BackgroundIn zoology, species descriptions conventionally rely on invasive morphological techniques, frequently leading to damage of the specimens and thus only a partial understanding of their structural complexity. More recently, non-destructive imaging techniques have successfully been used to describe smaller fauna, but this approach has so far not been applied to identify or describe larger animal species. Here, we present a combination of entirely non-invasive as well as minimally invasive methods that permit taxonomic descriptions of large zoological specimens in a more comprehensive manner.ResultsUsing the single available representative of an allegedly novel species of deep-sea cephalopod (Mollusca: Cephalopoda), digital photography, standardized external measurements, high-field magnetic resonance imaging, micro-computed tomography, and DNA barcoding were combined to gather all morphological and molecular characters relevant for a full species description. The results show that this specimen belongs to the cirrate octopod (Octopoda: Cirrata) genus Grimpoteuthis Robson, 1932. Based on the number of suckers, position of web nodules, cirrus length, presence of a radula, and various shell characters, the specimen is designated as the holotype of a new species of dumbo octopus, G. imperator sp. nov. The digital nature of the acquired data permits a seamless online deposition of raw as well as derived morphological and molecular datasets in publicly accessible repositories.ConclusionsUsing high-resolution, non-invasive imaging systems intended for the analysis of larger biological objects, all external as well as internal morphological character states relevant for the identification of a new megafaunal species were obtained. Potentially harmful effects on this unique deep-sea cephalopod specimen were avoided by scanning the fixed animal without admixture of a contrast agent. Additional support for the taxonomic placement of the new dumbo octopus species was obtained through DNA barcoding, further underlining the importance of combining morphological and molecular datasets for a holistic description of zoological specimens.
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