Phytoplankton communities in a coastal and offshore stations of the northern Adriatic Sea approached by network analysis and different statistical descriptors. (5th March 2023) - Neri, Francesca; Romagnoli, Tiziana; Accoroni, Stefano; Ubaldi, Marika; Garzia, Angela; Pizzuti, Andrea; Campanelli, Alessandra; Grilli, Federica; Marini, Mauro; Totti, Cecilia
Abstract: The Northern Adriatic Sea is one of the most productive areas of the Mediterranean Sea. Long-term series of phytoplankton are crucial to detect changes in the marine ecosystems, due to its high sensitiveness to environmental conditions. In this study, we compared two long-term phytoplankton time series (1988–2019) related to a coastal and an offshore stations located along the LTER Senigallia-Susak transect (Northern Adriatic Sea), using several statistical descriptors: diversity indices, multivariate statistical analyses (PCA, HCPC, NMDS), IndVal (indicator value analysis) and graph-network analysis. The coastal station was found to be more variable than the offshore one, being directly affected by the Western Adriatic Current and therefore by riverine inputs. The two stations appeared to be more different in winter and autumn, and more similar in summer when riverine waters spread offshore in stratified conditions. Due to its more oligotrophic condition, the offshore phytoplankton community showed a higher biodiversity than the coastal one, where phytoplankton blooms occurred frequently. Graph-network analysis turned out to be a useful tool to study the phytoplankton community through the number of interactions occurring among phytoplankton taxa, that was higher at the offshore station. This study highlighted that any evaluation of the Good Environmental Status (as required by the Marine Strategy Framework Directive) should consider the oceanographic differences between different areas, combining several statistical approaches. Highlights: Phytoplankton annual cycle differed in coastal and offshore stations. A higher diversity was found offshore. The two stations showed a higher similarity in summer. Graph-network analysis was useful to highlight structure of phytoplankton community. The combination of various indicators gave complementary information.