One of the greatest challenges for biodiversity conservation is the poor understanding of species diversity. AT-406 these clades was underestimated; and (ii) if so, determine by how much species richness was underestimated. 2.?Material and methods (a) Delimitation of candidate species We classified frog lineages using the categories defined by Vieites from 36 localities and 208 from 65 localities in six countries in the Amazon Basin (figures ?(figures11and ?and22= 125, 133 and 51 individuals were included in the DNA, morphological and bioacoustic analyses, respectively. The corresponding sample sizes for were = 136, 137 and 26. Tissue samples were either frozen or stored in 95 per cent ethanol or dimethyl sulphoxide buffer. Total genomic DNA was extracted from samples using DNeasy Tissue Kits (Qiagen, Inc., Valencia, CA, USA). Voucher specimens for most samples are available in several museums (electronic supplementary material, appendix S1). Figure?1. (mitochondrial DNA (mtDNA) phylogeny, (12S + 16S mtDNA phylogeny, (and and = 136) and concatenated 12S, 16S and COI genes for a smaller subset of individuals for which COI data were also available (= 118). ML analyses were conducted using program GARLI v. 0.951 [28]. Model choice was based on Akaike information criterion (AIC) [29] using program MrModeltest v. 2.2 [30]. Analyses were terminated after 10 000 generations without an improvement in tree topology. Support was evaluated using 100 bootstrap replicates with each replicate terminated after 5000 replications without a topology improvement. Bayesian analyses were conducted using MrBayes v. 3.1.2 [31] and using three partitioning strategies for the mitochondrial data (1 partition, partitioning by gene and partitioning by gene and stems and loops) and three partitioning strategies for the nuclear data (1 partition, partitioning by gene and partitioning by gene and codon position). Model choice for each partition was based on AIC in MrModeltest v. 2.2 (see the electronic supplementary material, table S2 for a summary of character variation and MrModeltest results). Bayesian analyses were performed with two replicate searches of 2 106 generations each with four Markov chains and trees sampled every 1000 generations. We used a conservative burn-in that was determined by examining stationarity of the likelihood scores and convergence of posterior probabilities between the two runs using the standard deviation of split frequencies. The best partitioning strategy for each dataset was selected by comparing Bayes factors [32]. Time to most recent common ancestor (TMRCA) of major nodes was estimated using mitochondrial 12S and 16S genes with the Bayesian Markov Monte Carlo method implemented in program BEAST v. 1.4.8 [33]. Following Weigt and specimens using digital calipers AT-406 (accurate to the nearest AT-406 0.01 mm). Measurements were taken following Funk (mean = 22.1C, s.d. = 2.2C) and (mean = 23.7C, s.d. = 1.7C). Fast Fourier transformation size was 2048 and the spectral analysis had a frequency resolution of 21.5 Hz. The measured variables were: (i) dominant and fundamental frequency, (ii) note duration, (iii) number of notes, and (iv) rise time. calls have a complex structure consisting of an amplitude-modulated prefix and a whine-like frequency sweep. Thus for from 36 localities and 208 from 65 localities uncovered many undescribed, cryptic species (figures ?(figures11 and ?and2).2). In both and toadlets In Amazonian [41] and clade E to [25,42]. Clades A, C, D, E and G are CCS because they have significant morphological and/or bioacoustic differences from all other clades. Furthermore, clades A, C and D are sympatric, indicating that they are reproductively isolated. Clades B and F are UCS because although they are genetically divergent, well-supported clades, we lack morphological and/or bioacoustic data. mtDNA and nDNA phylogenies generally agreed and revealed similar distinct genetic groups (figure 1clades. SVL, a measure of body size, varied Rabbit Polyclonal to NCoR1 significantly among clades (ANOVA, < 0.001; figure 1< 0.001), as did PC2 (< 0.001). Frogs in clade D had proportionally shorter limbs than those in clades A, B and E. Clade E frogs were wider than those in clades A and D, and clade G frogs were wider than clade A, C and D frogs. In the DFA, frogs from clades A, C, D and G could be assigned fairly accurately (74.2C100% assigned correctly; electronic supplementary material, table S5). However, we were unable to find qualitative morphological characters diagnostic of clades. PCA of bioacoustic variables showed striking differences (figure 1< 0.001), with clade D having higher frequency calls.