Long range gene flow beyond predictions from oceanographic transport in a tropical marine foundation species

Abstract

The transport of passively dispersed organisms across tropical margins remains poorly understood. Hypotheses of oceanographic transportation potential lack testing with large scale empirical data. To address this gap, we used the seagrass species, Halodule wrightii, which is unique in spanning the entire tropical Atlantic. We tested the hypothesis that genetic differentiation estimated across its large-scale biogeographic range can be predicted by simulated oceanographic transport. The alternative hypothesis posits that dispersal is independent of ocean currents, such as transport by grazers. We compared empirical genetic estimates and modelled predictions of dispersal along the distribution of H. wrightii. We genotyped eight microsatellite loci on 19 populations distributed across Atlantic Africa, Gulf of Mexico, Caribbean, Brazil and developed a biophysical model with high-resolution ocean currents. Genetic data revealed low gene flow and highest differentiation between (1) the Gulf of Mexico and two other regions: (2) Caribbean-Brazil and (3) Atlantic Africa. These two were more genetically similar despite separation by an ocean. The biophysical model indicated low or no probability of passive dispersal among populations and did not match the empirical genetic data. The results support the alternative hypothesis of a role for active dispersal vectors like grazers.

Unravelling the role of oceanographic connectivity in the distribution of genetic diversity of marine forests at the global scale

“…average Fst: 0.33 ± 0.01), even when vast oceanic distances separate them (Tavares et al, 2023). Moreover, considering the role of long-distance events can shed light on potential colonization pathways beyond distribution fronts, particularly as new habitats may become suitable under future climate change (Bernardes Batista et al, 2018;Fraser et al, 2018;Gillespie et al, 2012).…”

“…shipping routes; Hudson et al, 2016;Saebi et al, 2020) or animal transportation (e.g. zoochory; Green & Figuerola, 2005;Lovas-Kiss et al, 2024;Proctor, 1968;Tavares et al, 2023).…”

Coastal oceanographic connectivity estimates at the global scale

“…Simulations of oceanographic connectivity were conducted with a biophysical modelling framework, previously used and validated against empirical demographic and genetic data from diverse ecological groups, such as fish 11 , molluscs 17,18,21 , macroalgae 3,14 , seagrass 22 and mangroves 2 . The model was conducted globally with surface data on the direction and intensity of ocean currents at the daily basis, derived from the Global Ocean Physics Reanalysis (GLORYS12V1), provided by the EU Copernicus Marine Service.…”