The 1st component (PC1, 52.32% variance) clearly separated harvest from cold-treated samples.
The 1st component (F1) which explains most of the variance in the data set (highest Eigenvalue) is the axis separating the non-infected controls from the infected animals.
In general, uncentered data practically channel all of the original's data variance in the 1st component (variances 98.5% and 98.3% for cases A, B respectively).
About two-third (62.85%) of the variability in nest habitat characteristic was explained by the 1st component of the CatPCA (eigenvalue for dimension one = 5.03, Cronbach's α = 0.92).
The 1st component accounted for 46.3% of the total variance in number of invasive species (F1, 22 = 19.002, p<0.001) (Table S4).
The 1st component accounted for 80.8% of the total variance in the number of invasive species (F3, 24 = 263.532, p<0.001) (Table S3).
In Figure 16 we show the scatter plot of the data on the 1st component vector of the time & stimulant (population) mode.
The 1st component reflects mainly the mean of the original data Fig. 5 Non-centered yet scaled SVD-based PCA on a bi-variate data set composed by a post- and a pre-fire MODIS surface reflectance band 2. Black dots and grey asterisks are respectively samples of burned surfaces and vegetation.
