Network analysis identifies weak and strong links in a metapopulation system

Abstract

The identification of key populations shaping the structure and connectivity of metapopulation systems is a major challenge in population ecology. The use of molecular markers in the theoretical framework of population genetics has allowed great advances in this field, but the prime question of quantifying the role of each population in the system remains unresolved. Furthermore, the use and interpretation of classical methods are still bounded by the need for a priori information and underlying assumptions that are seldom respected in natural systems. Network theory was applied to map the genetic structure in a metapopulation system by using microsatellite data from populations of a threatened seagrass, Posidonia oceanica, across its whole geographical range. The network approach, free from a priori assumptions and from the usual underlying hypotheses required for the interpretation of classical analyses, allows both the straightforward characterization of hierarchical population structure and the detection of populations acting as hubs critical for relaying gene flow or sustaining the metapopulation system. This development opens perspectives in ecology and evolution in general, particularly in areas such as conservation biology and epidemiology, where targeting specific populations is crucial.conservation biology ͉ gene flow ͉ networks ͉ population genetics U nderstanding the connectivity between components of a metapopulation system and their role as weak or strong links remains a major challenge of population ecology (1-3). Advances in molecular biology fostered the use of indirect approaches to understand metapopulation structure, based on describing the distribution of gene variants (alleles) in space within the theoretical framework of population genetics (4-7). Yet, the premises of the classical Wright-Fisher model (4, 6), such as ''migration-drift'' and ''mutation-drift'' equilibrium (8), ''equal population sizes'' or symmetrical rate migration among populations, are often violated in real metapopulation systems. Threatened or pathogen species, for example, are precisely studied for their state of demographic disequilibrium due to decline and local extinctions in the first case, or to their complex dynamics of local decline and sudden pandemic burst in the second. Furthermore, the underlying hypotheses of equal population size and symmetrical migration rates hamper the identification of putative population ''hubs'' centralizing migration pathways or acting as sources in a metapopulation system, which is a central issue in ecology in general, and in conservation biology or epidemiology in particular. Finally, complementary methods of genetic structure analyses, such as hierarchical AMOVA and coalescent methods rely on a priori information (or priors) as to the clustering or demographic state of populations, requiring either subjective assumptions or the availability of reliable demographic, historical or ecological information that are seldom available.Network theory is emerging as a powerful tool to un...

Networks of spatial genetic variation across species

“…This procedure leads to networks of genetic variation containing the smallest link set that sufficiently explains the genetic covariance structure among patches. This methodology contrasts with the pruning proposed by a recent paper based on a cutoff strength of the genetic similarity below which links were removed (14). Our method also extends Dyer and Nason's procedure by taking into account the observed allelic frequency when calculating the genetic similarity among patches.…”

“…More recently, this approach has benefited from a network perspective (the so-called population graphs) embracing the simultaneous statistical relationships between all populations (10). To date, those papers that have applied network theory to explain spatial patterns of genetic variation have all focused on a single species (10)(11)(12)(13)(14). The question now is to what extent we can generalize the conclusions of these single-species studies to other related species.…”

“…Our approach is based on the integration of population graphs as a way to prune the original network of spatial genetic variation in a meaningful and informative way, and modularity analysis as a way to describe the structure of such a simplified network. This integrated approach, together with the extension to multispecies assemblages, makes our study stand out from previous papers (10)(11)(12)(13)(14).…”

Identifying critical regions in small-world marine metapopulations

“…A network perspective is extremely useful for understanding metapopulation structure and dynamics (14,21,29,33,35,(41)(42)(43)(44). However, there are several caveats to its application.…”

A genotype network reveals homoplastic cycles of convergent evolution in influenza A (H3N2) haemagglutinin

“…The conventional way to study evolutionary processes with genotypic data (but see [27,28]) is to construct phylogenetic trees that reflect the evolutionary relationships among genes, individuals or species [29]. Different genotypes are leaf nodes on such a tree.…”