Volume 16 Issue 4
Aug.  2020
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FAN Xiumei, YANG Shenglong, ZHANG Shengmao, ZHU Wenbin, CUI Xuesen. Forecasting fishing ground of mackerel (Scomber australasicus) in Arabian Sea based on habitat suitability index[J]. South China Fisheries Science, 2020, 16(4): 8-17. DOI: 10.12131/20190255
Citation: FAN Xiumei, YANG Shenglong, ZHANG Shengmao, ZHU Wenbin, CUI Xuesen. Forecasting fishing ground of mackerel (Scomber australasicus) in Arabian Sea based on habitat suitability index[J]. South China Fisheries Science, 2020, 16(4): 8-17. DOI: 10.12131/20190255
shu

Forecasting fishing ground of mackerel (Scomber australasicus) in Arabian Sea based on habitat suitability index

  • 1.

    East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences/Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture and Rural Affairs, Shanghai 200090, China

  • 2.

    Key and Open Laboratory of Remote Sensing Information Technology in Fishing Resource, Chinese Academy of Fishery Sciences, Shanghai 200090, China

  • 3.

    Marine Fisheries Research Institute of Zhejiang, Zhoushan 316021, China

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  • Received Date: December 10, 2019
  • Revised Date: January 19, 2020
  • Accepted Date: April 09, 2020
  • Available Online: April 27, 2020
    Graphical Abstract
    • Abstract

  • In order to better understand and sustainably develop and utilize the mackerel (Scomber australasicus) resources in the Arabian Sea, according to the Chinese light purse seine production data of mackerel in the high sea of the Arabian Sea during the main fishing seasons (January, February, October and November) from 2016 to 2017, combining with the environmental data of sea surface temperature (SST), sea level anomaly (SLA), mixed-layer thickness (MLT), chlorophyll-a concentration (CHL), we established the habitat suitability index (HSI) models, which were based on catch (FC) and fishing times (FT), FC-HSI model and FT-HSI mo-del. In the sea area with HSI greater than 0.6, the actual catches in 2016 and 2017 accounted for 76.25% and 80.03%, respectively. Using the actual production data in 2018 to verify the prediction accuracy of FC-HSI and FT-HSI models, it is found that in the sea area with HSI greater than 0.6, the actual catches accounted for 45.68% and 50.15%, respectively, which indicates that the prediction result of FT-HSI model was slightly better than that of FC-HSI model. This study shows that the FT-HSI model based on SST, MLT, SLA and CHL can better predict the central fishing ground of mackerel in the Arabian Sea.

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    • References (31)
  • [1]
    杨胜龙, 范秀梅, 唐峰华, 等. 阿拉伯海鲐鱼渔场时空分布及其与海洋环境的关系[J]. 热带海洋学报, 2019, 38(4): 91-100.
    [2]
    郑元甲, 李建生, 张其永, 等. 中国重要海洋中上层经济鱼类生物学研究进展[J]. 水产学报, 2014, 38(1): 149-160.
    [3]
    李纲, 陈新军. 夏季东海渔场鲐鱼产量与海洋环境因子的关系[J]. 海洋学研究, 2009, 27(1): 1-8. doi: 10.3969/j.issn.1001-909X.2009.01.001
    [4]
    杨胜龙, 范秀梅, 伍玉梅, 等. 基于GAM模型的阿拉伯海鲐鱼渔场分布与环境关系[J]. 生态学杂志, 2019, 38(8): 2466-2470.
    [5]
    武胜男, 陈新军. 西北太平洋日本鲭渔业生物学和渔业海洋学研究进展[J]. 广东海洋大学学报, 2018, 38(2): 91-100. doi: 10.3969/j.issn.1673-9159.2018.02.013
    [6]
    CHEN X J, LI G, FENG B, et al. Habitat suitability index of chub mackerel (Scomber japonicus) from July to September in the East China Sea[J]. J Ocean, 2009, 65(1): 93-102. doi: 10.1007/s10872-009-0009-9
    [7]
    杨胜龙, 范秀梅, 张忭忭, 等. 阿拉伯海域围网渔场时空分布及其与海表环境因子的关系[J]. 中国农业科技导报, 2018, 21(9): 149-158.
    [8]
    龚彩霞, 陈新军, 高峰, 等. 栖息地适宜性指数在渔业科学中的应用进展[J]. 上海海洋大学学报, 2011, 20(2): 260-269.
    [9]
    LEE D, SON S, LEE C I, et al. Spatio-temporal variability of the Habitat Suitability Index for the Todarodes pacificus (Japanese common squid) around South Korea[J]. Remote Sens, 2019, 11(23): 2720. doi: 10.3390/rs11232720
    [10]
    ZHOU W, XU H, LI A, et al. Comparison of habitat suitability index models for purpleback flying squid (Sthenoteuthis oualaniensis) in the open South China Sea[J]. Appl Ecol Environ Res, 2019, 17(2): 4903-4913. doi: 10.15666/aeer/1702_49034913
    [11]
    陈新军, 刘必林, 田思泉, 等. 利用基于表温因子的栖息地模型预测西北太平洋柔鱼(Ommastrephes bartramii)渔场[J]. 海洋与湖沼, 2009, 40(6): 707-713. doi: 10.3321/j.issn:0029-814X.2009.06.006
    [12]
    郭刚刚, 张胜茂, 樊伟, 等. 基于表层及温跃层环境变量的南太平洋长鳍金枪鱼栖息地适应性指数模型比较[J]. 海洋学报, 2016, 38(10): 44-51.
    [13]
    蒋瑞, 陈新军, 雷林, 等. 秋冬季智利竹䇲鱼栖息地指数模型比较[J]. 水产学报, 2017, 41(2): 240-249.
    [14]
    KARA A B, ROCHFORD P A, HURLBURT H E. An optimal definition for ocean mixed layer depth[J]. J Geophysical Res (Oceans), 2000, 105(C7): 16803-16821. doi: 10.1029/2000JC900072
    [15]
    HUANG P Q, L U Y Z, ZHOU S Q. An objective method for determining ocean mixed layer depth with applications to WOCE data[J]. J Atmospheric Ocean Technol, 2018, 35(3): 441-458. doi: 10.1175/JTECH-D-17-0104.1
    [16]
    高璐, 许金电, 丘福文, 等. 阿拉伯海上层海温的双峰特征[J]. 应用海洋学学报, 2018, 37(2): 161-172. doi: 10.3969/J.ISSN.2095-4972.2018.02.002
    [17]
    雷茜, 罗红霞, 白林燕, 等. 阿拉伯海区域气溶胶时空动态变化及海域叶绿素a浓度特征[J]. 生态学报, 2019, 39(9): 3110-3120.
    [18]
    ZHANG Z, ZHANG Y, WANG W. Three-compartment structure of subsurface-intensified mesoscale eddies in the ocean[J]. J Geophysical Res (Oceans), 2017, 122(3): 1653-1664. doi: 10.1002/2016JC012376
    [19]
    李曰嵩, 潘灵芝, 严利平, 等. 基于个体模型的东海鲐鱼渔场形成机制研究[J]. 海洋学报, 2014, 36(6): 67-74.
    [20]
    CHAUHAN P, NAGUR C, MOHAN M, et al. Surface chlorophyll-a distribution in Arabian Sea and Bay of Bengal using IRS-P4 Ocean Colour Monitor satellite data[J]. Curr Sci, 2001, 80(2): 127-129.
    [21]
    郑宁宁, 孙丽, 丁宁, 等. 有害微藻抑藻细菌多样性及抑藻机制研究进展[J]. 微生物学通报, 2019, 46(5): 1204-1219.
    [22]
    崔雪森, 周为峰, 唐峰华, 等. 基于约束线性回归的柔鱼栖息地指数渔场预报模型构建[J]. 渔业科学进展, 2018, 39(1): 64-72. doi: 10.11758/yykxjz.20161207002
    [23]
    范江涛, 陈国宝, 陈作志. 基于栖息地指数的南海北部枪乌贼渔情预报模型构建[J]. 南方水产科学, 2017, 12(4): 11-16. doi: 10.3969/j.issn.2095-0780.2017.04.002
    [24]
    MADHUPRATAP M, NAIR K, GOPALAKRISHNAN T, et al. Arabian Sea oceanography and fisheries of the west coast of India[J]. Curr Sci, 2001, 81(4): 355-361.
    [25]
    MADHUPRATAP M, SHETYE S, NAIR K, et al. Fishery, problems and coastal oceanography[J]. Curr Sci, 1994, 66(5): 340-348.
    [26]
    赵辉, 齐义泉, 王东晓, 等. 南海叶绿素浓度季节变化及空间分布特征研究[J]. 海洋学报, 2005, 27(4): 45-52.
    [27]
    易炜, 郭爱, 陈新军. 不同环境因子权重对东海鲐鱼栖息地模型的影响研究[J]. 海洋学报, 2017, 39(12): 90-97.
    [28]
    SINGH R P, PRASAD A K, KAYETHA V K, et al. Enhancement of oceanic parameters associated with dust storms using satellite data[J]. J Geophysical Res (Oceans), 2008, 113, dioi: https://doi.org/10.1029/2008JC004815.
    [29]
    唐峰华, 杨胜龙, 范秀梅, 等. 基于Argo的西北太平洋公海柔鱼渔场垂直水温结构的变化特征[J]. 上海海洋大学学报, 2019, 28(3): 427-437.
    [30]
    杨胜龙, 张忭忭, 靳少非, 等. 中西太平洋延绳钓黄鳍金枪鱼渔场时空分布与温跃层关系[J]. 海洋学报, 2015, 37(6): 78-87.
    [31]
    王良明, 李渊, 张然, 等. 西北太平洋日本鲭资源丰度分布与表温和水温垂直结构的关系[J]. 中国海洋大学学报(自然科学版), 2019, 49(11): 29-38.
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