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Fishery analysis using gradient-dependent optimal interpolation

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Abstract

The current lack of high-precision information on subsurface seawater is a constraint in fishery research. Based on Argo temperature and salinity profiles, this study applied the gradient-dependent optimal interpolation to reconstruct daily subsurface oceanic environmental information according to fishery dates and locations. The relationship between subsurface information and matching yellowfin tuna (YFT) in the western and central Pacific Ocean (WCPO) was examined using catch data from January 1, 2008 to August 31, 2017. The seawater temperature and salinity results showed differences of less than ±0.5°C and ±0.01 compared with the truth observations respectively. Statistical analysis revealed that the most suitable temperature for YFT fishery was 28–29°C at the near-surface. The most suitable salinity range for YFT fishery was 34.5–36.0 at depths shallower than 300 m. The suitable upper and lower bounds on the depths of the thermocline were 90–100 m and 300–350 m, respectively. The thermocline characteristics were prominent, with a mean temperature gradient exceeding 0.08°C/m. These results indicate that the profiles constructed by gradient-dependent optimal interpolation were more accurate than those of the nearest profiles adopted.

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Acknowledgements

The research is supported by the China National Scientific Seafloor Observatory. We are grateful to the SKFC of China for providing us with the data from the WCPO purse seine fishery, the China Argo Real-time Data Center for the near-real-time observations, and the National Oceanographic Data Center for providing us with the climate data. We thank Wiley Editing Services (www.wileyauthors.com/eeo/preparation) for editing this manuscript.

Funding

The National Natural Science Foundation of China under contract No. 4210060098; the Foundation of Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources under contract No. A1-2006-21-200201.

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Authors and Affiliations

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

    Chunling Zhang & Danyang Wang

  2. Project Management Office of China National Scientific Seafloor Observatory, Tongji University, Shanghai, 200092, China

    Zhenfeng Wang

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  1. Chunling Zhang
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  2. Danyang Wang
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  3. Zhenfeng Wang
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Correspondence to Chunling Zhang or Zhenfeng Wang.

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Zhang, C., Wang, D. & Wang, Z. Fishery analysis using gradient-dependent optimal interpolation. Acta Oceanol. Sin. 41, 116–126 (2022). https://doi.org/10.1007/s13131-021-1895-y

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  • DOI: https://doi.org/10.1007/s13131-021-1895-y

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