Data Set

Range-Wide North American Freshwater Mussels (Unionidae, Ambleminae) 2D and 3D Morphometric Datasets

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https://scholar.colorado.edu/concern/datasets/fb494b38g
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Abstract
  • This dataset submission provides two complementary morphometric datasets—2D linear and 3D volumetric—generated to investigate shell variation and resource allocation in freshwater mussels (Subfamily: Ambleminae) across environmental gradients within eight major U.S. water resource regions in North America. The 2D dataset comprises linear measurements for 1,169 specimens across 10 species representing three tribes: Lampsilini (Cyprogenia stegaria, Dromus dromas, Obliquaria reflexa, Obovaria subtrotunda), Pleurobemini (Fusconaia flava, Fusconaia subrotunda, Pleurobasus cooperianus), and Quadrulini (Pustulosa pustulosa, Theliderma metanevra, Quadrula quadrula). Specimens were sourced from four major natural history collections (USNM, UMMZ, WNHC, and ANSP). Data includes specimen information, linear shell measurements (length, width, and inflation) as well as calculated inflation indices to assess morphological response to river flow. The 3D Volumetric Dataset focuses on 110 specimens of Fusconaia subtrotunda (smooth-shelled) and Pustulosa pustulosa (sculptured). Models were generated via structured light scanning at 0.05 mm resolution (Artec Space Spider). All specimens in both datasets have locality and collecting event metadata included, are georeferenced and contained National Hydrography Dataset Plus (NHDPlusV2)-derived COMID, annual mean river flow rates, and HUC levels (HUC2 to HUC12). These datasets serve as a high-resolution resource for evolutionary biologists and malacologists exploring the intersection of shell plasticity, hydrology, and functional tradeoffs.

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Academic Affiliation
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Publisher
Dernière modification
  • 2026-02-12
Emplacement
  • United States, , United States
Resource Type
Déclaration de droits
DOI
Peer Reviewed
Language
Access right
  • Awaiting Peer Review
Citation
  • Tan, Andy D.Y, Tan, Yu Kai (2025). Microlending 2017 Data Set [Data set]. University of Colorado Boulder.

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