  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 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 of usual underlying
hypothesis required for the interpretation of classical analysis, 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 major perspectives
in ecology and evolution in general, particularly in areas such as conservation
biology and epidemiology, where targeting specific populations is crucial.
