In 1962, a series of in situ primary production measurements began in the Adriatic Sea, at a station near the island of Vis. To this day, over 55 years of monthly measurements through the photic zone have been accumulated, including close to 3000 production measurements at different depths. The measurements are conducted over a six-hour period around noon, and the average production rate extrapolated linearly over day length to calculate daily production. Here, a non-linear primary production model is used to correct these estimates for potential overestimation of daily production due to linear extrapolation. The assimilation numbers are recovered from the measured production profiles and subsequently used to model production at depth. Using the recovered parameters, the model explained 87% of variability in measured normalized production at depth. The model is then used to calculate daily production at depth, and it is observed to give on average 20% lower daily production at depth than the estimates based on linear extrapolation. Subsequently, water column production is calculated, and here, the model predicted on average 26% lower water column production. With the recovered parameters and the known magnitude of the overestimation, the time-series of water column production is then re-established with the non-linearly-corrected data. During this 55-year period, distinct regimes were observed, which were classified with a regime shift detection method. It is then demonstrated how the recovered parameters can be used in a remote sensing application. A seasonal cycle of the recovered assimilation number is constructed along with the seasonal cycle of remotely-sensed chlorophyll. The two are then used to model the seasonal cycle of water column production. An upper and a lower bound on the seasonal cycle of water column production based on remotely-sensed chlorophyll data are then presented. Measured water column production was found to be well within the range of remotely-sensed estimates. With this work, the utility of in situ measurements as a means of providing information on the assimilation number is presented and its application as a reference for remote sensing models highlighted.

Concentrations of polycyclic aromatic hydrocarbons (PAH) were studied in 36 sediment samples collected from 29 sites in the central Adriatic Sea. The total concentration of PAH showed high variability, ranging from 42.85 µg kg⁻¹ in open sea sediments to 28,662 µg kg⁻¹ in the sediments of Šibenik Bay. Unsubstituted, parent PAH were dominant PAH compounds in the entire area of Šibenik Bay and most of the stations in the coastal area. In Kaštela Bay, methyl PAH concentrations were higher than the concentrations of unsubstituted PAH, whereas in the sediments along the mid-Adriatic transect, similar concentrations of both PAH fractions were determined. PAH sources were investigated by applying the Positive Matrix Factorization software developed by the U.S. Environmental Protection Agency (USEPA). The results indicate the presence of four sources, two of which can be considered petrogenic and two pyrogenic. The contribution of the sources to the total concentration PAH at each station indicates the dominance of pyrogenic sources in Šibenik Bay and at most stations in the coastal area. In the sediments along the mid-Adriatic transversal, as well as in Kaštela Bay, PAHs originate mainly from petrogenic sources. The obtained results show that PMF can be a suitable tool for control of PAH pollution and thus, for the management of various activities in the Adriatic region. Seasonal differences between the contributions of sources in the Kaštela and Šibenik bays indicate that the contribution of traffic to the total concentration of PAH was higher during the tourist season. The carcinogenic risk of PAH determined by toxicity equivalent (TEQ) calculations showed an increased carcinogenic risk in the whole area of Šibenik Bay, regardless of the number of PAH compounds considered for the calculations. A low PAH-related carcinogenic risk was found for the rest of the study area.

Artificial neural network analysis (ANN) is used to study the seasonal distribution of viruses and microbial food web (MFW) components in the open Adriatic Sea. The effect of viruses within the MFW is often overlooked, although viruses play an important role in microbial community dynamics. The results showed that the strongest influence is found in the nonlinear relationship between viruses and temperature. In addition, the algorithm showed that the number of viral populations in the P-limited open sea varies by season and according to the abundance of their main hosts, HB. A strong positive relationship between viruses and HB was found in more than 50% of the observed data. Moreover, this algorithm confirmed the association of the virus with the autotrophic part of the picoplankton and with heterotrophic nanoflagellates. The dynamics of the four resulting clusters, characterized by biological and environmental parameters, is described as a cyclic pattern in the water layer above the thermocline. Neural gas network analysis has been shown to be an excellent tool for describing changes in MFW components in the open Adriatic.

The seasonal and spatial distributions of particulate phosphorus (PP) in the water column of the coastal area and open sea of the middle Adriatic Sea area were investigated for the first time. The relationship between PP and two other important forms of phosphorus (dissolved inorganic phosphorus (DIP), and organic phosphorus (P-ORG)), and the relationship between PP and other nutrients (nitrogen and silicon salts) and oceanographic parameters (temperature, salinity, oxygen saturation, chlorophyll a) from the water column were also examined. PP concentrations ranged from 0.007 μmol dm-3 in the open sea near Palagruža archipelago to 0.589 μmol dm-3 in the Krka River estuary. In the coastal area, PP concentrations were highest in autumn and lowest in winter. The vertical distribution of PP concentrations in the water column of the coastal area were highest in the surface layer during most of the year due to input of PP by freshwater inflows. In the open sea area, there were no significant seasonal or vertical differences in the distribution of PP concentrations in the water column. Seasonal analysis of the total phosphorus pool (PP, DIP and P-ORG) in the water column indicated that PP and P-ORG concentrations were higher in the coastal area compared to the open sea, while DIP concentrations were comparable. The results further demonstrate that PP can be an important fraction of the total phosphorus pool. A significant positive correlation was found between PP and chlorophyll a, indicating that PP was mainly of biological origin, and with nutrient salts of nitrogen and silicon, while a negative correlation was found with salinity.