title: Detecting populations in the 'ambiguous' zone: kinship-based estimation of population structure at low genetic divergence.
abstract: Identifying population structure is one of the most common and important objectives of spatial analyses using population genetic data. Population structure is detected either by rejecting the null hypothesis of a homogenous distribution of genetic variation, or by estimating low migration rates. Issues arise with most current population genetic inference methods when the genetic divergence is low among putative populations. Low levels of genetic divergence may be as a result of either high ongoing migration or historic high migration but no current, ongoing migration. We direct attention to recent developments in the use of the tempo-spatial distribution of closely related individuals to detect population structure or estimate current migration rates. These 'kinship-based' approaches complement more traditional population-based genetic inference methods by providing a means to detect population structure and estimate current migration rates when genetic divergence is low. However, for kinship-based methods to become widely adopted, formal estimation procedures applicable to a range of species life histories are needed.
authors.affiliation: Department of Genetics, Microbiology and Toxicology, Stockholm University, SE-106 91 Stockholm, Sweden Department of Forest and Wildlife Ecology, University of Wisconsin Madison, 1630 Linden Drive, Madison, WI 53706, USA.
authors.forename: Per J
authors.initials: PJ
authors.lastname: Palsbøll
authors.forename: M
authors.initials: M
authors.lastname: Zachariah Peery
authors.forename: Martine
authors.initials: M
authors.lastname: Bérubé