LAUSR

Identifying areas of endemism has represented a great challenge, from the search for their definition, the design of methodologies, and the management of essential information to identify areas where the distributions of at least two taxa overlap. Endemicity Analysis is a widely used method that offers good results; however, an evaluation of the results is necessary. We evaluated the previous establishment of the minimum endemicity index of the species as a criterion to identify areas of endemism, applicated to a set of taxa with endemic and preferential distribution to the Sierra Madre Oriental. The taxa included in our analyses were 178 species of plants, vertebrates, and invertebrates. First, we varied the parameter set minimum score species in the software and the size of the cell. Next, we established criteria to evaluate the results obtained: areas supported by unique sets of species, good fit to the area, and sympatric distribution of taxa (extensive or homopatrid). After choosing the minimum ei with the best performance, we modified the study method for the endemicity analysis (Endemicity Analysis with Progressive Species Elimination). Our results indicate that the variation of the ei influenced the number of areas obtained by the program, decreasing considerably after evaluating the first criterion. The best fit to the cells occurred when we set 0.8 as the minimum ei in both cell sizes. The visually-preview of the sympatrid relationships allowed to recognize areas that do not present congruent distributions, although they meet the two previous criteria evaluated. The areas of endemism identified at different scales and those identified with the implementation of our modification were complementary.