根据2003年连云港海州湾渔业生态修复水域的本底调查资料,应用Ecopath with Ecosim(Ew E)软件中的Ecopath模块,本研究构建了该区域的生态系统能量流动简易模型,初步评估了该区域的初始生态系统稳定性。结果表明:连云港海州湾渔业生态修复水域初始生态系统能量流动主要以牧食食物链为主,54.00%的能量通过牧食食物链向上传递。系统各功能组营养级在1.00~4.37。系统总流量为21946.70t/km^2/a,系统总初级生产力9500.00 t/km^2/a。系统的能量流动主要集中在6个营养级,来自初级生产者的转化效率为14.20%,来自碎屑的转化效率为13.60%,系统平均转化效率为13.80%。系统初级生产力与总呼吸量的比值为4.51,连接指数为0.27,杂食指数为0.21,Finn循环指数为2.62%,平均能流路径为2.22。连云港海州湾渔业生态修复水域生态系统的成熟度和稳定性较低,系统尚未发展成熟,还有较大的发展空间,可为鱼类等主要消费群体提供较多的能量供给。本研究结果可为海州湾人工鱼礁效果评价提供重要的基础数据。
El Nio events in the central equatorial Pacific (CP) are gaining increased attention,due to their increasing intensity within the global warming context.Various physical processes have been identified in the climate system that can be responsible for the modulation of El Nio,especially the effects of interannual salinity variability.In this work,a comprehensive data analysis is performed to illustrate the effects of interannual salinity variability using surface and subsurface salinity fields from the Met Office ENSEMBLES (EN3) quality controlled ocean dataset.It is demonstrated that during the developing phase of an El Nio event,a negative sea surface salinity (SSS) anomaly in the western-central basin acts to freshen the mixed layer (ML),decrease oceanic density in the upper ocean,and stabilize the upper layers.These related oceanic processes tend to reduce the vertical mixing and entrainment of subsurface water at the base of the ML,which further enhances the warm sea surface temperature (SST) anomalies associated with the El Nio event.However,the effects of interannually variable salinity are much more significant during the CP-El Nio than during the eastern Pacific (EP) El Nio,indicating that the salinity effect might be an important contributor to the development of CP-El Nio events.
ZHENG Fei 1,WAN Li-Ying 2,and WANG Hui 3 1 International Center for Climate and Environment Science (ICCES),Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China 2 Key Laboratory of Research on Marine Hazards Forecasting,National Marine Environmental Forecasting Center,Beijing 100081,China 3 National Meteorological Center,Beijing 100081,China