Correlations of the five variables with the first (solid lines) and second (dashed lines) component displayed in the left panel. The right panel shows the percentage of variance of each variable for the first (solid lines) and the second (dashed lines) components. Years in the x-labels correspond to the first year of the season (i.e. 1996 for 1996–1997 season).</p
<p>First two principal components are shown. Each individual is represented by one dot and the color...
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
<p>Scores of a principal component analysis on climatic variables for the “full” and “wintering” dat...
<p>The first principal component was plotted on the x-axis and the second principal component was pl...
Results for 56 pooled samples based on AAFpool of 22,324 SNPs are summarized. PCA scores of the firs...
<p>Correlation values of each climatic variable with the two first axes of the principal components ...
<p>PCA of temperature (days above 13°C), average male size, male and female aggression, mating behav...
<p>Component correlation matrix of principal component analysis (PCA) used to determine relationship...
<p>Projection of the environmental variables (arrows) and the sampling dates (colored points) on the...
<p>The graph represents the number of PCA components considered and the related percentage of varian...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
<p>Two principal components, explaining 66.3% of the total variation, were retained from the PCA ana...
<p>Notes: using test z-scores; HVLT-R: Hopkins Verbal Learning Test–Revised; CTT: Color Trail Test; ...
<p>Representation of the two first components summarizing our data set. The co-ordinates of the comp...
<p>The first principal component accounts for 94.7% of variation and the second component explained ...
<p>First two principal components are shown. Each individual is represented by one dot and the color...
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
<p>Scores of a principal component analysis on climatic variables for the “full” and “wintering” dat...
<p>The first principal component was plotted on the x-axis and the second principal component was pl...
Results for 56 pooled samples based on AAFpool of 22,324 SNPs are summarized. PCA scores of the firs...
<p>Correlation values of each climatic variable with the two first axes of the principal components ...
<p>PCA of temperature (days above 13°C), average male size, male and female aggression, mating behav...
<p>Component correlation matrix of principal component analysis (PCA) used to determine relationship...
<p>Projection of the environmental variables (arrows) and the sampling dates (colored points) on the...
<p>The graph represents the number of PCA components considered and the related percentage of varian...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
<p>Two principal components, explaining 66.3% of the total variation, were retained from the PCA ana...
<p>Notes: using test z-scores; HVLT-R: Hopkins Verbal Learning Test–Revised; CTT: Color Trail Test; ...
<p>Representation of the two first components summarizing our data set. The co-ordinates of the comp...
<p>The first principal component accounts for 94.7% of variation and the second component explained ...
<p>First two principal components are shown. Each individual is represented by one dot and the color...
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
<p>Scores of a principal component analysis on climatic variables for the “full” and “wintering” dat...