南海中南部海域细鳞圆鲹资源密度与海洋环境因子的关系

Relationship between stock density of Decapterus macarellus and marine enviroental factors in central-southern South China Sea

  • 摘要: 细鳞圆鲹 (Decapterus macarellus) 是南海重要的中上层经济鱼类,也是南海灯光罩网渔业的主要捕捞对象。为揭示南海中南部细鳞圆鲹资源密度的时空变化特征及其关键环境驱动因子,基于2017、2020、2023年春季南海中南部渔业调查数据,结合8种海洋环境因子 海洋表面盐度 (Sea surface salinity, SSS)、海洋表面温度 (Sea surface temperature, SST)、海面高度 (Sea surface height, SSH)、叶绿素a (Chl a) 浓度、海水深度 (Ocean depth, Depth)、离岸距离 (Offshore distance, DIS)、温度梯度 (Temperature gradient, TGR) 和混合层厚度 (Mixed layer thickness, MLT),采用广义加性模型 (Generalized Additive Model, GAM) 分析了细鳞圆鲹资源密度与海洋环境之间的关系。通过皮尔逊相关系数、VIF检验和AIC准则进行模型优化。结果显示:南海中南部细鳞圆鲹渔场春季呈现明显的区域性分布差异,SST和Chl a浓度是影响资源密度的主要因子;最优GAM总偏差解释率为47.1%。研究表明,南海中南部细鳞圆鲹春季分布主要受海表温度、Chl a浓度和水深的共同影响,其中Chl a浓度对渔场渔获量的影响最为显著。

     

    Abstract: The mackerel scad (Decapterus macarellus), a commercially important pelagic species in the South China Sea, is a primary target for the light falling-net fishery in that region. To elucidate the spatio-temporal variation in the resource density of D. macarellus in the central-southern South China Sea and identify the key environmental factors, we analyzed the fishery survey data collected during the spring seasons of 2017, 2020 and 2023. Eight oceanographic variables were considered, including sea surface salinity (SSS), sea surface temperature (SST), sea surface height (SSH), chlorophyll a (Chl a) concentration, ocean depth (Depth), offshore distance (DIS), temperature gradient (TGR), and mixed layer thickness (MLT). We assessed the relationship between the resource density of D. macarellus and these environmental factors by using Generalized Additive Model (GAM), and optimized the model by using Pearson correlation coefficients, variance inflation factor (VIF) analysis, and the Akaike information criterion (AIC). The results reveal significant regional differences in the spring distribution of D. macarellus fishing grounds in the central-southern South China Sea. SST and Chl a concentration were the primary factors influencing resource density. The optimal GAM model explained 47.1% of the total deviance. The results suggest that the spring distribution of D. macarellus in that region is mainly influenced by a combination of SST, Chl a concentration and ocean depth, with Chl a concentration exerting the most pronounced effect on the fishery catches.

     

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