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Journal of Oceanology and Limnology

, Volume 36, Issue 3, pp 942–955 | Cite as

Examining spatiotemporal distribution and CPUE-environment relationships for the jumbo flying squid Dosidicus gigas offshore Peru based on spatial autoregressive model

  • Yongjiu Feng (冯永玖)
  • Xinjun Chen (陈新军)
  • Yang Liu (刘杨)
Article
  • 41 Downloads

Abstract

The spatiotemporal distribution and relationship between nominal catch-per-unit-effort (CPUE) and environment for the jumbo flying squid ( Dosidicus gigas ) were examined in offshore Peruvian waters during 2009–2013. Three typical oceanographic factors affecting the squid habitat were investigated in this research, including sea surface temperature (SST), sea surface salinity (SSS) and sea surface height (SSH). We studied the CPUE-environment relationships for D. gigas using a spatially-lagged version of spatial autoregressive (SAR) model and a generalized additive model (GAM), with the latter for auxiliary and comparative purposes. The annual fishery centroids were distributed broadly in an area bounded by 79.5°–82.7°W and 11.9°–17.1°S, while the monthly fishery centroids were spatially close and lay in a smaller area bounded by 81.0°–81.2°W and 14.3°–15.4°S. Our results show that the preferred environmental ranges for D. gigas offshore Peru were 20.9°–21.9°C for SST, 35.16–35.32 for SSS and 27.2–31.5 cm for SSH in the areas bounded by 78°–80°W/82–84°W and 15°–18°S. Monthly spatial distributions during October to December were predicted using the calibrated GAM and SAR models and general similarities were found between the observed and predicted patterns for the nominal CPUE of D. gigas. The overall accuracies for the hotspots generated by the SAR model were much higher than those produced by the GAM model for all three months. Our results contribute to a better understanding of the spatiotemporal distributions of D. gigas offshore Peru, and offer a new SAR modeling method for advancing fishery science.

Keyword

Dosidicus gigas spatiotemporal distribution generalized additive model (GAM) spatial autoregressive (SAR) model offshore Peru 

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Copyright information

© Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Yongjiu Feng (冯永玖)
    • 1
    • 2
    • 3
    • 4
  • Xinjun Chen (陈新军)
    • 1
    • 2
    • 3
    • 4
  • Yang Liu (刘杨)
    • 1
  1. 1.College of Marine SciencesShanghai Ocean UniversityShanghaiChina
  2. 2.The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources (Shanghai Ocean University)Ministry of EducationShanghaiChina
  3. 3.National Engineering Research Center for Oceanic Fisheries (Shanghai Ocean University)ShanghaiChina
  4. 4.Collaborative Innovation Center for Distant-water FisheriesShanghaiChina

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