Aim: Population connectivity of benthic marine organisms depends
strongly on planktonic larval dispersal and is controlled by
geographic distance and oceanographic structure. We examine
isolation by distance versus resistance to barriers (ocean
current boundaries) against a background of post‐glacial habitat
expansion in a small benthic fish of the Adriatic Sea.
Location: Adriatic Sea, Eastern Mediterranean.
Taxon: Tripterygion tripteronotum.
Methods: We performed population genetic analyses using
mitochondrial control region sequences of 550 individuals from
25 locations sampled along the Eastern Adriatic coast.
Investigations of population structure included differentiation
tests, cluster analyses and distance‐based redundancy analysis.
We then ran Lagrangian simulations of passive larval drift to
examine correlations among population structure, geographic
distance and the Adriatic gyre system. To test for signatures of
a post‐glacial range expansion, we modelled the demographic
history of the populations and examined the geographic
distribution of genetic diversity.
Results: Genetic population structure corresponded to the
Adriatic gyres without additional effect of geographic distance.
Inference of northward‐biased gene flow between the northern and
the Istrian gyre was consistent with simulated trajectories of
passive drift, whereas the phylogeographic break coinciding with
the boundary between the Central and the Northern Adriatic gyre
was stronger than predicted by drift simulations. Genetic
connectivity of populations within gyres was high. Genetic
signatures of population expansion were consistent with a rapid
post‐glacial recolonization of the northern Adriatic.
Main conclusions: The combination of dense sampling and passive
drift simulation allowed us to distinguish among effects of
geographic distance, oceanographic features and
palaeoenvironmental changes on current population structure.
Comparisons between realized and potential connectivity
illustrate the value of integrating different data sources to
understand population structure and inform conservation
planning.