To understand how hydrological and biological factors affect near-to off-shore variations in the siphonophore community,we sampled zooplankton at 82 stations in the northern South China Sea during summer,winter,and sp...To understand how hydrological and biological factors affect near-to off-shore variations in the siphonophore community,we sampled zooplankton at 82 stations in the northern South China Sea during summer,winter,and spring.Forty-one species of siphonophore were collected by vertical trawling.The species richness of siphonophores increased from the nearshore to offshore regions in all three seasons of investigation,with maximum richness in summer and minimum richness in winter.The abundance of siphonophores was also higher in summer than in spring and winter,concentrated in the nearshore region in the warm season and scattered in the offshore region in the cold season.Four siphonophore groups were classified according to the frequency of occurrence:nearshore,near-offshore,offshore,and tropical pelagic.Among them,the nearshore group had higher abundance nearshore compared with the offshore.The tropical pelagic group had higher species number offshore than nearshore.Spatial and temporal fluctuations in taxonomic composition and abundance of siphonophores were due to the influence of the coastal upwelling and surface ocean currents of the South China Sea,driven by the East Asia monsoonal system.展开更多
Sea surface temperature （SST） variation in the Subei coastal waters, East China, which is important for the ecological environment of the Yellow Sea where Enteromorphaprolifera blooms frequently, is affected by the ...Sea surface temperature （SST） variation in the Subei coastal waters, East China, which is important for the ecological environment of the Yellow Sea where Enteromorphaprolifera blooms frequently, is affected by the East Asian winter monsoon （EAWM）, El Nifio-Southem Oscillation （ENSO）, and Pacific Decadal Oscillation （PDO）. In this study, correlations between climatic events and SST anomalies （SSTA） around the Subei （North Jiangsu Province, East China） Coast from 1981-2012 are analyzed, using empirical orthogonal function （EOF） and correlation analyses. First, a key region was determined by EOF analysis to represent the Subei coastal waters. Then, coherency analyses were performed on this key region. According to the correlation analysis, the EAWM index has a positive correlation with the spring and summer SSTA of the key region. Furthermore, the Nifio3.4 index is negatively correlated with the spring and summer SSTA of the key region 1 year ahead, and the PDO has significant negative coherency with spring SSTA and negative coherency with summer SSTA in the key region 1 year ahead. Overall, PDO exhibits the most significant impact on SSTA of the key region. In the key region, all these factors are correlated more significantly with SSTA in spring than in summer. This suggests that outbreaks ofEnteromorpha prolifera in the Yellow Sea are affected by global climatic changes, especially the PDO.展开更多
Based on faults surveying and research data in the Tianjin offshore areas,through studying tectonic structure,Quaternary activity,deep structure,stress and strain fields and seismicity in the Tianjin offshore areas,th...Based on faults surveying and research data in the Tianjin offshore areas,through studying tectonic structure,Quaternary activity,deep structure,stress and strain fields and seismicity in the Tianjin offshore areas,the activity and tectonic features of the faults are determined synthetically.Using seismo-geological data,and the historical and modern seismicity data,the frequency-magnitude relationship model normalized by 500a is established and based on the relationship between the upper limit of maximum magnitude M u and a t/b,the maximum magnitudes of the sea section of the Haihe river fault and the Haiyi fault are calculated.Then Poisson probability model is adopted and the quantitative parameters,such as the maximum magnitude,occurrence probability,recurrence cycle of the faults in the south Tianjin offshore areas in the coming 50～200a,are calculated.展开更多
基金Supported by the Key Knowledge Innovation Program of Chinese Academy of Sciences(No.KZCX2-YW-Q07)the National Natural Science Foundation of China(Nos.31101619,41130855)the Chinese Offshore Investigation and Assessment(No.908-01-ST08)
文摘To understand how hydrological and biological factors affect near-to off-shore variations in the siphonophore community,we sampled zooplankton at 82 stations in the northern South China Sea during summer,winter,and spring.Forty-one species of siphonophore were collected by vertical trawling.The species richness of siphonophores increased from the nearshore to offshore regions in all three seasons of investigation,with maximum richness in summer and minimum richness in winter.The abundance of siphonophores was also higher in summer than in spring and winter,concentrated in the nearshore region in the warm season and scattered in the offshore region in the cold season.Four siphonophore groups were classified according to the frequency of occurrence:nearshore,near-offshore,offshore,and tropical pelagic.Among them,the nearshore group had higher abundance nearshore compared with the offshore.The tropical pelagic group had higher species number offshore than nearshore.Spatial and temporal fluctuations in taxonomic composition and abundance of siphonophores were due to the influence of the coastal upwelling and surface ocean currents of the South China Sea,driven by the East Asia monsoonal system.
基金Supported by the National Basic Research Program of China(973 Program)(No.2010CB950403)the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA11020301)+1 种基金the National Natural Science Foundation of China(No.41176018)the Special Fund for Marine Research in the Public Interest(No.201005006)
文摘Sea surface temperature （SST） variation in the Subei coastal waters, East China, which is important for the ecological environment of the Yellow Sea where Enteromorphaprolifera blooms frequently, is affected by the East Asian winter monsoon （EAWM）, El Nifio-Southem Oscillation （ENSO）, and Pacific Decadal Oscillation （PDO）. In this study, correlations between climatic events and SST anomalies （SSTA） around the Subei （North Jiangsu Province, East China） Coast from 1981-2012 are analyzed, using empirical orthogonal function （EOF） and correlation analyses. First, a key region was determined by EOF analysis to represent the Subei coastal waters. Then, coherency analyses were performed on this key region. According to the correlation analysis, the EAWM index has a positive correlation with the spring and summer SSTA of the key region. Furthermore, the Nifio3.4 index is negatively correlated with the spring and summer SSTA of the key region 1 year ahead, and the PDO has significant negative coherency with spring SSTA and negative coherency with summer SSTA in the key region 1 year ahead. Overall, PDO exhibits the most significant impact on SSTA of the key region. In the key region, all these factors are correlated more significantly with SSTA in spring than in summer. This suggests that outbreaks ofEnteromorpha prolifera in the Yellow Sea are affected by global climatic changes, especially the PDO.
基金funded by earthquake security infrastructure of Tianjin 11th "Five-year Plan" (Tianjin Development and Reforming Office[2009]-1230),the Spark Program of Earthquake Sciences(Grant No.XH13002)
文摘Based on faults surveying and research data in the Tianjin offshore areas,through studying tectonic structure,Quaternary activity,deep structure,stress and strain fields and seismicity in the Tianjin offshore areas,the activity and tectonic features of the faults are determined synthetically.Using seismo-geological data,and the historical and modern seismicity data,the frequency-magnitude relationship model normalized by 500a is established and based on the relationship between the upper limit of maximum magnitude M u and a t/b,the maximum magnitudes of the sea section of the Haihe river fault and the Haiyi fault are calculated.Then Poisson probability model is adopted and the quantitative parameters,such as the maximum magnitude,occurrence probability,recurrence cycle of the faults in the south Tianjin offshore areas in the coming 50～200a,are calculated.
