To investigate the impacts of nutrient concentrations and N:P:Si ratios on the ecosystem of the Huanghai Sea (Yellow Sea), the current status and long-term variation of nutrients concentrations and ratios as well as phytoplankton community structure in the Huanghai Sea were collected and analyzed. The results reveal great annual and seasonal fluctuations in the nutrient concentrations and N:P:Si ratios during 1998-2008 with no clear pattern observed in the whole region. Yet on a seasonal scale of spring and in the coastal regions such as the Jiaozhou Bay and Sanggou Bay, the increase of DIN concentration and N:P ratio as well as the decrease of phosphate and silicate concentrations and Si:N ratios were relatively significant. Many pelagic ecosystem changes have occurred concurrent with these changes of the nutrient regime, such as the recent increase of primary production, changes of phytoplankton chlorophyll a biomass and abundance, an increase of eutrophication, and occurrence of HABs. In addition, new trends in the variation of nutrients seem to be developing in some particular transect such as 36°N, which suggests that long-term and systematic ecosystem monitoring in the Huanghai Sea is necessary. 相似文献
Samples were collected with a plankton net in the four seasonal cruises during 2006-2007 to study the seasonal variability of the zooplankton community in the southwest part of Huanghai Sea Cold Water Mass (HSCWM, Yellow Sea Cold Water Mass). The spatial and temporal variations of zooplankton species composition, biomass, abundance and biodiversity were examined. A total of 122 zooplankton species and 30 pelagic larvae were identified in the four cruises. Calanus sinicus and Aidanosagitta crassa were the most dominant species, and Themisto gaudichaudi and Euphausia pacifica were widely distributed in the HSCWM area. The spatial patterns of non-gelatinous zooplankton (removing the high water content groups) were similar to those of the total zooplankton biomass in autumn, but different significantly in the other three seasons. The seasonal means of zooplankton biomass in spring and summer were much higher than that in autumn and winter. The total zooplankton abundance averaged 283.5 ind./m~3 in spring (highest), 192.5 ind./m~3 in summer, 165.5 ind./m~3 in autumn and 65.9 ind./m~3 in winter (lowest), and the non-gelatinous groups contributed the most total abundance. Correlation analysis suggests that the non-gelatinous zooplankton biomass and abundance had a significant positive correlation in the whole year, but the relationship was insignificant between the total zooplankton biomass and abundance in spring and summer. The diversity index H of zooplankton community averaged 1.88 in this study, which was somewhat higher than historical results. Relatively low diversity in summer was related to the high dominance of Calanus sinicus, probably due to the strongest effect of the HSCWM in this season. 相似文献
This paper reported a tornado hazard happened on June 23, 2016, in Yancheng city, Jiangsu Province. The moving footprint of this huge tornado was from west to east. Shuoji, Chenliang, Goudun, Banhu, Xingou, Wutan towns in Funing district and Sheyang town in Sheyang district were severely hit by this tornado. This tornado along with rainstorm and hailstorm had claimed 99 lives and caused more than 3800 flats to collapse as well as damaged 48 high-voltage circuits. As the cold air from northwest met the subtropical high pressure system that forms over relatively cool water bodies (i.e., Indian and Pacific Oceans), such a powerful meteorological phenomenon was initiated. The strong connective airflow intensified the development of this tornado. Based on the preliminary investigation and analysis of this tornado, cost-effective timber structures with adequate anchorage of the framing to foundations and adequate connection between walls and roofs may be recommended to ensure occupants safety and reduce potential damage in these extreme wind events. Additionally, it is suggested to utilize early warning system along with geographical information system (GIS), Global Positioning System (GPS), and remote sensing (RS) (3S) to monitor and precast the occurrence of rainfall, hailstorm, and tornado hazards in future.
