Spatial position and microsatellite genotyping of S. ciliata plants
The patterns and intensity of fine-scale spatial genetic structure (FSGS) can vary among populations within species depending on the interplay between different demographic and environmental factors. Theoretical models predict that FSGS will increase especially with local density variation due to static habitat heterogeneities, but few empirical studies have examined the differences in FSGS among populations with different degrees of spatial heterogeneity. In this study we used spatial autocorrelation methods to assess spatial demographic and genetic structures of five demographically stable but spatially heterogeneous populations of high-mountain specialist Silene ciliata Poiret (Caryophyllaceae). In each population we recorded the geographical location of every individual and genotyped 96 of them using 8 microsatellite markers. We found significant FSGS in three out of the five populations and a significant positive association between spatial demographic and genetic structures, thereby supporting the importance of fine-scale aggregation of plants on intraespecific FSGS variation. Contrary to previous findings in other plant species, the population with highest plant density was the one with strongest FSGS, probably due to reduced long-term gene dispersal rates in fragmented habitats and lower pollinator mobility in response to high densities and spatial aggregation of plants. Overall our results support the importance of fine-scale aggregation of plants on intraspecific FSGS variation, and stress the importance of combining FSGS analyses with explicit characterization of local spatial distribution of individuals and habitat to better understand the mechanisms generating intraspecific variation in FSGS across landscapes.
In August and September 2010, we established one 10x10m plot in each of five S. ciliata populations distributed along the Sierra de Guadarrama (Figure 1, Table 1). Additional information about the selected populations can be found in Lara-Romero et al. 2014. In each study plot, we mapped every adult S. ciliata individual using two high-resolution Differential Global Navigation Satellite System (DGNSS) receivers (Viva GS15, Leica, Switzerland) with an absolute accuracy of 5 cm for x and y coordinates. We also collected leaf material of 96 adult plants per plot for genetic analysis. In order to increase sample size of shorter inter-individual distances for autocorrelation analysis, plants were selected using a clustered random sampling design (sensu Storfer et al. 2007). Namely we randomly selected 24 sample locations in each plot, where we collected leaf material of four individuals located in close proximity to each other. Portions of leaves with no sign of parasites, fungal infection or drought injuries were collected, and subsequently cleaned and dried in silica gel. DNA was extracted using the DNeasy Plant minikit (QIAGEN, Barcelona, Spain) with 10¿20 mg of dried S. ciliata tissue. Ten microsatellite loci previously used in genetic studies of S. ciliata were selected for genotyping: Sci1224, Sci1208, Sci0106, Sci1443 EST-2HTS, EST-8HTS, EST-37HTS, EST-X4-3, EST-G34D06 and EST-G47A02 (García-Fernández et al. 2012b) Specifications of PCR reactions and amplification are detailed in García Fernández et al. (2012b). Samples were run on an automated DNA sequencer (ABI PRISM 3730, Applied Biosystems, California, USA) in Parque Científico de Madrid (Madrid, Spain). Fragment sizes were assigned to alleles using GeneMarker version 1.85 (SoftGenetics, State College, Pennsylvania, USA. After checking, we discarded locus Sci1443 and EST-SSR X4-3 because of inconsistent allelic scoring and the possible presence of null alleles, respectively.
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