A molecular phylogeny of the Laelia alliance (Orchidaceae) and a reassessment of Laelia and Schomburgkia
We provide a molecular phylogenetic analysis of the Laelia alliance based on sampling of 20 of an estimated 24 species, and seven plastid regions plus nrITS 1 & 2 analyzed using maximum parsimony, maximum likelihood, and Bayesian inference. Furthermore, we used coded indels
to evaluate their effect on the phylogenetic relationships and/or support values (bootstrap and posterior probabilities). Our results confirm the existence of two clades, the long known Laelia (endemic to México at middle to high elevations) and Schomburgkia (a more widely
distributed taxon). Both clades were strongly supported by PP values and moderate BS; thus, we preferred to recognize them as separate genera with a reappraised morphology and taxonomic delimitation. The inclusion of coded indels in the analyses was of great utility; we could identify the
probable hybrid origin of L. gouldiana and L. halbingeriana. We propose new combinations to accommodate the taxonomic changes resulting from our study. We transfer L. anceps subsp. anceps, L. anceps subsp. dawsonii, L.
aurea, L. mottae, and L. rubescens to Schomburgkia, with the second taxon elevated to species level; the molecular evidence together with previous published work on the morphology, phenology and geography of the group support these decisions. Lastly,
the recently described genus Encabarcenia is considered as a synonym of Schomburgkia and, as a result, a new combination is proposed.
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Keywords: HYBRIDIZATION; INDEL CODING; MOLECULAR PHYLOGENY; ORCHIDACEAE; SPLITTING
Document Type: Research Article
Affiliations: 1: Universidade Estadual de Feira de Santana, Departamento de Ciências Biológicas, Av. Transnordestina s.n., 44036-900 Feira de Santana, Bahia, Brazil;, Email: lizandropf@gmail.com 2: Herbario CICY, Centro de Investigación Científica de Yucatán, A.C. (CICY), Calle 43 No. 130, Colonia Chuburná de Hidalgo, C.P. 97200, Mérida, Yucatán, México
Publication date: 2016-12-01
Impact Factor (2016): 2.45
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