Development of a three-dimensional growth prediction model for the Japanese scallop in Funka Bay, Japan, using OGCM and MODIS

Author:

Liu Yang1,Saitoh Sei-Ichi12,Ihara Yu3,Nakada Satoshi4,Kanamori Makoto5,Zhang Xun2,Baba Katsuhisa6,Ishikawa Yoichi7,Hirawake Toru12

Affiliation:

1. Arctic Research Center, Hokkaido University, Kita-21 Nishi-11 Kita-ku, Sapporo 001-0021, Japan

2. Laboratory of Marine Bioresource and Environment Sensing, Faculty of Fisheries Sciences, Hokkaido University, 3-1-1 Minato, Hakodate, Hokkaido 041-8611, Japan

3. Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan

4. Faculty of Maritime Sciences, Kobe University, 5-1-1, Fukae-minamimachi, Higashinada-ku, Kobe 658-0022, Japan

5. Hakodate Fisheries Research Institute, Fisheries Research Department, Hokkaido Research Organization, Bentencho, Hakodate, Hokkaido 040-0051, Japan

6. Fisheries Research Department, Hokkaido Research Organization, 38, Hamamachi, Yoichi, Hokkaido 046-8555, Japan

7. Data Research Center for Marine-Earth Sciences, Japan Agency for Marine Earth-Science and Technology (JAMSTEC), 3173-25 Showamachi, Kanazawa-ward Yokohama, Kanagawa 236-0001, Japan

Abstract

Abstract The Japanese scallop (Patinopecten (Mizuhopecten) yessoensis) is an important commercial species in Funka Bay, Japan, where it is farmed using the hanging culture method. Our study was based on 6 years (from 2006 to 2011) of monthly in situ observations of scallop growth at Yakumo station. To produce a basic spatial distribution dataset, we developed an interpolation solution for the shortage of Chl-a concentration data available from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. Additionally, we integrated four-dimensional variational (4D-VAR) assimilation water temperature data from ocean general circulation models (OGCMs), with four vertical levels (6, 10, 14, and 18 m) from the sea surface. Statistical models, including generalized additive models (GAMs) and generalized linear models, were applied to in situ observation data, satellite data, and 4D-VAR data to identify the influence of environment factors (interpolated Chl-a, temperature, and depth) on the growth of scallops, and to develop a three-dimensional growth prediction model for the Japanese scallops in Funka Bay. We considered three methods to simulate the growth process of scallops (accumulation, summation, and product), and used them to select the most suitable model. All the interpolated Chl-a concentrations and 4D-VAR temperature data were verified by shipboard data. The results revealed that GAM, using an accumulation method that was based on a combination of integrated temperature, integrated log Chl-a, depth, and number of days, was best able to predict the vertical and spatial growth of the Japanese scallop. The predictions were verified by in situ observations from different depths (R2 = 0.83–0.94). From the distribution of three-dimensional predicted scallop growth maps at each depth, it was suggested that the growth of the Japanese scallop was most favourable at 6 m and least favourable at 18 m, although variations occurred in each aquaculture region in different years. These variations were probably due to the ocean environment and climate variation.

Publisher

Oxford University Press (OUP)

Subject

Ecology,Aquatic Science,Ecology, Evolution, Behavior and Systematics,Oceanography

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