RESEARCH ARTICLE DNA Barcoding Survey of Anurans across the Eastern Cordillera of Colombia and the Impact of the Andes on Cryptic Diversity

Carlos E. Guarnizo1*, Andrea Paz2, Astrid Muñoz-Ortiz2,3, Sandra V. Flechas2, Javier Méndez-Narváez2, Andrew J. Crawford2,4

1 Departamento de Zoologia, Universidade de Brasília, 70910–900, Brasília, DF, Brazil, 2 Department of Biological Sciences, Universidad de los Andes, A.A. 4976, Bogotá, Colombia, 3 Department of Basic Sciences, Universidad de la Salle, Bogotá, Colombia, 4 Smithsonian Tropical Research Institute, Apartado, a11111 0843–03092, Panamá, Republic of Panama

* [email protected]

Abstract

OPEN ACCESS Colombia hosts the second highest amphibian species diversity on Earth, yet its fauna re- mains poorly studied, especially using molecular genetic techniques. We present the results Citation: Guarnizo CE, Paz A, Muñoz-Ortiz A, Flechas SV, Méndez-Narváez J, Crawford AJ (2015) of the first wide-scale DNA barcoding survey of anurans of Colombia, focusing on a transect DNA Barcoding Survey of Anurans across the across the Eastern Cordillera. We surveyed 10 sites between the Magdalena Valley to the Eastern Cordillera of Colombia and the Impact of the west and the eastern foothills of the Eastern Cordillera, sequencing portions of the mito- Andes on Cryptic Diversity. PLoS ONE 10(5): chondrial 16S ribosomal RNA and cytochrome oxidase subunit 1 (CO1) genes for 235 indi- e0127312. doi:10.1371/journal.pone.0127312 viduals from 52 nominal species. We applied two barcode algorithms, Automatic Barcode Academic Editor: Jesus E. Maldonado, Smithsonian Gap Discovery and Refined Single Linkage Analysis, to estimate the number of clusters or Conservation Biology Institute, UNITED STATES “unconfirmed candidate species” supported by DNA barcode data. Our survey included Received: January 8, 2015 ~7% of the anuran species known from Colombia. While barcoding algorithms differed Accepted: April 13, 2015 slightly in the number of clusters identified, between three and ten nominal species may be Published: May 22, 2015 obscuring candidate species (in some cases, more than one cryptic species per nominal

Copyright: © 2015 Guarnizo et al. This is an open species). Our data suggest that the high elevations of the Eastern Cordillera and the low el- access article distributed under the terms of the evations of the Chicamocha canyon acted as geographic barriers in at least seven nominal Creative Commons Attribution License, which permits species, promoting strong genetic divergences between populations associated with the unrestricted use, distribution, and reproduction in any Eastern Cordillera. medium, provided the original author and source are credited.

Data Availability Statement: Data are available through the Dryad database with doi:10.5061/dryad. k4q1q. Funding: Field and laboratory work were financed by Introduction grant number 156-09 from Ecopetrol. The funder had no role in study design, data collection and analysis, The Northern Andes of South America have the highest diversity of species on Earth per unit decision to publish, or preparation of the manuscript. of surface area and host multiple hotspots of species richness and endemism for plants and ver- tebrates [1–3]. In spite of its megadiversity, the number of described species in the Andes ap- Competing Interests: The authors explicitly state that funding from Ecopetrol does not alter the authors' pears to be considerably underestimated [4–6]. The limited resources to study the Andean adherence to PLoS ONE policies on sharing data biodiversity is unfortunate since the tropical Andes is among the most threatened biomes in and materials. the world due to emergent pathogens [7], habitat deterioration [8], and global climate change

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[9–11]. Some evidence suggests that a major global wave of extinction has already begun [12,13], implying that much of the Andean undiscovered diversity may disappear before it is described by science. Among vertebrates, tropical frogs have the highest species discovery rate over recent de- cades [14–20]. Intrinsic characteristics of anurans, such as their permeable skin and small body size [21–23], combined with their low dispersal abilities [24,25], and for some species, niche conservatism [1,26], promote geographic isolation and speciation, especially in heterogeneous topographies at middle elevations [1,27]. Unfortunately, tropical frogs are also among the most threatened vertebrates of the tropics [28,29]. Some authors suggest that the same attributes that make amphibians so diverse could also make them particularly susceptible to human- induced threats such as habitat fragmentation, climate change, and pathogens [30,31]. For these reasons, amphibian biodiversity surveys should be a priority in the Andes. The fast and accurate description of novel diversity of amphibians in tropical mountains would help us not only to understand why the Andes are so diverse, but also to design better conservation strate- gies to reduce potential negative impacts of further habitat degradation. In Colombia, the Andes are divided into three cordilleras. Among these, the Eastern Cordil- lera is the widest in terms of area, and harbors higher species richness of vertebrates compared with the other two cordilleras (excluding the coastal Pacific slope of the Western Cordillera, also known as biogeographic Chocó [32]). The Eastern Cordillera lies between a humid low- land savanna (with Amazonian influences) drained by the Orinoco and Amazon rivers on the east side and the relatively arid Magdalena Valley on the west side. The two slopes of the East- ern Andes are separated by the Eastern Andes ridge, an uninterrupted ridge at 2500 m that ! extends for 600 km, and are, therefore, potentially under different environmental conditions that may promote alternative local adaptations. The species diversity of the eastern slope of the Eastern Cordillera is higher for organisms such as butterflies, frogs, birds, rodents, and bats [32], perhaps reflecting the fact that, A) the eastern slope receives high humidity from the north-eastern trade winds, promoting an Amazonian-influenced fauna in its foothills, in con- trast to the relatively arid western foothills [32], and B) the eastern slope faces the Colombian and Venezuelan savannas in the north and the Amazonian lowlands in the south, facilitating biological exchange between the Eastern Cordillera and these contrasting regions. Several authors have provided important insights on the processes that may explain the tre- mendous diversity of vertebrates of the Eastern Cordillera of Colombia [32–35]. These studies agree that the dynamic and recent uplift history of the Eastern Cordillera [36] makes geological history and topography a strong candidate to explain current diversity patterns. Lynch et al. [37], for instance, suggested that the recently uplifted Andes promoted diversification in two different ways: a) by fragmenting lowland populations on either side of the Eastern Andes ridge, and b) by fragmenting populations by means of nonsynchronous uplifting of Andean blocks that generate topographic complexity restricting gene flow. These authors observed that several closely related frog species occur allopatrically in similar elevational bands, supporting the idea that high summits and low valleys isolate populations and promote diversification. Another perspective suggests that more recent climatic cycles during the Quaternary had a pro- found effect of the demographic patterns of Andean species, alternately promoting or restrict- ing migration during the glacial and interglacial periods [35]. While the fundamental insights above were reached through abundant morphology-based taxonomic studies on the vertebrates of Colombia’s Eastern Cordillera, the region is remark- ably unexplored in terms of molecular systematic and phylogeographic analyses. While the number of molecular studies of vertebrates in this region has been increasing in recent years [38–45], the total number of studies is still very low relative to the remarkable species diversity. Tropical biodiversity studies at the molecular genetic level tend to reveal many undescribed or

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‘cryptic’ species because speciation is not always accompanied by obvious morphological evo- lution [46]. Thus, we expect that genetic surveys of the Eastern Cordillera of Colombia should reveal further cryptic diversity, and therefore, novel insights on the patterns and processes as- sociated with diversification. DNA barcoding is a methodology that can be used for “specimen identification”, i.e., to as- sign unidentified specimens to named species, or “species discovery”, i.e., to assign novel speci- mens to unnamed genealogical clusters that may correspond to species [47]. In general, barcode algorithms for specimen identification compare individual DNA sequences against a reference library of homologous sequences from known samples whose identification is sup- ported by curated voucher specimens. If genetic distances between the unknown sample and any known species in the reference library are smaller than a pre-established threshold, the un- known specimen likely corresponds to the closest species in the reference collection. Alterna- tively, if genetic distances are larger than the threshold, the unknown specimen may correspond to a species not in the reference library or possibly to an as yet undescribed new species [48]. This threshold is known as the barcode gap [49]. This technique is controversial because thresholds may vary among taxonomic groups, they may not be agreed upon by taxon- omist, or they may not exist at all, i.e., there may be substantial overlap between intra- and in- terspecific pairwise genetic distances within one taxonomic group [49,50]. In response to this potential drawback several algorithms have been designed to try to optimize the threshold se- lection, or compare multiple thresholds in one barcode analysis [51–53]. DNA barcode analyses for species discovery are proficient at organizing unknown speci- mens into groups or clusters based on genetic distance or genealogical information. No algo- rithm, however, can confirm if these divergent clusters are indeed species, given that DNA sequence data from a single gene may not provide enough information for species delimitation [54]. Thus, while DNA barcodes cannot identify new species, they can help greatly in flagging unusual specimens that merit more careful revision using taxonomic characters appropriate for the group in question [55]. Under a program of integrative taxonomy, for example, candi- date species are lineages that show divergent DNA sequence data as well as distinctiveness in one other source of character information, such as morphology, while ‘unconfirmed candidate species’ is a provisional designation based on DNA data or alternative characters [55]. Another potential drawback that might appear in DNA barcode analyses is the lack of con- sideration for geographic variation [53,56]. If sampling individuals from single localities, the potentially increasing variation in genetic distance over increasing geographical distance within species [57] may not be considered and the distinctiveness of species barcodes may be overesti- mated [53]. In other words, new sequences that originate from outside of the sampled range are easily misinterpreted as coming from other species [58]. Recent studies have shown, how- ever, that adding samples from a greater proportion of the species range, even the addition of a single sample from a different population, leads to a higher number of accurate DNA barcode identifications [51,58]. We performed the first DNA barcoding survey of anurans of Colombia that includes multi- ple species, genera and families, along with multiple localities per species (when possible), fo- cusing on a transect passing through the Eastern Cordillera of the Colombian Andes, starting in the foothills of the savannah, or Llanos region, in the east and ending in the lowlands of the Magdalena Valley on the western side. Our main questions were: A) compared with external morphology, what is the performance of DNA barcoding of anurans in terms of specimen identification and species discovery in the Eastern Cordillera of the Colombian Andes? And B) is there genetic evidence that the Eastern Cordillera ridge has acted as a geographic barrier sep- arating eastern and western populations? Our study provides the first molecular sampling and analysis of anurans along a geographical transect across both slopes of the eastern Cordillera of

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Fig 1. Geographic distribution of the ten localities surveyed for anurans. Left: Map codes refer to the localities listed in Table 1. Right: Three- dimensional map with vertical exaggeration (the vertical scale is larger than the horizontal scale) that displays the topographic complexity of the terrain. Black dots and numbers indicate the same localities shown on the left. doi:10.1371/journal.pone.0127312.g001

Colombia. Our results shed light on the effectiveness of the DNA barcode methodology in ac- complishing in a short period of time specimen identification and species discovery in a high- diversity tropical region.

Methods Sampling Specimens were sampled from 10 sites along an elevation transect across the Eastern Cordillera of Colombia (Fig 1, Table 1). Between 3 and 4 people worked during each fieldtrip to each lo- cality, providing a mean sampling effort of 80 person-hours per site. Sampled individuals were preliminary identified and allocated to nominal species using external morphology. We collect- ed a maximum of five individuals of the same nominal species at each locality. Sampled indi- viduals were euthanized by topical application of benzocaine gel (i.e., tooth ache medicine). Tissue samples for DNA barcode analyses were obtained from the liver or skeletal muscle tissue and stored in an NaCl-saturated 0.25 M EDTA buffer containing 20% DMSO [59]. Vouchers were fixed in 10% formalin or 85% ethanol, stored in 70% ethanol and then deposited in the Museo de Historia Natural ANDES at the Universidad de los Andes. The species names, field collection numbers, museum numbers, localities, Barcode of Life Data Systems (BoLD) Process ID [60] for each specimen, and GenBank accession numbers for each sequence used in the present study are provided in the S1 Table.

PCR and sequencing methods Genomic DNA was extracted using the DNeasy Blood & Tissue kit (Qiagen, Valencia, CA, USA) following the manufacturer’s protocol. We amplified two mitochondrial gene fragments, including the 5’ end of the faster evolving cytochrome oxidase subunit I (CO1) gene, also known as the DNA Barcode of Life for animals [61], and the more slowly evolving ribosomal 16S gene fragment which still boasts greater representation of amphibians in GenBank [62].

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Table 1. Description of localities and individuals used in the barcode analyses. For map codes see Fig 1. Localities are ordered from north to south.

Locality Map Lat N, Long Elevation Slope of the Eastern Number of individuals Number of individuals code W (m) Cordillera collected sequenced (gene) Sabana de A 7.3496, 159 Western 21 21 (16S), 18 (CO1) Torres -73.4981 El Rasgón B 7.0416, 2849 Western 10 10 (16S), 10 (CO1) -72.9588 Piedecuesta C 6.9923, 1000 Western 6 6 (16S), 6 (CO1) -73.0528 San Vicente D 6.8988, 474 Western 23 23 (16S), 21 (CO1) -73.4305 Puente Nacional E 5.9028, 1702 Western 24 24 (16S), 22 (CO1) -73.6949 Pajarito F 5.4108, 2351 Eastern 13 13 (16S), 13 (CO1) -72.6710 Miraflores G 5.1953, 1532 Eastern 27 27 (16S), 25 (CO1) -73.1462 Orocué H 4.7969, 134 Eastern 15 15 (16S), 14 (CO1) -71.3512 Sabanalarga I 4.7729, 313 Eastern 51 50 (16S), 41 (CO1) -73.3737 San Juan de J 3.3765, 448 Eastern 47 47 (16S), 40 (CO1) Arama -73.8790 doi:10.1371/journal.pone.0127312.t001

Two primer pairs were used to amplify and Sanger-sequence the CO1-5’ gene: dgLCO1490 (5’–GGTCAACAAATCATAAAGAYATYGG–3’) plus dgHCO2198 (5’–TAAACTTCAGGGT GACCAAARAAYCA–3’)[63], and Chmf4 (5’–TYTCWACWAAYCAYAAAGAYATCGG–3’) plus Chmr4 (5’—ACYTCRGGRTGRCCRAARAATCA–3’)[64]. The 16S gene fragment was amplified and sequenced with the primers 16Sar (5'–CGCCTGTTTATCAAAAACAT–3') and 16Sbr (5'–CCGGTCTGAACTCAGATCACGT–3') and standard reaction conditions [65]. PCR products were cleaned using Exonuclease I and Shrimp Alkaline Phosphatase enzymes [66]. Both genes were sequenced bi-directionally to confirm base calls. Assembly and editing of chromatograms were performed with SEQUENCHER software version 4.7 (GeneCodes Corp., Ann Arbor, MI, USA). The sequences of each gene were aligned independently using MUSCLE [67] and reviewed by eye. Our alignments are available from the Dryad data repository: doi:10. 5061/dryad.k4q1q.

DNA barcoding methods Species identity and species discovery were implemented using two algorithms designed to sta- tistically detect barcode gaps and identify distinct clusters of DNA sequences. First, we used the Automated Barcode Gap Discovery or ABGD method (available at http://wwwabi.snv.jussieu. fr/public/abgd/). ABGD first estimates the distribution of pairwise genetic distances between the aligned sequences and then it statistically infers multiple potential barcode gaps as minima in the distribution of pairwise distances, thereby partitioning the sequences such that the dis- tance between two sequences taken from distinct clusters will be larger than the barcode gap [52]. The software also recursively applies this procedure to the previously obtained groups of sequences to get finer partitions. Since the analysis identifies similar DNA sequences first, with- out removing gapped sites in the alignment, ABGD (and RESL, below) is not affected by gaps caused by the inclusion of divergent samples such as additional taxonomic genera or families. The ABGD algorithm has been shown to provide good performance in terms of species

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identification compared with other DNA barcode algorithms [51]. The CO1, 16S, and concatenated alignments were processed in ABGD using the complete sequence data, the Kimura two-parameter (K2P) nucleotide substitution model [68], and the following settings: prior for the maximum value of intraspecific divergence between 0.001 and 0.1, 10 recursive steps within the primary partitions defined by the first estimated gap, and a gap width of 1.0. K2P is the standard model of DNA substitution for barcode studies, and performs as well as more complex models in identifying specimens [69]. In order to contrast the results obtained by the ABGD algorithm we used the Barcode Index Number discordance analysis available in BoLD [70], a public DNA sequence database devoted to aiding in the acquisition, storage, analysis, and publication of DNA barcode records includ- ing chromatograms, images, collection data, and additional DNA sequences (http://www. boldsystems.org). The method uses a Refined Single Linkage (RESL) Analysis algorithm, which follows two main steps: First, it employs single linkage clustering as a tool for the preliminary assignment of the CO1 sequences to a cluster (using genetic distances between every pair of se- quences), and second, it uses Markov clustering, a method that groups together CO1 sequences with high sequence similarity and connectivity, and separates those with lower similarity and sparse connectivity. Such connectivity is explored through random walks of the genetic dis- tance similarity network [70]. Finally, RESL defines the boundaries of each cluster selected by generating clusters using a range of values for the inflation parameter in the Markov clustering and then selects that which maximizes the Silhouette Index [65]. Since the RESL algorithm was designed to deal with large quantities of sequences, it does not need prior information on the barcode gap, as with ABGD. The RESL assignment is only performed for specimens with CO1 sequences of more than 300 base pairs (bp), and thus we applied this method to 213 specimens (see below). In order to be able to compare ABGD and RESL in terms of the number of clusters inferred, we performed an additional analysis using the same CO1 alignment in both algorithms. We did not included more algorithms in our analysis since our main focus was to contrast how different clusters of individuals are formed using either external morphology or DNA, rather than comparing the performance of several different DNA barcode algorithms, as previous studies have already done [51,71–73]. In addition to the distance-based analyses mentioned above, we also evaluated a character- based phylogenetic approach. We estimated maximum likelihood (ML) gene genealogies for each gene and the combined dataset using RAxML-VI-HPC [74] with a GTRGAMMA model of evolution. We conducted 100 independent ML tree searches and used the—f a option imple- menting 1000 rapid bootstrap replicates. Our intention in estimating the ML tree was to obtain the bootstrap support for derived nodes that may represent species, rather than attempting to estimate phylogenetic relationships among genera or families.

Colombian Eastern Andes as a geographic barrier To test if the Eastern Andes ridge affected the local genetic differentiation of the species sam- pled across both sides of the Eastern Cordillera we used the program LocalDiff [75]. This pro- gram uses a Bayesian approach to characterize non-stationary patterns of isolation by distance, in other words, when genetic differentiation between individuals increases at different rates in different regions of the habitat [75]. Non-stationary patterns of isolation by distance may arise in the presence of barriers to gene flow because genetic differentiation accumulates faster with distance around the barrier [75]. Since local genetic differentiation (among populations over small geographical scales) should be larger in regions of abrupt genetic changes, we estimated a similarity matrix 1 –

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(observed genetic distance/maximum genetic distance) as a measure of intraspecific local dif- ferentiation. Genetic distances were normalized dividing them by the maximum genetic dis- tance found within each lineage, so they would rank between 0 (the site with the lowest local differentiation) and 1 (the site with the highest local differentiation), facilitating its comparison with other studies. Local genetic differentiation was estimated with kriging [76], a method that interpolates genetic distances in unsampled neighboring sites based on genetic distances mea- sured at the sampling sites, such that local genetic differentiation can be estimated continu- ously across space. The interpolation is dependent on a weighted average of the values measured at the sampling sites, and the weights rely on a parametric function that provides the decay of the similarity matrix with geographic distance. The output of the program LocalDiff generates a minimum convex polygon that encompasses all sampling sites within a species, where warmer colors represent areas with stronger local genetic differentiation. The local dif- ferentiation at each sampled location corresponds to the average (over neighbors) pairwise ge- netic distance between the individual at the sampled location and a putative neighboring site at a pre-specified geographic distance [76]. Genetic distances between all 16S haplotype pairs were estimated assuming the K2P model in MEGA 4.0 [77], using the pairwise-deletion option. We used the 16S dataset because, as op- posed to CO1, 16S data were obtained from all geographic sites. In LocalDiff we implemented the following parameters: 2 fictional neighboring populations in the vicinity of each sampled site, and a geographic distance between the neighbors and the sampling sites of 0.1 km. Local- Diff measures were averaged over 1000 replicates. Because LocalDiff is an extension of isolation by distance [57], we checked if population dif- ferentiation indeed increased with increasing geographical distance by estimating the relation- ship between geographic and genetic distances with multiple matrix regression with randomization (MMRR) [78], which tests the significance of a simple or multiple regression using a randomized permutation procedure to account for the potential non-independence among samples. Geographic distances were estimated with Geographic Distance Matrix Gener- ator [79]. We performed the MMRR method using the R function from Ian Wang [78] with 10,000 permutations.

Ethics Statement Procedures for capture and handling of live animals in the field were approved by the Colom- bian Ministry of the Environment, under research and collecting permit N°15 and access to ge- netic resources permit N°44. None of the species collected for this study is listed in the Convention on International Trade in Endangered Species of Wild Fauna and Flora—CITES (www.cites.org). The frogs were collected on private property, and permission was received from landowners prior to sampling.

Results We surveyed ten localities (Table 1) and collected 232 individual frogs representing eight taxo- nomic families, 25 genera, and 52 nominal species (Table 2). The localities on the eastern slope of the Eastern Cordillera all showed greater species richness than sites on the western slope. 52% of nominal species were collected on the eastern slope, 36% on the western slope, and 11% were found on both sides of the Eastern Cordillera (Table 2). We obtained DNA sequence data from the 16S ribosomal gene fragment for all 237 sampled individuals, consisting of 579 aligned bp, excluding gapped sites. We obtained CO1-5’ gene se- quences for 213 individuals (658 bp, with no length variation among individuals). The discrep- ancy between the two genes in the number of individuals sequenced was due to problems with

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Table 2. Description of the nominal species identified a priori with external morphology. Species are organized alphabetically by family and then by genera.

Nominal species Family Number of individuals within Species found in how many Flank of the Eastern species localities? Cordillera Allobates niputidea Aromobatidae 1 1 Western Allobates ranoides Aromobatidae 2 1 Eastern Rheobates palmatus Aromobatidae 9 3 Both Rhinella humboldti Bufonidae 4 2 Eastern Rhinella margaritifera Bufonidae 5 2 Eastern Rhinella marina Bufonidae 10 5 Both Espadarana andina Centrolenidae 2 1 Western Hyalinobatrachium Centrolenidae 1 1 Eastern esmeralda Rulyrana flavopunctata Centrolenidae 1 1 Eastern Craugastor longirostris Craugastoridae 2 1 Western Pristimantis carranguerorum Craugastoridae 1 1 Eastern Pristimantis douglasi Craugastoridae 3 1 Western Pristimantis frater Craugastoridae 6 2 Easten Pristimantis lutitus Craugastoridae 1 1 Western Pristimantis miyatai Craugastoridae 7 2 Western Pristimantis savagei Craugastoridae 6 2 Eastern Pristimantis taeniatus Craugastoridae 3 1 Eastern Pristimantis vilarsi Craugastoridae 6 1 Eastern Dendrobates truncatus Dendrobatidae 3 1 Western Agalychnis terranova Hylidae 2 1 Western Dendropsophus ebraccatus Hylidae 2 1 Western Dendropsophus mathiassoni Hylidae 13 3 Eastern Dendropsophus Hylidae 4 2 Western microcephalus Dendropsophus cf. stingi Hylidae 10 3 Eastern Dendropsophus subocularis Hylidae 3 1 Western Hyloscirtus cf. phyllognathus Hylidae 1 1 Eastern Hypsiboas boans Hylidae 1 1 Eastern Hypsiboas crepitans Hylidae 14 5 Both Hypsiboas lanciformis Hylidae 4 1 Eastern Hypsiboas pugnax Hylidae 7 2 Western Hypsiboas punctatus Hylidae 6 2 Eastern Phyllomedusa Hylidae 4 2 Eastern hypochondrialis Pseudis paradoxa Hylidae 1 1 Eastern Scinax cf. kennedyi Hylidae 5 2 Eastern Scinax rostratus Hylidae 7 3 Both Scinax ruber Hylidae 10 4 Both Scinax wandae Hylidae 7 2 Eastern Smilisca phaeota Hylidae 1 1 Western Trachycephalus typhonius Hylidae 1 1 Eastern Adenomera andreae Leptodactylidae 3 1 Eastern Engystomops pustulosus Leptodactylidae 5 3 Western Leptodactylus colombiensis Leptodactylidae 7 3 Both Leptodactylus fuscus Leptodactylidae 6 4 Both (Continued)

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Table 2. (Continued)

Nominal species Family Number of individuals within Species found in how many Flank of the Eastern species localities? Cordillera Leptodactylus insularum Leptodactylidae 2 1 Western Leptodactylus knudseni Leptodactylidae 2 1 Eastern Leptodactylus lineatus Leptodactylidae 3 1 Eastern Leptodactylus mystaceus Leptodactylidae 1 1 Eastern Physalaemus fischeri Leptodactylidae 6 3 Eastern Pleurodema brachyops Leptodactylidae 1 1 Western Pseudopaludicola llanera Leptodactylidae 7 3 Eastern Pseudopaludicola pusilla Leptodactylidae 2 1 Western Elachistocleis ovalis Microhylidae 9 3 Eastern doi:10.1371/journal.pone.0127312.t002

PCR amplification of the CO1-5’ fragment, despite using two sets of primer with numerous de- generate bases. The topologies of the character-based ML trees for CO1 and 16S agreed in terms of clade membership and support for terminal nodes, though not in terms of the rela- tionships among basal groups. We therefore present here the ML tree based on the concatenat- ed alignment as our best estimate, though again our goal was to identify nominal species and potential unconfirmed candidates species, not to resolve generic and family-level relationships (Fig 2). Bootstrap support for terminal nodes was high (>95%) but was low for basal nodes. In terms of species delimitation, the ABGD algorithm produced a stable number of clusters (or “hypothetical species”) for each independent gene and the concatenated alignment across a wide number of intraspecific thresholds (S1 Fig). ABGD recovered 47 clusters based on 16S, 54 clusters based on CO1, and 56 clusters using the concatenated alignment. Given that both genes independently recovered congruent groups, from now on we discuss the groups formed in terms of the concatenated alignment (56 clusters), since it is supported by more data (when contrasting ABGD and RESL we refer to the CO1 alignment only, see below). For the concatenated matrix we chose 6% based on the observed ‘barcode gap’ in the bimodal distribu- tion of pairwise genetic distances (S1 Fig). It is worth noticing that our concatenated alignment contained a small proportion of missing data, since 23 individuals were not sequenced for CO1. Therefore, the resolution might be lower in those clades with 16S sequence data only. In three cases individuals identified as members of the same nominal species (given their strong morphological similarity) were genetically highly divergent and split into paired clusters by ABGD: Scinax ruber (3 clusters), S. wandae (two clusters), and Hypsiboas punctatus (two clusters). These three nominal species might, therefore, correspond to three named species plus four unnamed cryptic species according to the ABGD algorithm. The RESL analysis employing only the CO1 data (Fig 2) recovered a total of 65 clusters (11 more than the ABGD algorithm using the same gene). Of these clusters, 10 records were single- tons thus providing the first reports of these lineages in BoLD. In eight cases, individuals iden- tified as members of the same nominal species were split by RESL into paired clusters: S. wandae, Engystomops pustulosus, Pseudopaludicola llanera, Hypsiboas crepitans, H. punctatus, Pristimantis miyatai, Leptodactylus colombiensis, and L. fuscus. Two additional nominal species were split into three clusters: Scinax ruber and Rheobates palmatus. These 10 nominal species might, therefore, contain an additional 11 unnamed cryptic species, according to the RESL algorithm. The RESL algorithm appeared to have a slightly lower threshold separating CO1 haplotypes into different clusters compared with ABGD. For instance, the nominal species E. pustulosus,

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Fig 2. Maximum likelihood gene genealogy of the combined dataset (16S + CO1). Numbers on branches are bootstrap support values as estimated using the software RAxML. Horizontal grey boxes delineate the nominal species identified a priori. Nominal species with asterisks were divided into more than one cluster by at least one DNA barcoding algorithm. Vertical lines indicate the grouping of individuals by each algorithm, RESL and ABGD. Single asterisk (*) indicates nominal species that were split by RESL but not by ABGD. Double asterisks (**) indicate nominal species divided congruently by both algorithms.

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Nominal species without asterisks were grouped into a single cluster by both algorithms. Black triangles indicate clades geographically separated by the high-elevation ridge of the Eastern Cordillera. Black inverted triangles indicate clades geographically separated by the Chicamocha canyon. doi:10.1371/journal.pone.0127312.g002

P. llanera, H. crepitans, and L. fuscus were grouped in a single cluster each by the ABGD algo- rithm, but split into two or three clusters each by the RESL algorithm, confirming that RESL is more sensitive and potentially more subject to false positives compared with ABGD. The re- maining clusters were concordant between the two algorithms (85% of the nominal species). In summary, out of the original 52 nominal species for which we obtained CO1 data, the ABGD algorithm suggested 54 clusters based on a gap of 1.0, while the RESL algorithm increased to 65 the number of potential species. We confirmed the prevalence of isolation by distance with the MMRR algorithm, finding significant (P < 0.05) associations between geographic and genetic distances in all seven nomi- nal species sampled on multiple localities (L. colombiensis:r2 = 0.74, P = 0.0039; H. crepitans:r2 = 0.14, P = 0.0007; L. fuscus:r2 = 0.60, P = 0.0035; R. palmatus:r2 = 0.90, P = 0.0142; S. ruber:r2 = 0.40, P = 0.0002; R. marina:r2 = 0.23, P = 0.0007; and R. humboldti:r2 = 0.40, P = 0.03219). The majority of species that were sampled on both sides of the Eastern Cordillera ridge (R. marina, L. fuscus, L. colombiensis, H. crepitans, and, R. humboldti) displayed a steep gradient in the local genetic differentiation (the genetic distance per unit of geographic distance) that in- creased parallel to the ridge (Fig 3). In these species, the more abrupt change between low local genetic differentiation (colder colors) and high local genetic differentiation (warmer colors) oc- curs near-by the geographic area that corresponds to the ridge (Fig 3), suggesting that a) the Eastern Cordillera ridge is acting as a barrier separating western flank and eastern flank sites, and b) that within these species, local genetic differentiation is higher in the western slope of the Eastern Cordillera. Even though we did not sample R. palmatus on both sides of the ridge, we found a steep change in local genetic differentiation in the area corresponding the Chicamo- cha canyon, a low elevation valley that reaches depths of 400 m (Fig 3). Scinax ruber, which had strongly divergent samples from a far eastern site (Orocué) in the Llanos east of the Cordil- lera was the only species showing a local genetic differentiation gradient perpendicular to the ridge. We were not able to test local genetic differentiation in the other nominal species given that these were collected in just one or two localities or the barcode algorithms divided them into different clusters.

Discussion Species identification and discovery across the Eastern Cordillera Our DNA barcoding survey of 52 nominal species corresponds to 7.3% of all anuran species of Colombia (of a total of 710 anurans recorded as of October 2014 [80]). In terms of species iden- tification, external morphology revealed fewer entities than DNA barcoding, not surprisingly, with 52 nominal species identified with morphology versus 56 and 65 clusters identified with molecular data (ABGD and RESL, respectively). The two DNA-based algorithms were somewhat dissimilar in terms of the agreement be- tween the nominal species and clusters. ABGD revealed that only three of the nominal species identified a priori contained cryptic lineages, while in RESL, this number increased to ten. We suggest, then, that the ABGD algorithm would be more appropriate for identifying uncon- firmed candidate species, as it is more conservative and groups haplotypes independently of their taxonomy. The RESL algorithm, on the other hand, would be preferable for species identi- fication, since it is less conservative and compares the DNA barcodes against a reference

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Fig 3. Map of local genetic differentiation in the seven nominal species sampled from both flanks of the Eastern Cordillera. For each species, the triangle on the left represents the minimum convex polygon that encompasses the sampling sites of each species. Warmer colors represent greater genetic distances between sampled sites and unsampled neighbors. The map on the right represents topography, with the dotted line indicated the spatial location of the polygon on the left. Black stars are western flank localities and white stars are eastern flank localities. Numbers correspond to map codes in Fig 1 and Table 1. Local genetic differentiation corresponds to one minus the expected correlation between sampled sites and neighboring unsampled sites located at 0.1 km. doi:10.1371/journal.pone.0127312.g003

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database of identified samples, and thereby suggests names for the unknown sequences. Of course, any species identification method is only as reliable as the database upon which it is based [60], in this case BoLD. Regarding species discovery, we found that the nominal species E. pustulosus, P. llanera, H. crepitans, L. fuscus, R. palmatus, P. miyatai, and L. colombiensis, were split into two or more groups by the less conservative RESL algorithm. Since this algorithm requires low genetic di- vergence to separate entities, these seven species might correspond to either highly divergent conspecific lineages, or unconfirmed candidate species separated by narrow genetic diver- gences. Amphibian species frequently show relative morphological stasis despite strong genetic divergences (well above the proposed thresholds to identify species using DNA barcode mark- ers) [18,62]. Moreover, convergence and parallelism are often found among even relatively closely related amphibians [81,82]. It is likely, therefore, that species diversity becomes masked with the exclusive use of morphological characters to describe diversity [83]. A barcode ap- proach allows even the non-specialist to be able to flag genetically divergent groups whose tax- onomic status require further expert investigation using independent data. The more conservative ABGD identified three nominal species that we believe are highly likely to contain cryptic diversity given their very deep genetic divergences: H. punctatus, S. wandae and S. ruber. This is not surprising for S. ruber, which has been shown to contain sub- stantial cryptic diversity in a recent study of populations in French Guyana [84]. As H. puncta- tus, S. wandae and S. ruber are geographically even more widespread across lowland sites that our sampling included, we suspect each of these nominal species to contain a multitude of cryptic lineages each, overlooked by previous studies based in morphology. A good example of the underestimation of diversity in lowland frog species is the case of Dendropsophus minutus, a widespread species in South America that displays 43 statistically supported deep mitochon- drial lineages, many of which likely correspond to undescribed cryptic species [85]. Curiously, both algorithms missed the two divergent clades within Rhinella marina separated by the east- ern Cordillera ridge. We explain this result by the fact that R. marina had several CO1 missing sequences, decreasing the overall resolution of this clade and the performance of both algo- rithms identifying groups. This observation highlights the relevance of CO1 (compared with 16S) detecting groups separated by narrow genetic divergences, and also, the possible role that missing data can have on the performance of genetic barcode algorithms. It is clear that the DNA barcode technique outperformed our morphological identifications in terms of both accuracy and time. The question is what to do with the outcomes of barcode surveys. For example, we found three highly divergent groups within the nominal species S. ruber, while Fouquet et al. [84] found six. Our candidates and Fouquet’s candidates are differ- ent entities since they were sampled in distant geographic regions. One of the goals of rapid biodiversity description is to characterize communities and biogeographic regions, such as the tropical Andes, in short time spans. The use of standardized markers and data bases goes a long way towards facilitating comparisons among disparate studies, yet ascribing a formal name to all these divergent groups might still be difficult, especially if it required the interna- tional shipment of type specimens. Padial et al. [55] suggested a strategy that could speed up the characterization of biogeographic regions using barcoding techniques. Their approach pro- poses to designate the provisional label of ‘unconfirmed candidate species’ to groups of speci- mens within nominal species that show unusually large genetic distances. The lineage would then be identified through the combination of the Linnaean binomial species name of the most closely related nominal species, followed by the abbreviation "Ca" (for candidate), adding a nu- merical code indicating the particular candidate species group. This system potentially would help researchers to be aware of what particular candidate species have been found, avoiding re- peating or ignoring genetic clusters that have been already published. Also, it may speed up the

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naming process by taxonomists, making more evident the groups that contain undescribed di- versity. Similarly, the standardized barcode database, BoLD, scans all CO1 sequences in the da- tabase and labels each cluster identified by its RESL algorithm numerically, creating a Barcode Index Number [70].

The Eastern Cordillera as a geographic barrier DNA barcode analyses can go beyond describing biodiversity patterns by studying the process- es that generate or erase such patterns [48,86]. In addition to characterizing the diversity of lin- eages in our survey, we also explored the role that the Eastern Cordillera may have played in increasing intraspecific divergence within nominal species sampled from both flanks. A map of local genetic differentiation showed that in five out of six species, the steepest change in genetic distances per unit of geographic distances was parallel and in close proximity to the Eastern Andes ridge. Genetic differentiation varies spatially due to several factors, including migration and other demographic processes [86], extinction and re-colonization of demes [87] and of course historical biogeographic processes [88], and teasing apart these factors is often challeng- ing. The fact that the same pattern was found in five species of different taxonomic families, however, strongly suggests that local genetic differentiation was not the product of idiosyncrat- ic processes, but the general effect of the Eastern Andes ridge reducing gene flow between pop- ulations across both sides of the ridge. The observation of genetically divergent conspecific populations from opposite slopes of the Andes has been described in multiple anuran species including R. marina [89], E. pustulosus [90], R. palmatus [42,91], and Dendropsophus labialis [43], as well as in several species of An- dean birds [92,93]. This evidence supports the fact that tropical lowland species (as opposed to temperate species) have strong difficulties crossing high elevation summits, a hypothesis for- mulated by Janzen almost 50 years ago [94], prior to the advent of DNA sequence analyses. Also, we confirmed the results of Muñoz-Ortiz et al. [91] finding that valleys are also important geographic features that restrict gene flow in mid-elevation species such as R. palmatus. Wier [95] suggested that Andean low valleys are more important promoting vicariance than Andean high summits, because the major uplift activity of the northern Andes was too recent for strong genetic divergences to build-up across such barriers, whereas low-elevation barriers have had more time to generate divergence. We found strong evidence, however, that both high eleva- tion summits and low elevation valleys are a prevalent force isolating populations and promot- ing genetic divergence in Andean anurans. This result agrees with Lynch et al. [34], suggesting that the nonsynchronous uplift of the Eastern Cordillera generated a topographic complexity that likely fragmented populations and promoted diversification in the past. Certainly, the comparison of high and low elevations as geographic barriers should be explored in more detail in future studies including more species and additional Andean landscapes. We hypothesize that the reason why five different species showed higher local genetic differ- entiation in the western flank of the Eastern Cordillera (relative to the eastern flank) is because it has a more complex topography and climate than the homogeneous Llanos in the eastern flank (Fig 3), and complex topographies and climates have been found to increase genetic di- vergence [27,96]. Curiously, our survey found both higher genetic differentiation among sites and lower species richness in the western flank. In other words, it appears that the western flank has higher beta diversity relative to the eastern flank, while the eastern flank has higher alpha diversity. We hypothesize that this observation is explained by the fact that the eastern flank localities contain multiple widely distributed species living in sympatry, due to the lack of geographic barriers in the flat Llanos Orientales, while in the western flank the complex

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topography and environmental heterogeneity of the Magdalena Valley isolates populations, in- creasing the diversity among sites. Even though we focused our discussion on the effects of topography and climate fragment- ing anuran populations, we cannot claim these are the only factors playing role in the diversifi- cation of the Eastern Cordillera. There are abundant studies that have shown how the idiosyncratic natural history of each species can be relevant explaining biological diversifica- tion. For example, small body sizes in the Malagasy mantellid frogs have been shown to limit the dispersal capabilities and to low physiological tolerances, causing strongly fragmented ranges [23]. Also, call variation (instead of landscape features) has been shown to promote ge- netic divergence and speciation in the lowland Amazonian frog, Engystomops petersi [97]. Even though we agree with Lynch et al. [34] that topography and climate are in general the most im- portant factors explaining the current diversity of the Eastern Cordillera, it is fundamental to further explore how the natural history of Andean species promotes their diversification or extinction. We found clear evidence for the key role of the Eastern Cordillera in creating genetic diver- gence at the nominally intraspecific level. More evidence, however, needs to be collected in order to determine not only how the Andes shape genetic variation, but also how it shapes the ecology and phenotypes of these species.

Conclusions Here we performed the first wide-scale DNA barcode survey of anurans in Colombia. We found that DNA barcoding is a method that outperformed our morphological identifications allowing us to complete the survey in a short period of time and to flag specimens from popula- tions that require further taxonomic and ecological scrutiny. We also found, using a novel Bayesian kriging approach, that both summits and valleys of the Eastern Andes of Colombia are important geographic features promoting intraspecific genetic divergence across several frog species, and that the eastern and western flanks have contrasting diversity levels. It is somewhat accepted that tropical lowland species have rather wide geographic distributions, while montane species have very restricted ranges. We believe, however, that due to morpho- logical stasis, a significant proportion of lowland species diversity has been underestimated by the predominant use of morphology in previous estimations [85,98]. It is quite possible that fu- ture genetic analyses will keep fragmenting the wide distributions of lowland species, which might change our current perception of tropical lowland vs. highland diversity patterns. We recommend that DNA barcoding surveys spend the additional effort, when possible, to collect multiple specimens from multiple localities that cover the geographic extent of each species in order to recover a better proportion of the intraspecific variability [99], which in turn allows for extended analyses of the genetic variation of the species found in the survey and their geo- graphic patterns. The tropical Andes in general, and Colombia specifically, still represent a poorly known region in terms of its biodiversity. We encourage researchers to include DNA barcode analyses in addition to the fundamental morphological analyses in future surveys of biodiversity of the tropical Andes [98]

Supporting Information S1 Fig. ABGD additional information. Left: Histogram showing the distribution of pairwise genetic distances (Kimura 2-parameter) among all samples using the combined dataset. The arrow indicates the threshold selected as separating within-species genetic variation and between-species genetic divergence. Right: Plot depicting how the number of clusters or hypo- thetical species recovered by the ABGD algorithm varies across increasing ‘prior intraspecific

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genetic divergences’ or thresholds. Recursive partitions are obtained by allowing the threshold to vary among species. (PDF) S1 Table. Detailed information on the samples collected. Field number, museum code, nom- inal species designation, collecting locality, BoLD ProcessID, ABGD cluster membership, RESL cluster membership (BIN), and GenBank accession number for each sample included in this study. NA correspond to missing voucher specimens. (PDF)

Acknowledgments We thank Á.M. Suarez, N.R. Pinto, L.S. Barrientos, L.M. Escobar, D. Moen, C. Sarmiento, F.L. Meza, E.P. Ramos, J.E. Ortega, Á.A. Velásquez, J.S. Mendoza and A. Dapper for their help with fieldwork, and Á.M. Suarez and A. Farfán for help in the Museum. We also thank C. Sarmiento for help with lab protocols and Á.M. Suarez and J.D. Lynch for help with morphological identi- fications. We specially want to thank all the landowners for their hospitality allowing us to work on their property. Samples were obtained with research and collecting permit N° 15 and access to genetic resources permit N° 44 to A.J.C. by the Ministerio de Ambiente, Vivienda y Desarrollo Territorial.

Author Contributions Conceived and designed the experiments: CEG AJC. Performed the experiments: AMO SVF JMN. Analyzed the data: CEG AP. Contributed reagents/materials/analysis tools: AJC. Wrote the paper: CEG AP AJC.

References 1. Hutter CR, Guayasamin JM, Wiens JJ (2013) Explaining Andean megadiversity: the evolutionary and ecological causes of glassfrog elevational richness patterns. Ecology Letters 16: 1135–1144. doi: 10. 1111/ele.12148 PMID: 23802805 2. Myers N, Mittermeier R, Mittermeier C, da Fonseca G, Kent J (2000) Biodiversity hotspots for conserva- tion priorities. Nature 403: 853–858. PMID: 10706275 3. Orme C, Davies R, Burgess M, Eigenbrod F, Pickup N, Olson VA, et al. (2005) Global hotspots of spe- cies richness are not congruent with endemism or threat. Nature 436: 1016–1019. PMID: 16107848 4. Torres-Carvajal O, Reeder T (2007) New Andean species of Stenocercus (Squamata: Iguania) from the eastern Cordillera in Colombia. Copeia 2007: 56–61. 5. Sarkinen TE, Marcelo-Pena JL, Yomona AD, Simon MF, Pennington RT, Hughes Colin E (2011) Un- derestimated endemic species diversity in the dry inter-Andean valley of the Rio Maranon, northern Peru: An example from Mimosa (Leguminosae, Mimosoideae). Taxon 60: 139–150. 6. Santos JC, Coloma LA, Summers K, Caldwell JP, Ree R, Cannatella DC (2009) Amazonian amphibian diversity is primarily derived from late Miocene Andean lineages. PLoS Biology 7: e1000056. doi: 1000010.1001371/journal.pbio.1000056 7. Lips KR, Diffendorfer J, Mendelson III JR, Sears MW (2008) Riding the wave: reconciling the roles of disease and climate change in amphibian declines. PLoS biology 6: e72. doi: 10.1371/journal.pbio. 0060072 PMID: 18366257 8. Feeley KJ, Silman MR (2010) Land-use and climate change effects on population size and extinction risk of Andean plants. Global Change Biology 16: 3215–3222. 9. Bush MB (2002) Distributional change and conservation on the Andean flank: a palaeoecological per- spective. Global Ecology and Biogeography 11: 463–473. 10. Chevallier P, Pouyaud B, Suarez W, Condom T (2011) Climate change threats to environment in the tropical Andes: glaciers and water resources. Regional Environmental Change 11: 179–187. 11. Vuille M, Francou B, Wagnon P, Juen I, Kaser G, Mark BG (2008) Climate change and tropical Andean glaciers: Past, present and future. Earth-Science Reviews 89: 79–96.

PLOS ONE | DOI:10.1371/journal.pone.0127312 May 22, 2015 16 / 20 DNA Barcoding of Anurans of the Colombian Andes

12. Vredenburg VT, Knapp RA, Tunstall TS, Briggs CJ (2010) Dynamics of an emerging disease drive large-scale amphibian population extinctions. Proceedings of the National Academy of Sciences 107: 9689–9694. doi: 10.1073/pnas.0914111107 PMID: 20457913 13. Wake DB, Vredenburg VT (2008) Are we in the midst of the sixth mass extinction? A view from the world of amphibians. Proceedings of the National Academy of Sciences 105: 11466–11473. 14. Fouquet A, Gilles A, Vences M, Marty C, Blanc M, Gemmell NJ (2007) Underestimation of species rich- ness in Neotropical frogs revealed by mtDNA analyses. PLoS one 2: e1109. PMID: 17971872 15. Funk WC, Caminer M, Ron SR (2012) High levels of cryptic species diversity uncovered in Amazonian frogs. Proceedings of the Royal Society B: Biological Sciences 279: 1806–1814. doi: 10.1098/rspb. 2011.1653 PMID: 22130600 16. Stuart BL, Inger RF, Voris HK (2006) High level of cryptic species diversity revealed by sympatric line- ages of Southeast Asian forest frogs. Biology letters 2: 470–474. PMID: 17148433 17. Crawford AJ, Cruz C, Griffith E, Ross H, Ibáñez R, Lips KR, et al. (2013) DNA barcoding applied to ex situ tropical amphibian conservation programme reveals cryptic diversity in captive populations. Molec- ular Ecology Resources 13: 1005–1018. doi: 10.1111/1755-0998.12054 PMID: 23280343 18. Fouquet A, Gilles A, Vences M, Marty C, Blanc M, Gemmell NJ (2007) Underestimation of species rich- ness in Neotropical frogs revealed by mtDNA analyses. PLoS One 2: e1109. PMID: 17971872 19. Glaw F, Kohler J (1998) Amphibian species diversity exceeds that of mammals. Herpetological Review 29: 11–11. 20. Köhler J, Glaw F, Vences M (2008) Trends in rates of amphibian species descriptions. Threatened am- phibians of the world Lynx Edicions, Barcelona 18. 21. Gonzales-Voyer A, Padial J, Castroviejo Fisher S (2011) Correlates of species richness in the largest Neotropical amphibian radiation. Journal of Evolutionary Biology 24: 931–942. doi: 10.1111/j.1420- 9101.2011.02243.x PMID: 21401771 22. Pabijan M, Wollenberg K, Vences M (2012) Small body size increases the regional differentiation of populations of tropical mantellid frogs (Anura: Mantellidae). Journal of evolutionary biology 25: 2310–2324. doi: 10.1111/j.1420-9101.2012.02613.x PMID: 22998688 23. Wollenberg KC, Vieites DR, Glaw F, Vences M (2011) Speciation in little: the role of range and body size in the diversification of Malagasy mantellid frogs. BMC evolutionary biology 11: 217. doi: 10.1186/ 1471-2148-11-217 PMID: 21777445 24. Beebee T (2005) Conservation genetics of amphibians. Heredity 95: 423–427. PMID: 16106261 25. Smith MA, Green DM (2005) Dispersal and the metapopulation paradigm in amphibian ecology and conservation: are all amphibian populations metapopulations? Ecography: 110–128. 26. Romdal TS, Araújo MB, Rahbek C (2012) Life on a tropical planet: niche conservatism and the global diversity gradient. Global Ecology and Biogeography 22: 344–350. 27. Guarnizo CE, Cannatella DC (2013) Genetic divergence within frog species is greater in topographical- ly more complex regions. Journal of Zoological Systematics and Evolutionary Research 51: 333–340. 28. Hoffmann M, Hilton-Taylor C, Angulo A, Böhm M, Brooks TM, Butchart SHM, et al. (2010) The impact of conservation on the status of the world’s vertebrates. Science 330: 1503–1509. doi: 10.1126/ science.1194442 PMID: 20978281 29. Stuart SN, Chanson JS, Cox NA, Young BE, Rodrigues AS, Fischman DL, et al. (2004) Status and trends of amphibian declines and extinctions worldwide. Science 306: 1783–1786. PMID: 15486254 30. Hof C, Araújo MB, Jetz W, Rahbek C (2011) Additive threats from pathogens, climate and land-use change for global amphibian diversity. Nature 480: 516–519. doi: 10.1038/nature10650 PMID: 22089134 31. Cheng TL, Rovito SM, Wake DB, Vredenburg VT (2011) Coincident mass extirpation of neotropical am- phibians with the emergence of the infectious fungal pathogen Batrachochytrium dendrobatidis. Pro- ceedings of the National Academy of Sciences 108: 9502–9507. doi: 10.1073/pnas.1105538108 PMID: 21543713 32. Kattan GH, Franco P, Rojas V, Morales G (2004) Biological diversification in a complex region: a spatial analysis of faunistic diversity and biogeography of the Andes of Colombia. Journal of Biogeography 31: 1829–1839. 33. Duellman WE (1999) Patterns of Distribution of Amphibians: a Global Perspective: Johns Hopkins Uni- versity Press. 34. Lynch J, Ruiz-Carranza P, Ardila-Robayo M (1997) Biogeographic patterns of Colombian frogs and toads. Rev Acad Colomb Cienc 21: 237–248. 35. Hooghiemstra H, Van der Hammen T (2004) Quaternary Ice-Age dynamics in the Colombian Andes: developing an understanding of our legacy. Philosophical Transactions of the Royal Society B: Biologi- cal Sciences 359: 173–181. PMID: 15101574

PLOS ONE | DOI:10.1371/journal.pone.0127312 May 22, 2015 17 / 20 DNA Barcoding of Anurans of the Colombian Andes

36. Horton BK, Parra M, Saylor JE, Nie J, Mora A, Torres V, et al. (2010) Resolving uplift of the northern Andes using detrital zircon age signatures. GSA today 20: 4–10. 37. Lynch JD, Ruiz-Carranza PM, Ardila-Robayo MC (1997) Biogeographic patterns of Colombian frogs and toads. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales 21: 237–248. 38. Cadena CD, Cuervo AM (2010) Molecules, ecology, morphology, and songs in concert: how many spe- cies is Arremon torquatus (Aves: Emberizidae)? Biological Journal of the Linnean Society 99: 152–176. 39. Gutiérrez-Pinto N, Cuervo AM, Miranda J, Pérez-Emán JL, Brumfield RT, Cadena CD et al. (2012) Non-monophyly and deep genetic differentiation across low-elevation barriers in a Neotropical montane bird Basileuterus tristriatus; Aves: Parulidae). Molecular Phylogenetics and Evolution 64: 156–165. doi: 10.1016/j.ympev.2012.03.011 PMID: 22484358 40. Chaves JA, Weir JT, Smith TB (2011) Diversification in Adelomyia hummingbirds follows Andean uplift. Molecular Ecology 20: 4564–4576. doi: 10.1111/j.1365-294X.2011.05304.x PMID: 21981387 41. Guarnizo CE, Escallón C, Cannatella D, Amézquita A (2012) Congruence Between Acoustic Traits and Genealogical History Reveals a New Species of Dendropsophus (Anura: Hylidae) in the High Andes of Colombia. Herpetologica 68: 523–540. 42. Bernal XE, Guarnizo C, Luddecke H (2005) Geographic variation in advertisement call and genetic structure of Colostethus palmatus (Anura, Dendrobatidae) from the Colombian Andes. Herpetologica 61: 395–408. 43. Guarnizo CE, Amezquita A, Bermingham E (2009) The relative roles of vicariance versus elevational gradients in the genetic differentiation of the high Andean tree frog, Dendropsophus labialis. Molecular Phylogenetics and Evolution 50: 84–92. doi: 10.1016/j.ympev.2008.10.005 PMID: 18957324 44. Cadena C, Klicka J, Ricklefs R (2007) Evolutionary differentiation in the Neotropical montane region: Molecular phylogenetics and phylogeography of Buarremon brush-finches (Aves, Emberizidae). Mo- lecular Phylogenetics and Evolution 44: 993–1016. PMID: 17275342 45. Vargas-Ramírez M, Moreno-Arias R (2014) Unknown Evolutionary Lineages and Population Differenti- ation in Anolis heterodermus (Squamata: Dactyloidae) from the Eastern and Central Cordilleras of Co- lombia Revealed by DNA Sequence Data. South American Journal of Herpetology 9: 131–141. 46. Bickford D, Lohman DJ, Sodhi NS, Ng PK, Meier R, Winker K, et al. (2007) Cryptic species as a window on diversity and conservation. Trends in Ecology & Evolution 22: 148–155. 47. Collins R, Cruickshank R (2013) The seven deadly sins of DNA barcoding. Molecular Ecology Re- sources 13: 969–975. doi: 10.1111/1755-0998.12046 PMID: 23280099 48. Hajibabaei M, Singer GA, Hebert PD, Hickey DA (2007) DNA barcoding: how it complements taxono- my, molecular phylogenetics and population genetics. TRENDS in Genetics 23: 167–172. PMID: 17316886 49. Wiemers M, Fiedler K (2007) Does the DNA barcoding gap exist?–a case study in blue butterflies (Lepi- doptera: Lycaenidae). Frontiers in Zoology 4: 1–16. PMID: 17207286 50. Meyer CP, Paulay G (2005) DNA barcoding: error rates based on comprehensive sampling. PLoS biol- ogy 3: e422. PMID: 16336051 51. Paz A, Crawford AJ (2012) Molecular-based rapid inventories of sympatric diversity: A comparison of DNA barcode clustering methods applied to geography-based vs clade-based sampling of amphibians. Journal of Biosciences 37: 887–896. PMID: 23107924 52. Puillandre N, Lambert A, Brouillet S, Achaz G (2012) ABGD, Automatic Barcode Gap Discovery for pri- mary species delimitation. Molecular Ecology 21: 1864–1877. doi: 10.1111/j.1365-294X.2011.05239.x PMID: 21883587 53. Meier R, Shiyang K, Vaidya G, Ng PK (2006) DNA barcoding and taxonomy in Diptera: a tale of high in- traspecific variability and low identification success. Systematic biology 55: 715–728. PMID: 17060194 54. DeSalle R (2006) Species discovery versus species identification in DNA barcoding efforts: response to Rubinoff. Conservation Biology 20: 1545–1547. PMID: 17002772 55. Padial JM, Miralles A, De la Riva I, Vences M (2010) Review: The integrative future of taxonomy. Front Zool 7: 16. doi: 10.1186/1742-9994-7-16 PMID: 20500846 56. Bergsten J, Bilton DT, Fujisawa T, Elliott M, Monaghan MT, Balke M, et al. (2012) The effect of geo- graphical scale of sampling on DNA barcoding. Systematic Biology 6: 851–869. 57. Wright S (1943) Isolation by distance. Genetics 28: 114–138. PMID: 17247074 58. Lou M, Golding GB (2012) The effect of sampling from subdivided populations on species identification with DNA barcodes using a Bayesian statistical approach. Molecular Phylogenetics and Evolution 65: 765–773. doi: 10.1016/j.ympev.2012.07.033 PMID: 22906810

PLOS ONE | DOI:10.1371/journal.pone.0127312 May 22, 2015 18 / 20 DNA Barcoding of Anurans of the Colombian Andes

59. Seutin G, White BN, Boag PT (1991) Preservation of avian blood and tissue samples for DNA analyses. Canadian Journal of Zoology 69: 82–90. 60. Ratnasingham S, Hebert PD (2007) BOLD: The Barcode of Life Data System (http://www.barcodinglife. org). Molecular Ecology Notes 7: 355–364. PMID: 18784790 61. Hebert PD, Ratnasingham S, de Waard JR (2003) Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. Proceedings of the Royal Society of London Series B: Bi- ological Sciences 270: S96–S99. PMID: 12952648 62. Vences M, Thomas M, Van Der Meijden A, Chiari Y, Vieites DR (2005) Comparative performance of the 16S rRNA gene in DNA barcoding of amphibians. Frontiers in Zoology 2: 5. PMID: 15771783 63. Meyer CP, Geller JB, Paulay G (2005) Fine scale endemism on coral reefs: archipelagic differentiation in turbinid gastropods. Evolution 59: 113–125. PMID: 15792232 64. Che J, Chen HM, Yang JX, Jin JQ, Jiang K, Yuan ZY, et al. (2012) Universal COI primers for DNA bar- coding amphibians. Molecular Ecology Resources 12: 247–258. doi: 10.1111/j.1755-0998.2011. 03090.x PMID: 22145866 65. Palumbi S (1996) Nucleic acids II: the polymerase chain reaction. In ‘Molecular Systematics’.(Eds Hillis DM, Moritz C. and Mable BK.) pp. 205–247. Sinauer Associates: Sunderland, MA. 66. Werle E, Schneider C, Renner M, Völker M, Fiehn W (1994) Convenient single-step, one tube purifica- tion of PCR products for direct sequencing. Nucleic Acids Research 22: 4354. PMID: 7937169 67. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nu- cleic Acids Research 32: 1792–1797. PMID: 15034147 68. Kimura M (1980) A simple method for estimating evolutionary rates of base substitutions through compara- tive studies of nucleotide sequences. Journal of Molecular Evolution 16: 111–120. PMID: 7463489 69. Collins RA, Boykin LM, Cruickshank RH, Armstrong KF (2012) Barcoding's next top model: an evaluation of nucleotide substitution models for specimen identification. Methods in Ecology and Evolution 3: 457–465. 70. Ratnasingham S, Hebert PD (2013) A DNA-based registry for all animal species: The Barcode Index Number (BIN) System. PLoS One 8: e66213. doi: 10.1371/journal.pone.0066213 PMID: 23861743 71. Hamilton CA, Hendrixson BE, Brewer MS, Bond JE (2014) An evaluation of sampling effects on multi- ple DNA barcoding methods leads to an integrative approach for delimiting species: A case study of the North American tarantula genus Aphonopelma (Araneae, Mygalomorphae, Theraphosidae). Molecular Phylogenetics and Evolution 71: 79–93. doi: 10.1016/j.ympev.2013.11.007 PMID: 24280211 72. Kekkonen M, Hebert PDN (2014) DNA barcode-based delineation of putative species: efficient start for taxonomic workflows. Molecular Ecology Resources 14: 706–715. doi: 10.1111/1755-0998.12233 PMID: 24479435 73. van Velzen R, Weitschek E, Felici G, Bakker FT (2012) DNA barcoding of recently diverged species: relative performance of matching methods. PloS one 7: e30490. doi: 10.1371/journal.pone.0030490 PMID: 22272356 74. Stamatakis A (2006) RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thou- sands of taxa and mixed models. Bioinformatics 22: 2688. PMID: 16928733 75. Duforet-Frebourg N, Blum MG (2014) Nonstationary patterns of isolation-by-distance: Inferring mea- sures of local genetic differentiation with bayesian kriging Evolution 68: 1110–1123. 76. Cressie N (1993) Statistics for Spatial Data: Wiley Series in Probability and Statistics. Wiley-Inter- science, New York. 77. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular Biology and Evolution 28: 2731–2739. doi: 10.1093/molbev/msr121 PMID: 21546353 78. Wang IJ, Glor RE, Losos JB (2013) Quantifying the roles of ecology and geography in spatial genetic di- vergence. Ecology letters 16: 175–182. doi: 10.1111/ele.12025 PMID: 23137142 79. Ersts P (2011) Geographic distance matrix generator (version 1.2. 3). American Museum of Natural History. Center for Biodiversity and Conservation. 80. AmphibiaWeb (2013) AmphibiaWeb: Information on amphibian biology and conservation [web applica- tion]. Berkeley, California Available: http://amphibiaweborg/ (Accessed 1 October 2014). 81. Wiens JJ, Chippindale PT, Hillis DM (2003) When are phylogenetic analyses misled by convergence? A case study in Texas cave salamanders. Systematic Biology 52: 501–514. PMID: 12857641 82. Wake DB (2009) What salamanders have taught us about evolution. Annu Rev Ecol Evol Syst 40: 333–352. 83. Vences M, Thomas M, Bonett R, Vieites D (2005) Deciphering amphibian diversity through DNA bar- coding: chances and challenges. Philosophical Transactions of the Royal Society B: Biological Sci- ences 360: 1859–1868. PMID: 16221604

PLOS ONE | DOI:10.1371/journal.pone.0127312 May 22, 2015 19 / 20 DNA Barcoding of Anurans of the Colombian Andes

84. Fouquet A, Vences M, Salducci M, Meyer A, Marty C, Blanc M, et al. (2007) Revealing cryptic diversity using molecular phylogenetics and phylogeography in frogs of the Scinax ruber and Rhinella margariti- fera species groups. Molecular Phylogenetics and Evolution 43: 567–582. PMID: 17303441 85. Gehara M, Crawford AJ, Orrico VG, Rodríguez A, Lötters S, Fouquet A, et al. (2014) High levels of di- versity uncovered in a widespread nominal taxon: continental phylogeography of the Neotropical tree frog Dendropsophus minutus. PloS one 9: e103958. doi: 10.1371/journal.pone.0103958 PMID: 25208078 86. Barton N, Wilson I (1995) Genealogies and geography. Philosophical Transactions of the Royal Society of London Series B: Biological Sciences 349: 49–59. PMID: 8748019 87. Wade MJ, McCauley DE (1988) Extinction and recolonization: their effects on the genetic differentiation of local populations. Evolution: 995–1005. 88. Avise JC (2000) Phylogeography: the history and formation of species: Harvard University Press. 89. Slade R, Moritz C (1998) Phylogeography of Bufo marinus from its natural and introduced ranges. Pro- ceedings of the Royal Society of London Series B: Biological Sciences 265: 769–777. PMID: 9628036 90. Weigt LA, Crawford AJ, Rand AS, Ryan MJ (2005) Biogeography of the túngara frog, Physalaemus pustulosus: a molecular perspective. Molecular Ecology 14: 3857–3876. PMID: 16202101 91. Muñoz-Ortiz A, Velásquez-Álvarez ÁA, Guarnizo CE, Crawford AJ (2015) Of peaks and valleys: testing the roles of orogeny and habitat heterogeneity in driving allopatry in mid‐elevation frogs (Aromobatidae: Rheobates) of the northern Andes. Journal of Biogeography 42: 193–205. 92. Valderrama E, Pérez-Emán JL, Brumfield RT, Cuervo AM, Cadena CD (2014) The influence of the complex topography and dynamic history of the montane Neotropics on the evolutionary differentiation of a cloud forest bird (Premnoplex brunnescens, Furnariidae). Journal of Biogeography 41: 1533–1546. 93. Parra JL, Remsen J Jr, Alvarez-Rebolledo M, McGuire JA (2009) Molecular phylogenetics of the hum- mingbird genus Coeligena. Molecular Phylogenetics and Evolution 53: 425–434. doi: 10.1016/j.ympev. 2009.07.006 PMID: 19596453 94. Janzen D (1967) Why mountain passes are higher in the tropics. The American Naturalist 101: 233. 95. Weir JT (2009) Implications of genetic differentiation in neotropical montane forest birds. Annals of the Missouri Botanical Garden 96: 410–433. 96. Moritz C, Patton J, Schneider C, Smith T (2000) Diversification of forest faunas: An integrated molecu- lar approach. Annual Review of Ecology and Systematics 31: 533–563. 97. Funk W, Cannatella D, Ryan M (2009) Genetic divergence is more tightly related to call variation than landscape features in the Amazonian frogs Physalaemus petersi and P. freibergi. Journal of Evolution- ary Biology 22: 1839–1853. doi: 10.1111/j.1420-9101.2009.01795.x PMID: 19583696 98. Padial JM, De La Riva I (2007) Integrative taxonomists should use and produce DNA barcodes. Zoo- taxa 1586: 67–68. 99. Murphy RW, Crawford AJ, Bauer AM, Che J, Donnellan SC, Fritz U, et al. (2013) Cold Code: the global initiative to DNA barcode amphibians and nonavian reptiles. Molecular Ecology Resources 13: 161–167.

PLOS ONE | DOI:10.1371/journal.pone.0127312 May 22, 2015 20 / 20 S1 Fig. ABGD additional information

Left: Histogram showing the distribution of pairwise genetic distances (Kimura 2- parameter) among all samples using the combined dataset. The arrow indicates the threshold selected as separating within-species genetic variation and between-species genetic divergence. Right: Plot depicting how the number of clusters or hypothetical species recovered by the ABGD algorithm varies across increasing ‘prior intraspecific genetic divergences’ or thresholds. Recursive partitions are obtained by allowing the threshold to vary among species.

S1 Table. Detailed information on the samples collected.

Field number, museum code, nominal species designation, collecting locality, BoLD ProcessID,

ABGD cluster membership, RESL cluster membership (BIN), and GenBank accession number for each sample included in this study. NA correspond to missing voucher specimens.

OTUs Field Museum Process ABGD OTUs RESL 16S GenBank CO1 GenBank Nominal species Locality number Number BOLD (16S + (cox1) Accession # Accession # cox1)

AJC 4091 ANDES-A 1111 Adenomera andreae Sabanalarga, Casanare BSECO042-11 53 BOLD:ABU5979 KP149345 KP149148

AJC 4093 ANDES-A 1106 Adenomera andreae Sabanalarga, Casanare BSECO044-11 53 BOLD:ABU5979 KP149454 KP149245

AJC 4094 ANDES-A 1113 Adenomera andreae Sabanalarga, Casanare BSECO045-11 53 BOLD:ABU5979 KP149377 KP149175

AJC 3510 ANDES-A 602 Agalychnis terranova San Vicente, Santander BSAMS118-12 31 BOLD:ACC1259 KP149386 KP149183

AJC 3515 ANDES-A 601 Agalychnis terranova San Vicente, Santander BSAMS120-12 31 BOLD:ACC1259 KP149341 KP149144

Not sequenced AJC 3897 ANDES-A 1730 Allobates niputidea Sabana de Torres, Santander BSECO324-11 44 Not sequenced for KP149362 CO1 for CO1

AJC 3900 ANDES-A 1731 Allobates niputidea Sabana de Torres, Santander BSECO327-11 44 BOLD:ABV7978 KP149439 KP149233

AJC 3383 ANDES-A 1073 Allobates ranoides Sabanalarga, Casanare BSECO100-11 14 BOLD:ABA1656 KJ130661 KJ130697

AJC 3385 ANDES-A 1247 Allobates ranoides Sabanalarga, Casanare BSECO372-11 14 BOLD:ABA1656 KJ130698 KJ130662

AJC 3873 ANDES-A 1732 Craugastor longirostris Sabana de Torres, Santander BSECO302-11 41 BOLD:AAZ9403 KP149480 KP149268

AJC 3885 Craugastor longirostris Sabana de Torres, Santander BSECO313-11 41 BOLD:AAZ9403 KP149315 KP149119 NA

AJC 3881 ANDES-A 1733 Dendrobates truncatus Sabana de Torres, Santander BSECO310-11 42 BOLD:AAA5634 KP149428 KP149223

AJC 3882 ANDES-A 1734 Dendrobates truncatus Sabana de Torres, Santander BSECO311-11 42 BOLD:AAA5634 KP149285 KP149090

AJC 3886 ANDES-A 1735 Dendrobates truncatus Sabana de Torres, Santander BSECO314-11 42 BOLD:AAA5634 KP149287 KP149092

AJC 3502 ANDES-A 1222 Dendropsophus ebraccatus San Vicente, Santander BSAMS111-12 28 BOLD:ACC1363 KP149426 KP149221

AJC 3504 ANDES-A 1736 Dendropsophus ebraccatus San Vicente, Santander BSAMS113-12 28 BOLD:ACC1363 KP149355 KP149156

AJC 1740 ANDES-A 1593 Dendropsophus mathiassoni San Juan de Arama, Meta BSECO173-11 1 BOLD:ABA0401 KP149436 KP149230

AJC 1746 ANDES-A 1737 Dendropsophus mathiassoni San Juan de Arama, Meta BSECO179-11 1 BOLD:ABA0401 KP149479 KP149267

AJC 1749 ANDES-A 1738 Dendropsophus mathiassoni San Juan de Arama, Meta BSECO182-11 1 BOLD:ABA0401 KP149393 KP149189

AJC 2111 ANDES-A 1740 Dendropsophus mathiassoni San Juan de Arama, Meta BSECO217-11 1 BOLD:ABA0401 KP149304 KP149108

AJC 2112 ANDES-A 1741 Dendropsophus mathiassoni San Juan de Arama, Meta BSECO218-11 1 BOLD:ABA0401 KP149298 KP149102

AJC 2313 ANDES-A 1742 Dendropsophus mathiassoni Orocué, Casanare BSAMS083-12 1 BOLD:ABA0401 KP149389 KP149185

AJC 2322 ANDES-A 1163 Dendropsophus mathiassoni Orocué, Casanare BSAMS086-12 1 BOLD:ABA0401 KP149399 KP149214

Not sequenced AJC 2323 ANDES-A 1161 Dendropsophus mathiassoni Orocué, Casanare BSAMS087-12 1 Not sequenced for KP149399 CO1 for CO1

AJC 3923 ANDES-A 1270 Dendropsophus mathiassoni San Juan de Arama, Meta BSECO186-11 1 BOLD:ABA0401 KP149474 KP149262

AJC 3933 ANDES-A 1268 Dendropsophus mathiassoni San Juan de Arama, Meta BSECO196-11 1 BOLD:ABA0401 KP149309 KP149113

AJC 4052 ANDES-A 1085 Dendropsophus mathiassoni Sabanalarga, Casanare BSECO013-11 1 BOLD:ABA0401 KP149281 KP149086

AJC 4060 ANDES-A 1079 Dendropsophus mathiassoni Sabanalarga, Casanare BSECO008-11 1 BOLD:ABA0401 KP149305 KP149109

AJC 4070 ANDES-A 1066 Dendropsophus mathiassoni Sabanalarga, Casanare BSECO021-11 1 BOLD:ABA0401 KP149310 KP149114

AJC 4095 ANDES-A 1074 Dendropsophus mathiassoni Sabanalarga, Casanare BSECO046-11 1 BOLD:ABA0401 KP149464 KP149254

AJC 3869 Dendropsophus microcephalus Sabana de Torres, Santander BSECO298-11 40 BOLD:AAC1019 KP149375 KP149173 NA

AJC 3887 ANDES-A 1295 Dendropsophus microcephalus Sabana de Torres, Santander BSECO315-11 40 BOLD:AAC1019 KP149423 KP149218 AJC 4035 ANDES-A 1743 Dendropsophus microcephalus San Vicente, Santander BSAMS182-12 40 BOLD:AAC1019 KP149342 KP149145

AJC 4038 ANDES-A 1451 Dendropsophus microcephalus San Vicente, Santander BSAMS184-12 40 BOLD:AAC1019 KP149404 KP149199

AJC 3384 ANDES-A 1230 Dendropsophus cf. stingi Sabanalarga, Casanare BSECO371-11 15 BOLD:ABA0313 KP149313 KP149117

AJC 3999 ANDES-A 1491 Dendropsophus cf. stingi Miraflores, Boyacá BSECO152-11 15 BOLD:ABA0313 KJ817825 KJ817831

AJC 4001 ANDES-A 1466 Dendropsophus cf. stingi Miraflores, Boyacá BSECO154-11 15 BOLD:ABA0313 KP149441 KP149235

AJC 4003 ANDES-A 1492 Dendropsophus cf. stingi Miraflores, Boyacá BSECO156-11 15 BOLD:ABA0313 KJ817824 KJ817830

AJC 4004 ANDES-A 1493 Dendropsophus cf. stingi Miraflores, Boyacá BSECO157-11 15 BOLD:ABA0313 KJ817826 KJ817832

AJC 4005 ANDES-A 1467 Dendropsophus cf. stingi Miraflores, Boyacá BSECO158-11 15 BOLD:ABA0313 KP149369 KP149167

AJC 4110 ANDES-A 1130 Dendropsophus cf. stingi Sabanalarga, Casanare BSECO060-11 15 BOLD:ABA0313 KJ817827 KJ817833

AJC 4111 ANDES-A 1490 Dendropsophus cf. stingi Sabanalarga, Casanare BSECO061-11 15 BOLD:ABA0313 Pending Pending

LSB 373 ANDES-A 1488 Dendropsophus cf. stingi Pajarito, Boyacá BSECO263-11 15 BOLD:ABA0313 KJ817828 KJ817834

LSB 374 ANDES-A 1489 Dendropsophus cf. stingi Pajarito, Boyacá BSECO264-11 15 BOLD:ABA0313 KJ817829 KJ817835

Not sequenced for Not sequenced AJC 3837 ANDES-A 1277 Dendropsophus subocularis Puente Nacional, Santander BSECO276-11 36 KP149434 CO1 for CO1

AJC 3845 ANDES-A 1278 Dendropsophus subocularis Puente Nacional, Santander BSECO284-11 36 BOLD:ABV9393 KP149306 KP149110

AJC 3847 ANDES-A 1274 Dendropsophus subocularis Puente Nacional, Santander BSECO286-11 36 BOLD:ABV9393 KP149412 KP149207

AJC 1742 ANDES-A 1744 Elachistocleis ovalis San Juan de Arama, Meta BSECO175-11 3 BOLD:ABA1508 KP149470 KP149259

AJC 2306 ANDES-A 1745 Elachistocleis ovalis Orocué, Casanare BSAMS082-12 3 BOLD:ABA1508 KP149445 KP149238

AJC 2381 ANDES-A 1157 Elachistocleis ovalis Orocué, Casanare BSAMS103-12 3 BOLD:ABA1508 KP149457 KP149247

AJC 3374 ANDES-A 1070 Elachistocleis ovalis Sabanalarga, Casanare BSECO091-11 3 BOLD:ABA1508 KP149484 KP149272

AJC 3377 ANDES-A 1069 Elachistocleis ovalis Sabanalarga, Casanare BSECO094-11 3 BOLD:ABA1508 KP149288 KP149093

AJC 3379 ANDES-A 1240 Elachistocleis ovalis Sabanalarga, Casanare BSECO096-11 3 BOLD:ABA1508 KP149400 KP149195

AJC 3970 ANDES-A 1239 Elachistocleis ovalis Sabanalarga, Casanare BSECO082-11 3 BOLD:ABA1508 KP149387 KP149184

AJC 3972 ANDES-A 1236 Elachistocleis ovalis Sabanalarga, Casanare BSECO084-11 3 BOLD:ABA1508 KP149487 KP149274

AJC 3507 ANDES-A 1032 Engystomops pustulosus San Vicente, Santander BSAMS116-12 29 BOLD:ABV7902 KP149280 KP149085

AJC 3859 ANDES-A 1746 Engystomops pustulosus Piedecuesta, Santander BSECO328-11 29 BOLD:ABV7902 KP149458 KP149248

AJC 3862 ANDES-A 1747 Engystomops pustulosus Piedecuesta, Santander BSECO331-11 29 BOLD:ABV7902 KP149413 KP149208

AJC 3872 ANDES-A 1748 Engystomops pustulosus Sabana de Torres, Santander BSECO301-11 29 BOLD:ABV7902 KP149356 KP149157

AJC 3875 ANDES-A 1749 Engystomops pustulosus Sabana de Torres, Santander BSECO304-11 29 BOLD:ABV7903 KP149340 KP149143

AJC 2302 ANDES-A 1750 Espadarana andina Puente Nacional, Santander BSECO122-11 7 BOLD:ABU6599 KP149354 KP149155

AJC 3387 ANDES-A 1751 Espadarana andina Puente Nacional, Santander BSECO105-11 7 BOLD:ABU6599 KP149447 KP149240

LSB 384 ANDES-A 1248 Hyalinobatrachium esmeralda Pajarito, Boyacá BSECO274-11 56 BOLD:ABU6258 KP149361 KP149161

LSB 369 ANDES-A 1818 Hyloscirtus cf. phyllognathus Pajarito, Boyacá BSECO259-11 54 BOLD:ABU6239 KP149337 KP149140

AJC 3443 ANDES-A 1752 Hypsiboas boans San Juan de Arama, Meta BSECO220-11 20 BOLD:AAI7867 KP149456 KP149246

AJC 3396 ANDES-A 1753 Hypsiboas crepitans Puente Nacional, Santander BSECO104-11 16 BOLD:ABZ3336 KP149283 KP149088

AJC 3505 ANDES-A 1528 Hypsiboas crepitans San Vicente, Santander BSAMS114-12 16 BOLD:ABZ3336 KP149290 KP149095

AJC 3838 ANDES-A 1529 Hypsiboas crepitans Puente Nacional, Santander BSECO277-11 16 BOLD:ABZ3336 KP149481 KP149269

AJC 3839 ANDES-A 1754 Hypsiboas crepitans Puente Nacional, Santander BSECO278-11 16 BOLD:ABA0429 KP149448 KP149241

AJC 3840 ANDES-A 1530 Hypsiboas crepitans Puente Nacional, Santander BSECO279-11 16 BOLD:ABZ3336 KP149420 KP149215

AJC 3842 ANDES-A 1531 Hypsiboas crepitans Puente Nacional, Santander BSECO281-11 16 BOLD:ABZ3336 KP149402 KP149197

AJC 3844 ANDES-A 1532 Hypsiboas crepitans Puente Nacional, Santander BSECO283-11 16 BOLD:ABZ3336 KP149316 KP149120

AJC 3925 ANDES-A 1534 Hypsiboas crepitans San Juan de Arama, Meta BSECO188-11 16 BOLD:ABA0429 KP149475 KP149263 AJC 3934 ANDES-A 1535 Hypsiboas crepitans San Juan de Arama, Meta BSECO197-11 16 BOLD:ABA0429 KP149477 KP149265

AJC 4010 ANDES-A 1507 Hypsiboas crepitans Miraflores, Boyacá BSECO370-11 16 BOLD:ABA0429 KP149317 KP149121

AJC 4014 ANDES-A 1508 Hypsiboas crepitans Miraflores, Boyacá BSECO163-11 16 BOLD:ABA0429 BSECO163 KP149256

AJC 4019 ANDES-A 1509 Hypsiboas crepitans Miraflores, Boyacá BSECO168-11 16 BOLD:ABA0429 KP149378 KP149176

AJC 4108 ANDES-A 1063 Hypsiboas crepitans Sabanalarga, Casanare BSECO058-11 16 BOLD:ABA0429 KP149370 KP149168

AJC 4116 ANDES-A 1284 Hypsiboas crepitans Sabanalarga, Casanare BSECO066-11 16 BOLD:ABA0429 KP149478 KP149266

AJC 3373 ANDES-A 1054 Hypsiboas lanciformis Sabanalarga, Casanare BSECO090-11 12 Not sequenced for KP149451 Pending CO1

AJC 3971 ANDES-A 1231 Hypsiboas lanciformis Sabanalarga, Casanare BSECO083-11 12 Not sequenced for BSECO083 Pending CO1 Not sequenced AJC 3973 ANDES-A 1053 Hypsiboas lanciformis Sabanalarga, Casanare BSECO085-11 12 Not sequenced for BSECO085 CO1 for CO1

AJC 3975 ANDES-A 1238 Hypsiboas lanciformis Sabanalarga, Casanare BSECO087-11 12 BOLD:ABX7699 KP149371 KP149169

AJC 3501 ANDES-A 1541 Hypsiboas pugnax San Vicente, Santander BSAMS110-12 27 BOLD:ABV8158 KP149407 KP149202

AJC 3503 ANDES-A 1207 Hypsiboas pugnax San Vicente, Santander BSAMS112-12 27 BOLD:ABV8158 KP149471 KP149169

AJC 3529 ANDES-A 1453 Hypsiboas pugnax San Vicente, Santander BSAMS124-12 27 BOLD:ABV8158 KP149296 KP149101

AJC 3870 ANDES-A 1533 Hypsiboas pugnax Sabana de Torres, Santander BSECO299-11 27 BOLD:ABV8158 KP149417 KP149212

AJC 3871 ANDES-A 1538 Hypsiboas pugnax Sabana de Torres, Santander BSECO300-11 27 BOLD:ABV8158 KP149418 KP149213

AJC 3874 ANDES-A 1539 Hypsiboas pugnax Sabana de Torres, Santander BSECO303-11 27 BOLD:ABV8158 KP149327 KP149130

AJC 3878 ANDES-A 1540 Hypsiboas pugnax Sabana de Torres, Santander BSECO307-11 27 BOLD:ABV8158 KP149409 KP149204

AJC 3921 ANDES-A 1755 Hypsiboas punctatus San Juan de Arama, Meta BSECO184-11 45 BOLD:ABA0585 KP149469 KP149258

AJC 3922 ANDES-A 1756 Hypsiboas punctatus San Juan de Arama, Meta BSECO185-11 45 BOLD:ABA0585 KP149390 KP149186

AJC 3928 ANDES-A 1757 Hypsiboas punctatus San Juan de Arama, Meta BSECO191-11 45 BOLD:ABA0585 KP149392 KP149188

AJC 3932 ANDES-A 1758 Hypsiboas punctatus San Juan de Arama, Meta BSECO195-11 45 BOLD:ABA0585 KP149476 KP149264

AJC 4064 ANDES-A 1044 Hypsiboas punctatus Sabanalarga, Casanare BSECO016-11 52 BOLD:ABA0584 KP149397 KP149193

AJC 4100 ANDES-A 1242 Hypsiboas punctatus Sabanalarga, Casanare BSECO051-11 52 BOLD:ABA0584 KP149307 KP149111

AJC 3848 ANDES-A 1761 Leptodactylus colombiensis Puente Nacional, Santander BSECO287-11 37 BOLD:ABV8030 KP149318 KP149122

AJC 3978 ANDES-A 1456 Leptodactylus colombiensis Miraflores, Boyacá BSECO132-11 37 BOLD:ABA1440 KP149468 KP149257

AJC 3981 ANDES-A 1460 Leptodactylus colombiensis Miraflores, Boyacá BSECO135-11 37 BOLD:ABA1440 KP149403 KP149198

AJC 3986 ANDES-A 1457 Leptodactylus colombiensis Miraflores, Boyacá BSECO140-11 37 BOLD:ABA1440 KP149444 KP149237

AJC 4000 ANDES-A 1762 Leptodactylus colombiensis Miraflores, Boyacá BSECO153-11 37 BOLD:ABA1440 KP149302 KP149106

LSB 378 ANDES-A 1250 Leptodactylus colombiensis Pajarito, Boyacá BSECO268-11 37 BOLD:ABA1440 KP149459 KP149249

AJC 2301 ANDES-A 1169 Leptodactylus fuscus Orocué, Casanare BSAMS081-12 6 BOLD:ABA0407 KP149398 KP149194

AJC 3467 ANDES-A 1763 Leptodactylus fuscus San Juan de Arama, Meta BSECO243-11 6 BOLD:ABA0407 KP149410 KP149205

AJC 3892 ANDES-A 1193 Leptodactylus fuscus Sabana de Torres, Santander BSECO319-11 6 BOLD:ABV8011 KP149449 KP149242

AJC 3893 ANDES-A 1188 Leptodactylus fuscus Sabana de Torres, Santander BSECO320-11 6 BOLD:ABV8011 KP149446 KP149239

AJC 4078 ANDES-A 1059 Leptodactylus fuscus Sabanalarga, Casanare BSECO029-11 6 BOLD:ABA0407 KP149301 KP149105

AJC 4088 ANDES-A 1048 Leptodactylus fuscus Sabanalarga, Casanare BSECO039-11 6 BOLD:ABA0407 KP149352 KP149153

Not sequenced AJC 4104 ANDES-A 1116 Leptodactylus fuscus Sabanalarga, Casanare BSECO054-11 6 Not sequenced for KP149349 CO1 for CO1

AJC 3509 ANDES-A 1760 Leptodactylus insularum San Vicente, Santander BSAMS117-12 30 BOLD:AAJ1153 KP149348 KP149150

AJC 3517 ANDES-A 1172 Leptodactylus insularum San Vicente, Santander BSAMS121-12 30 BOLD:AAJ1153 KP149424 KP149219

AJC 3429 ANDES-A 1145 Leptodactylus knudseni Orocué, Casanare BSAMS109-12 10 BOLD:ACA5872 KP149492 KP149277

AJC 3451 ANDES-A 1764 Leptodactylus lineatus San Juan de Arama, Meta BSECO228-11 22 BOLD:ABA0568 KP149432 KP149226

AJC 3456 ANDES-A 1765 Leptodactylus lineatus San Juan de Arama, Meta BSECO233-11 22 BOLD:ABA0568 KP149329 KP149132 AJC 3462 ANDES-A 1221 Leptodactylus lineatus San Juan de Arama, Meta BSECO238-11 22 BOLD:ABA0568 KP149293 KP149098

AJC 3448 ANDES-A 1759 Leptodactylus mystaceus San Juan de Arama, Meta BSECO225-11 21 BOLD:ABA0408 KP149336 KP149139

AJC 4092 ANDES-A 1109 Leptodactylus mystaceus Sabanalarga, Casanare BSECO043-11 21 BOLD:ABA0408 KP149359 KP149222

AJC 3453 ANDES-A 1212 Phyllomedusa hypochondrialis San Juan de Arama, Meta BSECO230-11 23 BOLD:ABA0575 KP149427 KP149222

AJC 3459 ANDES-A 1766 Phyllomedusa hypochondrialis San Juan de Arama, Meta BSECO252-11 23 BOLD:ABA0575 KP149279 KP149084

AJC 4072 ANDES-A 1103 Phyllomedusa hypochondrialis Sabanalarga, Casanare BSECO023-11 23 BOLD:ABA0575 KP149489 KP149275

AJC 4103 ANDES-A 1105 Phyllomedusa hypochondrialis Sabanalarga, Casanare BSECO053-11 23 BOLD:ABA0575 KP149374 KP149172

AJC 2316 ANDES-A 1353 Physalaemus fischeri Orocué, Casanare BSAMS084-12 8 BOLD:ABA1319 KP149433 KP149227

AJC 3316 ANDES-A 1162 Physalaemus fischeri Orocué, Casanare BSAMS105-12 8 BOLD:ABA1319 Pending KP149134

AJC 3452 ANDES-A 1292 Physalaemus fischeri San Juan de Arama, Meta BSECO229-11 8 BOLD:ABA1319 KP149472 KP149261

AJC 3956 ANDES-A 1767 Physalaemus fischeri San Juan de Arama, Meta BSECO254-11 8 BOLD:ABA1319 KP149364 KP149163

AJC 4065 ANDES-A 1104 Physalaemus fischeri Sabanalarga, Casanare BSECO017-11 8 BOLD:ABA1319 KP149328 KP149131

AJC 4090 ANDES-A 1097 Physalaemus fischeri Sabanalarga, Casanare BSECO041-11 8 BOLD:ABA1319 KP149373 KP149171

AJC 3894 ANDES-A 1768 Pleurodema brachyops Sabana de Torres, Santander BSECO321-11 43 BOLD:AAE4476 KP149314 KP149118

LSB 385 ANDES-A 1254 Pristimantis carranguerorum Pajarito, Boyacá BSECO275-11 57 BOLD:ABU7033 KP149324 KP149128

AJC 3472 ANDES-A 1778 Pristimantis douglasi El Rasgón, Santander BSECO343-11 25 BOLD:ABV7786 KP149380 KP149178

AJC 3486 ANDES-A 1769 Pristimantis douglasi El Rasgón, Santander BSECO355-11 25 BOLD:ABV7786 KP149289 KP149094

AJC 3492 ANDES-A 1770 Pristimantis douglasi El Rasgón, Santander BSECO361-11 25 BOLD:ABV7786 KP149286 KP149091

AJC 3977 ANDES-A 1518 Pristimantis frater Miraflores, Boyacá BSECO131-11 47 BOLD:ABA0337 KP149367 KP149165

AJC 3982 ANDES-A 1520 Pristimantis frater San Juan de Arama, Meta BSECO136-11 47 BOLD:ABA0337 KP149368 KP149166

AJC 3984 ANDES-A 1522 Pristimantis frater Miraflores, Boyacá BSECO138-11 47 BOLD:ABA0337 KP149415 KP149210

AJC 3987 ANDES-A 1523 Pristimantis frater Miraflores, Boyacá BSECO141-11 47 BOLD:ABA0337 KP149363 KP149162

AJC 4011 ANDES-A 1499 Pristimantis frater Miraflores, Boyacá BSECO160-11 47 BOLD:ABA0337 KP149326 KP149129

AJC 4015 ANDES-A 1501 Pristimantis frater Miraflores, Boyacá BSECO164-11 47 BOLD:ABA0337 KP149461 KP149251

AJC 4018 ANDES-A 1503 Pristimantis frater Miraflores, Boyacá BSECO167-11 47 BOLD:ABA0337 KP149414 KP149209

AJC 3490 ANDES-A 1771 Pristimantis lutitus El Rasgón, Santander BSECO359-11 26 BOLD:ABV9411 KP149401 KP149196

Not sequenced AJC 3407 Pristimantis miyatai PuenteNacionalSAN BSECO118-11 18 Not sequenced for KP149388 NA CO1 for CO1

AJC 3475 ANDES-A 1772 Pristimantis miyatai El Rasgón, Santander BSECO345-11 18 BOLD:AAT9778 KP149490 KP149276

AJC 3477 ANDES-A 1773 Pristimantis miyatai El Rasgón, Santander BSECO346-11 18 BOLD:AAT9778 KP149395 KP149191

AJC 3478 ANDES-A 1779 Pristimantis miyatai El Rasgón, Santander BSECO347-11 18 BOLD:AAT9778 KP149440 KP149234

AJC 3479 ANDES-A 1774 Pristimantis miyatai El Rasgón, Santander BSECO348-11 18 BOLD:AAT9778 KP149396 KP149192

AJC 3498 ANDES-A 1775 Pristimantis miyatai El Rasgón, Santander BSECO367-11 18 BOLD:AAT9778 KP149437 KP149231

AJC 3499 ANDES-A 1776 Pristimantis miyatai El Rasgón, Santander BSECO368-11 18 BOLD:AAT9778 KP149300 KP149104

AJC 3856 ANDES-A 1777 Pristimantis miyatai Puente Nacional, Santander BSECO295-11 18 BOLD:ABV8595 KP149351 KP149152

AJC 3995 ANDES-A 1497 Pristimantis savagei Miraflores, Boyacá BSECO148-11 49 BOLD:AAV6745 KP149382 KP149180

AJC 4012 ANDES-A 1500 Pristimantis savagei Miraflores, Boyacá BSECO161-11 49 BOLD:AAV6745 KP149291 KP149096

LSB 375 ANDES-A 1260 Pristimantis savagei Pajarito, Boyacá BSECO265-11 49 BOLD:AAV6745 KP149299 KP149103

LSB 377 ANDES-A 1259 Pristimantis savagei Pajarito, Boyacá BSECO267-11 49 BOLD:AAV6745 KP149405 KP149200

LSB 381 ANDES-A 1256 Pristimantis savagei Pajarito, Boyacá BSECO271-11 49 BOLD:AAV6745 KP149425 KP149220

LSB 383 ANDES-A 1255 Pristimantis savagei Pajarito, Boyacá BSECO273-11 49 BOLD:AAV6745 KP149411 KP149206

AJC 3861 ANDES-A 1782 Pristimantis taeniatus Piedecuesta, Santander BSECO330-11 39 BOLD:AAT9777 KP149311 KP149115 AJC 3864 ANDES-A 1780 Pristimantis taeniatus Piedecuesta, Santander BSECO333-11 39 BOLD:AAT9777 KP149358 KP149159

AJC 3867 ANDES-A 1781 Pristimantis taeniatus Piedecuesta, Santander BSECO336-11 39 BOLD:AAT9777 KP149365 KP149164

AJC 2113 ANDES-A 1783 Pristimantis vilarsi San Juan de Arama, Meta BSECO219-11 5 BOLD:ABA0338 KP149391 KP149187

AJC 3450 ANDES-A 1286 Pristimantis vilarsi San Juan de Arama, Meta BSECO227-11 5 BOLD:ABA0338 KP149334 KP149138

AJC 3944 ANDES-A 1784 Pristimantis vilarsi San Juan de Arama, Meta BSECO207-11 5 BOLD:ABA0338 KP149278 KP149083

AJC 3945 ANDES-A 1785 Pristimantis vilarsi San Juan de Arama, Meta BSECO208-11 5 BOLD:ABA0338 KP149438 KP149232

AJC 3946 ANDES-A 1786 Pristimantis vilarsi San Juan de Arama, Meta BSECO209-11 5 BOLD:ABA0338 KP149384 KP149181

AJC 3957 ANDES-A 1787 Pristimantis vilarsi San Juan de Arama, Meta BSECO249-11 5 BOLD:ABA0338 KP149333 KP149137

AJC 2382 ANDES-A 1121 Pseudis paradoxa Orocué, Casanare BSAMS104-12 11 BOLD:ACA5628 KP149394 KP149190

AJC 3454 ANDES-A 1227 Pseudopaludicola llanera San Juan de Arama, Meta BSECO231-11 24 BOLD:ABA1351 KP149338 KP149141

AJC 3799 ANDES-A 1789 Pseudopaludicola llanera San Juan de Arama, Meta BSECO245-11 24 BOLD:ABA1350 KP149453 KP149244

AJC 4109 ANDES-A 1117 Pseudopaludicola llanera Sabanalarga, Casanare BSECO059-11 24 BOLD:ABA1350 KP149292 KP149097

AJC 4115 ANDES-A 1253 Pseudopaludicola llanera Sabanalarga, Casanare BSECO065-11 24 BOLD:ABA1350 KP149482 KP149270

AJC 4117 ANDES-A 1115 Pseudopaludicola llanera Sabanalarga, Casanare BSECO067-11 24 BOLD:ABA1350 KP149332 KP149136

AJC 4127 ANDES-A 1114 Pseudopaludicola llanera Sabanalarga, Casanare BSECO078-11 24 BOLD:ABA1350 KP149483 KP149271

AJC 4037 ANDES-A 1790 Pseudopaludicola pusilla San Vicente, Santander BSAMS183-12 50 BOLD:ACC1655 KP149344 KP149147

AJC 4039 ANDES-A 1791 Pseudopaludicola pusilla San Vicente, Santander BSAMS185-12 50 BOLD:ACC1655 KP149486 KP149273

AJC 3398 ANDES-A 1476 Rheobates palmatus Puente Nacional, Santander BSECO130-11 17 BOLD:AAY0187 KJ130701 KJ130665

AJC 3401 ANDES-A 1477 Rheobates palmatus Puente Nacional, Santander BSECO111-11 17 BOLD:AAY0187 KJ130725 KJ130691

AJC 3403 ANDES-A 1478 Rheobates palmatus Puente Nacional, Santander BSECO110-11 17 BOLD:AAY0187 KJ130724 KJ130690

AJC 3404 ANDES-A 1479 Rheobates palmatus Puente Nacional, Santander BSECO119-11 17 BOLD:AAY0187 KJ130711 KJ130676

AJC 3406 ANDES-A 1480 Rheobates palmatus Puente Nacional, Santander BSECO113-11 17 BOLD:AAY0187 KJ130721 KJ130687

AJC 3514 ANDES-A 603 Rheobates palmatus San Vicente, Santander BSAMS119-12 17 Not sequenced for KJ130706 Not sequenced CO1 for CO1

AJC 3526 ANDES-A 1481 Rheobates palmatus San Vicente, Santander BSAMS123-12 17 BOLD:ACC1597 KJ130702 KJ130666

AJC 3860 ANDES-A 1482 Rheobates palmatus Piedecuesta, Santander BSECO329-11 17 BOLD:ABV8088 KJ130699 KJ130663

AJC 3953 ANDES-A 1483 Rheobates palmatus Puente Nacional, Santander BSECO128-11 17 BOLD:AAY0187 KJ130700 KJ130664

AJC 3954 ANDES-A 1484 Rheobates palmatus Puente Nacional, Santander BSECO129-11 17 BOLD:AAY0187 KJ130705 Pending

AJC 3533 ANDES-A 1213 Rhinella humboldti San Vicente, Santander BSAMS126-12 34 BOLD:ACC1400 KP149421 KP149216

Not sequenced AJC 3968 ANDES-A 1038 Rhinella humboldti Sabanalarga, Casanare BSECO080-11 34 Not sequenced for KP149346 CO1 for CO1 Not sequenced AJC 4023 ANDES-A 1792 Rhinella humboldti San Juan de Arama, Meta BSECO257-11 34 Not sequenced for KP149473 CO1 for CO1 Not sequenced AJC 4024 ANDES-A 1793 Rhinella humboldti San Juan de Arama, Meta BSECO253-11 34 Not sequenced for KP149366 CO1 for CO1 Not sequenced AJC 4073 ANDES-A 1034 Rhinella humboldti Sabanalarga, Casanare BSECO024-11 34 Not sequenced for KP149488 CO1 for CO1

AJC 3991 ANDES-A 1465 Rhinella margaritifera Miraflores, Boyacá BSECO145-11 48 BOLD:ABU5671 KP149312 KP149116

AJC 3994 ANDES-A 1464 Rhinella margaritifera Miraflores, Boyacá BSECO147-11 48 BOLD:ABU5671 KP149339 KP149142

AJC 3996 ANDES-A 1463 Rhinella margaritifera Miraflores, Boyacá BSECO149-11 48 BOLD:ABU5671 KP149416 KP149211

LSB 368 ANDES-A 1817 Rhinella margaritifera Pajarito, Boyacá BSECO258-11 48 BOLD:ABU5671 KP149322 KP149126

LSB 380 ANDES-A 1261 Rhinella margaritifera Pajarito, Boyacá BSECO270-11 48 BOLD:ABU5671 KP149282 KP149087

AJC 3850 ANDES-A 1794 Rhinella marina Puente Nacional, Santander BSECO289-11 38 BOLD:AAB1186 KP149353 KP149154

AJC 3851 ANDES-A 1795 Rhinella marina Puente Nacional, Santander BSECO290-11 38 BOLD:AAB1186 KP149350 KP149151

AJC 3852 ANDES-A 1796 Rhinella marina Puente Nacional, Santander BSECO291-11 38 BOLD:AAB1186 KP149422 KP149217

AJC 3877 ANDES-A 1797 Rhinella marina Sabana de Torres, Santander BSECO306-11 38 BOLD:AAB1186 KP149357 KP149158 AJC 3895 ANDES-A 1798 Rhinella marina Sabana de Torres, Santander BSECO322-11 38 BOLD:AAB1186 KP149331 KP149135

Not sequenced AJC 3943 ANDES-A 1799 Rhinella marina San Juan de Arama, Meta BSECO206-11 38 Not sequenced for KP149485 CO1 for CO1 Not sequenced AJC 3997 ANDES-A 1800 Rhinella marina Miraflores, Boyacá BSECO151-11 38 Not sequenced for KP149383 CO1 for CO1 Not sequenced AJC 4002 ANDES-A 1801 Rhinella marina Miraflores, Boyacá BSECO155-11 38 Not sequenced for KP149360 CO1 for CO1 Not sequenced AJC 4020 ANDES-A 1802 Rhinella marina Miraflores, Boyacá BSECO169-11 38 Not sequenced for KP149450 CO1 for CO1 Not sequenced AJC 4021 ANDES-A 1803 Rhinella marina Miraflores, Boyacá BSECO170-11 38 Not sequenced for KP149297 CO1 for CO1 Not sequenced AJC 4029 ANDES-A 1804 Rhinella marina San Juan de Arama, Meta BSECO256-11 38 Not sequenced for KP149430 CO1 for CO1 Not sequenced AJC 4077 ANDES-A 1805 Rhinella marina Sabanalarga, Casanare BSECO028-11 38 Not sequenced for KP149335 CO1 for CO1 Not sequenced AJC 4125 ANDES-A 1806 Rhinella marina Sabanalarga, Casanare BSECO075-11 38 Not sequenced for KP149325 CO1 for CO1

LSB 376 Rulyrana flavopunctata Pajarito, Boyacá BSECO266-11 55 BOLD:ABU6070 KP149462 KP149252 NA

AJC 1747 ANDES-A 1808 Scinax cf. kennedyi San Juan de Arama, Meta BSECO180-11 2 BOLD:ABA0510 KP149308 KP149112

Not sequenced AJC 4051 ANDES-A 1062 Scinax cf. kennedyi Sabanalarga, Casanare BSECO012-11 2 Not sequenced for KP149321 CO1 for CO1

AJC 4061 ANDES-A 1058 Scinax cf. kennedyi Sabanalarga, Casanare BSECO009-11 2 BOLD:ABA0510 KP149429 KP149224

AJC 4074 ANDES-A 1060 Scinax cf. kennedyi Sabanalarga, Casanare BSECO025-11 2 BOLD:ABA0510 KP149463 KP149253

AJC 1741 ANDES-A 1807 Scinax cf. kennedyi San Juan de Arama, Meta BSECO174-11 2 BOLD:ABA0510 KP149408 KP149203

AJC 3422 ANDES-A 599 Scinax rostratus San Vicente, Santander BSAMS108-12 19 BOLD:ACC1535 KP149284 KP149089

AJC 3506 ANDES-A 1809 Scinax rostratus San Vicente, Santander BSAMS115-12 19 BOLD:ACC1535 KP149435 KP149229

Not sequenced AJC 2324 ANDES-A 1165 Scinax ruber Orocué, Casanare BSAMS088-12 9 Not sequenced for KP149491 CO1 for CO1

AJC 3378 ANDES-A 1504 Scinax ruber Sabanalarga, Casanare BSECO095-11 13 BOLD:ABA0385 KP149452 KP149243

AJC 3446 ANDES-A 1290 Scinax ruber San Juan de Arama, Meta BSECO223-11 13 BOLD:ABA0385 KP149466 KP149255

AJC 3532 ANDES-A 1210 Scinax ruber San Vicente, Santander BSAMS125-12 33 BOLD:ACC1578 KP149347 KP149149

AJC 3534 ANDES-A 1449 Scinax ruber San Vicente, Santander BSAMS127-12 33 BOLD:ACC1578 KP149295 KP149100

AJC 3884 ANDES-A 1810 Scinax ruber Sabana de Torres, Santander BSECO312-11 9 BOLD:ABV8597 KP149330 KP149133

AJC 3936 ANDES-A 1811 Scinax ruber San Juan de Arama, Meta BSECO199-11 13 BOLD:ABA0385 KP149294 KP149099

AJC 3940 ANDES-A 1812 Scinax ruber San Juan de Arama, Meta BSECO203-11 13 BOLD:ABA0385 KP149320 KP149124

AJC 4053 ANDES-A 1040 Scinax ruber Sabanalarga, Casanare BSECO014-11 13 BOLD:ABA0385 KP149379 KP149177

AJC 4054 ANDES-A 1046 Scinax ruber Sabanalarga, Casanare BSECO015-11 13 BOLD:ABA0385 KP149442 KP149236

AJC 1743 ANDES-A 1813 Scinax wandae San Juan de Arama, Meta BSECO176-11 4 BOLD:ABA0452 KP149376 KP149174

AJC 3461 ANDES-A 1287 Scinax wandae San Juan de Arama, Meta BSECO237-11 4 BOLD:ABA0452 KP149431 KP149225

AJC 3464 ANDES-A 1814 Scinax wandae San Juan de Arama, Meta BSECO240-11 4 BOLD:ABA0452 KP149460 KP149250

AJC 3942 ANDES-A 1815 Scinax wandae San Juan de Arama, Meta BSECO205-11 4 BOLD:ABA0452 KP149372 KP149170

AJC 3974 ANDES-A 1072 Scinax wandae Sabanalarga, Casanare BSECO086-11 46 BOLD:ABA1339 KP149323 KP149127

AJC 4105 ANDES-A 1077 Scinax wandae Sabanalarga, Casanare BSECO056-11 46 BOLD:ABA1339 KP149381 KP149179

AJC 4120 ANDES-A 1234 Scinax wandae Sabanalarga, Casanare BSECO070-11 46 BOLD:ABA1339 KP149319 KP149123

AJC 3525 ANDES-A 1816 Smilisca phaeota San Vicente, Santander BSAMS122-12 32 BOLD:AAB3398 KP149385 KP149182

AJC 4063 ANDES-A 1035 Trachycephalus thyphonius Sabanalarga, Casanare BSECO011-11 51 BOLD:ABA1587 KP149406 KP149201