin Tuna (T. albacares), Big Eye Tuna (T. obesus) dan Southern Bluefin Tuna (T. maccoyii). The tuna fisheries have contributed significant jobs or livelihood to the coastal communities. Profit and revenue sharing is a common remuneration system found on tuna fisheries though out Indonesia. However, these fishers are vulnerable given their economic and welfare conditions and of usually limited options of others livelihood. Small fishers have limited access to livelihoods, access to finance and access to skills or fishing technology. Therefore, the inclusion of socio-economic performance or indicators into the tuna fisheries management is crucial in Indonesia.

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Mohammad Imron ◽  
MUHAMMAD IRSYAD TAWAQAL ◽  
ROZA YUSFIANDAYANI

Abstract. Imron M, Tawaqal MI, Yusfiandayani R. 2021. Fishing ground and tuna productivity by tuna longline based on Benoa Bay, Bali, Indonesia. Biodiversitas 22: 961-968. The success of a longline fishing operation depends on several things such as the skill of the crew, bait used, fishing season, fishing operation, the total of fish caught, the price of the fish, productivity, and fishing grounds. Information about productivity and fishing ground becomes important to increase effectiveness and optimal profit. The methodology is carried out by conducting a survey to collect data to be processed and analyzed using productivity analysis based on Landing per Unit Effort (LPUE) and fishing activity analysis from the Vessel Monitoring System (VMS) to determine the Fishing Ground. We calculate tuna productivity from catch production (landing) per effort, meanwhile fishing ground use VMS data. Production tuna was landed at Benoa Bali from 2016-2018 fluctuated. In 2016 production of tuna albacore took a portion of 34.60%, yellowfin tuna 43.56%, bigeye tuna 15.44%, and southern bluefin tuna 6.26%. Production of tuna albacore took a portion of 35.61%, yellowfin tuna 42.64%, bigeye tuna 12.49%, and southern bluefin tuna 9.26% in 2017. Production albacore took a portion of 36.41%, yellowfin tuna 41.56%, bigeye tuna 11.79%, and southern bluefin tuna 10.24% in 2018. The highest productivity of albacore was in August 2018 with LPUE value 1.0099, yellowfin tuna was in July 2018 with LPUE value 1.2431, big eye tuna was in November 2018 with LPUE value 0.5538, and bluefin was at December 2017 with LPUE value 0.3864. The result of VMS data processing showed that tuna longline vessel based at Benoa has several locations of fishing grounds based on fishing activity for example Hindia High Seas, WPP NRI 714 (Telo gulf and Banda Sea), WPP NRI 718 (Aru Sea, Arafura Sea, and Timor Sea), ZEEI WPP NRI 718.


Author(s):  
Hari Eko Irianto

Indonesia merupakan negara produsen ikan tuna terbesar kelima di dunia. Terdapat  beberapa jenis ikan tuna  yang banyak diperdagangkan di pasar internasional, terutama bluefin tuna, southern bluefin tuna, bigeye tuna, yellowfin tuna, albacore, dan skipjack.  Ikan tuna termasuk komoditas yang cepat mengalami proses kemunduran mutu bila tidak disimpan pada suhu rendah dan juga dapat menghasilkan senyawa histamin yang berbahaya bagi manusia yang mengkonsumsinya. Ikan tuna segar bermutu baik dapat diperoleh dengan menerapkan teknik penanganan dan penyimpanan yang benar segera setelah ikan ditangkap. Cara penanganan ikan tuna setelah ditangkap yang sering diterapkan adalah penggancoan, pendaratan ke atas kapal, pematian, perusakan saluran saraf dengan alat Taniguchi, pembuangan darah, pembuangan insang dan isi perut,  pembersihan, serta penyimpanan dingin. Mutu ikan tuna dipengaruhi oleh faktor-faktor biologis dan non-biologis. Faktor-faktor biologis yang berpengaruh meliputi spesies, umur, ukuran, tingkat kematangan seksual, dan adanya parasit atau penyakit, sedangkan faktor-faktor non-biologis adalah metode penangkapan, teknik penanganan, teknik pendinginan, dan teknik penyimpanan.


2002 ◽  
Vol 59 (6) ◽  
pp. 1002-1013 ◽  
Author(s):  
Arnaud Bertrand ◽  
Erwan Josse ◽  
Pascal Bach ◽  
Philippe Gros ◽  
Laurent Dagorn

We studied relationships between tropical tunas (albacore (Thunnus alalunga), bigeye (Thunnus obesus), and yellowfin (Thunnus albacares)) and their biotic and abiotic environments through simultaneous acoustic observations of tunas and their prey, experimental longline catch, and oceanographic data in French Polynesia. Vertical habitat limits were estimated based on temperature and dissolved oxygen at capture data. We then studied tuna-micronekton relationships to better understand how tuna occupy the pelagic space. At a regional scale, tunas were more abundant in areas rich in prey with favourable hydrological conditions. Inside such areas, at the scale of a longline set, however, the longline catches were maximal only when prey were not distributed in dense patches (except for yellowfin tuna). We interpreted this result by considering that areas with high prey abundance attract tunas, but at a small scale, if prey are patchy distributed, tunas are more inclined to feed on them rather than on longline baits. The effect of patches on yellowfin tuna catch per unit effort (CPUE) does not appear likely because this species also feeds on the mixed layer, where patch density was very low. Not only hydrological characteristics, but also prey density and prey patch characteristics, should be taken into account for interpreting longline CPUE data.


2012 ◽  
Vol 18 (1) ◽  
pp. 19
Author(s):  
Lilis Sadiyah ◽  
Natalie Dowling ◽  
Budi Iskandar Prisantoso

Abundance indices based on nominal CPUE do not take into account confounding factors such as fishing strategy and environmental conditions, that can decouple any underlying abundance signal in the catch rate. As such, the assumption that CPUE is proportional to abundance is frequently violated. CPUE standardisation is one of the common analyses applied. The aims of this paper were to provide a statistical modelling framework for conducting CPUE standardisations using the Observer Program data for bigeye tuna, yellowfin tuna, albacore and southern bluefin tuna, and provide a comparison in the trends between the nominal CPUEs and their standardised indices obtained. The CPUE standardisations were conducted on the Observer Program collected between 2005 and 2007, by applying GLM analysis using the Tweedie distribution. The results suggested that year, area, HBF and bait factors significantly influenced the nominal CPUEs for the four tuna species of interest. Some extreme peaks and troughs in the nominal time series were smoothed in the standardised CPUE time<br />series. The high degree of temporal variability that is still shown in the standardised CPUE trends suggests that the data are too sparse to give any meaningful indication of proxy abundance. Nevertheless, this may also suggest that variables used in the GLMs do not sufficiently account for all<br />of the confounding factors, or abundance may indeed be truly variable.


2013 ◽  
Vol 70 (7) ◽  
pp. 1439-1450 ◽  
Author(s):  
Ashley J. Williams ◽  
Bruno M. Leroy ◽  
Simon J. Nicol ◽  
Jessica H. Farley ◽  
Naomi P. Clear ◽  
...  

Abstract Williams, A. J., Leroy, B. M., Nicol, S. J., Farley, J. H., Clear, N. P., Krusic-Golub, K., and Davies, C. R. Comparison of daily- and annual-increment counts in otoliths of bigeye (Thunnus obesus), yellowfin (T. albacares), southern bluefin (T. maccoyii) and albacore (T. alalunga) tuna. – ICES Journal of Marine Science, 70: . Information on the age of individuals is often required for models assessing the status of stocks. Techniques used to estimate age of tuna have varied across species and agencies, precluding meta-analyses of age and growth. We compared age estimates obtained from commonly used ageing techniques for four important tuna species: bigeye tuna, yellowfin tuna, southern bluefin tuna, and albacore tuna. Estimates of age from counts of annual increments in transverse-sectioned otoliths were generally higher than those from counts of daily increments in transverse and longitudinal sections for all species, particularly for fish older than two years. However, annual counts produced younger estimates, on average, relative to daily counts for bigeye and yellowfin tuna younger than one year. Estimates derived from daily increments in longitudinal and transverse sections were generally similar, although longitudinal sections produced relatively older age estimates for individuals older than two years. A linear or non-linear increase in the magnitude of differences between ageing methods was the best-approximating model in all cases except when comparing daily-increment counts between transverse and longitudinal otolith sections for southern bluefin tuna. These observations are consistent with a narrowing of daily increments with increasing age, resulting in underestimates of age relative to those derived from annual increments. We conclude that (i) daily increments are unsuitable for ageing individuals over two years, especially for southern bluefin and albacore, (ii) longitudinal sections are more precise and produce older age estimates than transverse sections for daily-age estimates, (iii) there are considerable differences in these trends between species, likely dependent on longevity, and (iv) parameter estimates and/or conclusions based on meta-analyses using age data derived from different ageing methods are likely confounded with methodological biases. This result demonstrates that greater effort is required to provide consistent, validated methods for routine age determination to support the assessment and management of these valuable populations.


Author(s):  
Pratita Budi Utami ◽  
Tridoyo Kusumastanto ◽  
Nimmi Zulbainarni ◽  
Nisa Ayunda

Tingginya permintaan tuna sirip kuning baik dalam memenuhi kebutuhan pasar mancanegara dan pasar lokal, berdampak pada keberlanjutan perikanan tuna tersebut. Wilayah perairan Flores Timur adalah salah satu lokasi migrasi bagi tuna sirip kuning; Kecamatan Larantuka merupakan tempat pendaratan terpenting bagi nelayan lokal handline tuna sirip kuning. Kegiatan perikanan tuna sirip kuning ini merupakan salah satu pendapatan utama bagi nelayan lokal dan pemerintah daerah setempat. Penelitian ini bertujuan untuk mengestimasi tingkat eksploitasi dan menganalisa rezim pemanfaatan dari perikanan handline tuna sirip kuning di Larantuka, Flores Timur. Model bioekonomi Fox dan Copes digunakan dalam penelitian untuk menganalisa tingkat lestari sumber daya tuna ekor kuning dari pendekatan input dan output. Hasil estimasi dari kedua model menunjukkan bahwa tingkat pemanfaatan sumber daya ikan tuna sirip kuning oleh nelayan lokal handline masih dalam zona lestari secara ekonomi dan ekologi. Maximum economic yield (MEY) merupakan strategi terbaik untuk mengelola keberlanjutan perikanan tuna sirip kuning di perairan Flores Timur. Melalui pengelolaan rezim MEY diperkirakan dapat menyerap tenaga kerja lebih dari 30 orang, peningkatan armada alat penangkapan sebanyak 25 unit dan pemasukan keuntungan secara ekonomi sebesar Rp68.123.060.000,00 per tahun.Title: Bioeconomic Analysis of Yellowfin Tuna Fishery in Larantuka of East Flores Regency, Indonesia The high demand for yellowfin tuna both in national and international markets has a consequence to the fish resources sustainability. Eastern Flores water is a major area of this tuna mobility; the district of Larantuka is the central port for local yellowfin tuna handline fisheries. These activities are substantial incomes for the local community and regional government. This study, therefore, aims to calculate fish exploitation level and to analyze appropriate management for yellowfin tuna fisheries in Larantuka, East Flores. The bioeconomics Fox and Copes models are used to evaluating the optimal fisheries from input and output approaches. The models’ applications demonstrated that yellowfin tuna handline fisheries are currently estimated sustainable both in ecology and economics. During the study period, the maximum economic yield (MEY) is a recommended strategy to manage yellowfin tuna fisheries in Larantuka, Eastern Flores. The strategy contributes to increasing the number of workers about 30 people, the number of fishing fleets about 25 units and reaching the economic rent  IDR 68.123.060.000,00 in a year


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