Species Delimitation: A Case Study in a Problematic Ant Taxon

Department of Entomology, University of Georgia, Athens, GA 30602, USA.
Systematic Biology (Impact Factor: 14.39). 03/2010; 59(2):162-84. DOI: 10.1093/sysbio/syp089
Source: PubMed


Species delimitation has been invigorated as a discipline in systematics by an influx of new character sets, analytical methods, and conceptual advances. We use genetic data from 68 markers, combined with distributional, bioclimatic, and coloration information, to hypothesize boundaries of evolutionarily independent lineages (species) within the widespread and highly variable nominal fire ant species Solenopsis saevissima, a member of a species group containing invasive pests as well as species that are models for ecological and evolutionary research. Our integrated approach uses diverse methods of analysis to sequentially test whether populations meet specific operational criteria (contingent properties) for candidacy as morphologically cryptic species, including genetic clustering, monophyly, reproductive isolation, and occupation of distinctive niche space. We hypothesize that nominal S. saevissima comprises at least 4-6 previously unrecognized species, including several pairs whose parapatric distributions implicate the development of intrinsic premating or postmating barriers to gene flow. Our genetic data further suggest that regional genetic differentiation in S. saevissima has been influenced by hybridization with other nominal species occurring in sympatry or parapatry, including the quite distantly related Solenopsis geminata. The results of this study illustrate the importance of employing different classes of genetic data (coding and noncoding regions and nuclear and mitochondrial DNA [mtDNA] markers), different methods of genetic data analysis (tree-based and non-tree based methods), and different sources of data (genetic, morphological, and ecological data) to explicitly test various operational criteria for species boundaries in clades of recently diverged lineages, while warning against over reliance on any single data type (e.g., mtDNA sequence variation) when drawing inferences.

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