Large-scale biogeographic patterns are reflected in the genetic structure of a broadcast spawning stony coral

Abstract

Countries in the Western Indian Ocean (WIO) and along the Red Sea are particularly vulnerable to coral reef degradation, and understanding the degree of connectivity among coral reefs is a first step toward efficient conservation. The aim of this study is to investigate the genetic diversity, population structure and connectivity patterns of the broadcast spawning coral Acropora tenuis, first at a large scale comparing the Red Sea and the WIO, and second at a smaller scale comparing sites within the WIO. In total 689 individual A. tenuis colonies were sampled on 28 locations in Saudi Arabia, Kenya, Tanzania, Mozambique and Madagascar and analysed with seven microsatellite markers. The sample site in the Red Sea was found to be differentiated from all other sites in the WIO, which confirms the hypothesised genetic break. High differentiation was found between the African mainland and Madagascar and within Madagascar. However, there is evidence for long-distance larval dispersal for A. tenuis in the North Mozambique Channel region, with exchange between northern Mozambique and northern Madagascar. The sites in the southwest of Madagascar show mixing with sites in northern Madagascar, as well as exchange with sites in northern Mozambique and Tanzania. Southern Mozambique forms a separate group in Bayesian clustering. High genetic connectivity was found for most sites along the East African mainland coast, with no indication for strict genetic barriers. These results support biophysical modelling studies, which propose Tanzania as a seeding source of larvae for downstream Kenya. These patterns of high genetic connectivity combined with contemporary dispersal barriers can be explained by the long larval duration of A. tenuis and the prevailing northbound East African Coast Current that facilitates higher genetic connectivity along the northern East African Coast, while eddies in the Mozambique Channel are causing larval retention in southern Mozambique and Madagascar.

Global coral genomic vulnerability explains recent reef losses

“…Third, genetic diversity within datasets followed a scaling relationship with area ( 18 ) that confirmed decreasing gene flow with increasing geographic distance, as observed in other Acropora populations ( Fig. S24 ) ( 19, 20 ).…”

Coral reef potential connectivity in the southwest Indian Ocean

“…Our analyses group the entire Mozambique Channel region together at low numbers of clusters (supplementary materials, fig. S7), indicative of frequent larval dispersal across the basin, further supported by population genetics from a broadcasting coral (van der Ven et al, 2022). However, with finer granularity, it is clear that a (permeable) dispersal barrier exists across the Mozambique Channel (fig.…”

“…On the other hand, no such barrier was identified by Spalding et al (2007), or other population genetic analyses (e.g. Souter and Grahn, 2008; van der Ven et al, 2022). Spalding et al (2007) instead identified an ecoregion boundary in northern Kenya.…”

“…In general, however, the prediction of strong coral connectivity along the path of the East African Coastal Current is strongly supported by coral population genetics (Souter and Grahn, 2008;Souter et al, 2009;van der Ven et al, 2016van der Ven et al, , 2021van der Ven et al, , 2022, although there is also evidence for local-scale genetic differentiation. For instance, Souter et al (2009) found significant differentiation between corals sampled in northeast and west Zanzibar, and most other samples in the region.…”

Biophysical models resolution affects coral connectivity estimates

“…Given the vastness of coral reef ecosystems like the GBR, the number of reefs composing them, and the huge number of larvae released during spawning events, it is impossible to directly validate our models by tracking individual larvae in the water. Indirect validation of larvae dispersal based on genetic markers [51][52][53] is also not an option as the processes driving genetic differentiation take place on time scales of multiple generations 54 , where we only simulated one spawning event. The simulated hydrodynamics, which drive larval dispersal, has however been properly validated 20,38,47 .…”