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Volume 44 Issue 2
Feb.  2022
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Article Contents
Wu Zhen,Zhang Chongliang,Xue Ying, et al. Spatial heterogeneity of demersal fish in the offshore waters of Shandong[J]. Haiyang Xuebao,2022, 44(2):21–28 doi: 10.12284/hyxb2022072
Citation: Wu Zhen,Zhang Chongliang,Xue Ying, et al. Spatial heterogeneity of demersal fish in the offshore waters of Shandong[J]. Haiyang Xuebao,2022, 44(2):21–28 doi: 10.12284/hyxb2022072

Spatial heterogeneity of demersal fish in the offshore waters of Shandong

doi: 10.12284/hyxb2022072
  • Received Date: 2021-08-13
  • Rev Recd Date: 2021-12-06
  • Available Online: 2021-12-25
  • Publish Date: 2022-02-01
  • According to the bottom trawl survey data of fishery resources in the offshore waters of Shandong from 2016 to 2017, the spatial autocorrelation and spatial heterogeneity of demersal fish in the offshore waters of Shandong were examined by using spatial autocorrelation indices and variogram. The results showed that there were significant spatial aggregation patterns and spatial autocorrelation in the demersal fish in the offshore waters of Shandong. The spatial autocorrelations were strong in spring, summer and winter, and weak in autumn. From the perspective of spatial distribution, the areas of high relative abundance index of demersal fish were mainly located in the southern waters of Shandong in spring and summer, and areas of high relative abundance greatly decreased in autumn and winter, while the areas of low value were mainly in the Laizhou Bay and adjacent waters in four seasons. The parameters of variogram showed that there was a strong nugget effect in autumn, and the spatial heterogeneity of random part accounted for 76.0% of the total spatial heterogeneity. The spatial heterogeneity of random part in spring, summer and winter only accounted for 26.2%, 27.7% and 23.6% of the total spatial heterogeneity. In the spatial autocorrelation and spatial heterogeneity of demersal fish showed seasonal variation in the offshore waters of Shandong, which was to some extent related with changes in environmental factors such as water temperature.
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  • [1]
    Planque B, Loots C, Petitgas P, et al. Understanding what controls the spatial distribution of fish populations using a multi-model approach[J]. Fisheries Oceanography, 2011, 20(1): 1−17. doi: 10.1111/j.1365-2419.2010.00546.x
    [2]
    李哈滨, 王政权, 王庆成. 空间异质性定量研究理论与方法[J]. 应用生态学报, 1998, 9(6): 651−657. doi: 10.3321/j.issn:1001-9332.1998.06.018

    Li Habin, Wang Zhengquan, Wang Qingcheng. Theory and methodology of spatial heterogeneity quantification[J]. Chinese Journal of Applied Ecology, 1998, 9(6): 651−657. doi: 10.3321/j.issn:1001-9332.1998.06.018
    [3]
    唐启升, 叶懋中. 山东近海渔业资源开发与保护[M]. 北京: 中国农业出版社, 1990: 139−154.

    Tang Qisheng, Ye Maozhong. Exploitation and Protection of Fishery Resources in the Offshore Waters of Shandong[M]. Beijing: China Agriculture Press, 1990: 139−154.
    [4]
    程济生. 黄渤海近岸水域生态环境与生物群落[M]. 青岛: 中国海洋大学出版社, 2004: 209−218.

    Cheng Jisheng. Ecological Environment and Biological Community in the Coastal Waters of the Yellow Sea and the Bohai Sea[M]. Qingdao: China Ocean University Press, 2004: 209−218.
    [5]
    Matheron G. Principles of geostatistics[J]. Economic Geology, 1963, 58(8): 1246−1266. doi: 10.2113/gsecongeo.58.8.1246
    [6]
    Petitgas P, Woillez M, Rivoirard J, et al. Handbook of geo-statistics in R for fisheries and marine ecology[R]. Denmark: ICES, 2017.
    [7]
    Rossi R E, Mulla D J, Journel A G, et al. Geostatistical tools for modeling and interpreting ecological spatial dependence[J]. Ecological Monographs, 1992, 62(2): 277−314. doi: 10.2307/2937096
    [8]
    Platt T, Denman K L. Spectral analysis in ecology[J]. Annual Review of Ecology and Systematics, 1975, 6: 189−210. doi: 10.1146/annurev.es.06.110175.001201
    [9]
    Rivoirard J, Simmonds J, Foote KG, et al. Geostatistics for Estimating Fish Abundance[M]. Oxford: Blackwell Science, 2000.
    [10]
    Sullivan P J. Stock abundance estimation using depth-dependent trends and spatially correlated variation[J]. Canadian Journal of Fisheries and Aquatic Sciences, 1991, 48(9): 1691−1703. doi: 10.1139/f91-201
    [11]
    Simard Y, Marcotte D, Bourgault G. Exploration of geostatistical methods for mapping and estimating acoustic biomass of pelagic fish in the Gulf of St. Lawrence: Size of echo-integration unit and auxiliary environmental variables[J]. Aquatic Living Resources, 1993, 6(3): 185−199. doi: 10.1051/alr:1993020
    [12]
    苏奋振, 周成虎, 仉天宇, 等. 东海水域中上层鱼类资源的空间异质性[J]. 应用生态学报, 2003, 14(11): 1971−1975. doi: 10.3321/j.issn:1001-9332.2003.11.037

    Su Fenzhen, Zhou Chenghu, Zhang Tianyu, et al. Spatial heterogeneity of pelagic fishery resources in the East China Sea[J]. Chinese Journal of Applied Ecology, 2003, 14(11): 1971−1975. doi: 10.3321/j.issn:1001-9332.2003.11.037
    [13]
    苏奋振, 周成虎, 史文中, 等. 东海区底层及近底层鱼类资源的空间异质性[J]. 应用生态学报, 2004, 15(4): 683−686. doi: 10.3321/j.issn:1001-9332.2004.04.029

    Su Fenzhen, Zhou Chenghu, Shi Wenzhong, et al. Spatial heterogeneity of demersal fish in East China Sea[J]. Chinese Journal of Applied Ecology, 2004, 15(4): 683−686. doi: 10.3321/j.issn:1001-9332.2004.04.029
    [14]
    张寒野, 程家骅. 东海区小黄鱼空间格局的地统计学分析[J]. 中国水产科学, 2005, 12(4): 419−423. doi: 10.3321/j.issn:1005-8737.2005.04.009

    Zhang Hanye, Cheng Jiahua. Geostatistical analysis on spatial patterns of small yellow croaker (Larimichthys polyactis) in the East China Sea[J]. Journal of Fishery Science of China, 2005, 12(4): 419−423. doi: 10.3321/j.issn:1005-8737.2005.04.009
    [15]
    杨铭霞. 基于地统计学的西北太平洋柔鱼资源丰度空间变异研究[D]. 上海: 上海海洋大学, 2014.

    Yang Mingxia. Spatial variability of abundance index for Ommastrephes bartramii in the Northwest Pacific Ocean based on geostatistical methods[D]. Shanghai: Shanghai Ocean University, 2014.
    [16]
    中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. GB/T 12763.6−2007, 海洋调查规范 第6部分: 海洋生物调查[S]. 北京: 中国标准出版社 2007.

    General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China, Standardization Administration of the People’s Republic of China. GB/T 12763.6−2007, Specifications for oceanographic survey—Part 6: Marine biological survey[S]. Beijing: Standards Press of China, 2007.
    [17]
    中华人民共和国农业部. SC/T 9403−2012, 海洋渔业资源调查规范[S]. 北京: 中国农业出版社, 2013.

    Ministry of Agriculture of the PRC. SC/T 9403−2012, Technical specification for marine fishery resources survey[S]. Beijing: China Agriculture Press, 2013.
    [18]
    梁严威. 基于地统计和ESDA的东南太平洋智利竹筴鱼时空动态的研究[D]. 上海: 上海海洋大学, 2015.

    Liang Yanwei. Temporal dynamics of Trachurus murphyi in the Southeast Pacific based on geostatistical methods and ESDA[D]. Shanghai: Shanghai Ocean University, 2015.
    [19]
    汤国安, 杨昕. ArcGIS地理信息系统空间分析实验教程[M]. 2版. 北京: 科学出版社, 2012: 439−442.

    Tang Guoan, Yang Xin. Experimental Course of Spatial Analysis of GIS in ArcGIS[M]. 2nd ed. Beijing: Science Press, 2012: 439−442.
    [20]
    Mitchel A, Griffin L S. The ESRI Guide to GIS Analysis, Volume 2: Spatial Measurements and Statistics[M]. Redlands: ESRI Press, 2005.
    [21]
    冯永玖, 陈新军, 杨铭霞, 等. 基于ESDA的西北太平洋柔鱼资源空间热点区域及其变动研究[J]. 生态学报, 2014, 34(7): 1841−1850.

    Feng Yongjiu, Chen Xinjun, Yang Mingxia, et al. An exploratory spatial data analysis-based investigation of the hot spots and variability of Ommastrephes bartramii fishery resources in the northwestern Pacific Ocean[J]. Acta Ecologica Sinica, 2014, 34(7): 1841−1850.
    [22]
    Getis A, Ord J K. The analysis of spatial association by use of distance statistics[J]. Geographical Analysis, 1992, 24(3): 189−206.
    [23]
    Anselin L. Local indicators of spatial association-LISA[J]. Geographical Analysis, 1995, 27(2): 93−115.
    [24]
    张松林, 张昆. 空间自相关局部指标Moran指数和G系数研究[J]. 大地测量与地球动力学, 2007, 27(3): 31−34.

    Zhang Songlin, Zhang Kun. Contrast study on Moran and Getis−Ord indexes of local spatial autocorrelation indices[J]. Journal of Geodesy and Geodynamics, 2007, 27(3): 31−34.
    [25]
    孙洪泉. 地质统计学及其应用[M]. 徐州: 中国矿业大学出版社, 1990: 59−96.

    Sun Hongquan. Geostatistics and Its Application[M]. Xuzhou: China University of Mining and Technology Press, 1990: 59−96.
    [26]
    王政权. 地统计学及在生态学中的应用[M]. 北京: 科学出版社, 1999: 65−101.

    Wang Zhengquan. Geostatistics and Its Application in Ecology[M]. Beijing: Science Press, 1999: 65−101.
    [27]
    杨晓明, 戴小杰, 朱国平. 基于地统计分析西印度洋黄鳍金枪鱼围网渔获量的空间异质性[J]. 生态学报, 2012, 32(15): 4682−4690. doi: 10.5846/stxb201112011840

    Yang Xiaoming, Dai Xiaojie, Zhu Guoping. Geostatistical analysis of spatial heterogeneity of Yellowfin Tuna (Thunnus albacares) purse seine catch in the western Indian Ocean[J]. Acta Ecologica Sinica, 2012, 32(15): 4682−4690. doi: 10.5846/stxb201112011840
    [28]
    刘璋温. 赤池信息量准则AIC及其意义[J]. 数学的实践与认识, 1980(3): 64−72.

    Liu Zhangwen. Akaike’s information criterion and its significance[J]. Journal of Mathematics in Practice and Theory, 1980(3): 64−72.
    [29]
    陈新军, 刘必林. 渔业资源生物学[M]. 北京: 科学出版社, 2017: 157−161.

    Chen Xinjun, Liu Bilin. Fishery Resources Biology[M]. Beijing: Science Press, 2017: 157−161.
    [30]
    任一平. 渔业资源生物学[M]. 北京: 中国农业出版社, 2020: 46−53.

    Ren Yiping. Biology of Fishery Resources[M]. Beijing: China Agriculture Press, 2020: 46−53.
    [31]
    石强. 渤、黄海冬、夏季节风生流场年际变化时空模态与环流变异[J]. 应用海洋学学报, 2019, 38(1): 93−108. doi: 10.3969/J.ISSN.2095-4972.2019.01.011

    Shi Qiang. Spatiao-temporal modes and circulation variation on the interannual variation of seasonal mean wind-driven current field in the Bohai Sea and Yellow Sea in winter and summer[J]. Journal of Applied Oceanography, 2019, 38(1): 93−108. doi: 10.3969/J.ISSN.2095-4972.2019.01.011
    [32]
    王小荟. 海州湾主要鱼种的空间分布及其与环境因子的关系[D]. 青岛: 中国海洋大学, 2013.

    Wang Xiaohui. Spatial distribution of dominant fish species in Haizhou Bay and their relationships with environmental factors[D]. Qingdao: Ocean University of China, 2013.
    [33]
    张芸欣. 东海区小眼绿鳍鱼渔业生物学特性研究[D]. 舟山: 浙江海洋大学, 2019.

    Zhang Yunxin. Study on the biological characteristics of C. kumu fishery in the East China Sea area[D]. Zhoushan: Zhejiang Ocean University, 2019.
    [34]
    周志鹏. 黄海细纹狮子鱼种群生物学特征的季节变化和年际变化[D]. 上海: 上海海洋大学, 2012.

    Zhou Zhipeng. Interannual and seasonal variances of population biological characteristic of snailfish, Liparis tanakae in Yellow Sea[D]. Shanghai: Shanghai Ocean University, 2012.
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