Abstract
AbstractAimIsolation is expected to lead to negative impacts on populations due to a reduction in effective population size and gene flow, exacerbating the effects of genetic drift, which might be stronger in peripheral and fragmented populations. Fagus sylvatica (European beech) in southern Sweden presents a gradient of isolation towards the leading range edge of the species. We sought to determine the impact of long‐term isolation on genetic diversity and population genetic structure within populations of this species.LocationSamples were obtained from 14 sites towards the northern edge of the native range of beech in Sweden.TaxonFagaceae.MethodsUsing historical sources, we obtained area‐ and distance‐based measures of isolation. We measured genetic diversity and structure by using nuclear microsatellite marker data, and performed parentage analysis to estimate external pollen‐mediated gene flow. We implemented a partial least squares regression to determine the effects of isolation on each of the genetic diversity estimators and the measures of external pollen‐mediated gene flow.ResultsLong‐term isolation generally had a negative impact on genetic diversity, which is exacerbated over time, further affecting progeny and suggesting that isolated populations are subject to strong genetic drift, possibly due to the combination of founder events and persistent small population sizes. Bayesian cluster analysis revealed that isolation was also acting as a barrier to gene flow in the north‐eastern distribution of beech.Main conclusionsIsolation at the leading range edge of beech in Sweden has created gradients of contemporary gene flow within the species. The long‐term cumulative effects of isolation on this wind‐pollinated tree species and its negative impacts on genetic diversity and gene flow, could lead to inbreeding depression and higher extinction risk where populations remain small and isolated.
Highlights
Individual-based assignment methods were performed on the adult cohort using GENELAND 4.0.4 (Guillot et al, 2005) a spatially explicit Bayesian clustering model
Since primers for F. sylvatica are known to be subject to null alleles (Chybicki & Burczyk, 2009), the null allele model was implemented as recommended by (Guillot, Santos, & Estoup, 2008)
Repeats of 10 runs were performed for each K value, set from 1 to 10, with each run consisting of 500,000 Markov Chain Monte-Carlo (MCMC) iterations, with a burn-in period of 100,000, using the correlated allele frequency model (Falush, Stephens & Pritchard (2003) and the admixture ancestry model
Summary
Individual-based assignment methods were performed on the adult cohort using GENELAND 4.0.4 (Guillot et al, 2005) a spatially explicit Bayesian clustering model. To determine the initial number of K, the uncorrelated allele frequency model with a spatial prior was used, with K varying from 1 to 13. Since primers for F. sylvatica are known to be subject to null alleles (Chybicki & Burczyk, 2009), the null allele model was implemented as recommended by (Guillot, Santos, & Estoup, 2008). To check compliance of inferred clusters with modelling assumptions (Guillot, Lebloit, Coulon, & A.C., 2009), we performed tests for gametic disequilibrium within the three inferred clusters and genetic differentiation between pairs of clusters in FSTAT 2.9.3.2 (Goudet, 1995).
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