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Long-term data series (1971–2015) of physical and biogeochemical parameters were analyzed in order to assess trends and variability of oceanographic conditions in the northern Adriatic Sea (NAS), a mid-latitude shallow continental shelf strongly impacted by river discharges, human activities and climate changes. Interpolation maps and statistical models were applied to investigate seasonal and spatial variability, as well as decadal trends of temperature, salinity, chlorophyll-a and nutrients. This analysis shows that sea surface temperature increased by +0.36% year−1 over four decades. Annual mean flow of the Po River markedly changed due to the occurrence of periods of persistent drought, whereas the frequency of flow rates higher than 3000 m3 s−1 decreased between 2006 and 2015. Moreover, we observed a long-term decrease in surface phosphate concentrations in Po River water (−1.34% year−1) and in seawater (in summer −2.56% year−1) coupled, however, to a significant increase in nitrate concentration in seawater (+3.80% year−1) in almost all seasons. These changes indicate that the nutrient concentrations in the NAS have been largely modulated, in the last forty years, by the evolution of environmental management practices and of the runoff. This implies that further alteration of the marine environment must be expected as a consequence of the climate changes.

The dinoflagellate Alexandrium minutum is known for the production of potent neurotoxins affecting the health of human seafood consumers via paralytic shellfish poisoning (PSP). The aim of this study was to investigate the relationship between the toxin content and the expression level of the genes involved in paralytic shellfish toxin (PST) production. The algal cultures were grown both in standard f/2 medium and in phosphorus/nitrogen limitation. In our study, LC-HRMS analyses of PST profile and content in different Mediterranean A. minutum strains confirmed that this species was able to synthesize mainly the saxitoxin analogues Gonyautoxin-1 (GTX1) and Gonyautoxin-4 (GTX4). The average cellular toxin content varied among different strains, and between growth phases, highlighting a decreasing trend from exponential to stationary phase in all culture conditions tested. The absolute quantities of intracellular sxtA1 and sxtG mRNA were not correlated with the amount of intracellular toxins in the analysed A. minutum suggesting that the production of toxins may be regulated by post-transcriptional mechanisms and/or by the concerted actions of alternative genes belonging to the PST biosynthesis gene cluster. Therefore, it is likely that the sxtA1 and sxtG gene expression could not reflect the PST accumulation in the Mediterranean A. minutum populations under the examined standard and nutrient limiting conditions.

Microalgae are one of the most promising biodiesel feedstocks due to their efficiency in CO2 fixation and high neutral lipid productivity. Nutrient-stress conditions, including nitrogen starvation, enhance neutral lipid content, but at the same time lead to a reduction of biomass. To maximize lipid production in the diatom Skeletonema marinoi, we investigated two different nitrogen starvation approaches. In the first experimental approach, inocula were effectuated in modified f/2 media with decreasing nitrogen concentration, while in the second experiment, nitrate concentration was gradually reduced through a collection/resuspension system in which the culture was periodically collected and resuspended in culture medium with a lower nitrate concentration. In the first approach, the neutral lipid accumulation was accompanied by a strong biomass reduction, as was expected, whereas the second experiment generated cultures with significantly higher neutral lipid content without affecting biomass production. The total proteins and total carbohydrates, which were also quantified in both experiments, suggest that in S. marinoi, neutral lipid accumulation during nutrient starvation did not derive from a new carbon partition of accumulated carbohydrates.

Increased anthropic pressure on the coastal zones of the Mediterranean Sea caused an enrichment in nutrients, promoting microalgal proliferation. Among those organisms, some species, such as the dinoflagellate Alexandrium minutum, can produce neurotoxins. Toxic blooms can cause serious impacts to human health, marine environment and economic maritime activities at coastal sites. A mathematical model predicting the presence of A. minutum in coastal waters of the NW Adriatic Sea was developed using a Random Forest (RF), which is a Machine Learning technique, trained with molecular data of A. minutum occurrence obtained by molecular PCR assay. The model is able to correctly predict more than 80% of the instances in the test data set. Our results showed that predictive models may play a useful role in the study of Harmful Algal Blooms (HAB).