Endemism of lizards in the Chihuahuan Desert province: An approach based on endemicity analysis

Abstract

Biogeography is the discipline that studies present and past distribution patterns ofbiological diversity and their underlying environmental (ecological) and historical causes(Sanmartín, 2012). It is known that different geological and climatic events occurring in thepast affect the distributions of co-existing taxa over time, establishing correlateddiversification patterns and groups of taxa from different time slices (divergence times) in asingle area of endemism (Morrone et al., 2016; Noguera-Urbano, 2016). Areas ofendemism (AEs) are the basic units in historical biogeographic studies (Morrone, 1994), aswell as for conservation biology (Whitakker et al., 2005), and are the result of taxaevolutionary processes (for example, vicariance/allopatric speciation). An area ofendemism is identified by the congruent distribution of two or more taxa (Platnick, 1991;Morrone, 1994; Szumik et al., 2002). Thus, taxa that have similar geographicaldistributions may have been influenced by common historical factors (Szumik et al., 2002).The Chihuahuan Desert (hereafter CD) is a biogeographic province that encompasses thenorthern region of Mexico and it is limited by the Sierra Madre Occidental and the SierraMadre Oriental provinces (Morrone, 2005, 2017). It is characterized by xeric environmentsand forests in high altitudes. The geographical extension of CD has enabled severalgeographical regionalization approaches. The identity of the CD as a natural region hasbeen supported by biogeographical analyses of different taxa: reptiles (Smith, 1941),mammals (Goldman and Moore, 1945), plants (Rzedowski, 1978; Arriaga et al., 1997),insects (Morrone, 1999, 2002, 2004 a, b) and it has been also delimited by applyingmorphotectonic criteria (Ferrusquía-Villafranca, 1990).In the last decades, different methods have emerged to identify EAs (Szumik et al., 2002;Szumik and Goloboff, 2004; Oliveira et al., 2015), and several problems have arisen in theidentification of AEs related to the use of different criteria of spatial congruence betweenspecies required to conform an AE. This issue has been discussed in different studies(Casagranda et al., 2009; Aagesen et al., 2013; Szumik and Goloboff, 2015; Szumik et al.,2018). The Endemicity Analysis (EA), implemented in the NDM/VNDM software, is oneof the most effective methods for identifying areas of endemism because it evaluates spatialcongruence of taxa over a set of cells (Szumik et al., 2002; Szumik and Goloboff, 2004)and considers the general concept of areas of endemism. EA identifies nested, overlappingand disjoint areas (Carine et al., 2009; Casagranda et al., 2009, 2012) and allows a varietyof analytical possibilities (see Escalante et al., 2013; Weirauch et al., 2016), including theuse of higher taxa for the identification of AEs, showing that some AEs recognized byspecies-level taxa also adjust well to the distribution of other higher level taxa i. e. genera,family (Szumik and Goloboff, 2015).Different studies using EA have been performed in northern Mexico (including theChihuahuan Desert, CD) with mammals (Escalante et al., 2007, 2009, 2010, 2013), insects(Rivas-Soto, 2011) and reptiles (Fernández-Badillo, 2013), but lizards have never beenincluded in EA studies as a group. Moreover, most of previous analyses have beenrestricted to northern Mexico without considering the distribution of taxa in the UnitedStates, limiting the endemicity patterns to geopolitical boundaries, which may not resemblenatural patterns. Because of this, Morafka, (2012) suggested that biological, ecological andphysiographic characteristics, as well as the total spatial distribution of taxa, should be usedto better characterize the naturalness of the CD in a historical biogeographic frame(Morrone et al., 2005).The main goal of this paper is to identify areas of endemism in the CD, using 81 species oflizards distributed throughout the province, by applying the EA implemented inNDM/VNDM software (Goloboff, 2004). The data are analyzed under different geographicscales (cell sizes) and using higher taxa (genera and families) together with species asanalytical units, in order to explore patterns at different taxonomic levels. We searched forthe times of divergence of endemic taxa in those AEs with high endemicity values, in orderto reconstruct the history of areas of endemism through time (Riddle et al., 2008).