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Genome-wide SNP Data Reveal an Overestimation of Species Diversity in a Group of Hawkmoths
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2019-05-29
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2019-08-01
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speciation
species delineation
gene flow
RAD-sequencing
taxonomy
oversplitting
species delineation
gene flow
RAD-sequencing
taxonomy
oversplitting
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Abstract: The interface between populations and evolving young species continues to generate much contemporary debate in systematics depending on the species concept(s) applied but which ultimately reduces to the fundamental question of “when do nondiscrete entities become distinct, mutually exclusive evolutionary units”? Species are perceived as critical biological entities, and the discovery and naming of new species is perceived by many authors as a major research aim for assessing current biodiversity before much of it becomes extinct. However, less attention is given to determining whether these names represent valid biological entities because this is perceived as both a laborious chore and an undesirable research outcome. The charismatic spurge hawkmoths (Hyles euphorbiae complex, HEC) offer an opportunity to study this less fashionable aspect of systematics. To elucidate this intriguing systematic challenge, we analyzed over 10,000 ddRAD single nucleotide polymorphisms from 62 individuals using coalescent-based and population genomic methodology. These genome-wide data reveal a clear overestimation of (sub)species-level diversity and demonstrate that the HEC taxonomy has been seriously oversplit. We conclude that only one valid species name should be retained for the entire HEC, namely Hyles euphorbiae, and we do not recognize any formal subspecies or other taxonomic subdivisions within it. Although the adoption of genetic tools has frequently revealed morphologically cryptic diversity, the converse, taxonomic oversplitting of species, is generally (and wrongly in our opinion) accepted as rare. Furthermore, taxonomic oversplitting is most likely to have taken place in intensively studied popular and charismatic organisms such as the HEC.
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Copyright © The Author(s) 2019. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse,
distribution, and reproduction in any medium, provided the original work is properly cited.
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1759-6653
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1759-6653