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Lee A. Weigt

Researcher at National Museum of Natural History

Publications -  47
Citations -  6125

Lee A. Weigt is an academic researcher from National Museum of Natural History. The author has contributed to research in topics: DNA barcoding & Population. The author has an hindex of 29, co-authored 45 publications receiving 5728 citations. Previous affiliations of Lee A. Weigt include Smithsonian Institution & Field Museum of Natural History.

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Evidence for Three Major Clades within the Snapping Shrimp Genus Alpheus Inferred from Nuclear and Mitochondrial Gene Sequence Data

TL;DR: Phylogenies for Alpheus suggest that specialized ecological requirements and modified claw morphologies have evolved independently several times and support the sister species status of transisthmian pairs analyzed previously, although very similar pairs were not always resolved with the more slowly evolving nuclear loci.
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An Unprecedented Aggregation of Whale Sharks, Rhincodon typus , in Mexican Coastal Waters of the Caribbean Sea

TL;DR: A second, much denser aggregation of whale sharks (dubbed “the Afuera”) that occurs east of the tip of the Yucatán Peninsula in the Caribbean Sea, with two whale shark aggregation areas, high coastal productivity and a previously-unknown scombrid spawning ground is reported.
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Using DNA barcoding to assess Caribbean reef fish biodiversity: expanding taxonomic and geographic coverage.

TL;DR: The barcode data are providing new insights into Caribbean shorefish diversity, allowing for more and more accurate DNA-based identifications of larvae, juveniles, and unknown specimens.
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Phenotypic and Genetic Divergence in Three Species of Dart-Poison Frogs With Contrasting Parental Behavior

TL;DR: It is demonstrated that the color and pattern variation among populations of D. pumilio is not matched by higher levels of mitochondrial DNA sequence divergence relative to P. lugubris or Minyobates sp.
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DNA barcoding in land plants: developing standards to quantify and maximize success

TL;DR: It is argued that the efficacy of any particular plant DNA barcode selection should reflect the anticipated performance of the resulting barcode database in assignment of a query sequence to species, and a measure of barcode efficacy based on the rationale of database performance, "the probability of correct identification" (PCI).