Areas of endemism of Lauraceae: new insights on the biogeographic regionalization of the Espinhaço Range, Brazil

Abstract

Using Lauraceae as a study case, we aimed in this article to: (i) delimit areas of endemism in the Espinhaço Range, Brazil; (ii) compare these areas of endemism with those previously delimited, as well as with the centres of endemism; (iii) evaluate the association between areas of endemism and vegetation types; and (iv) classify the areas of endemism according to the International Code of Area Nomenclature (ICAN). Based on a recent survey of 99 species from the Espinhaço Range, our dataset consisted of 34 endemic species belonging to nine genera. Following previous studies, we performed parsimony analysis of endemicity (PAE) using a grid square size of 0.5° × 0.5°. We delimited four areas of endemism of Lauraceae: (i) Antônio dos Santos, (ii) Conceição do Mato Dentro, (iii) Itambé do Mato Dentro, and (iv) Rio de Contas; and confirmed six previously delimited areas of endemism: (i) Southern MG, (ii) Southern Mountains Complex, (iii) Conceição do Mato Dentro, (iv) Diamantina Plateau, (v) Serra do Cabral, and (vi) Chapada Diamantina. The areas of endemism Conceição do Mato Dentro, Serra do Cabral, Diamantina, and Serra do Cipó were classified as subdistricts in the Diamantina Plateau district of the Southern Espinhaço province. We summarized and mapped all areas of endemism corresponding to the provinces, districts, and subdistricts that cover the Espinhaço Range. Areas of endemism and centres of endemism are contrasted. Finally, we highlight that the biogeographic studies along this mountain range should embrace higher taxa with representative species in different types of vegetation in order to enrich the majority of the endemism studies mainly concentrated on the campo rupestre. Unusual distribution patterns, diversity of vegetation types, and the presence of restricted species and monophyletic groups open up opportunities to carry out integrative studies concerning the biogeographic regionalization of the ER at multiple spatio-temporal scales.