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Genetic structure is influenced by landscape features: empirical evidence from a roe deer population
Author(s) -
COULON A.,
GUILLOT G.,
COSSON J.F.,
ANGIBAULT J. M. A.,
AULAGNIER S.,
CARGNELUTTI B.,
GALAN M.,
HEWISON A. J. M.
Publication year - 2006
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/j.1365-294x.2006.02861.x
Subject(s) - genetic structure , population , structuring , biology , gene flow , ecology , landscape connectivity , landscape epidemiology , population genetics , genetic variation , evolutionary biology , landscape ecology , biological dispersal , habitat , genetics , demography , gene , finance , sociology , economics
The delimitation of population units is of primary importance in population management and conservation biology. Moreover, when coupled with landscape data, the description of population genetic structure can provide valuable knowledge about the permeability of landscape features, which is often difficult to assess by direct methods (e.g. telemetry). In this study, we investigated the genetic structuring of a roe deer population which recently recolonized a fragmented landscape. We sampled 1148 individuals from a 40 × 55‐km area containing several putative barriers to deer movements, and hence to gene flow, namely a highway, rivers and several canals. In order to assess the effect of these landscape features on genetic structure, we implemented a spatial statistical model known as geneland which analyses genetic structure, explicitly taking into account the spatial nature of the problem. Two genetic units were inferred, exhibiting a very low level of differentiation ( F ST = 0.008). The location of their boundaries suggested that there are no absolute barriers in this study area, but that the combination of several landscape features with low permeability can lead to population differentiation. Our analysis hence suggests that the landscape has a significant influence on the structuring of the population under study. It also illustrates the use of geneland as a powerful method to infer population structure, even in situations of young populations exhibiting low genetic differentiation.