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Nexus-formatted text file of ISSR band presence/absence for 75 loci in Corallorhiza bentleyi

Citation

Barrett, Craig (2020), Nexus-formatted text file of ISSR band presence/absence for 75 loci in Corallorhiza bentleyi, Dryad, Dataset, https://doi.org/10.5061/dryad.cz8w9gj2p

Abstract

Mycoheterotrophic plants derive most or all carbon and nutrients from fungal partners and represent poorly understood components of forest biodiversity. Many are rare or endangered yet can be ecological indicators of forest ecosystem function due to their often highly specific fungal host requirements. One such species is the IUCN red-listed (‘vulnerable’), fully mycoheterotrophic orchid, Corallorhiza bentleyi. This recently described species is among the rarest plants in Appalachia, known from five counties in Virginia and West Virginia, USA. The species has a restricted range, small population size, and is self-pollinating. Here, an integrative approach was taken in conservation genetic assessment of C. bentleyi using floral morphometrics, simple-sequence repeats, and fungal host DNA to characterize variation within and among sampling localities. Morphology reveals some differentiation among individuals from six sampling localities. Surprisingly, most genetic variation is found within localities, contrary to the expectation for a selfing species. Fungal host DNA reveals extreme specificity upon a few genotypes of a single ectomycorrhizal host species, Tomentella fuscocinerea, across all localities. The conservation implications of morphological, genetic, and symbiotic diversity in this vulnerable species are discussed, and additional assessment of conservation status is recommended based on: an obligate reproductive mode of selfing, preventing benefits of outcrossing among genetically non-identical individuals; extreme host specificity, severely restricting niche space; and highly fragmented habitat under threat from anthropogenic disturbance. This study underscores the importance of integrative conservation assessment, analyzing multiple data sources, and reveals patterns not readily apparent from census-based assessments alone.