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A micro X-ray computed tomography dataset of South African hermit crabs (Crustacea: Decapoda: Anomura: Paguroidea) containing scans of two rare specimens and three recently described species.
- Source :
-
GigaScience . Apr2018, Vol. 7 Issue 4, p1-N.PAG. 7p. - Publication Year :
- 2018
-
Abstract
- Background: Along with the conventional deposition of physical types at natural history museums, the deposition of 3-dimensional (3D) image data has been proposed for rare and valuable museum specimens, such as irreplaceable type material. Findings: Micro computed tomography (µCT) scan data of 5 hermit crab species from South Africa, including rare specimens and type material, depicted main identification characteristics of calcified body parts. However, low-image contrasts, especially in larger (>50 mm total length) specimens, did not allow sufficient 3D reconstructions of weakly calcified and fine characteristics, such as soft tissue of the pleon, mouthparts, gills, and setation. Reconstructions of soft tissue were sometimes possible, depending on individual sample and scanning characteristics. The raw data of seven scans are publicly available for download from the GigaDB repository. Conclusions: Calcified body parts visualized from µCT data can aid taxonomic validation and provide additional, virtual deposition of rare specimens. The use of a nondestructive, nonstaining µCT approach for taxonomy, reconstructions of soft tissue structures, microscopic spines, and setae depend on species characteristics. Constrained to these limitations, the presented dataset can be used for future morphological studies. However, our virtual specimens will be most valuable to taxonomists who can download a digital avatar for 3D examination. Simultaneously, in the event of physical damage to or loss of the original physical specimen, this dataset serves as a vital insurance policy. [ABSTRACT FROM AUTHOR]
- Subjects :
- *HERMIT crabs
*ANIMAL species
*COMPUTED tomography
Subjects
Details
- Language :
- English
- ISSN :
- 2047217X
- Volume :
- 7
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- GigaScience
- Publication Type :
- Academic Journal
- Accession number :
- 129598948
- Full Text :
- https://doi.org/10.1093/gigascience/giy022