The Effect of the Marine Environment on the Distribution of Sthenoteuthis oualaniensis in the East Equatorial Indian Ocean

文献类型： 外文期刊

第一作者： Liu, Shigang

作者： Liu, Shigang;Zhang, Liyan;Kang, Jianhua;Song, Puqing;Miao, Xing;Lin, Longshan;Wang, Rui;Li, Yuan;Zhang, Liyan;Lian, Peng

作者机构：

关键词： east equatorial Indian Ocean; environmental factors; distribution; generalized additive model; Symplectoteuthis oualaniensis

期刊名称：FISHES （ 影响因子：2.4； 五年影响因子：2.4 ）

ISSN：

年卷期： 2025 年 10 卷 4 期

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收录情况： SCI

摘要： Sthenoteuthis oualaniensis is one of the most commercially important marine cephalopod species distributed throughout tropical and subtropical waters of the Indo-Pacific Seas. The Indian Ocean is a main fishing ground for S. oualaniensis with a high population density. To explore the distribution of S. oualaniensis in the east equatorial Indian Ocean, four surveys were carried out using light-lift-net fishing vessels. Meanwhile, marine environmental data were also collected, including the sea surface temperature, sea temperature at 100 m depth, mixed layer depth, sea surface chlorophyll-a concentration, sea surface height, and eddy kinetic energy. Generalized Additive Models were used to analyze the relationship between the catch per unit effort (CPUE) for S. oualaniensis and environmental factors. The results showed that the average CPUE of S. oualaniensis was 14.55 kg/h in the four surveys, which was considerably lower than in the South China Sea and Northwest Indian Ocean. In terms of seasonal distribution, the high-CPUE stations were closer to the continental shelf in spring, while they shifted towards the deeper and offshore water in autumn, demonstrating a seasonal migration trend. Pearson correlation analysis showed that CPUE reflected a significant negative correlation with both sea temperature at 100 m depth and eddy kinetic energy (p < 0.001). The Generalized Additive Models revealed that sea surface height was the most significant factor affecting CPUE with a variance explanation of 30.1%. Furthermore, the optimal CPUE prediction model was established by stepwise regression, which contains two factors, sea surface height and eddy kinetic energy, with a variance explanation of 34.9%. This study provides insights into the environmental factors influencing the distribution of S. oualaniensis, which is essential for the sustainable utilization and management of this species.

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