Japan Geoscience Union Meeting 2023

Presentation information

[J] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-CG Complex & General

[A-CG40] Coastal Ecosystems - 1. Water Cycle and Land-Ocean Interactions

Thu. May 25, 2023 10:45 AM - 12:00 PM 102 (International Conference Hall, Makuhari Messe)

convener:Masahiko Fujii(Atmosphere and Ocean Research Institute, The University of Tokyo), Tomohiro Komorita(Faculty of Environmental and Symbiotic Sciences, Prefectural University of Kumamoto), Makoto Yamada(Faculty of Economics, Ryukoku University), Ryo Sugimoto(Faculty of Marine Biosciences, Fukui Prefectural University), Chairperson:Masahiko Fujii(Faculty of Environmental Earth Science), Ryo Sugimoto(Faculty of Marine Biosciences, Fukui Prefectural University)

11:30 AM - 11:45 AM

[ACG40-10] Prediction of potential fishing grounds of swordtip squid (Uroteuthis edulis) based on a physical-biochemical coupled model

*Takeshi Ito1, Katsumi Takayama, Naoki Hirose1 (1.Kyushu University)

Keywords:Habitat Suitability Index model, Lower trophic ecosystem model, Swordtip squid, Ocean data assimilation model

The swordtip squid (Uroteuthis edulis), which is eaten alive (lively squid) in northwest Kyushu, Japan, is aneconomically important fish species in the region. However, the total catch of this species in Japan has declined by more than 80% in the last three decades. To understand and predict the spatio-temporal distribution of fish species, we developed a one-dimensional ecosystem (NPZD) model and a habitat suitability index (HSI) model for southwest Iki Island, northwest Kyushu, Japan. Subsequently, we conducted three numerical experiments with the HSI model, with and without (only the physical data of the ocean) the NPZD model data (phytoplankton or zooplankton concentrations). In the HSI model with zooplankton concentrations, we found a stronger positive relationship between the HSI model values and the daily fisheries catch data of the swordtip squid than that using only the physical variables of the ocean as the environmental parameters. Thus, our study indicates that the performance of the fishing ground prediction model will improve by utilizing the lower trophic ecosystem model, such as zooplankton concentrations. Furthermore, our results would provide important implications for the conservation and management of this species and the efficiency of fishing operations.