The Role of Ocean Circulation Dynamics in Structuring Genetic Connectivity of Marine Fish Populations Along the West African Coast

Ocean circulation systems are fundamental determinants of larval dispersal and population connectivity in broadcast-spawning marine fish, yet the mechanistic linkage between oceanographic transport and population genetic structure along the West African coast remains theoretically underspecified. This research investigates the ocean circulation drivers of genetic connectivity for three commercially important marine fish species (Sardinella aurita, Sciaena umbra, and Scomber colias) along the West African coast between Senegal and Gabon, with particular focus on the Nigerian maritime zone. Biophysical larval transport modelling using a Lagrangian particle-tracking framework coupled with a regional ocean circulation model (ROMS-CROCO) was used to generate predicted connectivity matrices. Population genomic data from 2bRAD genotyping (8,000 loci) were generated for 360 individuals from 12 sampling sites. Isolation-by-distance, isolation-by-oceanography, and environmental association analyses were performed to attribute genetic differentiation to physical barriers versus oceanographic transport. The Guinea Current and its seasonal reversal were identified as the dominant circulation features structuring larval dispersal. Biophysical model predictions of connectivity were significantly correlated with genetic connectivity for all three species (Mantel test r values 0.61 to 0.79). The upwelling cell off Cape Palmas emerged as an oceanographic barrier for two species, producing significant FST values of 0.08 to 0.12 across the Cape. The Nigerian continental shelf exhibited moderate self-recruitment (35 to 52 percent) for all species, with strongest connectivity to Beninese and Ghanaian shelf populations. This research provides an original theoretical architecture linking oceanographic transport models with population genomics. Keywords: population connectivity, ocean circulation, West Africa, biophysical modelling, population genomics.