18 research outputs found

    AFLP matrix Ulmus

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    The data file contains two spread sheets. The first shows the AFLP data - in the first column the sample codes, in the second the location codes and in the third the species. The next 385 columns represent the different markers, named according to the primer combination and fragment size. Marker presence is noted as "1", marker absence is noted as "0". The second spread sheet contains location information: location code, country, city,longitude (lon),latitude (lat), number of samples (N) and remarks. Coordinates are in decimal degrees

    Genotypes and phenotypes of adults and seeds from four Fagus sylvatica stands characterised by different management regimes

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    The archive contains microsatellite genotypes, geographical locations and phenotypic characteristics of adults and seeds of four beech stands characterised by different management regimes. Details are reported in the readme.txt file

    Parameters describing within-population genetic structure in the studied beech plots.

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    <p><i>F</i><sub>1</sub>, average kinship coefficient between individuals of the first distance class (0–20 m); <i>b</i><sub>F</sub>, regression slope of the kinship estimator <i>F</i><sub>ij</sub> computed among all pairs of individuals against geographical distances; <i>Sp</i>, intensity of SGS; <i>Nc</i>, mean number of clusters from GENELAND analyses<i>; θ</i><sub>ST</sub>, differentiation among clusters within each plot; <i>F</i><sub>IS</sub>, inbreeding coefficient estimated by INEst.</p>*<p><i>P</i><0.05,</p>**<p><i>P</i><0.01,</p>***<p><i>P</i><0.001.</p

    Characteristics of investigated beech plots.

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    a<p>Plot codes were formed by the indication of country (G = Germany, NL = The Netherlands, A = Austria, F = France, I = Italy) and intensity of disturbance (l = low, h = high).</p>b<p>Austrian plots are subplots of Piotti et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073391#pone.0073391-Piotti1" target="_blank">[26]</a> plots.</p>c<p>Italian plots studied by Paffetti et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073391#pone.0073391-Paffetti1" target="_blank">[25]</a> are subplots of the ones analyzed here.</p

    Assessment of the power of the marker set to detect SGS by spatially explicit simulations.

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    <p>For illustration of the results, the distribution of the kinship coefficient <i>F</i><sub>1</sub> between neighbours at generation 64 was used as the focal statistic (grey dots and boxplots) and compared to <i>i</i>) the no-structure 95% confidence intervals of <i>F</i><sub>1</sub> from the Fh and Fl populations (dotted lines, see legend in the left panel) obtained by random shuffling of individual geographic locations, and <i>ii</i>) real <i>F</i><sub>1</sub> values from Fh and Fl (black dots in the left panel) and their confidence intervals (grey areas). Results from simulations with 4 and 20 loci (right and left panels, respectively) are reported. Parameter settings for the 4 simulated scenarios were σ<sub>g = </sub>12 m and D = 20 trees/ha (HIGH-SGS), σ<sub>g = </sub>12 m and D = 35 trees/ha (Fl-like SGS), σ<sub>g = </sub>29 m and D = 50 trees/ha (Fh-like SGS), σ<sub>g = </sub>72 m and D = 145 trees/ha (LOW-SGS).</p

    Correlograms from spatial autocorrelation analysis using the correlation coefficient <i>r</i> by Smouse & Peakall [29] and even distance classes.

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    <p>Shaded areas represent the 95% confidence interval obtained through random shuffling (1000 times) of individual geographic locations, black lines around mear <i>r</i> values represent 95% confidence intervals around mean r values generated by bootstrapping (1000 times) pair-wise comparisons within each distance class.</p
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