Evaluation of growth-dependent survival during early stages of Pacific bluefin tuna using otolith microstructure analysis

2017 ◽  
Vol 68 (11) ◽  
pp. 2008 ◽  
Author(s):  
Mikio Watai ◽  
Taiki Ishihara ◽  
Osamu Abe ◽  
Seiji Ohshimo ◽  
Carlos Augusto Strussmann

The present study used otolith analysis-based body size back-calculation to: (1) evaluate the hypothesis of growth-dependent survival in young Pacific bluefin tuna (PBF; Thunnus orientalis) from the north-western Pacific Ocean; (2) identify critical developmental stages for survival; and (3) compare interannual differences in early growth. To this end, we compared the daily growth trajectories of a large number of larvae (standard length (SL) <15mm), juveniles (15≤SL≤150mm), and young-of-year (YOY; SL >150mm) collected between 2011 and 2015. Otolith radius and SL were highly correlated and yielded a single relationship applicable for the five year-classes. Body size back-calculation showed that only larvae with fast, steady growth successfully transitioned to the juvenile stage. The ontogenetic analysis of daily growth rates revealed interannual differences only in larvae, and not in the larval stage of juveniles and YOY. Neither sudden decreases nor increases in growth rates were observed during the larval stage of any of the stages, suggesting that the observed variability in larval body size may be the result of individual differences in growth rates rather than of drastic, one-time events. Overall, the results of the present study indicate that growth-dependent survival of larvae may be the most critical for PBF recruitment.

2014 ◽  
Vol 80 (6) ◽  
pp. 1205-1214 ◽  
Author(s):  
Yosuke Tanaka ◽  
Hiroshi Minami ◽  
Yuka Ishihi ◽  
Kazunori Kumon ◽  
Kentaro Higuchi ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Naoto Ienaga ◽  
Kentaro Higuchi ◽  
Toshinori Takashi ◽  
Koichiro Gen ◽  
Koji Tsuda ◽  
...  

AbstractClosed-cycle aquaculture using hatchery produced seed stocks is vital to the sustainability of endangered species such as Pacific bluefin tuna (Thunnus orientalis) because this aquaculture system does not depend on aquaculture seeds collected from the wild. High egg quality promotes efficient aquaculture production by improving hatch rates and subsequent growth and survival of hatched larvae. In this study, we investigate the possibility of a simple, low-cost, and accurate egg quality prediction system based only on photographic images using deep neural networks. We photographed individual eggs immediately after spawning and assessed their qualities, i.e., whether they hatched normally and how many days larvae survived without feeding. The proposed system predicted normally hatching eggs with higher accuracy than human experts. It was also successful in predicting which eggs would produce longer-surviving larvae. We also analyzed the image aspects that contributed to the prediction to discover important egg features. Our results suggest the applicability of deep learning techniques to efficient egg quality prediction, and analysis of early developmental stages of development.


Aquaculture ◽  
2021 ◽  
pp. 736562
Author(s):  
Koji Murashita ◽  
Hiroshi Hashimoto ◽  
Toshinori Takashi ◽  
Takeshi Eba ◽  
Kazunori Kumon ◽  
...  

2016 ◽  
Vol 174 ◽  
pp. 30-39 ◽  
Author(s):  
Yumi Okochi ◽  
Osamu Abe ◽  
Sho Tanaka ◽  
Yukio Ishihara ◽  
Akio Shimizu

2014 ◽  
Vol 81 (1) ◽  
pp. 113-121 ◽  
Author(s):  
Yasuo Agawa ◽  
Mayui Iwaki ◽  
Takafumi Komiya ◽  
Tomoki Honryo ◽  
Kouhei Tamura ◽  
...  

2014 ◽  
Vol 47 (7) ◽  
pp. 2040-2049 ◽  
Author(s):  
Takayuki Ohnishi ◽  
Amal Biswas ◽  
Kohshi Kaminaka ◽  
Takahiro Nakao ◽  
Masashi Nakajima ◽  
...  

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