Phytoplankton dynamics are highly variable in coastal ecosystems because physical, chemical and biological influences are forced in complex ways. Many important processes that influence coastal phytoplankton dynamics are episodic (e.g. hurricanes, storms and seiches). However, phytoplankton variability at short-term scales is poorly understood. Despite that alteration of the magnitude and frequency of episodic events (storms, rains, droughts) is considered one of the consequences of future global climate change, the potential effects of such changes in coastal ecosystems have not been fully studied. This is due to the difficulty of studying episodic events characterized by unpredictable timing, and the inability of traditional sampling strategies to resolve the scales involved, particularly biological data. The capacity to obtain biological measurements at sufficient temporal and spatial resolution is now possible with new emerging technologies that allow autonomous data of phytoplankton at the species and group levels. The Imaging Flow-Cytobot is a submersible particle analyzer and imager that combines aspects of microscopy and flow cytometry capable of unattended long-term deployments. It produces high-quality images that allow phytoplankton cells to be identified thereby providing taxonomically resolved estimates of phytoplankton abundance with fine temporal resolution. This project will explore phytoplankton biodiversity, variability and their relation to environmental factors at relevant ecosystem timescales. Continuous planktonic and oceanographic high-frequency time series obtained with high technology sensors will be combined with a detailed statistical analysis of the measured time series and molecular analysis of phytoplankton biodiversity. Further research as proposed here is needed for a better understanding and prediction of coastal ecosystem responses to environmental change, which is essential for the appropriate management of coastal marine resources