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

作     者：YANG Shenglong SONG Liming ZHANG Yu FAN Wei ZHANG Bianbian DAI Yang ZHANG Heng ZHANG Shengmao WU Yumei YANG Shenglong;SONG Liming;ZHANG Yu;FAN Wei;ZHANG Bianbian;DAI Yang;ZHANG Heng;ZHANG Shengmao;WU Yumei

作者机构：College of Marine SciencesShanghai Ocean UniversityShanghai 201306China Key Laboratory of Oceanic and Polar FisheriesMinistry of AgricultureEast China Sea Fisheries Research InstituteChinese Academy of Fishery SciencesShanghai 200090China Key and Open Laboratory of Remote Sensing Information Technology in Fishing ResourceEast China Sea Fisheries Research InstituteChinese Academy of Fishery SciencesShanghai 200090China 

出 版 物：《Journal of Ocean University of China》 (中国海洋大学学报（英文版）)

年 卷 期：2020年第19卷第3期

页      面：669-680页

核心收录：

学科分类：07[理学] 0713[理学-生态学] 

基　　金：supported by the National Natural Science Foundation of China (No.41606138) the Special Funds of Basic Research of Central Public Welfare Institute (Nos.2019T09, 2016Z01-02) the National Key Research and Development Project of China (No.2019YFD 0901405) the Fund of Key Laboratory of Open-Sea Fishery Development, Ministry of Agriculture, P.R.China (No.LOF2018-01) 

主　　题：CPUE Argo buoy data Thunnus obesus vertical distribution generalized additive model Atlantic Ocean 

摘      要：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℃ and 9℃ as the preferred swimming depth, while the lower limit of the temperature(12℃) 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℃ 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℃ 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 i