DOI: 10.5061/dryad.jm63xsj5z
title: Data from: A spectacular new species of Habenaria (Orchidaceae) from southern Brazilian Amazon

description: A new Habenaria species from the state of Mato Grosso is described and
 illustrated. Habenaria gracilisegmenta was discovered in campinarana
 sub-forest, in northern Mato Grosso state, on the southern edge of the
 Brazilian Amazon. The species is distinguished by its slender habit, few,
 delicate flowers, and very long, thin lateral segments of the petals and
 lip, and its morphological affinity with other Neotropical species is
 unclear. A molecular phylogenetic analysis revealed that the new species
 does not belong to any of the Neotropical subclades of the genus,
 constituting an additional lineage. The species is one of two of the genus
 endemic to the Brazilian Amazon, and considered threatened by the small
 number of known populations and restricted distribution.
description: <b><i>Taxon Sampling for Phylogenetic
 Analyses</i></b>—The datasets for the phylogenetic analyses
 were basically the same as those used by Batista et al. (2013) to infer
 the phylogenetic relationships of the New World
 <i>Habenaria</i>, although a few other species addressed in
 later works were included (Batista et al. 2014, Pedron et al. 2014), and
 most of the Old World taxa and duplicate terminals were excluded. The data
 set consisted of the combined ITS and partial <i>matK</i> DNA
 sequences of 167 terminals of approximately 159 Neotropical
 <i>Habenaria</i> taxa, corresponding to 53% of the total
 number of species known from the Neotropical region (Batista et al. 2011a,
 2011b), and four African <i>Habenaria</i> species.
 <i>Gennaria diphylla </i>Parlatore was used as the outgroup.
 Voucher information, geographic origins, and GenBank accession numbers can
 be found in Batista et al.<i> </i>(2013, 2014) and Pedron et
 al. (2014). GenBank accession numbers for the newly sequenced accession of
 <i>H. gracilisegmenta</i> are provided in Appendix
 1. <b><i>Molecular
 Markers</i></b>—Nucleotide sequences from one nuclear (ITS)
 and one plastid (<i>matK</i>) genome region were analyzed. The
 ITS regions consisted of the 3’ and 5’ ends of the 18S and 26S ribosomal
 RNA genes, respectively, internal transcribed spacers (ITS1 and ITS2), and
 the intervening 5.8S gene of the nuclear ribosomal multigene family. For
 the <i>matK</i> gene, we used an internal fragment of
 approximately 630 bp. DNA extraction, amplification, and sequencing were
 carried out following standard protocols, as described by Batista et al.
 (2013). Bidirectional sequence reads were obtained for all of the DNA
 regions, and the resulting sequences were edited and assembled using
 Staden Package software (Bonfield et al. 1995).
 The edited sequences were aligned using MUSCLE (Edgar 2004), and the
 resulting alignments were manually adjusted using MEGA6 software (Tamura
 et al. 2013). <b><i>Phylogenetic
 Analyses</i></b>—The data were analyzed using parsimony and
 Bayesian inferences. Searches were performed only with a combined matrix,
 as no cases of strongly supported incongruences were detected in previous
 analyses with the same datasets (Batista et al<i>. </i>2013).
 Phylogenetic analyses using maximum parsimony (MP) were performed using
 PAUP* version 4 (Swofford 2002) with Fitch parsimony (equal weights,
 unordered characters, Fitch 1971) as the optimality criterion. Each search
 consisted of 1000 replicates of random taxon additions, with branch
 swapping using the tree-bisection and reconnection (TBR) algorithm, saving
 ≤ 10 trees per replicate to avoid extensive swapping on suboptimal
 islands. Internal support was evaluated by character bootstrapping
 (Felsenstein 1985) using 1000 replicates, simple addition, and TBR branch
 swapping, saving ≤10 trees per replicate. For bootstrap support levels, we
 considered bootstrap percentages (BS) of 50%–70% as weak, 71%–85% as
 moderate, and &gt;85% as strong (Kress et al. 2002). Bayesian analysis was
 performed using MrBayes v. 3.1.2 (Ronquist et al<i>.</i> 2005)
 as<b> </b>implemented in the Cyberinfrastructure for
 Phylogenetic Research (CIPRES) Portal 2.0 (Miller et al. 2010), treating
 each DNA region as a separate partition. An evolutionary model for each
 DNA region was selected using the Akaike information criterion (AIC) in
 MrModeltest 2 (Nylander 2004), and the GTR + I + G model was selected for
 both data sets. The unlink command was used to unlink parameters among
 each partition. Each analysis consisted of two independent runs, each with
 four chains, for 10,000,000 generations, sampling one tree every 1000
 generations. To improve chain swapping, the temperature parameter for
 heating the chains was lowered to 0.1 in the combined analysis.
 Convergence between the runs was evaluated using the average standard
 deviation of split frequencies (&lt; 0.01) and was achieved after
 2,125,000 generations. After discarding the first 2,500 trees (25%) as the
 burn-in, the remaining trees were used to assess topology and posterior
 probabilities (PPs) in a majority-rule consensus. Posterior probabilities
 (PPs) in Bayesian analysis are not directly comparable to bootstrap
 percentages, being generally much higher (Erixon et al.<i>
 </i>2003). We therefore used criteria similar to a standard
 statistical test, considering groups with PPs &gt; 0.95 as strongly
 supported, groups with PPs ranging from 0.90–0.95 as moderately supported,
 and groups with PPs &lt; 0.90 as weakly
 supported.