Literature DB >> 19793351

Spatial genetic structure in continuous and fragmented populations of Pinus pinaster Aiton.

A I De-Lucas1, S C González-Martínez, G G Vendramin, E Hidalgo, M Heuertz.   

Abstract

Habitat fragmentation, i.e., the reduction of populations into small isolated remnants, is expected to increase spatial genetic structure (SGS) in plant populations through nonrandom mating, lower population densities and potential aggregation of reproductive individuals. We investigated the effects of population size reduction and genetic isolation on SGS in maritime pine (Pinus pinaster Aiton) using a combined experimental and simulation approach. Maritime pine is a wind-pollinated conifer which has a scattered distribution in the Iberian Peninsula as a result of forest fires and habitat fragmentation. Five highly polymorphic nuclear microsatellites were genotyped in a total of 394 individuals from two population pairs from the Iberian Peninsula, formed by one continuous and one fragmented population each. In agreement with predictions, SGS was significant and stronger in fragments (Sp = 0.020 and Sp = 0.026) than in continuous populations, where significant SGS was detected for one population only (Sp = 0.010). Simulations suggested that under fat-tailed dispersal, small population size is a stronger determinant of SGS than genetic isolation, while under normal dispersal, genetic isolation has a stronger effect. SGS was always stronger in real populations than in simulations, except if unrealistically narrow dispersal and/or high variance of reproductive success were modelled (even when accounting for potential overestimation of SGS in real populations as a result of short-distance sampling). This suggests that factors such as nonrandom mating or selection not considered in the simulations were additionally operating on SGS in Iberian maritime pine populations.

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Year:  2009        PMID: 19793351     DOI: 10.1111/j.1365-294X.2009.04372.x

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


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