The Environmental Niche of the Tuna Purse Seine Fleet in the Western and Central Pacific Ocean Based on Different Fisheries Data
文献类型: 外文期刊
作者: Yang, Shenglong 1 ; Yu, Linlin 1 ; Wang, Fei 1 ; Chen, Tianfei 1 ; Fei, Yingjie 4 ; Zhang, Shengmao 1 ; Fan, Wei 1 ;
作者机构: 1.Minist Agr & Rural Affairs, Key Lab Fisheries Remote Sensing, Shanghai 200090, Peoples R China
2.Chinese Acad Fishery Sci, East China Sea Fisheries Res Inst, Key & Open Lab Remote Sensing Informat Technol Fis, Shanghai 200090, Peoples R China
3.Shanghai Ocean Univ, Coll informat, Shanghai 201306, Peoples R China
4.Univ Shanghai Sci & Technol, Coll Sci, Shanghai 200093, Peoples R China
关键词: tuna purse seine fleet; fishing vessel trajectory; automatic identification system; commercial fishery data; MaxEnt; spatiotemporal
期刊名称:FISHES ( 影响因子:2.3; 五年影响因子:2.4 )
ISSN:
年卷期: 2023 年 8 卷 2 期
页码:
收录情况: SCI
摘要: Understanding the spatial pattern of human fishing activity is very important for fisheries resource monitoring and spatial management. The environmental preferences of tropical tuna purse seine fleet in the Western and Central Pacific Ocean (WCPO) were constructed and compared at different spatial scales based on the fishing effort (FE) data from the available automatic identification system (AIS) and commercial fishery data compiled from the Western and Central Pacific Fisheries Commission (WCPFC), using maximum entropy (MaxEnt) methods. The MaxEnt models were fitted with FE and commercial fishery data and remote sensing environmental data. Our results showed that the area under the curve (AUC) value each month based on the commercial fishery data (1 degrees) and FE at 0.25 degrees and 0.5 degrees spatial scales was greater than 0.8. The AUC values each month based on the FE data at a 1 degrees scale ranged from 0.775 to 0.829. The AUC values based on commercial fishing data at the 1 degrees scale were comparable to the model results based on FE data at the 0.5 degrees scale and inferior to the model results based on FE data at the 0.25 degrees scales. Overall, the sea surface temperature (SST), temperature at 100 metres (T100), oxygen concentration at 100 metres (O100) and total primary production (PP) had the greatest influence on the distribution of the purse seine tuna fleet. The oxygen concentration at 200 metres (O200), distance to shore (DSH), dissolved oxygen (Dox), EKE, mixed layer depth (Mld), sea surface salinity (SSS), salinity at 100 metres (S100) and salinity at 200 metres (S200) had moderate influences, and other environmental variables had little influence. The suitable habitat areas varied in response to environmental conditions. The purse seine tuna fleet was mostly present at locations where the SST, T100, O100, O200 and PP were 28-30 degrees C, 27-29 degrees C, 150-200 mmol/m(3) and 5-10 mg/m(-3), respectively. The MaxEnt models enable the integration of AIS data and high-resolution environmental data from satellite remote sensing to describe the spatiotemporal distribution of the tuna purse seine fishery and the influence of environmental variables on the distribution, and can provide forecasts for fishing ground distributions based on future remote sensing environmental data.
- 相关文献
作者其他论文 更多>>
-
Comparative Analysis of Prediction Models for Trawling Grounds of the Argentine Shortfin Squid Illex argentinus in the Southwest Atlantic High Seas Based on Vessel Position and Fishing Log Data
作者:Xiang, Delong;Sun, Yuyan;Zhu, Hanji;Wang, Jianhua;Huang, Sisi;Zhang, Shengmao;Zhang, Famou;Zhang, Heng;Xiang, Delong;Sun, Yuyan;Huang, Sisi;Zhang, Shengmao;Zhang, Famou;Zhang, Heng;Xiang, Delong;Sun, Yuyan;Huang, Sisi;Zhang, Shengmao;Zhang, Famou;Zhang, Heng;Zhu, Hanji;Wang, Jianhua
关键词:Southwest Atlantic;
Illex argentinus ; AIS; deep learning; fishing ground prediction -
Computation and analysis of phenotypic parameters of Scylla paramamosain based on YOLOv11-DYPF keypoint detection
作者:Wu, Chong;Zhang, Shengmao;Wang, Wei;Wu, Zuli;Yang, Shenglong;Chen, Wei;Wu, Chong;Zhang, Shengmao;Zhang, Shengmao
关键词:Scylla paramamosain; Mud crab; Keypoint detection; YOLOv11; Multi-scale fusion; Dynamic upsampling; Support vector regression (SVR)
-
Evaluation Method for Artificial Reefs Based on Multi-Object Tracking
作者:Wu, Zuli;Song, Yifan;Cui, Xuesen;Zhang, Shengmao;Quan, Weimin;Shi, Yongchuang;Xiong, Xinquan;Li, Penglong;Wu, Zuli;Cui, Xuesen;Zhang, Shengmao;Quan, Weimin;Shi, Yongchuang;Song, Yifan;Xiong, Xinquan;Li, Penglong
关键词:artificial reef; sonar images; multi-object tracking (MOT) algorithm; three-dimensional position evaluation
-
Enhancing Landmark Point Detection in Eriocheir Sinensis Carapace with Differentiable End-to-End Networks
作者:Wu, Chong;Wang, Shuxian;Zhang, Shengmao;Zheng, Hanfeng;Wang, Wei;Yang, Shenglong;Wu, Chong;Zhang, Shengmao;Zheng, Hanfeng
关键词:Eriocheir sinensis; Chinese mitten crab; landmark detection; Gaussian heatmaps; deep convolutional neural network; DSNT module; generalization ability; power consumption
-
Assessment of Fish Biomass and Distribution in a Nuclear Power Plant's Water Intake Zone Using Acoustic and Trawl Methods
作者:Wu, Zuli;Song, Yunpeng;Zhao, Guoqing;Shi, Yongchuang;Wu, Yumei;Zhang, Shengmao;Wu, Zuli;Zhao, Guoqing;Shi, Yongchuang;Wu, Yumei;Zhang, Shengmao;Song, Yunpeng
关键词:resource density; acoustic assessment; dominant species; spatiotemporal distribution
-
A Lightweight Deep Learning Model for Forecasting the Fishing Ground of Purpleback Flying Squid (Sthenoteuthis oualaniensis) in the Northwest Indian Ocean
作者:Zhang, Shengmao;Chen, Junlin;Han, Haibin;Tang, Fenghua;Cui, Xuesen;Shi, Yongchuang;Zhang, Shengmao;Chen, Junlin;Han, Haibin
关键词:deep learning; lightweight; Northwest Indian Ocean; remote sensing data;
Sthenoteuthis oualaniensis -
Impact of stocking density of largemouth bass on the self-cleaning performance of a circular aquaculture tank
作者:Qu, Xiaoyu;Tao, Yi;Wang, Fei;Gao, Yang;Li, Dezhen;Zu, Fuzhi;Feng, Dejun;Wu, Yanfei;Wu, Lianhui;Hu, Jiajun
关键词:Largemouth bass; stocking density; aquaculture tanks; waste collection; hydrodynamic characteristic



