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      The Potential Vertical Distribution of Bigeye Tuna ( Thunnus obesus) and Its Influence on the Spatial Distribution of CPUEs in the Tropical Atlantic Ocean

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          Understanding the potential vertical distribution of bigeye tuna ( Thunnus obesus) is necessary to understand the catch rate fluctuations and the stock assessment of bigeye tuna. To characterize the potential vertical distribution of this fish while foraging and determine the influences of the distribution on longline efficiency in the tropical Atlantic Ocean, the catch per unit effort ( CPUE) data were compiled from the International Commission for the Conservation of Atlantic Tunas and the Argo buoy data were downloaded from the Argo data center. The raw Argo buoy data were processed by data mining methods. The CPUE was standardized by support vector machine before analysis. We assumed the depths with the upper and lower limits of the optimum water temperatures of 15°C and 9°C as the preferred swimming depth, while the lower limit of the temperature (12°C) associated with the highest hooking rate as the preferred foraging depth ( D12) of bigeye tuna during the daytime in the Atlantic Ocean. The preferred swimming depth and foraging depth range in the daytime were assessed by plotting the isobath based on Argo buoy data. The preferred swimming depth and vertical structure of the water column were identified to investigate the spatial effects on the CPUE by using a generalized additive model (GAM). The empirical cumulative distribution function was used to assess the relationship between the spatial distribution of CPUE and the depth of 12°C isolines and thermocline. The results indicate that 1) the preferred swimming depth of bigeye tuna in the tropical Atlantic is from 100 m to 400 m and displays spatial variation; 2) the preferred foraging depth of bigeye tuna is between 190 and 300 m and below the thermocline; 3) the number of CPUEs peaks at a relative depth of 30–50 m (difference between the 12°C isolines and the lower boundary of the thermocline); and 4) most CPUEs are within the lower depth boundary of the thermocline levels ( LDBT) which is from 160 m to 230 m. GAM analysis indicates that the general relationship between the nominal CPUE and LDBT is characterized by a dome shape and peaks at approximately 190 m. The oceanographic features influence the habitat of tropical pelagic fish and fisheries. Argo buoy data can be an important tool to describe the habitat of oceanic fish. Our results provide new insights into how oceanographic features influence the habitat of tropical pelagic fish and fisheries and how fisheries exploit these fish using a new tool (Argo profile data).

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          Author and article information

          Journal of Ocean University of China
          Science Press and Springer (China )
          02 May 2020
          01 June 2020
          : 19
          : 3
          : 669-680
          1College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
          2Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture; East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China
          3Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China
          Author notes
          *Corresponding author: SONG Liming, Tel: 0086-21-61900311, E-mail: lmsong@
          Copyright © Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2020.

          The copyright to this article, including any graphic elements therein (e.g. illustrations, charts, moving images), is hereby assigned for good and valuable consideration to the editorial office of Journal of Ocean University of China, Science Press and Springer effective if and when the article is accepted for publication and to the extent assignable if assignability is restricted for by applicable law or regulations (e.g. for U.S. government or crown employees).

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