Unveiling region-specific autecological patterns of benthic diatoms in Northern Italy: implications for river bioassessment

• This is the first comprehensive work on diatom autecology in Italy. • Expanded diatom ecological dataset fills key gaps in current monitoring indices. • Nutrient optima are consistently lower than those reported in previous studies. • Reliable baseline for biomonitoring and impact assessment in diverse river types. Autecology describes the interactions of individual taxa with their environment and represents a cornerstone for the ecological status assessment of aquatic ecosystems. Biological indices widely rely on species-specific ecological requirements, indicator values, and sensitivities. Among bioindicators, benthic diatoms are particularly relevant, yet their ecological patterns are often complex and not always univocally defined, while the ecological profiles of many taxa remain uncertain. Furthermore, estimates of ecological preferences strongly depend on the reference dataset, and autecological information is often valid only at regional scales. In this study, optimum values and tolerance ranges for more than 400 diatom taxa were calculated with respect to 10 environmental parameters. The analysis is based on assemblage composition and environmental data collected between 2009 and 2019 in the framework of the WFD application in the Po River District (Northern Italy). Special attention was devoted to nutrient-related preferences, with a focus on species of particular interest, whose ecological preferences are still understudied. In detail, we focused on rare species (e.g., Nitzschia puriformis , Nitzschia alicae ), threatened taxa (e.g., Achnanthidium lineare ), and diatoms displaying an invasive behaviour (e.g., Achnanthidium delmontii , Achnanthidium druartii , Achnanthidium rivulare , Achnanthidium subhudsonis ). This study represents the first large-scale contribution to diatom autecology in Italy. Together, these findings contribute to a more accurate bioassessment framework and emphasise the need for region-specific autecological data in river monitoring programs.