The surface flow dynamics of the AS are characterized, with a certain seasonal variability, by a general cyclonic circulation (Russo and Artegiani, 1996). Levantine intermediate waters and Ionian surface waters flow northward from the Otranto Channel along the Balkans coast within the Eastern Adriatic Current (EAC), and return southward with the Western Adriatic Current (WAC) along the Italian peninsula (Orlić et al., 1992). Coastal currents exhibit seasonal variability, with the WAC generally stronger in summer, and the EAC stronger in winter (Zore, 1956; Poulain, 2001). Prevalently during winter, part of the EAC recirculates, shaping the nearly-permanent Southern Adriatic Gyre in the southern sub-basin (López-Márquez et al., 2019), and less frequently, the Northern and Central Adriatic gyres (Martin et al., 2009) in the upper and middle sub-basins. These eddies partially favor the cross-basin (east-to-west) transport via their northern rims (López-Márquez et al., 2019), and also result in the pumping of highly productive waters that entail rich areas favorable for mesopelagic spawners (Specchiulli et al., 2016).

Tides in the AS are amplified northwesterly (from the Strait of Otranto to the northernmost Adriatic), reaching amplitudes up to 1 m in the Venice shoreline, an exceptionally large value in the Mediterranean basin (Medvedev et al., 2020). The influence of tides and local winds, namely Bora and Sirocco, induce an important variability in the main circulation pattern (Orlić et al., 1994). The dry, cold and strong northeasterly Bora, more frequent in winter storms, provokes a double gyre response in the North Adriatic circulation, consisting of a cyclonic loop drifting northward and an anticyclonic drifting southward (Kuzmić et al., 2006). Otherwise, the wetter and warmer southeasterly Sirocco, typical from late autumn to early spring, tends to accumulate water near the northernmost coasts (Pasarić et al., 2007; Molinaroli et al., 2023), usually strengthening the EAC (Book et al., 2007) and weakening or even reversing the WAC (Bignami et al., 2007). Summer winds (e.g. the northwesterly Mistral) are weaker and more stable, which favors a slower and steadier circulation during this period (Pasarić et al., 2009).

The AS is a recognized biodiversity hotspot in the Mediterranean, driven by the nutrient transport and runoff by rivers and the consequent phytoplankton primary production, and marked by the strong seasonality of the Po River discharges (Cozzi and Giani, 2011). It is a highly productive fishing ground (Cavraro et al., 2022), grouped into two Geographical Subareas (GSA17 in the north, and GSA18 in the south, as shown in Figure 1 ) according to the General Fisheries Commission for the Mediterranean (GFCM, 2009). GSA17 has a wide variety of seabed habitats, from shallow and muddy bottoms in the east to steep and rocky bottoms in the west, whereas GSA18 is predominantly deep, steep, and rocky, supporting sensitive marine habitats that are under high fishing pressure (Grati et al., 2018). Despite the differences, both GSAs share important fish stocks (UNEP/MAP-RAC/SPA, 2015), which has led to the proposal of a large transboundary marine protected area (Bastari et al., 2016). Particularly, the AS supports regionally important fisheries of small pelagic stocks such as sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus) (Morello and Arneri, 2009), which are widely distributed throughout the whole AS. Over the last two decades, sardine specimens in the AS have tended to spawn from early autumn until late spring (Zorica et al., 2020). The peak of reproductive activity occurs between November and February, primarily depending on environmental parameters such as temperature (Zorica et al., 2019). In contrast to the AS, the spawning period for S. pilchardus appears to end earlier in other Mediterranean areas (Tsikliras et al., 2010; Basilone et al., 2021). The Adriatic anchovy spawns from the end of March (winter) to October (autumn), with its peak spawning season occurring in July (Zorica et al., 2020). According to Somarakis et al. (2004) and Basilone et al. (2006), the species’ reproductive peak is in the summer in the central Mediterranean. In the Bay of Biscay, anchovy spawn earlier and for a shorter period, peaking in May and June (Motos, 1996).

As for the bottom trawl fishery, the European hake (Merluccius merluccius) is the most important target species in terms of both landed weight and value for the fleets involved (Arneri and Morales, 2000). Unlike the other demersal species, it has two recognized spawning phases in the AS: the first occurring in winter in deeper waters, and then, a second occurring in summer after an adult migration to shallower waters (Ungaro et al., 1993; Vrgoč et al., 2004). Based on a recent study conducted on specimens sampled from the GSA17 (Candelma et al., 2021), the hake reproductive season peaks from April to July. However, spawning females can be found throughout the year, indicating a protracted spawning period (Zorica et al., 2019). It should be noted that the reproductive peak of M. merluccius varies in different geographical areas. Along the Tunisian coasts, the main peak is recorded from June to October, with minor peaks in January and April (Khoufi et al., 2014). In the Gulf of Lion, spawning is highlighted in autumn (Morales-Nin and Moranta, 2004). Along the Portuguese coast, spawning peaks are observed in March, May, and August (Costa, 2013). In North Atlantic waters, the spawning peak lasts from January to April (Alvarez et al., 2004; Murua and Motos, 2006).

Medium-sized pelagic fish species such as the Atlantic mackerel (Scomber scombrus), horse mackerel (Trachurus trachurus) and Mediterranean horse mackerel (Trachurus mediterraneus), despite their relatively lower commercial value compared to other pelagic fish species, play also a key trophic role as mesopredators in the basin (Da Ros et al., 2023), with their reproductive activity peaking in winter, late winter and summer, respectively (Jardas et al., 2004; Zardoya et al., 2004). High variability in range and peak spawning season is associated with latitude, with T. trachurus spawning season extending up to 8 months, with a peak in spring, in both the Atlantic and the Mediterranean (Abaunza et al., 2003). Other relevant fish stocks targeted by the bottom fleet are the red mullet (Mullus barbatus) and the common pandora (Pagellus erythrinus), with a spawning peak during summer (Carbonara et al., 2015; Muntoni, 2015; Zorica et al., 2020), as well as flatfish species such as the common sole (Solea solea), with a spawning peak in winter (Fanelli et al., 2022).

Some of the authors previously cited in their works indicate that some of the most important spawning and nursery grounds on the AS for these species are the Gulf of Trieste, Po Delta, Gargano Cape, Manfredonia Gulf, Kvarner Gulf, and the northern and the central Italian coastlines (see locations in Figure 1 ). Management measures intended to protect marine resources in the AS were additionally set out by the (GFCM, 2021) in the Pomo Pit ( Figure 1 ), an area recognized as a critical habitat for demersal species and identified as an Ecologically or Biologically Significant Area (EBSA) under the 1992 Convention on Biological Diversity.

Modeling the hydrodynamic processes of the Adriatic is challenging due to the large number of spatial scales involved and the extremely intricate coastal morphology (McKiver et al., 2016). Such complex application was carried out with a high-resolution numerical model, whose code is based on the Shallow Water Hydrodynamic Finite Element Model (hereafter SHYFEM; Umgiesser et al., 2004). SHYFEM solves the shallow water equations of motion for complex morphology and wide bathymetric gradients on unstructured grids. The effectiveness of SHYFEM is well-documented in various applications in Europe (Bajo et al., 2014; Umgiesser et al., 2014 among others) and in the Adriatic basin (Bellafiore and Umgiesser, 2010; Ghezzo et al., 2015, Ghezzo et al., 2018; Umgiesser et al., 2022 and citations therein). The version used in this study (SHYFEM-Tiresias, Ferrarin et al., 2019) covers the entire AS, from 12.05° E to 19.92° E and from 39.95° N to 45.80° N, including the small lagoons of Grado-Marano, Lesina and Venice and the Po Delta ( Figure 1 ).

The full numerical grid consists of 96,392 triangular elements with horizontal resolution varying from 5 km in the open-sea to a few dozens of meters along the coastlines ( Figure 2A ), and 72 vertical Z-layers of uneven discretization (Ferrarin et al., 2019). It includes the contribution of five boundary conditions, namely, the sea level, current velocity, temperature and salinity fluxes at the Strait of Otranto, and the freshwater discharges from 17 tributaries. Temperature and salinity fluxes were provided by the oceanographic fields of Mediterranean Forecast System (Tonani et al., 2008), and the freshwater discharges were obtained from monthly and annual climatological values at the river boundaries (for the location of tributaries, see Ferrarin et al., 2019 and references therein). Atmospheric forcing, i.e., pressure and wind, is given by the ECMWF ERA-5 atmospheric reanalysis (Hersbach et al., 2023).

The model outputs in this study are hourly surface values of zonal (u) and meridional (v) components of drift velocity, sea level, temperature, and salinity for the year 2018. The selected year is as a representative scenario for the general hydrographic conditions of the AS and is accessible in NetCDF through the Institute of Marine Sciences of the National Research Council of Italy (CNR-ISMAR) OpenDAP catalog (https://iws.ismar.cnr.it/thredds/catalog/emerge/catalog.html). It serves as a case study, examining spawning areas and intra-annual connectivity patterns, rather than assessing inter-annual variability, which is currently being investigated but not shown for simplicity in this first application. Supplementary Figure S1 displays the monthly averaged surface velocity data from SHYFEM and the ECMWF ERA-5 wind fields for the simulated months (January to December 2018). Winter and summer averaged surface circulation is presented in Figures 2B and C , respectively.

The synoptic fields in Figure 2 reveal similar circulation patterns, with the velocity field exhibiting greater variability in winter than in summer. The winter mean ( Figure 2B ) shows a more prevalent WAC in the northern sub-basin, and a stronger EAC along the north-flowing eastern rim of the southern gyre. The circulation is weaker in summer ( Figure 2C ), although the WAC is stronger along the south-flowing rim of the southern gyre in this season. Despite not being the most typical configuration reported in the AS, which is characterized by the presence of the EAC and the WAC and the three reported cyclonic gyres, the slight weakening of the currents during summer is not unusual. The prevailing northwesterly Mistral winds during summer intensify the east-to-west cross-basin transport, leading to stronger southeastward coastal currents and increased export to the northern Ionian Sea. During winter, the effect of both easterly and southeasterly winds disrupts the unidirectional shore transport, resulting in a more dispersed and irregular pattern within the basin.

Dispersal and connectivity were assessed by implementing a lagrangian particle tracking algorithm based on the open-source software OpenDrift (version 1.10.6, Dagestad et al., 2018). OpenDrift consists of several particle-based sub-models that can be used to predict the transport and fate of different types of elements. This study applies the main sub-model, OceanDrift, that uses neutral buoyant particles as tracers. Virtual particles represent propagules (i.e., eggs and larvae) with the typical biological traits of generic marine organisms ( Table 1 ). The analysis focuses on basin-scale larval connectivity from an ecosystem perspective, rather than on specific target species.

Horizontal trajectories were simulated by integrating the zonal and meridional velocity field using a 4^th order Runge-Kutta advection scheme, where particle positions are bilinearly interpolated using the model output data in the hydrodynamic grid. Vertical velocities, mainly associated with wind-driven upwelling/downwelling in certain AS areas, are of small magnitude (less than mm/s to cm/s) compared to horizontal velocities (cm/s to dm/s). Vertical motions are influenced by other phenomena such as diel cycles, feeding patterns, egg buoyancy or settlement due to changes in fat content, diurnal temperature variations affecting buoyancy, etc. As a result, the vertical velocity is poorly determined, with an uncertainty in its value that could even change its sign, for which it has not been considered in the advection module. Another simplification adopted in our method is that the tracers are fully-passive, meaning that complex larval traits, such as swimming capability, migrations, and natality and mortality rates are not considered in the approach. Under these assumptions, transport of eggs and developing larvae is determined by the PLD (i.e., the time propagules spend drifting with currents), the duration of spawning, and the time-varying horizontal velocity. To prevent particle stranding near the release site, a strategy of relocating particles to the open sea was implemented upon encountering the continental coastline or islands when oceanographic conditions allowed. The coastline was represented using the Global Self-Consistent Hierarchical High-Resolution Geography in its full resolution version (GSHHG_F, version 2.3.7). A 30-minute time step with non-additional diffusion nor wind field were added to the trajectories, as they were already included in the hydrodynamic simulation run of SHYFEM-Tiresias.

To investigate the spatial connectivity patterns, the AS basin was divided into 40 sub-zones, 21 along the coastlines and 19 distributed by the open sea ( Figure 3 ). These areas were partially selected based on the experience gained from studies on the circulation and ecological characteristics of the region of interest (Coll et al., 2010; Lipizer et al., 2014; UNEP/MAP-RAC/SPA, 2015; Bastari et al., 2016). Each area played, simultaneously, the role of source and destination of particles. Two hundred lagrangian particles as a representative number of propagules are seeded in each box randomly distributed in the surface layer, so each release allocates 8,000 new particles in the AS, and their position is computed every 30 min. To avoid any potential bias that could be introduced in trajectories if particles were only released at a single time of the day, particles are released four times per day for 14 days (56 releases, 448,000 particles in total). All the particle tracks were stored in netCDF format and the post-processing and visualization of the simulations were performed in Matlab (version 2023a).

In addition to the spatio-temporal analysis of the trajectories of eggs and larvae, several factors related to the biology and development of common fish stocks in the AS with influence on the dispersal pathways of particles were tested. Table 1 provides the biological parameters considered in the lagrangian experiments. The first one is the spawning time, understood as the time of particle release. Simulations were run for winter and summer, representing the most active spawning periods of the abundant species inhabiting the region. The second parameter being tested is the pelagic larval duration (PLD), which is the time between when a pelagic propagule leaves the spawning site and when it finally settles. In practice, the duration of egg and larval drift of marine organisms varies from weeks to months, depending on the ontogeny of fish larvae. The value of this parameter per species has been inferred from the literature cited in Table 1 . Overall, given the uncertainties in determining the transition from passive to active behavior, we considered a wide PLD of 60 days as a good compromise between a stable value for connectivity in the AS and an affordable computational time. To test the sensitivity to PLD, connectivity was recalculated for time windows ranging from 15 to 90 days (Section 4.3).

Two different methods were followed to address hydrodynamic connectivity ( Figure 4 ). First approach consisted in the so-called “connectivity matrix” ( Figure 4A ), which represents the probability of larval exchange among geographically separated sites (Cowen and Sponaugle, 2009). In this matrix, each cell is the number of particles (p) released from a certain source i (along the vertical axis) and collected in a certain destination j (along the horizontal axis), so C _i,j is the probability that an individual or group of individuals of population i will move to population j after a certain tracking time ( C ( i , j ) =   p ( j ) p ( i ) ). Diagonal cells of this matrix (where i = j) stand for the self-recruitment, i.e., the number of individuals that remain in the same region from which they were originally released, including particles that eventually return to the sourcing area (Cowen et al., 2006). Connectivity ratios (C, with values ranging from 0 to 1), therefore, quantify the strength of connectivity between different sites, with higher values indicating more favorable connections. Source-sink dynamics of larval dispersal can be elucidated with this approach, revealing the direction and intensity of connections. It further enables to estimate the potential and effectiveness of a given area as a nursery ground for developing larvae. Despite this, connectivity matrices only offer a partial depiction of larval connectivity complexity, neglecting crucial information such as the identification of areas that are rapidly dispersing, both dispersing and recruiting, or only recruiting for individuals through time.

Prompted by this lack of temporal information in the network, the second method used a more-recent approach developed by Defne et al. (2016). The method, called a “retention clock matrix” (RCM, hereafter), uses a clock in each cell to track the temporal changes in source-sink connections, evaluating the time-dependent connectivity (see Figure 4B ). Specifically, each retention clock describes the release event as a circular clock that tracks the number of particles (p) over the entire time scale of interest (T) (see inset of Figure 4B ). The time scale is discretized into slices with a temporal resolution of Δt_n ( C ( i , j , t n ) = p   ( j , t n ) p ( i , t 0 ) ). As in the conventional connectivity matrix, in all RCMs, the horizontal axis represents the boxes from which particles are released, and the vertical one is where the particles end up. The strength of connectivity between each possible combination of source-destination is depicted with a color scale, in which slices with the darkest color intensity indicate the larger fraction of particles moving from their origin to the destination. Naturally, domains with different retention characteristics have unique retention clocks, which reflect the rate at which particles are retained or lost within a domain through time. In slowly dissipating environments, the particle concentration, hence the clock, would gradually approach zero, indicating that individuals are being spawned at a slower rate than they are being dispersed. In rapidly dispersing domains, the clock would approach zero faster and a larger portion of it would remain at null values, suggesting that tracers are subjected to strong currents that result in direct connections to other domains. The opposite behavior is depicted by retentive domains, identified by clocks with connectivity values close to 1 at all-time scales, which indicate that spawned individuals are effectively retained due to physical or biological features that prevent their advection.

To account for the discrepancy in sizes and shapes of source and destination polygons (see Figure 3 ), the estimated connectivity in both cases was normalized by the areas (a) of each cell involved in the connection C   =   C × [ a ( i ) a ( j ) ] , so that the maximum value of the matrix is 1. In both methods, connectivity was only considered significant if the ratio C satisfied a minimum threshold of 0.01, meaning that at least 1% of the particles released from the source reached the destination polygon. Thus, the presence of either colored cells (in method 1) or clocks (in method 2) indicate a connection between the source and destination polygon, while a blank cell indicates that the connection is zero or less than 1%, and thus, negligible. The connectivity ratios C are hereinafter interpreted in the text as S# - D#, indicating particle transport from source (row number) to destination (column number), respectively. A numerical code made available to the scientific community by Defne et al. (2016) was adapted to calculate the RCMs in this study.

The mean connectivity matrix estimated at winter and summer for the year 2018 is illustrated in Figures 5A and B respectively, and the result of its difference (summer minus winter) is provided separately in Supplementary Figure S2 .

A characteristic feature of both winter and summer scenarios is the prevalence of high connectivity rates along the diagonal of the matrix. This indicates that these regions are characterized by a certain level of auto-retention of propagules. Self-retention probability differs greatly between the distinct boxes, ranging from 60% in the Kvarner Gulf (S13-D13) to 5% in Bosnia (S33-D33) for winter ( Figure 5A ), and from 55% in Manfredonia (S26-D26) to 4% in Brindisi (S34-D34) for summer ( Figure 5B ). This spatial difference is foreseeable, as the complex system of islands in the Kvarner Gulf, and the existence of a small cyclonic eddy in the Gulf of Manfredonia (see Figure 1 ) act as trap of propagules (Specchiulli et al., 2016; Sciascia et al., 2018), whilst Brindisi and Bosnia coasts, nearby the Strait of Otranto, are subjected to stronger advection by the EAC-WAC circulation system. Overall, self-retention in the northern and middle Adriatic sub-basins (areas 1-25) is more likely than in southern Adriatic sub-basin (areas 26-40), denoted by the darker color intensity of the former diagonal cells compared with the latter elements (~28% in areas 1-25, compared to ~13% in areas 26-40, in both winter and summer scenarios).

Considering also the connectivity values out of the diagonal, Gargano (D22) and Manfredonia (D26) during summer ( Figure 5B ), display a large fraction of particles arriving from S14-20 and S18-22, with mean connectivity values of 10% and 20%, respectively, and maximum reaching 50% (S18-D22) and 70% (S22-D26). This spatial pattern is to be expected, since the WAC acts as the main advection process along the Italian shelf, although it is also subject to seasonal fluctuations ( Supplementary Figure S1 ). Contrastingly, Istria (D9), Kvarner Gulf (D13), and the Kornati (D17), Korcula (D25), and Elaphiti (D29) Islands, exhibit external particle reception rates less than 5%. Extreme case is provided by D17 ( Figure 5B ), which shows zero reception of individuals from external boxes. These areas harbor relatively closed populations, receiving particles from a limited number of grounds, but suggest their potential as self-sustaining areas. During winter ( Figure 5A ), isolated self-sustaining areas are less obvious, although the shielding capacity of the Kornati Islands (D17), northern Croatia (D21) and the Korcula Islands (D25) is noteworthy, as they receive nearly null abundance of particles from the northern part of the basin. Areas D2 (Venice), D3 (Trieste), D5 (OpenSea2) and D9 (Istria) only receive particles from a small part of the southern sub-basin, while source areas S12 (OpenSea6), S13 (Kvarner Gulf), S17 (Kornati Islands), S21 (North Croatia), S24 (OpenSea12) and S25 (Korcula Islands) do not send any particles to the southern sub-basin. A striking example is the Kvarner Gulf (D13), which paradoxically shows minimal external particle receptions in summer, but high external particle exchange in winter, while remaining self-retaining (elevate connection with itself). This suggests that this area may play a hatchery and nursery role for marine species, as suggested by the previously cited authors (Zorica et al., 2020), and suggest the existence of physical processes determining the temporal evolution of the particles in the basin.

Based on the averaged result, we can derive macro-regions as combinations of boxes of our network. For instance, more evident in summer than in winter, areas 1-9 and 26-40 may be identified as two isolated regions with a slight or null inter-connection. A third area can be identified in 10-25 (central Adriatic), where the particle reception is mainly limited to the upper part of the connectivity matrix (northern and central Adriatic), with limited or no exchange with the southern sub-basin during summer. During winter, the prevailing currents over the AS inject more energy in the basin, leading to a wider dispersion of particles and a less distinct delineation of macro-regions. The seasonality is also evident by the significantly higher number of valid elements, i.e., cells with connectivity probabilities higher than 1%, in winter (~900 out of 1600, Figure 5A ) compared to summer (~600 out of 1600, Figure 5B ). The likely reason is the atmospheric forcing, which is less variable and more stable in summer, resulting in diminished velocities and consequently shorter drifter paths in this period. The much more dispersed transport because of the more variable atmospheric forcing during winter may create otherwise less structured connectivity patterns within the basin.

Temporally averaged connectivity matrices ( Figure 5 ; Supplementary Figure S2 ) highlight the role of circulation structures on particle dispersion and provide predictable connectivity patterns that show seasonal variability. However, it also shows that the selection of a temporal snapshot is subjective and can limit the analysis due to loss of information. It is more adequate to preserve the temporal information of connectivity, while benefiting from the simplicity of a connectivity matrix (Defne et al., 2016). To this end, the RCM for all source-destination pairs in the AS basin has been estimated for the same temporal configurations (winter and summer). A maximum time scale of 60 days is used for all model scenarios. Each slice on all retention clocks represents 5 days. The color scale in each clock represents the particle concentration at the selected time slice, with darker colors indicating larger fraction of particles moving from source to destination.

The temporal component of connectivity between specific areas must be directly related to the species-specific PLD to ensure the practical application of the research. Determining the time that propagules spend drifting with currents is a key issue in shaping the dispersal potential and population connectivity of a given area. As mentioned in Section 3.2, the range of plausible durations is broad and uncertain ( Table 1 ). While continuing to use the numerical model as a tool, it is worth exploring the dependence of connectivity on PLDs. To address this, we investigated the rate of particle reception in each area across a range of PLD windows from 15 days to 90 days, with intervals of 15 days ( Figure 9 ).

In the winter configuration ( Figure 9A ), subareas show particle receptions evenly distributed across the PLD windows, with the most significant connections forming after at least 30 days of simulation. This is particularly noticeable along the Italian shelf (areas 6, 10, 14, 18, 22, 26, 30, 34), where the probability of receiving particles is less than 5% within the initial 15 days and remains below 20% within the first 30 days. This hinders the possibility of early life stages persisting in these areas, but suggests the eventual occurrence of individuals at more-advanced developmental stages, a phenomenon partially supported by works reporting the Gulf of Manfredonia’s role as a nursery ground (Sciascia et al., 2018). An exception to this trend is evident in the northernmost Adriatic, specifically in Venice (1) and Trieste (2), where the highest rate of particle reception occurs within the initial 15 days (35% and 53%, respectively), indicating a higher probability of occurrence of early life stages in these regions.

During the summer ( Figure 9B ), the arrival times are remarkably short, characterized by an average probability of reception of 30% and a maximum of 70% within the first PLD window (0-15 days). The most favorable scenario is observed in Istria (9), where the highest probability of receipt is concentrated in the first 15 days, with no further particle arrivals after 30 days of tracking. This observation indicates a prevalence of individuals in early life stages in this subarea, aligning with prior research highlighting Istria’s role as a spawning ground (Zorica et al., 2020). Other potential spawning grounds are discerned in the southeastern Adriatic, specifically in OpenSea17 (35), Montenegro (37), and OpenSea19 (39). Favorable scenarios are also evident along the northern edges of the Adriatic gyres, favoring cross-shore connections, with peak reception occurring between 15 and 30 days of individual tracking.

From a biological perspective, these findings offer valuable insights into spawning strategies. According to our results, species with shorter PLD, such as the red mullet or anchovy (<40 days), would likely thrive along the Croatian coast in the summer, benefiting from the shorter arrival times and the more favorable oceanographic conditions. Conversely, species with longer PLD, such as sardine or hake (>40 days), would find the northern Adriatic and Italian shelf during winter advantageous.

Identifying the unique retentive characteristics of different areas in the AS is a crucial step in comprehending the distribution of marine species and designing effective conservation strategies in the basin. Our results indicate that particles exhibit a strong preferential direction along the coasts. The behavior in the Italian shelf was notably diverse, with some areas maintaining high self-sustaining ability during the summer and values shifting offshore in the winter. The Istrian coast ( Figure 1 ) is identified as a crucial habitat for species spawning success, particularly in the summer, where arrival times fall within the ranges of PLD estimated for abundant species in the basin, such as anchovy, red mullet, and common pandora ( Table 1 ). Areas distributed along the Italian shelf can be identified as essential nursery grounds, particularly when the region’s productivity is influenced by wind-induced upwelling and river discharges, creating favorable environmental conditions for larvae. During the summer, when the velocity is reduced, retention is promoted, coinciding with the spawning period of anchovy, Mediterranean horse mackerel, and hake ( Table 1 ). The variability observed during winter is attributed to environmental fluctuations, specifically the prevalence of strong winds that significantly affect the displacement of drifters. This phenomenon provides advantageous opportunities for marine species with longer PLD and spawning periods concentrated in winter, such as sardines and common soles (refer to Table 1 ). Many particles arrive after undergoing recirculation, a process that requires longer times and results in extended arrival durations.