Full
About the first author ZHOU Xueqian,born in 1998,a master candidate of Nanjing University,is engaged in sedimentology.
Outline
This research uses the basic end-member modeling algorithm,non-parametric estimation decomposition algorithm,and grain size-standard deviation method to evaluate the grain-size data of the Holocene sediments from core SE3 in the Hangzhou Bay area,in order to investigate the vertical distribution pattern of different grain-size end-members and their coupling relationship with environmental evolution. Results show that the basic end-member modeling algorithm acts as the best method in decomposing grain-size end-member in comparison with the other two methods. Five grain-size end-members were identified in the study area by the basic end-member modeling algorithm: EM1(clay and silt),EM2(coarse silt and very coarse silt),EM3(very coarse silt,very fine sand and fine sand),EM4(fine sand and medium sand)and EM5(medium sand and coarse sand). Their vertical distribution patterns are controlled by the evolution of sea level,depositional environment,and dynamic process. The coarse-grained end-members EM5 and EM4,representing bed load,are primarily supplied by the Qiantang River and distributed in the amalgamated fluvial channel,floodplain,and paleo-estuarine deposits. As sea levels rising,the content of proximal EM5 decreases upwards,while the content of relatively distal EM4 increases. The fine-grained end-members EM2 and EM1,representing suspended load,are distributed in the offshore shallow marine and present-day estuary stratigraphic units;they are mainly derived from the Changjiang by a combination of alongshore and tidal currents in a high sea-level setting. EM3,representing bed load with a normal distribution of grain size,is primarily distributed in the present-day estuary deposits,and probably represents the sediment transported and sorted by tidal currents and storm surges. This study sheds a new light in reconstructing the evolution history of sea level,environment,and source-to-sink processes in estuarine areas by using sensitive grain-size end-member algorithm analysis.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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