Spatio-temporal patterns of genetic variation in Arbacia lixula, a thermophilous sea urchin in expansion in the Mediterranean

The genetic structure of 13 populations of the amphiatlantic sea urchin Arbacia lixula, as well as temporal genetic changes in three of these localities, were assessed using ten hypervariable microsatellite loci. This thermophilous sea urchin is an important engineer species triggering the formation of barren grounds through its grazing activity. Its abundance seems to be increasing in most parts of the Mediterranean, probably favoured by warming conditions. Significant genetic differentiation was found both spatially and temporally. The main break corresponded to the separation of western Atlantic populations from those in eastern Atlantic and the Mediterranean Sea. A less marked, but significant differentiation was also found between Macaronesia (eastern Atlantic) and the Mediterranean. In the latter area, a signal of differentiation between the transitional area (Alboran Sea) and the rest of the Mediterranean was detected. However, no genetic structure is found within the Mediterranean (excluding Alboran) across the Siculo-Tunisian Strait, resulting from either enough gene flow to homogenize distance areas or/and a recent evolutionary history marked by demographic expansion in this basin. Genetic temporal variation at the Alboran Sea is as important as spatial variation, suggesting that temporal changes in hydrological features can affect the genetic composition of the populations. A picture of genetic homogeneity in the Mediterranean emerges, implying that the potential expansion of this keystone species will not be limited by intraspecific genetic features and/or potential impact of postulated barriers to gene flow in the region.

Cryptic species and parallel genetic structuring in Lethrinid fish: Implications for conservation and management in the southwest Indian Ocean

Analysis of genetic variation can provide insights into ecological and evolutionary diversification which, for commercially harvested species, can also be relevant to the implementation of spatial management strategies and sustainability. In comparison with other marine biodiversity hot spots, there has been less genetic research on the fauna of the southwest Indian Ocean (SWIO). This is epitomized by the lack of information for lethrinid fish, which support socioeconomically important fisheries in the region. This study combines comparative phylogeographic and population genetic analyses with ecological niche modeling to investigate historical and contemporary population dynamics of two species of emperor fish (Lethrinus mahsena and Lethrinus harak) across the SWIO. Both species shared similarly shallow phylogeographic patterns and modeled historical (LGM) habitat occupancies. For both species, allele frequency and kinship analyses of microsatellite variation revealed highly significant structure with no clear geographical pattern and nonrandom genetic relatedness among individuals within samples. The genetic patterns for both species indicate recurrent processes within the region that prevent genetic mixing, at least on timescales of interest to fishery managers, and the potential roles of recruitment variability and population isolation are discussed in light of biological and environmental information. This consistency in both historical and recurrent population processes indicates that the use of model species may be valuable in management initiatives with finite resources to predict population structure, at least in cases wherein biogeographic and ecological differences between taxa are minimized. Paradoxically, mtDNA sequencing and microsatellite analysis of samples from the Seychelles revealed a potential cryptic species occurring in sympatry with, and seemingly morphologically identical to, L. mahsena. BLAST results point to the likely misidentification of species and incongruence between voucher specimens, DNA barcodes, and taxonomy within the group, which highlights the utility and necessity of genetic approaches to characterize baseline biodiversity in the region before such model-based methods are employed.