2020MNRAS.499.5607M

We propose a phylogenetic approach (PA) as a novel and robust tool to detect galaxy populations (GPs) based on their chemical composition. The branches of the tree are interpreted as different GPs and the length between nodes as the internal chemical variation along a branch. We apply the PA using 30 abundance indices from the Sloan Digital Sky Survey to 475 galaxies in the Coma Cluster and 438 galaxies in the field. We find that a dense environment, such as Coma, shows several GPs, which indicates that the environment is promoting galaxy evolution. Each population shares common properties that can be identified in colour-magnitude space, in addition to minor structures inside the red sequence. The field is more homogeneous, presenting one main GP. We also apply a principal component analysis (PCA) to both samples, and find that the PCA does not have the same power in identifying GPs.