Data from: Sampling strategies for delimiting species: genes, individuals, and populations in the Liolaemus elongatus-kriegi complex (Squamata: Liolaemidae) in Andean-Patagonian South America

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.