<p>The (a) biogeochemical subprovinces of the Mediterranean Sea, as defined by the 5% threshold for the full multivariate array, and the (b–f) PC analysis arrow plots and time series of the retained PCs for each of the subprovinces, derived from the mean of all pixels in the subprovince for each month of the data set. Arrows that align well with an axis are well-explained by that axis. The longer the arrow, the more it contributes to explaining the variability of an axis. Variable abbreviations are as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111251#pone-0111251-g004" target="_blank">Figure 4</a>.</p
Dashed lines delimit climatic clusters that group 20% of the explained variance of PC1 and PC2. Gree...
<p>a) Principal Component Analysis performed on physicochemical data, with samples grouped by season...
<p>Principal component analysis of the abundance pattern of bacterial genera across the three cluste...
25 pages, 16 figures, 1 table[EN] A set of oceanographic data (13 variables, Table 1) taken between ...
<p>Dashed lines delimit the climatic clusters that group 10% of the explained variance by PC1 and PC...
In the framework of model complexity reduction, we investigate the ability of the principal componen...
<p>Principal coordinates analysis (PCA) of the nine measured environmental ...
<p>Principal component analysis (PCA) of rhizosphere (triangle) and bulk (square) communities of sed...
<p>Dots represent sites within estuaries. Vectors show the two-dimensional (PC1 and PC2) correlation...
<p>The ordination plot summarizes the variation of the environmental and biotic variables across the...
<p>Cumulatively, PC axes explain 78.7% (climate), 79.6% (soil and terrain), 56.6% (climate, soil and...
<p>The ordination plot summarizes the variation of the environmental and biotic variables across the...
<p>First PCA based on mean SST ranging from -1°C to 30°C. (<b>A</b>) First principal component (PC)....
Multivariate Principal Component Analysis (MPCA) is used to decompose a series of AVHRR SST maps an...
<p>Principal component analysis ordinations of a) pairwise abundance-unweighted UniFrac distances an...
Dashed lines delimit climatic clusters that group 20% of the explained variance of PC1 and PC2. Gree...
<p>a) Principal Component Analysis performed on physicochemical data, with samples grouped by season...
<p>Principal component analysis of the abundance pattern of bacterial genera across the three cluste...
25 pages, 16 figures, 1 table[EN] A set of oceanographic data (13 variables, Table 1) taken between ...
<p>Dashed lines delimit the climatic clusters that group 10% of the explained variance by PC1 and PC...
In the framework of model complexity reduction, we investigate the ability of the principal componen...
<p>Principal coordinates analysis (PCA) of the nine measured environmental ...
<p>Principal component analysis (PCA) of rhizosphere (triangle) and bulk (square) communities of sed...
<p>Dots represent sites within estuaries. Vectors show the two-dimensional (PC1 and PC2) correlation...
<p>The ordination plot summarizes the variation of the environmental and biotic variables across the...
<p>Cumulatively, PC axes explain 78.7% (climate), 79.6% (soil and terrain), 56.6% (climate, soil and...
<p>The ordination plot summarizes the variation of the environmental and biotic variables across the...
<p>First PCA based on mean SST ranging from -1°C to 30°C. (<b>A</b>) First principal component (PC)....
Multivariate Principal Component Analysis (MPCA) is used to decompose a series of AVHRR SST maps an...
<p>Principal component analysis ordinations of a) pairwise abundance-unweighted UniFrac distances an...
Dashed lines delimit climatic clusters that group 20% of the explained variance of PC1 and PC2. Gree...
<p>a) Principal Component Analysis performed on physicochemical data, with samples grouped by season...
<p>Principal component analysis of the abundance pattern of bacterial genera across the three cluste...