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南乔治亚岛冬季南极磷虾渔场时空分布及其驱动因子

陈广威1,陈吕凤1,2,朱国平1,2,3*,徐玉成4,田靖寰1,丁博1#br#   

  1. (1上海海洋大学海洋科学学院, 上海 201306; 2上海海洋大学国家远洋渔业工程技术研究中心, 上海 210306; 3上海海洋大学大洋渔业资源可持续开发省部共建教育部重点实验室, 极地海洋生态系统研究室, 上海 201306; 4辽宁远洋渔业有限公司, 辽宁大连 116113)
  • 出版日期:2017-10-10 发布日期:2017-10-10

Spatial-temporal distribution of fishing ground for Antarctic krill fishery in the South Georgia Island during the austral winter and its drivers.

CHEN Guang-wei1, CHEN Lv-feng1,2, ZHU Guo-ping1,2,3*, XU Yu-cheng4, TIAN Jing-huan1, Ding Bo1#br#   

  1. (1 College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; 2National  Engineering Research Center for Oceanic Fisheries (Shanghai Ocean University), Shanghai 201306, China; 3Polar Marine Ecosystem Lab, The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Shanghai Ocean University, Ministry of Education, Shanghai 201306, China; 4Liaoning Pelagic Fishery Co. Ltd., Dalian 116113, Liaoning, China).
  • Online:2017-10-10 Published:2017-10-10

摘要: 基于中国南极磷虾渔业科学观察员收集的数据,本文通过地理加权回归(GWR)模型分析了月份、海底深度和虾群深度对2013—2016年南乔治亚岛冬季南极磷虾渔业单位捕捞努力量渔获量(CPUE)的影响,揭示各驱动因子的时空差异。结果表明:2013—2016年南乔治亚岛南极磷虾渔业CPUE的较大值主要分布于6个旬别,即7月上旬—8月下旬,2014年的平均CPUE值最多,达到20.5±21.1 t·h-1,而最小CPUE平均值出现在2015年(10.4±10.5 t·h-1),各月份的平均CPUE存在显著性差异;渔场主要集中在53°00′S—54°30′S,35°15′W—38°30′W;2015年GWR模型拟合优度最高,2016年模型拟合优度最低;自南向北,虾群深度对南极磷虾渔业CPUE的空间效应(正相关性)呈现逐渐增强的趋势,而海底深度对CPUE的空间效应并不一致;GWR模型各年拟合优度均明显高于最小二乘法(OLS)模型中的拟合优度,说明GWR模型能更好地模拟驱动因子对CPUE影响的空间效应。本文结果可为研究南乔治亚岛南极磷虾渔场形成机制和渔业管理提供有效参考。

关键词: 线粒体DNA, 遗传结构, COII基因, 异色瓢虫, 地理种群, 遗传多样性

Abstract: Based on the data collected by scientific observers onboard Chinese Antarctic krill fishing vessel, the present study analyzed the effect of month, bottom depth and fishing depth on catch per unit effort (CPUE) of Antarctic krill fishery operated in the South Georgia Island during the austral winter 2013-2016 using geographically weighted regression (GWR) model and further revealed the drivers of the spatialtemporal differences. The results indicated that higher CPUEs were distributed in the first 10 days of July to the last 10 days of August. The highest mean CPUE was 20.5±21.1 t·h-1 in 2014, and the lowest mean CPUE was 10.4±10.5 t·h-1 in 2015. A significant difference was also found in average CPUE values among months. Fishing ground was concentrated in 53°00′S-54°30′ S, 35°15′W-38°30′W. The goodness of fit for GWR model was the highest in 2015, but the lowest in 2016. The spatial effect (positive correlation) of fishing depth on CPUE of Antarctic krill fishery was strengthened increasingly from south to north, but no consistent trend was observed for the spatial effect of bottom depth on CPUE. The goodness of fit for GWR model was higher than that of ordinary least square (OLS) model, indicating that GWR model was more suitable to present the spatial effect of drivers on CPUE. The results derived from the present study can provide effective references for studying forming mechanism of fishing ground and fishery management of Antarctic krill fishery in the South Georgia Island.

Key words: mitochondrial DNA, genetic structure, COII gene, geographic population, genetic diversity., Harmonia axyridis