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Paralytic Shellfish Poisoning (PSP) caused by the dinoflagellate Alexandrium catenella is a well-known global syndrome that negatively impacts human health and fishery economies. Understanding the population dynamics and ecology of this species is thus important for identifying determinants of blooms and associated PSP toxicity. Given reports of extensive genetic heterogeneity in the toxicity and physiology of Alexandrium species, knowledge of genetic population structure in harmful algal species such as A. catenella can also facilitate the understanding of toxic bloom development and ecological adaptation. In this study we employed microsatellite markers to analyze multiple A. catenella strains isolated from several sub-regions in the Gulf of Maine (GoM) during summer blooms, to gain insights into the sources and dynamics of this economically important phytoplankton species. At least three genetically distinct clusters of A. catenella were identified in the GoM. Each cluster contained representatives from different sub-regions, highlighting the extent of connectivity and dispersal throughout the region. This shared diversity could result from cyst beds created by previous coastal blooms, thereby preserving the overall diversity of the regional A. catenella population. Rapid spatiotemporal genetic differentiation of A. catenella populations was observed in local blooms, likely driven by natural selection through environmental conditions such as silicate and nitrate/nitrite concentrations, emphasizing the role of short-term water mass intrusions and biotic processes in determining the diversity and dynamics of marine phytoplankton populations. Given the wide-spread intraspecific diversity of A. catenella in GoM and potentially elsewhere, harmful algal blooms will likely persist in many regions despite global warming and changing environmental conditions in the future. Selection of different genetic lineages through variable hydrological conditions might impact toxin production and profiles of future blooms, challenging HAB control and prediction of PSP risk in the future.