Predicting the larval transport of Pacific oyster Crassostrea gigas during the seedling collection season. (11th September 2020)

• Record Type: Journal Article
• Authors: Kakehi, Shigeho; Shirai, Hidekazu; Magome, Shinya; Takagi, Takamasa; Okabe, Katsuaki; Takayanagi, Kazufumi; Hamaguchi, Masami; Ito, Hiroshi; Kamiyama, Takashi
• Is Part Of: Fisheries oceanography. Volume 29:Number 6(2020)
• Page Start: 484
• Page End: 504
• Publication Date: 2020-09-11
• Subjects: finite volume community ocean model -- hindcast -- larval transport -- Matsushima Bay -- Pacific oyster -- prediction -- seedling collection; Fishery oceanography -- Periodicals; 639.2
• DOI: 10.1111/fog.12491
• Languages: English
• ISSNs: 1054-6006

Abstract

Abstract: The collection of wild oyster seedlings is an integral part of Pacific oyster aquaculture, necessitating efficient methods of seedling collection. Matsushima Bay is a key area for the production of oyster seedlings in Japan. To predict the transport of oyster larvae in the bay during the 2017 seedling collection season, we conducted particle tracking based on the finite volume community ocean model. Larval sampling was conducted early in the seedling collection season to observe the horizontal distribution of hatched larvae, which was then used as the initial distribution for particle tracking. Particle tracking was driven by the predicted tidal elevation, past meteorological forcing variables, and historical river discharges from the period of June–July 2015. This yielded a prediction of larval distribution after one week had elapsed. The location of the predicted daily highest density was predominantly on the eastern side of the bay and did not change considerably over time. The predicted larval distribution differed markedly from the observed distribution of pre‐attachment stage larvae, suggesting that processes other than the circulation in the bay influence actual larval transport. A model that included larval mortality and ontogenetic vertical migration was able to approximate the observed larval distribution, indicating the importance of these processes. Sensitivity analyses for the parameters relating these processes revealed that larvae tend to remain in the bay when they grow quickly. Although there were some differences between predicted and observed outcomes, our study represents notable progress in demonstrating the potential for predicting oyster larval transport.