Volume 14 Issue 2
Apr.  2018
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FAN Jiangtao, FENG Xue, CHEN Zuozhi. Fishing ground analysis of Japanese horse mackerel in northern South China Sea based on vertical structure of water temperature[J]. South China Fisheries Science, 2018, 14(2): 124-128. DOI: 10.3969/j.issn.2095-0780.2018.02.017
Citation: FAN Jiangtao, FENG Xue, CHEN Zuozhi. Fishing ground analysis of Japanese horse mackerel in northern South China Sea based on vertical structure of water temperature[J]. South China Fisheries Science, 2018, 14(2): 124-128. DOI: 10.3969/j.issn.2095-0780.2018.02.017
shu

Fishing ground analysis of Japanese horse mackerel in northern South China Sea based on vertical structure of water temperature

  • 1.

    Key Field Scientific Experimental Station of South China Sea Fishery Resource and Environment, Ministry of Agriculture; South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China

  • 2.

    College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China

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  • Received Date: September 14, 2017
  • Revised Date: November 28, 2017
  • Available Online: January 07, 2019
    Graphical Abstract
    • Abstract
  • According to the survey data of the investigation of offshore resources in the northern South China Sea during 2014−2015, we analyzed the relationship among the fishing ground, vertical structure of temperature and water temperature in that area. The results show that the location of fishing ground was closely related to water temperature gradient, and the correlation coefficient of location of fishing ground and temperature gradient was different in different seasons. The correlation between location of fishing ground and temperature gradients of 20−25 m water layer was the highest in spring survey. There was high correlation between location of fishing ground and at the surface layer and 50 m water layer in summer survey. The location of fishing ground was closely related to the water layer of 10−15 m in autumn survey, and the correlation between fishing location and temperature gradient at 15−20 m water layer was the highest in winter survey. It is also found that the fishing ground of the northern South China Sea was sensitive to the change of water temperature gradient. The fishing ground was mainly located in the Beibu Gulf in spring and summer, and mainly in the sea area near the east of Hainan Island in Leizhou Peninsula during autumn and winter.
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    • References (25)
  • [1]
    陈国宝, 邱永松. 南海北部竹䇲鱼的生长、死亡及合理利用[J]. 湛江海洋大学学报, 2004, 24(1): 35-40.
    [2]
    SASSA C, TSUKAMOTO Y, NISHIUCHI K, et al. Spawning ground and larval transport processes of jack mackerel Trachurus japonicus in the shelf-break region of the southern East China Sea[J]. Cont Shelf Res, 2008, 28(18): 2574-2583.
    [3]
    杨吝, 张旭丰, 谭永光, 等. 南海北部灯光罩网渔获组成及其对渔业资源的影响[J]. 南方水产, 2009, 5(4): 41-46.
    [4]
    黄洪亮, 陈雪忠. 东南太平洋智利竹䇲鱼中层拖网捕捞技术[J]. 中国水产科学, 2005, 12(1): 99-103.
    [5]
    陈春光, 张敏, 邹晓荣, 等. 东南太平洋智利竹䇲鱼中心渔场的月间变动研究[J]. 南方水产科学, 2014, 10(5): 60-67.
    [6]
    牛明香, 李显森, 徐玉成. 智利外海竹䇲鱼中心渔场时空变动的初步研究[J]. 海洋科学, 2009, 33(11): 105-109.
    [7]
    张衡, 崔雪森, 樊伟. 基于遥感数据的智利竹䇲鱼渔场预报系统[J]. 农业工程学报, 2012, 28(15): 140-144.
    [8]
    张衡, 张胜茂. 东南太平洋智利竹䇲鱼渔场及单位捕捞努力量的时空分布[J]. 生态学杂志, 2011, 30(6): 1142-1146.
    [9]
    化成君, 张衡, 樊伟. 东南太平洋智利竹䇲鱼资源和渔场的时空变化[J]. 生态学报, 2011, 31(19): 5676-5681.
    [10]
    ZHANG C I, LEE J B. Stock assessment and management implications of horse mackerel (Trachurus japonicus) in Korean waters, based on the relationships between recruitment and the ocean environment[J]. Prog Oceanog, 2001, 49(1/2/3/4, SI): 513-537.
    [11]
    牛明香, 李显森, 徐玉成. 基于广义可加模型的时空和环境因子对东南太平洋智利竹䇲鱼渔场的影响[J]. 应用生态学报, 2010, 21(4): 1049-1055.
    [12]
    SASSA C, YAMAMOTO K, TSUKAMOTO Y, et al. Distribution and migration of age-0 Jack mackerel (Trachurus japonicus) in the East China and Yellow Seas, based on seasonal bottom trawl surveys[J]. Fish Oceanogr, 2009, 18(4): 255-267.
    [13]
    XIE S, WATANABE Y, SARUWATARI T, et al. Growth and morphological development of sagittal otoliths of larval and early juvenile Trachurus japonicus[J]. J Fish Biol, 2005, 66(6): 1704-1719.
    [14]
    王迎宾, 郑基, 郑献之, 等. 舟山渔场禁渔线以外海域单拖网鱼类群落结构变动分析[J]. 南方水产科学, 2012, 8(1): 8-15.
    [15]
    陈新军. 灰色系统理论在渔业科学中的应用[M]. 北京: 中国农业出版社, 2003: 89-93.
    [16]
    杜荣骞. 生物统计学[M]. 北京: 高等教育出版社, 2003: 138-147.
    [17]
    孙铭帅, 陈作志, 蔡研聪, 等. 空间插值法在北部湾渔业资源密度评估中的应用[J]. 中国水产科学, 2017, 24(4): 853-861.
    [18]
    陈新军, 陈峰, 高峰, 等. 基于水温垂直结构的西北太平洋柔鱼栖息地模型构建[J]. 中国海洋大学学报(自然科学版), 2012, 42(6): 52-60.
    [19]
    陈峰, 陈新军, 刘必林, 等. 西北太平洋柔鱼渔场与水温垂直结构关系[J]. 上海海洋大学学报, 2010, 19(4): 495-504.
    [20]
    崔雪森, 伍玉梅, 张晶, 等. 基于分类回归树算法的东南太平洋智利竹䇲鱼渔场预报[J]. 中国海洋大学学报, 2012, 42(Z2): 53-59.
    [21]
    杨胜龙, 马军杰, 伍玉梅, 等. 印度洋大眼金枪鱼和黄鳍金枪鱼渔场水温垂直结构的季节变化[J]. 海洋科学, 2012, 36(7): 97-103.
    [22]
    易倩, 陈新军. 基于信息增益法选取柔鱼中心渔场的关键水温因子[J]. 上海海洋大学学报, 2012, 21(3): 425-430.
    [23]
    郭爱, 陈新军. 利用水温垂直结构研究中西太平洋鲣鱼栖息地指数[J]. 海洋渔业, 2009, 31(1): 1-9.
    [24]
    胡振明, 陈新军, 周应祺. 秘鲁外海茎柔鱼渔场分布和水温结构的关系[J]. 水产学报, 2009, 33(5): 770-777.
    [25]
    许永久, 张敏. 东南太平洋智利竹䇲鱼渔场浮游生物数量分布及与渔场关系[J]. 海洋渔业, 2007, 29(4): 289-295.
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