*3.5. Multivariate Statistical Analyses*

Principal component analyses (PCA) is used to reduce the dimensionality of a multivariate data set to a few principal factors that determine the distributions of species. For this analysis all raw data for the totality of the samples and specimens were used. Raw data were processed using PAST (2.17) multivariate statistical software package of [85]. The resulting factor scores show the contribution of each factor in every sample, and therefore the down-core contribution of each factor. The total number of factors was defined by minimizing the remaining "random" variability, and by the possibility to relate the factors to modern hydrographic conditions and planktonic foraminiferal and pteropod ecology.
