Data from: The influence of locus number and information content on species delimitation: an empirical test case in an endangered Mexican salamander
Data files
Oct 14, 2016 version files 202.10 KB
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Ordinarium_Data.zip
202.10 KB
Abstract
Perhaps the most important recent advance in species delimitation has been the development of model-based approaches to objectively diagnose species diversity from genetic data. Additionally, the growing accessibility of next-generation sequence datasets provides powerful insights into genome-wide patterns of divergence during speciation. However, applying complex models to large datasets is time consuming and computationally costly, requiring careful consideration of the influence of both individual and population sampling, as well as the number and informativeness of loci on species delimitation conclusions. Here, we investigated how locus number and information content affect species delimitation results for an endangered Mexican salamander species, Ambystoma ordinarium. We compared results for an eight-locus, 137-individual dataset and an 89-locus, seven-individual dataset. For both datasets, we used species discovery methods to define delimitation models and species validation methods to rigorously test these hypotheses. We also used integrated demographic model selection tools to choose among delimitation models, while accounting for gene flow. Our results indicate that while cryptic lineages may be delimited with relatively few loci, sampling larger numbers of loci may be required to ensure that enough informative loci are available to accurately identify and validate shallow-scale divergences. These analyses highlight the importance of striking a balance between dense sampling of loci and individuals, particularly in shallowly-diverged lineages. They also confirm the presence of a currently unrecognized, endangered species in the western part of A. ordinarium's range.