Volume 11 Issue 2
Apr.  2015
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YANG Mingxia, CHEN Xinjun, FENG Yongjiu, GUAN Wenjiang. Analysis of fishing ground for Ommastrephes bartramii in the Northwest Pacific based on different statistical interpolation methods[J]. South China Fisheries Science, 2015, 11(2): 79-84. DOI: 10.3969/j.issn.2095-0780.2015.02.011
Citation: YANG Mingxia, CHEN Xinjun, FENG Yongjiu, GUAN Wenjiang. Analysis of fishing ground for Ommastrephes bartramii in the Northwest Pacific based on different statistical interpolation methods[J]. South China Fisheries Science, 2015, 11(2): 79-84. DOI: 10.3969/j.issn.2095-0780.2015.02.011
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Analysis of fishing ground for Ommastrephes bartramii in the Northwest Pacific based on different statistical interpolation methods

  • Key Lab. of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education; National Distant-Water Fisheries Engineering Research Center; Collaborative Innovation Center for Distant-Water Fisheries; College of Marine Sciences of Shanghai Ocean University; Shanghai 201306, China

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  • Received Date: June 02, 2014
  • Revised Date: September 06, 2014
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    • Abstract

  • Ommastrephes bartramii is one of the most important economic species caught by Chinese squid jigging fleets. Based on the abundance index (CPUE, catch per day in one fishing vessel) of O.bartramii from July to October in 2012, we applied five statistical interpolation methods (global polynomial, local polynomial, radial basis function, inverse distance weighted and ordinary Kriging) to analyze the fishing ground of O.bartramii in the Northwest Pacific. The results show that ordinary Kriging was the best method for analyzing CPUE distribution, followed by inverse distance weighted, radial basis function, global polynomial and local polynomial. The optimal method of ordinary kriging was considered as an example to predict the CPUE distribution from July to October, so as to obtain the change of monthly fishing ground distribution. Little difference was found between actual CPUE and predicted CPUE; the mean monthly CPUEs varied from 0.51 t · d-1 to 1.95 t · d-1 and their absolute errors were less than 0.15 t · d-1. Finally, we discussed the distribution of fishing ground and its variation by combining with marine environmental factors. It is indicated that ordinary Kriging interpolation method was suitable for forecasting the fishing ground of O.bartramii.

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