李东旭, 邹晓荣, 周淑婷. 中太平洋黄鳍金枪鱼CPUE时空分布及其与环境因子的关系[J]. 南方水产科学. DOI: 10.12131/20240047
引用本文: 李东旭, 邹晓荣, 周淑婷. 中太平洋黄鳍金枪鱼CPUE时空分布及其与环境因子的关系[J]. 南方水产科学. DOI: 10.12131/20240047
LI Dongxu, ZOU Xiaorong, ZHOU Shuting. Spatio-temporal distribution of Thunnus albacares CPUE and its relationship with environmental factors in central Pacific Ocean[J]. South China Fisheries Science. DOI: 10.12131/20240047
Citation: LI Dongxu, ZOU Xiaorong, ZHOU Shuting. Spatio-temporal distribution of Thunnus albacares CPUE and its relationship with environmental factors in central Pacific Ocean[J]. South China Fisheries Science. DOI: 10.12131/20240047

中太平洋黄鳍金枪鱼CPUE时空分布及其与环境因子的关系

Spatio-temporal distribution of Thunnus albacares CPUE and its relationship with environmental factors in central Pacific Ocean

  • 摘要: 中太平洋黄鳍金枪鱼(Thunnus albacares) 是中国金枪鱼延绳钓渔业的主要捕捞对象之一。为提高捕捞效率,促进资源可持续利用,利用2018—2022年中太平洋黄鳍金枪鱼延绳钓生产数据,结合不同水层的温度、叶绿素a浓度和海表盐度等环境因子,通过构建GAM和nodeGAM模型,分析了太平洋中部黄鳍金枪鱼单位捕捞努力量渔获量 (Catch perunit of effort, CPUE) 时空分布及其与环境因子的关系。结果表明:中太平洋黄鳍金枪鱼的盛渔期在5—7月,CPUE主要分布在赤道以南,在5°S附近最盛。与GAM模型 (偏差解释率为29.4%,均方误差为0.149) 相比,nodeGAM模型的拟合优度显著提高,偏差解释率达49.4% (提升68.02%),均方误差降至0.103 (降低30.87%)。2种模型均表明,表层温度≥27 °C、100 m水层温度15~20 °C、表层盐度34.2‰~35.2‰、叶绿素a质量浓度0.1~0.25 mg·m−3为黄鳍金枪鱼适宜的环境因子范围。与GAM模型相比,nodeGAM模型的拟合效果和解释能力更优,从模型输出的效应曲线来看,nodeGAM模型能更好地反映CPUE与环境因子间的非线性关系。

     

    Abstract: Yellowfin tuna (Thunnus albacares) is one of the primary target species in China's tuna longline fishing industry. In order to improve fishing efficiency and promote sustainable use of resources, based on the longline production data of T. albacares in central Pacific from 2018 to 2022, combining with the environmental factors, such as temperature at different water layers, concentration of chlorophyll a, and salinity of sea surface (SSS), we analyzed the spatio-temporal distribution of the catch perunit of effort (CPUE) of T. albacares in that sea area and its relationship with environmental factors by constructing two models (GAM and nodeGAM). The results show that the peak season of T. albacares in the central Pacific Ocean was from May to July, and the CPUE was mainly distributed in the southern equatorial Pacific, with the highest tuna catches near 5°S. Compared with the GAM model (Bias explained rate 29.4%, MSE 0.149), the nodeGAM model showed significantly better goodness-of-fit with a bias explained rate of 49.4% (68.02% enhancement), and the MSE reduced to 0.103 (Decrease of 30.87%). Both models indicate that T0 ≥27 °C, T100 of 15−20 °C, SSS of 34.2‰−35.2‰, and CHL-a concentration of 0.1−0.25 mg·m−3 were the suitable environmental ranges for T. albacares. Compared with the GAM model, the nodeGAM model has a better fitting effect and explanatory ability. According to the effect curves of the model output, the nodeGAM model can better reflect the nonlinear relationship between CPUE and environmental factors.

     

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