During routine monitoring of commercial purse seine catches in 2011, 87 fingerling specimens of scombrids were collected in the southern Adriatic Sea. Sequencing of the mitochondrial DNA control region locus inferred that specimens belonged to the Atlantic bluefin tuna, Thunnus thynnus (Linnaeus, 1758) (N = 29), bullet tuna, Auxis rochei (Risso, 1810) (N = 30) and little tunny, Euthynnus alletteratus, Rafinesque, 1810 (N = 28). According to previously published growth parameters, the age of the collected specimens was estimated at approximately 30–40 days, suggesting they might have been spawned in the Adriatic Sea, contrary to the current knowledge. A coupled modelling system with hydrodynamic (ROMS) and individual based model (IBM—Ichthyop) was set up to determine the location of the spawning event. Numerical simulations with the IBM model, both backward and forward in time, indicate commercial tuna cages in the middle Adriatic coastal area as possible spawning location. The two other non-commercial species likely opportunistically use the positive environmental (abiotic and biotic) conditions to spawn in the same area.

Chub mackerel, Scomber colias, is widely distributed in the warm waters of the Atlantic Ocean including the Mediterranean and Adriatic Seas. This medium-sized pelagic fish species occurs in deeper waters during the colder part of the year and schools are found in coastal waters during the warmer parts of the year, where they spawn and feed. Atlantic chub mackerel is one of the most important commercial fish throughout its habitat and as a consequence of its wide distribution and broad commercial exploitation, biological information on the growth and mortality is required for stock assessment and management. Despite the abundance and economic importance of S. colias in the Adriatic Sea, knowledge about its biology and population dynamics is still limited. Studies of the age, growth, mortality and exploitation rates of S. colias have not been undertaken previously in the Adriatic Sea. Therefore, the exploitation status of this species' stock in the Adriatic Sea is unknown. The purpose of this study was to provide information on the age, growth and length–weight relationship as well as estimates of mortality and exploitation rate in order to define the present state of the population in the Adriatic Sea.

The anchovy (Engraulis encrasicolus, Linnaeus, 1758), one of the most important small pelagic fish species in the Adriatic, is currently described as a species that can be considered overfished. From 2013 to 2020, samples of anchovy eggs and larvae were collected through scientific surveys during the summer months. The collected ichthyoplankton data were combined with environmental data (measured satellite sea surface temperature and chlorophyll data, numerically simulated salinity, maps of primary production) to identify anchovy spawning habitats and environmental conditions affecting the anchovy early life stages. For this large dataset, a nonlinear method called Growing Neural Gas Network analysis was used to explain the multiple dependencies between anchovy and the explanatory environmental variables and represent them in 9 patterns called Best Matching Unit (BMU). Obtained values of anchovy early life stages abundances (eggs/m²; larvae/m²) showed a clear negative trend, which was easily observed both in the time series and in the annual spatial distributions. Among all measured environmental parameters that were previously mentioned, salinity showed a significant increase, which can be attributed to the cyclonic phase of the bimodal oscillatory system of the Adriatic and Ionian Seas. The calculated BMUs showed several interesting results that shed new light on previous findings: (a) there is a split between the richer northern and poorer southern parts of the Adriatic in terms of anchovy eggs and larvae abundances, (b) the Kvarner Bay, the west coast of Istria and the area around Dugi otok are consistently rich spawning grounds, (c) decreased abundance in the southern areas is a result of the influence of salinity, (d) an increase in chlorophyll can lead to an increase in egg count, (e) the positive effects of upwelling can be negated by an increase in salinity, (f) increased primary production is followed by increased egg count. Upwelling, as one of the factors that can influence larval and egg abundance by bringing nutrients up from the seafloor, showed increased spatial and temporal variability during the investigated period, which depended on the wind regime. Our analysis showed that neural network analysis can successfully describe the effects and interplay of environmental factors on the abundance of anchovy early life stages.

During the summer of 2013 two scientific surveys (northern, at the beginning of July and southern, at the end of July) were carried out along the eastern Adriatic Sea. In these surveys, ichthyoplankton samples of anchovy (Engraulis encrasicolus, Linnaeus 1758) eggs and larvae were collected. In the whole investigated area, egg and larvae abundance varied from 2.61 to 1040.24 eggs m⁻² (geometric mean ± CL: 25.43 ± 1.48 eggs m⁻²) and 2.73 larvae m⁻² to 611.14 larvae m⁻² (geometric mean ± CL: 17.07 ± 1.41 larvae m⁻²), respectively. Higher abundance of anchovy early life stages was noted in the northern part of the investigated area. The length of the collected specimens lay within the range of 2.39–3.68 mm and those individuals were less than 12 h old. Analysis of spatial and temporal distribution of collected anchovy early life stages indicated their higher abundance in areas of upwelling (four areas were distinguished on the eastern Adriatic side). Larger and older specimens were collected at the beginning of July in the northern part of Adriatic indicating that the anchovy population in the Adriatic tends to shift among its spawning centres in this area. In general, anchovy eggs were accompanied by its larvae (r = 0.453, P < 0.05), while statistically significant negative correlation was obtained between egg abundance and temperature (r = −0.380, P < 0.05) as well as sea depth (r = −0.321, P < 0.05).