Pseudo-nitzschia H. Peragallo (1900) is a globally distributed genus of pennate diatoms that are important components of phytoplankton communities worldwide. Some members of the genus produce the neurotoxin domoic acid, so regular monitoring is in place. However, the identification of toxic members in routine samplings remains problematic. In this study, the diversity and seasonal occurrence of Pseudo-nitzschia species were investigated in the Gulf of Trieste, a shallow gulf in the northern Adriatic Sea. We used time series data from 2005 to 2018 to describe the seasonal and inter-annual occurrence of the genus in the area and its contribution to the phytoplankton community. On average, the genus accounted for about 15 % of total diatom abundance and peaked in spring and autumn, with occasional outbreaks during summer and large inter-annual fluctuations. Increased water temperature and decreased salinity positively affected the presence of some members of the genus, while strong effects could be masked by an unsuitable definition of the species complexes used for monitoring purposes. Therefore, combining morphological (TEM) and molecular analyses by sequencing the ITS, 28S and rbcL markers, eight species were identified from 83 isolated monoclonal strains: P. calliantha, P. fraudulenta, P. delicatissima, P. galaxiae, P. mannii, P. multistriata, P. pungens and P. subfraudulenta. A genetic comparison between the isolated strains and other strains in the Mediterranean was carried out and rbcL was inspected as a potential barcode marker in respect to our results. This is the first study in the Gulf of Trieste on Pseudo-nitzschia time series from a long-term ecological research (LTER) site coupled with molecular data. We show that meaningful ecological conclusions can be drawn by applying integrative methodology, as opposed to the approach that only considers species complexes. The results of this work will provide guidance for further monitoring efforts as well as research activities, including population genetics and genomics, associated with seasonal distribution and toxicity profiles.