Areas of endemism are considered the fundamental unit in historical biogeography because they are the entities to be compared in biogeographic analysis. However, until recently, there were no formal methods for its identification. In this paper, I applied two different methods for the identification of areas of endemism of the genus Liolaemus, the parsimony analysis of endemicity (PAE), and a recently proposed method based on an optimality criterion implemented in the computer program NDM. I analyzed the distributions of 29 species of Liolaemus inhabiting the Puna region in Northwestern Argentina. The analysis with NDM found four areas of endemism that show a repeated pattern of species groups, with the same groups in each area. On the other hand, results generated through PAE were not congruent with those of NDM and sometimes violated the definition of endemism. The patterns found suggest that these groups of species could have been affected by the same historical events.