Spatial genetic structure of a small rodent in a heterogeneous landscape

• DOI: 10.1111/j.1365-294x.2008.03950.x
• Publication Date: 2008-11-04T19:02:48Z
• Authors: B. GAUFFRE; A. ESTOUP; V. BRETAGNOLLE; J. F. COSSON
• Keywords: Gene Flow; 0301 basic medicine; 570; [SDE.MCG]Environmental Sciences/Global Changes; Population Dynamics; microsatellites; 03 medical and health sciences; clustering methods; computer simulation; Animals; Cluster Analysis; Computer Simulation; [SDE.ES]Environmental Sciences/Environment and Society; Alleles; Ecosystem; Models, Genetic; Arvicolinae; Genetic Variation; landscape genetics; Bayes Theorem; Sequence Analysis, DNA; 15. Life on land; [SDE.ES]Environmental Sciences/Environmental and Society; Genetics, Population; France; [SDE.BE]Environmental Sciences/Biodiversity and Ecology; gene flow; spatial genetic structure

AbstractGene flow in natural populations may be strongly influenced by landscape features. The integration of landscape characteristics in population genetic studies may thus improve our understanding of population functioning. In this study, we investigated the population genetic structure and gene flow pattern for the common vole,Microtus arvalis, in a heterogeneous landscape characterised by strong spatial and temporal variation. The studied area is an intensive agricultural zone of approximately 500 km2crossed by a motorway. We used individual‐based Bayesian methods to define the number of population units and their spatial borders without prior delimitation of such units. Unexpectedly, we determined a single genetic unit that covered the entire area studied. In particular, the motorway considered as a likely barrier to dispersal was not associated with any spatial genetic discontinuity. Using computer simulations, we demonstrated that recent anthropogenic barriers to effective dispersal are difficult to detect through analysis of genetic variation for species with large effective population sizes. We observed a slight, but significant, pattern of isolation by distance over the whole study site. Spatial autocorrelation analyses detected genetic structuring on a local scale, most probably due to the social organisation of the study species. Overall, our analysis suggests intense small‐scale dispersal associated with a large effective population size. High dispersal rates may be imposed by the strong spatio‐temporal heterogeneity of habitat quality, which characterises intensive agroecosystems.