Abstract
Estimating the rate of exchange of individuals among populations is a central concern to evolutionary ecology and its applications to conservation and management. For instance, the efficiency of protected areas in sustaining locally endangered populations and ecosystems depends on reserve network connectivity. The population genetics theory offers a powerful framework for estimating dispersal distances and migration rates from molecular data. In the marine realm, however, decades of molecular studies have met limited success in inferring genetic connectivity, due to the frequent lack of spatial genetic structure in species exhibiting high fecundity and dispersal capabilities. This is especially true within biogeographic regions bounded by well-known hotspots of genetic differentiation. Here, we provide an overview of the current methods for estimating genetic connectivity using molecular markers and propose several directions for improving existing approaches using large population genomic datasets. We highlight several issues that limit the effectiveness of methods based on neutral markers when there is virtually no genetic differentiation among samples. We then focus on alternative methods based on markers influenced by selection. Although some of these methodologies are still underexplored, our aim was to stimulate new research to test how broadly they are applicable to nonmodel marine species. We argue that the increased ability to apply the concepts of cline analyses will improve dispersal inferences across physical and ecological barriers that reduce connectivity locally. We finally present how neutral markers hitchhiking with selected loci can also provide information about connectivity patterns within apparently well-mixed biogeographic regions. We contend that one of the most promising applications of population genomics is the use of outlier loci to delineate relevant conservation units and related eco-geographic features across which connectivity can be measured.
Highlights
Inferring population connectivity from molecular data within a population genetic framework can shed light on the evolutionary and ecological processes that shape patterns of genetic diversity (Clobert et al 2012)
We rather aim at considering the new perspectives offered by the increasing number of markers in population genomic studies, with a special focus on the use of loci influenced by selection
Substantial progresses in our understanding of connectivity in nonmodel organism can be achieved with large population genomic datasets
Summary
Inferring population connectivity from molecular data within a population genetic framework can shed light on the evolutionary and ecological processes that shape patterns of genetic diversity (Clobert et al 2012). Population or parentage assignment methods allow estimating dispersal rates or distances without necessarily relying on demo-genetic models On the downside, these approaches generally require a great deal of data, very good knowledge of the species distribution, and make the sampling design critical as it must be representative of the postdispersal distribution of individuals (evaluation of long-distance dispersal might be especially difficult due to constraints in the size of the study area). More markers may enhance the statistical power of genetic studies and yield more precise estimates of small genetic differentiation values (Patterson et al 2006), but the signature of dispersal contained in the data may remain intrinsically small or inexistent It is not clear whether increasing the number of loci will help in situations where large effective population size keeps genetic structure down, even with restricted migration. The indirect effect of selection transiently generated at a linked neutral hitchhiker locus has revealed a sufficiently clear pattern to demonstrate demographic independence
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