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Developing short-term predictions for the distribution of Pacific oyster Crassostrea gigas larvae

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  • Aquaculture
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Abstract

To predict the larval transport of the Pacific oyster Crassostrea gigas, a particle tracking model using predicted tidal and residual currents has been developed for Matsushima Bay, Japan, a key area for the production of oyster seedlings. We conducted hydrographic observations to obtain three-dimensional distributions of temperature and salinity, which were used as the initial conditions for a residual current model. One-month forecast data for residual currents were calculated, being forced by historically averaged boundary conditions. The observed horizontal distribution of middle-sized larvae was used as the initial larval distribution for the particle tracking model. Prediction calculations of the particle tracking model were conducted for 3 days, during which time middle-sized larvae were assumed to grow to the pre-attachment stage. The predicted larval distribution was validated using the pre-attachment-stage larval distribution observed 3 days after middle-sized larval sampling. The drifting depth and mortality rate of larvae were estimated at 1.75 m and 0.430 day−1, respectively, from case studies related to these parameters. We aim to operate this model routinely and provide predictions of the distribution of pre-attachment stage oyster larvae. This will assist in installing collectors at appropriate times, leading to greater stability in seedling collection.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. The water-level data of the Naruse Rivers are downloaded from the Water Information System (http://www1.river.go.jp/, last accessed 12 May 2022).

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Acknowledgements

We thank Sanyo Techno Marine Inc. for providing mooring observational data. We also thank O. Ito and S. Takeshita, the captains of the chartered boats and K. Yokouchi of Japan Fisheries Research and Education Agency for their help in conducting the observations. We also thank M. Hamaguchi of Japan Fisheries Research and Education Agency for providing specific fluorescently labeled monoclonal antibodies for identifying Pacific oyster larvae and M. Satta of Seibutsu Seitai Kenkyusha, Ltd., for detecting and counting oyster larvae. We thank T. Arao, Y. Kashimura, and T. Watanabe of the National Agriculture and Food Research Organization and M. Hirai of IDEA Consultants, Inc. for their useful comments in conducting this research. This research was supported by the research program on development of innovative technology grants from the Project of the Bio-oriented Technology Research Advancement Institution (BRAIN). We thank Edanz English Editing Services (https://jp.edanz.com/ac) for editing the draft of this manuscript.

Funding

The research program on development of innovative technology grants from the Project of the Bio-oriented Technology Research Advancement Institution (BRAIN), 02001A, Shigeho Kakehi.

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Authors and Affiliations

  1. Shiogama Field Station, Fisheries Stock Assessment Center, Fisheries Resources Institute, Japan Fisheries Research and Education Agency, Shinhama-cho, Shiogama, Miyagi, 985-0001, Japan

    Shigeho Kakehi

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  1. Shigeho Kakehi
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S.K. designed the entire study, developed numerical models, conducted observations, analyzed obtained data, and wrote the manuscript.

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Correspondence to Shigeho Kakehi.

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Kakehi, S. Developing short-term predictions for the distribution of Pacific oyster Crassostrea gigas larvae. Fish Sci 88, 593–608 (2022). https://doi.org/10.1007/s12562-022-01621-1

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