Rapid variations of phytoplankton blooms and their dynamics off the Changjiang River Estuary

Frontiers in Marine Science(2024)

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摘要
Phytoplankton frequently blooms in estuaries and coastal seas. Numerous dynamic processes affect these regions, generating complex hydrodynamics that induce intense phytoplankton variability over multiple time scales. Especially, the variability over time scales of 100-101 days (event-scale) is a strong signal that is fundamental to coastal aquatic environments and ecosystems. Based on the historical monitoring of harmful algal bloom events and a fully coupled hydrodynamics-sediment-ecosystem numerical model, this study explored horizontal distribution patterns of the phytoplankton maximum off the Changjiang River Estuary over multiple time scales. Our results showed that the bloom events typically lasted less than a week and horizontal distribution of the horizontal chlorophyll maximum varied over the time scale of days. Tidal forcing was shown to dominate the periodic phytoplankton variability. The variations of river runoff and wind forcing also modulated this variability and added more disturbances. Increased runoff and enhanced summer monsoon wind caused the horizontal chlorophyll maximum to physically extend further offshore, while they also biologically stimulated phytoplankton blooms. The analysis of the time scale showed that the regulation of horizontal chlorophyll maximum responds faster to physical effects than in biological ones. At the same time, during neap tides, the adjustment of phytoplankton to the disturbances associated with the hydrodynamic processes was stably salient. Such adjustment was based on the adaptation to light availability and nutrient supply. This study contributes to the understanding of phytoplankton variability in estuaries affected by multiple physical-biological processes over the time scale of days and benefits to the management of environmental conservation.
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关键词
phytoplankton blooms,event-scale variations,Changjiang River Estuary,river plume,dynamic processes
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