Recovery of evolutionary history and delimiting species boundaries in widely distributed, poorly-known groups requires extensive geographic sampling, but this is difficult to design a priori because evolutionary diversity is often "hidden" by an inadequate taxonomy. Large data sets are needed, and these provide unique challenges for analysis when they span intra and inter-specific levels of divergence. Protocols have been designed to combine methods of analysis for DNA sequences that exhibit both very shallow and relatively deeper divergences (Crandall and Fitzpatrick, 1996). In this study we combine several tree-based phylogeny reconstruction methods with nested clade analysis, to extract maximum historical signal at various levels, in the poorly-known Liolaemus elongatus-kriegi complex in temperate South America. We implement the basic protocol of Wiens and Penkrot (2002) to test for species boundaries, and propose modifications to accommodate large data sets and gene regions with heterogeneous substitution rates. Combining haplotype trees with nested-clade analyses allowed testing of species boundaries on the basis of a priori defined criteria, and this approach suggests that the number of putative species could be doubled. We discuss these findings in the context of the advantages and limitations of a combined approach for retrieval of maximum historical information in large data sets, in the context of the yet formidable unresolved issues of sampling strategies.