scholarly journals Effects of gear characteristics on the presence of bigeye tuna (Thunnus obesus) in the catches of the purse-seine fishery of the eastern Pacific Ocean

2008 ◽  
Vol 65 (6) ◽  
pp. 970-978 ◽  
Author(s):  
Cleridy E. Lennert-Cody ◽  
Jason J. Roberts ◽  
Richard J. Stephenson

Abstract Lennert-Cody, C. E., Roberts, J. J., and Stephenson, R. J. 2008. Effects of gear characteristics on the presence of bigeye tuna (Thunnus obesus) in the catches of the purse-seine fishery of the eastern Pacific Ocean. – ICES Journal of Marine Science, 65: 970–978. Overfishing of bigeye tuna in the eastern Pacific Ocean has motivated a search for a practical means of reducing the catch of bigeye tuna in mixed species aggregations. To explore the effects of gear characteristics on the catch of bigeye tuna, a classification algorithm for the presence/absence of bigeye tuna catch in purse-seine sets on floating objects is developed, using the tree-based method, random forests. Although the location of the set was the strongest determinant of bigeye tuna catch with these data, bigeye tuna in some areas were more likely to be caught on floating objects with greater underwater depths and with deeper purse-seines. Misclassified sets that caught bigeye tuna were concentrated within certain vessels, suggesting the existence of additional vessel effects. Results indicate that fishers may avoid catching bigeye tuna in some areas by changing the depth of the material hanging from the floating object and the actual fishing depth of the purse-seine, or by moving to other fishing areas. Nonetheless, given the complexity of configuring a purse-seine, and the difficulties associated with monitoring compliance with gear regulations, fishery-wide gear restrictions would be problematic.

2014 ◽  
Vol 71 (7) ◽  
pp. 1774-1780 ◽  
Author(s):  
Daniel W. Fuller ◽  
Kurt M. Schaefer

Abstract Experiments were conducted to evaluate a fishing captain's ability to predict species composition, sizes, and quantities of tunas associated with drifting fish-aggregating devices (FADs), before encirclement with a purse-seine net. Operating in the equatorial eastern Pacific Ocean, during 11 May–23 July 2011, Captain Ricardo Diaz detected small quantities of bigeye (Thunnus obesus) and yellowfin (Thunnus albacares) tunas within large FAD-associated aggregations dominated by skipjack tuna (Katsuwonus pelamis). The captain's predictions were significantly related to the actual total catch and catch by species, but not to size categories by species. His predictions of species composition were most accurate when estimates of bigeye and yellowfin tuna were combined. If purse-seine captains are able to make accurate predictions of the proportion of bigeye and yellowfin tunas present in mixed-species aggregations associated with FADs, managers may wish to consider incentives to fishers to reduce the fishing mortality on those species.


2021 ◽  
Vol 241 ◽  
pp. 106001
Author(s):  
Osman Crespo-Neto ◽  
Eric Díaz-Delgado ◽  
Tatiana A. Acosta-Pachón ◽  
Raúl O. Martínez-Rincón

2021 ◽  
Vol 243 ◽  
pp. 106065
Author(s):  
Keisuke Satoh ◽  
Haikun Xu ◽  
Carolina V. Minte-Vera ◽  
Mark N. Maunder ◽  
Toshihide Kitakado

2009 ◽  
Vol 99 (2) ◽  
pp. 106-111 ◽  
Author(s):  
Sheng-Ping Wang ◽  
Mark N. Maunder ◽  
Alexandre Aires-da-Silva ◽  
William H. Bayliff

2018 ◽  
Author(s):  
Bruno Thierry Nyatchouba Nsangue ◽  
Zhou Cheng ◽  
Liuxiong Xu ◽  
Richard Kindong

This study highlighted the occurrence of a pelagic long line fishery targeting albacore tuna, yellowfin tuna and bigeye tuna in the high seas of eastern Pacific Ocean. Species selectivity of the fishing method was assessed. Hook depth, statistics of at-vessel survival rate grouped by hooks number, length frequency, weight frequency, length weight relationship, relative condition factor and Fulton’s condition factor were estimated for the target species. This fishing method proved highly selective for albacore tuna, where catches accounted for about 85% of catches, while other resources such as yellowfin tuna amounted to 4.8% and big eye tuna accounted for 9.70%. The results showed that, fish size increased with deeper depths. Hook No. 8 located at a critical depth indicated that fork lengths of tuna registered above this depth were significantly smaller than that those captured below it. Logistic regression model suggested a significant effect of hook depth on the catch efficiency. The highest density of catch efficiency was located at the depth of 167.57 m. An alternative strategy showed that hooks deployed at the depths ranging from 124 to 211 m will result in a more considerable fishing efficiency. The analyses also showed that the relative condition factors (Krel) of the three fish species were greater than (1) implying that they were in good physiological condition at the time of capture.


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