Connectivity Among Populations of the Top Shell Gibbula divaricata in the Adriatic Sea

Abstract

Genetic connectivity studies are essential to understand species diversity and genetic structure and to assess the role of potential factors affecting connectivity, thus enabling sound management and conservation strategies. Here, we analyzed the patterns of genetic variability in the marine snail Gibbula divaricata from five coastal locations in the central-south Adriatic Sea (central Mediterranean) and one in the adjacent northern Ionian Sea, using 21 described polymorphic microsatellite loci. Observed and expected heterozygosity varied from 0.582 to 0.635 and 0.684 to 0.780, respectively. AMOVA analyses showed that 97% of genetic variation was observed within populations. Nevertheless, significant, although small, genetic differentiation was found among nearly all of the pairwise FST comparisons. Over a general pattern of panmixia, three groups of populations were identified: eastern Adriatic populations, western Adriatic populations, and a third group represented by the single northern Ionian Sea population. Nonetheless, migration and gene flow were significant between these groups. Gibbula divaricata is thought to have a limited dispersal capacity related to its lecithotrophic trochophore larval stage. Our results indicated high levels of self-recruitment and gene flow that is mainly driven through coastline dispersion, with populations separated by the lack of suitable habitats or deep waters. This stepping-stone mode of dispersion together with the high levels of self-recruitment could lead to higher levels of population structuring and differentiation along the Adriatic Sea. Large effective population sizes and episodic events of long-distance dispersal might be responsible for the weak differentiation observed in the analyzed populations. In summary, the circulation system operating in this region creates natural barriers for dispersion that, together with life-history traits and habitat requirements, certainly affect connectivity in G. divaricata. However, this scenario of potential differentiation seems to be overridden by sporadic events of long-distance dispersal across barriers and large effective population sizes.

Genetic connectivity of two marine gastropods in the Mediterranean Sea: seascape genetics reveals species‐specific oceanographic drivers of gene flow

“…Gibbula divaricata inhabits very shallow rocky bottoms (typically, 0-1 m of depth) that are highly sheltered from wave action, including coastal lagoons, harbour areas and artificial hard structures, and tolerates some degree of pollution (López-Márquez, et al, 2019b…”

“…We selected a series of environmental variables potentially related to connectivity among the mollusc populations analysed, such as those previously analysed by us in a study on the Mediterranean coral Cladocora caespitosa (López-Márquez, Cushman, et al, 2019) ( Sea surface currents were considered as directional variables (Landguth et al, 2017;López-Márquez, et al, 2019b), the bathymetric data set as cost variables (Cushman et al, 2006) and SSTs (SST, SST_C and SST_W), together with salinity (SSS, SSS_F and SSS_S), as slope variables (Cushman, et al, 2013a;Yang et al, 2013a (Cushman et al, 2006;Dunning et al, 1992), we used unicor (Landguth et al, 2012) for cost and slope variables. In the case of directional variables, we used the directionality function implemented in unicor (Landguth et al, 2017) to calculate the asymmetric "current cost-distance" from the zonal and meridional velocities.…”

Phylogeographic structure and population connectivity of a small benthic fish (Tripterygion tripteronotum) in the Adriatic Sea

“…within the latitudinal range of the phylogeographic break in T. tripteronotum , such that the genetic divergences in T. tripteronotum and P. clavata may indeed coincide geographically. Other studies in the Adriatic Sea lack the necessary geographic sampling to locate genetic breaks (Carreras et al., 2017; Jahnke et al., 2017; Koblmüller et al., 2015; López‐Márquez et al., 2019; Schiavina et al., 2014).…”

“…The last column indicates whether the location was included as point of particle release in the Lagrangian drift simulations. N, sample size; H E , genetic diversity; h, number of different haplotypes; HR, haplotype richness (Boissin et al, 2016;Garoia, Guarniero, Piccinetti, & Tinti, 2004;Koblmüller et al, 2015;López-Márquez et al, 2019;Maltagliati et al, 2010;Papetti et al, 2013;Souche et al, 2015).…”

“…Despite the surging interest in seascape genetics in general and the oceanographic appeal of the Adriatic Sea, relatively few studies have addressed population structure in the Adriatic. Among those that did, some found that genetic clusters within species reflected the Adriatic sub‐basins (Carreras et al., 2017; Ledoux et al., 2018; Schiavina, Marino, Zane, & Melià, 2014), whereas in others, there was only weak or no differentiation by sub‐basins (Boissin et al., 2016; Garoia, Guarniero, Piccinetti, & Tinti, 2004; Koblmüller et al., 2015; López‐Márquez et al., 2019; Maltagliati et al., 2010; Papetti et al., 2013; Souche et al., 2015). In addition to the division into large sub‐basins, the ragged shoreline and wealth of near‐shore islands along the eastern Adriatic coast provide a richly structured environment, which could further shape population differentiation of littoral and benthic species on a more local scale (Ledoux et al., 2018).…”