An in‐depth investigation of cryptic taxonomic diversity in the rare endemic mustard Draba maguirei

Abstract

Premise: Previously published evidence suggests that Draba maguirei, a mustard endemic to a few localities in the Bear River, Wellsville, and Wasatch Mountains of northern Utah, may represent a cryptic species complex rather than a single species. Conservation concerns prompted an in-depth systematic study of this taxon and its putative relatives. Methods: Sampling most known populations of D. maguirei s.l. (D. maguirei var. maguirei and D. maguirei var. burkei), we integrate data from geography, ecology, morphology, cytogenetics and pollen, enzyme electrophoresis, and the phylogenetic analysis of nuclear internal transcribed spacer sequences to explore potential taxonomic diversity in the species complex. Results: Draba maguirei var. burkei is shown here to be a distinct species (D. burkei) most closely related to D. globosa, rather than to D. maguirei. Within D. maguirei s.s., the northern (high elevation) and southern (low elevation) population clusters are genetically isolated and morphologically distinguishable, leading to the recognition here of the southern taxon as D. maguirei subsp. stonei. Conclusions: Our study reveals that plants traditionally assigned to D. maguirei comprise three genetically divergent lineages (D. burkei and two newly recognized subspecies of D. maguirei), each exhibiting a different chromosome number and occupying a discrete portion of the geographic range. Although previously overlooked and underappreciated taxonomically, the three taxa are morphologically recognizable based on the distribution and types of trichomes present on the leaves, stems, and fruit. Our clarification of the diversity and distribution of these taxa provides an improved framework for conservation efforts.

GINSA: an accumulator for paired locality and next-generation small ribosomal subunit sequence data

“…For instance, evolutionary biologists rely on large molecular sequence datasets to study speciation trends ( Schlegel 1991 , Adl et al 2019 ). Large datasets help resolve cryptic diversity, which is a challenge seen across the tree of life—animals ( Marchán et al 2018 , Li and Wiens 2023 ), plants ( Vieu et al 2023 , Windham et al 2023 ), fungi ( Koufopanou et al 1997 , Pringle et al 2005 ), bacteria ( Meyer et al 2023 ), protists ( Wakeman and Leander 2013 , Krienitz et al 2015 , Martin et al 2016 ), archaea ( Câmara et al 2023 ), and viruses ( Roux et al 2019 ). Specialists across a range of taxa can therefore use GINSA to collect more data for their phylogenetic (SSU sequence) and biogeographic (locality) analyses.…”