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1998—2018年全球主要远洋渔场海洋表面叶绿素a浓度变化及其与海表温度的关联性

Variations of sea surface chlorophyll a concentrations and their correlation with sea surface temperature in major global oceanic fishing grounds from 1998 to 2018

  • 摘要: 叶绿素a(Chl a)浓度作为浮游植物生物量的关键指标,已成为全球海洋生态系统研究的核心内容之一。然而,全球气候变化背景下,不同渔场Chl a浓度对物理环境变化的响应仍不明确。本研究针对1998—2018年全球主要远洋作业渔场海洋表面Chl a浓度的变化情况进行了深入分析,旨在量化Chl a浓度与海表温度(SST)及气候指数的响应变化规律。选取太平洋、大西洋和印度洋的8个重要渔场为研究区域,利用多传感器融合的且具有高时空连续性的全球海洋表面Chl a浓度月度卫星遥感数据集,结合基于局部加权回归的季节-趋势分解方法、趋势与时间序列特征量化及中介效应模型,量化Chl a浓度与SST及气候指数之间的关联。结果显示,不同渔场Chl a浓度的波动范围、标准差、趋势斜率、季节性强度、趋势强度、波动周期和变异系数存在显著区域差异。从纬度分布来看,高纬度渔场(如太平洋西北部和大西洋西南部)的Chl a浓度普遍较高且波动较大,而中低纬度(赤道附近)渔场的Chl a浓度较低且与气候指数的相关性更显著,这可能与赤道区域受厄尔尼诺-南方涛动(ENSO)事件主导的气候变率有关;从南北半球的趋势来看,北半球多数渔场(如太平洋西北部、太平洋西部、太平洋东部、大西洋中部)Chl a浓度呈下降趋势,而南半球部分区域(如大西洋西南部、印度洋西部)则多表现为上升趋势,其中太平洋东南部渔场的Chl a浓度虽呈上升趋势,但该趋势不显著,不具生态学意义,而印度洋东部渔场的Chl a浓度却呈下降趋势的特殊区域。此外,中介效应分析显示,海洋尼诺指数(ONI)、印度洋偶极子(IOD)、北大西洋涛动(NAO)和太平洋年代际振荡(PDO)4种气候指数通过SST对Chl a浓度产生显著影响的区域主要集中在太平洋西北部、西部、大西洋中部和印度洋东部等渔场。相关性研究和中介效应分析表明海洋生态系统(以Chl a浓度为指征)对气候变化的响应较为复杂且具有显著的区域差异性。未来气候变化对全球不同渔场的影响将呈现显著差异,需针对各渔场制定差异化的适应性管理策略。

     

    Abstract: Chlorophyll a (Chl a) concentration, a key indicator of phytoplankton biomass, has become a variable in global marine ecosystem research. However, in the context of global climate change, the responses of Chl a concentration to changes in the physical environment across different fishing grounds remain unclear. In this study, the variations in sea surface Chl a concentrations over major global oceanic fishing grounds from 1998 to 2018 were systematically analyzed, aiming to quantify the response pattern of Chl a concentration to sea surface temperature (SST), and climate indices. Eight important oceanic fishing grounds in the Pacific, Atlantic, and Indian Oceans were selected as the study regions. Using a multi-sensor fused, high spatiotemporal continuity monthly satellite remote sensing dataset of global sea surface Chl a concentration, combined with the Seasonal-Trend decomposition procedure based on LOESS (STL), quantification of trends and time-series characteristics, and a mediation effect model, the associations between Chl a concentration and SST, as well as climate indices were quantified. Results show that significant regional differences in the fluctuation range, standard deviation, trend slope, seasonal strength, trend strength, dominant periods, and coefficient of variation of Chl a concentration exist among those oceanic fishing grounds. From the perspective of latitudinal distribution, high-latitude oceanic fishing grounds (e.g., fishing ground in the northwestern Pacific and the southwestern Atlantic Oceans) generally present higher and more variable Chl a concentrations, while mid- to low-latitude (near-equatorial) fishing grounds show lower Chl a concentrations and higher significant correlations with climate indices, which may be associated with climate variability dominated by ENSO events in equatorial regions. From the perspective of the hemispheric distribution, Chl a concentrations in most northern hemisphere fishing grounds (e.g., the northwestern Pacific, western Pacific, eastern Pacific, and central Atlantic Oceans) tend to decrease, while in some southern hemisphere regions (e.g., the southwestern Atlantic and western Indian Oceans), it tends to increase. Specially in the southeastern Pacific Ocean Chl a concentration shows a positive but extremely weak correlation with no significant, and in the eastern Indian Ocean, it represents a decreasing trend. Furthermore, mediation analysis indicates that 4 climate indices, namely the Ocean Nino Index (ONI), the Indian Ocean Dipole (IOD), the North Atlantic Oscillation (NAO), and the Pacific Interdecadal Oscillation (PDO), had significant effects on Chl a concentrations through SST in fishing grounds located in the northwestern and western Pacific, the central Atlantic and the eastern Indian Oceans. Both correlation analysis and mediation analysis suggest that marine ecosystems (as indicated by Chl a concentration) respond to climate change in a complex manner with pronounced regional heterogeneity. Consequently, future climate change will affect global oceanic fishing grounds differently, necessitating tailored adaptive management strategies for each region.

     

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