# Molecular and acoustic evidence for large-scale underestimation of frog species diversity on New Guinea

Flavien Ferreira, Paul Oliver, Fred Kraus, Rainer Günther, Stephen Richards, Burhan Tjaturadi, Evy Arida, Amir Hamidy, Awal Riyanto, Wahyu Trilaksono, et al.

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Flavien Ferreira, Paul Oliver, Fred Kraus, Rainer Günther, Stephen Richards, et al. Molecular and acoustic evidence for large-scale underestimation of frog species diversity on New Guinea. Frontiers of Biogeography, 2025, 18, pp.e137988. 10.21425/fob.18.137988. hal-05099207

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# Molecular and acoustic evidence for large-scale underestimation of frog species diversity on New Guinea

Flavien Ferreira<fnref n="1" />,®, Paul Oliver<fnref n="2" />,<fnref n="3" />,®, Fred Kraus<fnref n="4" />,®, Rainer Günther<fnref n="5" />,®, Stephen Richards<fnref n="6" />, Burhan Tjaturadi<fnref n="7" />, Evy Arida<fnref n="8" />, Amir Hamidy<fnref n="9" />, Awal Riyanto<fnref n="9" />, Wahyu Trilaksono<fnref n="9" />, Christophe Thébaud<fnref n="1" />,®, Antoine Fouquet<fnref n="1" />,®

Corresponding author: Flavien Ferreira (flavienferreira1@gmail.com)

**Editors** Christopher Burridge, Robert Whittaker

Received 27 September 2024 ♦ Accepted 31 January 2025 ♦

Published 8 May 2025

## Abstract

Species are fundamental units in biology; however, information on species diversity and distribution remain scarce for most taxonomic groups, especially in tropical rainforests. Such knowledge gaps are particularly acute in amphibians, the most threatened group of vertebrates, in which new species continue to be described at a high rate. Herein, using molecular-based approaches, we provide estimates for species diversity of frogs (Anura) in New Guinea and nearby islands, one of the biologically most diverse regions of the world. We first characterised taxonomic and geographic sampling for all available mitochondrial DNA sequences from native frog species. This led us to identify important molecular sampling gaps in the western half of New Guinea that we partially filled by adding 534 new sequences (16S rRNA). Large territories remain uncharted, particularly in the westernmost part of the central cordillera of New Guinea. Using our 16S rRNA dataset, we then delimited Molecular Operational Taxonomic Units (MOTUs), a subset of which was bioacoustically analysed. From a total of 369 delimited MOTUs, we found that 190 could not be assigned to any taxon. Amongst these, 123 are represented by specimens collected in the western half of New Guinea and 19 were supported as distinct by

bioacoustics, confirming that this portion of the island is home to many unrecognised species. Based on the estimated level of undescribed diversity in taxa and areas for which data are available, we extrapolate that New Guinea and neighbouring islands could host 800–1,200 frog species, with only 560 species described to date.

## Highlights

* We assembled the most comprehensive molecular dataset to date (16S rRNA) for frogs from New Guinea and neighbouring islands.

* We delimited 190 candidate species, of which 19 are supported by available bioacoustic data.

* We estimated the actual number of frog species on New Guinea and neighbouring islands to be between 800 and 1,200.

* Parts of New Guinea exhibit species-diversity levels comparable to similarly sized regions in Amazonia and Madagascar.

* Most unrecognised frog taxa in the region are likely confined to restricted geographical areas and, thus, likely sensitive to both land use and climate change.

<footnote n="1">1 Centre de Recherche sur la Biodiversité et l'Environnement, UMR 5300, CNRS, IRD, Université Paul Sabatier, Bâtiment 4R1, 118 Route de Narbonne, 31062 cedex 9 Toulouse, France</footnote>

<footnote n="2">2 Centre for Planetary Health and Food Security, Griffith University, 170 Kessels Road, Brisbane, Queensland, 4111, Australia</footnote>

<footnote n="3">3 Biodiversity and Geosciences, Queensland Museum, South Brisbane, Queensland, 4101, Australia</footnote>

<footnote n="4">4 Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA</footnote>

<footnote n="5">5 Museum für Naturkunde, Leibniz-Institut für Evolutions- und Biodiversitätsforschung, Invalidenstraße 43, 10115 Berlin, Germany</footnote>

<footnote n="6">6 Herpetology Department, South Australian Museum, North Terrace, Adelaide, South Australia 5000, Australia</footnote>

<footnote n="7">7 Center of Environment Studies, Sanata Dharma University, Yogyakarta, Indonesia</footnote>

<footnote n="8">8 Research Center for Applied Zoology, National Research and Innovation Agency (BRIN), Soekarno Science and Technology Park Jalan Raya Bogor-Jakarta km 46, Cibinong 16911 Indonesia</footnote>

<footnote n="9">9 Laboratory of Herpetology, Museum Zoologicum Bogoriense, Research Center for Biosystematics and Evolution, National Research and Innovation Agency (BRIN), Gd. Widyasatwaloka, Jl. Raya Jakarta Bogor km 46, Cibinong, West Java, Indonesia</footnote>
**Keywords**

Amphibians, 16S, integrative approach, IUCN, Linnean
shortfall, Microhylidae, New Guinea, taxonomy

**Introduction**

In the face of accelerating rates of global biodiversity loss, documenting and describing species remains a crucial challenge (Scheffers et al. 2012; Ceballos et al. 2017, 2020), especially in tropical regions where incomplete biodiversity knowledge and rapid biodiversity loss are most marked (Myers et al. 2000; Wilson et al. 2016; Guedes et al. 2020; Robertson et al. 2023). Knowledge gaps in species richness and distribution ("Linnean" and "Wallacean" shortfalls, respectively; Brown and Lomolino (1998); Lomolino (2004)) represent major obstacles to research and conservation (Nori et al. 2022; Baranzelli et al. 2023; Serrano et al. 2023) and their effect combined with the lack of resources allocated to taxonomy is referred to as the "taxonomic impediment" (Engel et al. 2021). This impediment is of particular concern in amphibians (Giam et al. 2012; Moura and Jetz 2021; Carné and Vieites 2024) because many new species are being described every year, especially in the Tropics, and yet they represent the most threatened group of vertebrates worldwide (Cordier et al. 2021; Luedtke et al. 2023).

DNA-based species-delimitation methods have been proposed as one strategy to mitigate the taxonomic impediment and they have become widely used for that purpose (Monaghan et al. 2009; Puillandre et al. 2012, 2021; Zhang et al. 2013; Yang 2015). Although these methods are fraught with potential pitfalls (Goldstein and DeSalle 2011; Sukumaran and Knowles 2017), they still provide an efficient way of flagging populations that may represent species unrecognised by current taxonomy (candidate species) and that should be the focus of further taxonomic investigation. Studies following this approach have recently estimated that some focal clades of tropical amphibians could be 2–6 times more diverse than recognised by current taxonomy (Fouquet et al. 2021, 2022; Ferreira et al. 2023; Carné and Vieites 2024).

The region comprising New Guinea and its neighbouring islands is both megadiverse and one of the least biologically studied of the world (Di Marco et al. 2017; Cámara-Leret et al. 2020; Oliver et al. 2022; Slavenko et al. 2023). It spans from the islands immediately west of New Guinea, the world's largest and highest tropical island, to northern Melanesia and represents a distinct zoogeographical region for amphibians (Holt et al. 2013). The resident amphibian fauna is currently the least threatened (Oliver et al. 2022) and species-richest globally for an insular region, with 560 recognised species, all of which are frogs (Frost 2024). Based on candidate species known to taxonomists working in the region, Oliver et al. (2022) suggested that frog diversity likely exceeds 700 species, a figure similar to current estimates

in Madagascar (Carné and Vieites 2024). However, several factors suggest this figure may be conservative: 1) many large or isolated areas remain unsurveyed on New Guinea; 2) taxonomic effort is very limited relative to the geographic area of the region (since 2000, most species have been described by the same six authors; Rodrigues et al. (2010); Frost (2024)); and 3) efforts to investigate frog diversity in the region integrating molecular data only started a decade ago (Oliver et al. 2013; Oliver et al. 2017; Arida et al. 2021; Hill et al. 2022; Ferreira et al. 2023).

Gaps in the knowledge of frog diversity on New Guinea are thought to be particularly substantial in the western half of the island, partly because of the paucity of field surveys in this area since the mid-20th century (Frodin 2007). Known frog species richness as well as projected number of extant species are currently far lower in the western half than in the eastern half of New Guinea (215 vs. 416 resident species, respectively) (IUCN 2024). In a first attempt to fill these knowledge gaps, Arida et al. (2021) conducted a DNA-based inventory of aquatic and terrestrial vertebrate communities in the westernmost peninsula of New Guinea, a region known as the Vogelkop Peninsula or Bird's Head. These analyses highlighted extensive frog lineage diversity, but no attempt was made to include taxonomically significant characters, such as morphology or calls nor to assess the extent to which lineages matched species recognised by taxonomy. Hence, the extent of unrecognised frog diversity in western New Guinea remains virtually untested.

Here, to better estimate frog species diversity on New Guinea and neighbouring islands, we first aimed to characterise the taxonomic and geographic sampling bias of existing molecular data (mitochondrial DNA from public databases) for frogs from the region. We complemented these data with additional sequences obtained from specimens collected recently in the western half of New Guinea. We re-evaluated species diversity estimates by delimiting Molecular Operational Taxonomic Units (MOTUs) using the 16S rRNA locus that has been advocated as useful to delimit amphibian candidate species (Vences et al. 2005; Fouquet et al. 2007). We then validated some of these MOTUs using bioacoustic data as additional lines of evidence (i.e. integrative taxonomy approach; Dayrat (2005); Padial et al. (2010)) because advertisement vocalisations are sensitive inherent species-isolating mechanisms and, therefore, highly relevant in delimiting frog species (Köhler et al. 2017). Finally, we derived estimates of species diversity that may remain to be described and provided a perspective on the magnitude of the taxonomic impediment for amphibians in the region.

**Methods**

**Sampling**

We focused on the region spanning from the islands in the northern and central Moluccas, across New Guinea to the Bismarck and Solomon Archipelago and refer to it as "the New Guinea region". We downloaded GenBank-deposited
mitochondrial DNA (mtDNA) sequences of frog species native to this region and compared the taxonomic and geographic distribution of the most commonly sequenced loci (COI, cytb, 12S and two non-overlapping regions of 16S rRNA, here referred as "16Sa" and "16Sb"). In addition, we downloaded the data of Arida et al. (2021) from the Barcoding of Life Database (BOLD) in order to increase geographic sampling. A summary of the genetic dataset is presented in Table 1 and the full list of sequences is available in the Suppl. material 2. Sequences were retrieved from GenBank using the filter tool, specifying genera occurring in our study region (based on the distributional data of the International Union for Conservation of Nature, IUCN, https://www.iucnredlist.org) and targeted loci. These data were further filtered to remove species that do not occur in the study region. Coordinates for sampling localities were directly retrieved from publications by contacting the authors or were georeferenced with a ~ 10 km precision using Google Earth and Mapcarta (https://mapcarta.com/) when only locality names were available.

## Species delimitation

Given the unevenness of taxonomic and geographic sampling across loci, we delimited MOTUs using the 16Sb locus only. To expand our sampling, we produced 534 new 16Sb sequences (DNA extraction and sequencing protocol in Suppl. material 1: appendix S1) from specimens collected in western New Guinea during field work undertaken over the last 20 years, including 160 (out of the 167) specimens that were included in Arida et al. (2021). The sequences were aligned using MAFFT (version 7) (Katoh et al. 2019) following the E-INS-i method. MOTUs were delimited using

three complementary single-locus methods: Automatic Barcode Gap Discovery (ABGD; Puillandre et al. (2012)); 2) single-rate Poisson Tree Processes (PTP; Zhang et al. (2013)); and 3) the Generalised Mixed Yule Coalescent approach (GMYC; Pons et al. (2006); Monaghan et al. (2009)); Briefly, 1) ABGD infers an intra- and interspecific threshold based on genetic distances, 2) PTP infers species boundaries from the number of substitutions on the branches of a Maximum-Likelihood phylogenetic tree and 3) GMYC uses an ultrametric tree to infer a temporal threshold delimiting species (each partitioning method is detailed in Suppl. material 1: appendix S2). For all methods, four species were used as outgroups: *Heleophryne purcelli*, *Leiopelma hochstetteri*, *Pipa pipa* and *Rhinophrynus dorsalis*. The final delimitation was based on a majority-rule consensus across the three partitions obtained (Dellicour and Flot 2018), i.e. defining as an MOTU any lineage supported by at least two of the three methods (Fig. 1; see the Suppl. material 2 for all delimitations' results). We followed the nomenclature of Frost (2024) and assigned taxon names to MOTUs represented by type specimens or to those geographically closest to the type locality in case of conflicting initial identifications.

## Integration of bioacoustic data

The robustness of the delimitations was further assessed for 38 MOTUs (i.e. 19 pairs) by searching for concordant patterns of acoustic differentiation (e.g. Fig. 1) using both published and newly acquired audio recordings (see Suppl. material 1: appendix S3 for data availability). These focal species complexes provided an overall evaluation of the robustness of the delimitation otherwise based on mtDNA only.

<figure><img src="image_3.png" /><figcaption>**Figure 1.** Species delimitation combining molecular and acoustic data, exemplified in an *Oreophryne* species complex. In this example, the species delimitation between *O. roedeli* and *O. cf. roedeli* 2 is confirmed by their difference in note repetition rate and mean number of pulses per note. The subtree was extracted from the ultrametric tree used for the GMYC analysis. Mean genetic p-distance (%) between lineages is indicated at the nodes. Dots above tree branches indicate posterior probabilities > 0.95. All detailed comparisons and specimen vouchers are presented in Suppl. material 1: appendix S3. Call data for *O. cf. roedeli* 1. and *O. cf. roedeli* 3 were unavailable.</figcaption></figure>
We investigated call variation following a note-centred approach (Köhler et al. 2017) with particular focus on: 1) note duration; 2) inter-note duration; 3) note repetition rate per second; 4) number of notes per call; 5) number of pulses per note; 6) amplitude modulation (i.e. increasing or decreasing amplitude within a note); 7) dominant frequency; and 8) note frequency modulation (absence, upward or downward). We conservatively considered slight variations in dominant frequency (7), note and inter-note duration (1 and 2) between allopatric MOTUs to be non-diagnostic, due to potential variation inherent to specimens' body size and recording environment temperature (Gerhardt and Huber 2002). On the other hand, non-overlapping numbers of notes per call (4), note amplitude modulation (6) and note frequency modulation (8) were considered as supporting the delimitations regardless of whether the MOTUs occurred in sympatry or allopatry. All comparisons are summarised in Suppl. material 1: table S1 and individually presented in Suppl. material 1: figs S1–S6.

## Spatial inferences

We undertook additional analyses in order to better characterise potential geographic bias in the distribution of: 1) genetic sampling and 2) MOTUs across the fifteen subregions (Fig. 2) that are representative of the geographic and environmental diversity within our study region (justifications in Suppl. material 1: appendix S4). MOTU richness and endemism per subregion were compared to estimates of species richness derived from IUCN species-distributional data (IUCN, https://www.iucnredlist.org). These distributional data are based on minimum-convex polygons defined for each MOTU/species (i.e. linking all outermost occurrence points), regardless of the potential non-suitability of habitat within polygons.

Richness was defined as the number of polygons intersecting each subregion or as simple presence in the case of MOTUs with fewer than two occurrences. Endemism was defined as the proportion of MOTUs/species uniquely found in each subregion. All maps were generated on QGIS v.3.20 (QGIS Development Team 2020).

## Results

### Taxonomic and spatial distribution

The complete dataset of mitochondrial data comprised 2301 DNA sequences (1767 from online repositories and 534 newly generated) (Table 1, Fig. 2, Suppl. material 1: fig. S7), representing 1537 specimens (out of which 1380 were georeferenced) distributed across 226 unique sampling localities (i.e. within a 10 km radius) and including six families: Microhylidae, Hylidae, Ceratobatrachidae, Ranidae, Myobatrachidae and Dicroglossidae. When considering all families and online data only, more sequences were available for the 12S locus, but we chose to focus on the 16Sb locus for the rest of our study because it had the most comprehensive taxonomic and geographic sampling (Table 1; Suppl. material 1: fig. S7A). Combining GenBank and newly acquired sequences, 16Sb is the best-sampled locus for all families (35% of all sequences), followed by 12S (21%), 16Sa (20%) and cytb (16%). Microhylidae was the most-represented family with 1523 sequences, followed by Hylidae (353) and Ceratobatrachidae (298). It is noteworthy that more than half of the Microhylidae sequences corresponded to three genera only (*Mantophryne*, *Hylophorbus* and *Choerophryne*) that have been the focus of specific studies using 12S, 16S (a and b) and cytb (Oliver et al. 2013; Oliver et al. 2017; Ferreira et al. 2023).

<figure><img src="image_4.png" /><figcaption>**Figure 2.** Distribution of sampled localities for all compiled georeferenced mtDNA sequences (12S, 16Sa, 16Sb, COI, cytb) of amphibians across the focal area, with the number of sequences per subregion indicated by grey shading. The vertical white-dashed line represents the international border between the western half (Indonesia) and the eastern half (Papua New Guinea) of the island of New Guinea. Abbreviations: CRW, western central range; CRC, central central range; CRE, eastern central range.</figcaption></figure>
<table><caption>**Table 1.** Details of compiled sequences for all Melanesian amphibians, by family and genus, on commonly sequenced mitochondrial loci. The column "taxonomic completion" indicates the proportion of recognised species (as per Frost (2024)) represented by molecular data. Details on which species are represented by molecular data are given in the Suppl. material 1. Abbreviation: GB, GenBank.</caption><thead><tr><th rowspan="2">Taxa</th><th colspan="2">12S</th><th colspan="2">16Sα</th><th colspan="2">16Sb</th><th colspan="2">cytb</th><th colspan="2">COI</th><th rowspan="2">Total sequences</th><th rowspan="2">Taxonomic completion (%)</th></tr><tr><th>GB</th><th>GB</th><th>GB</th><th>This study</th><th>Total</th><th>GB</th><th>GB</th><th>Arida et al. (2021)</th><th></th><th></th></tr></thead><tbody><tr><td><strong>Microhylidae</strong></td><td>346</td><td>365</td><td>126</td><td>218</td><td>344</td><td>366</td><td>4</td><td>98</td><td></td><td></td><td>1523</td><td>49</td></tr><tr><td>Mantophryne</td><td>119</td><td>120</td><td>2</td><td></td><td>2</td><td>121</td><td>1</td><td></td><td></td><td></td><td>363</td><td>100</td></tr><tr><td>Hylophorbus</td><td>81</td><td>84</td><td>70</td><td>1</td><td>71</td><td>52</td><td>1</td><td>18</td><td></td><td></td><td>307</td><td>94</td></tr><tr><td>Choerophryne</td><td>91</td><td>95</td><td>6</td><td>13</td><td>19</td><td>20</td><td></td><td></td><td></td><td></td><td>225</td><td>67</td></tr><tr><td>Oreophryne</td><td></td><td></td><td>9</td><td>48</td><td>57</td><td>46</td><td></td><td>15</td><td></td><td></td><td>118</td><td>45</td></tr><tr><td>Xenorhina</td><td>19</td><td>22</td><td>8</td><td>35</td><td>43</td><td>10</td><td>1</td><td>9</td><td></td><td></td><td>104</td><td>29</td></tr><tr><td>Asterophrys</td><td>17</td><td>18</td><td>3</td><td>34</td><td>37</td><td>7</td><td></td><td>15</td><td></td><td></td><td>94</td><td>87</td></tr><tr><td>Cophixalus</td><td></td><td></td><td>6</td><td>28</td><td>34</td><td>35</td><td></td><td>13</td><td></td><td></td><td>82</td><td>39</td></tr><tr><td>Callulops</td><td>15</td><td>16</td><td>4</td><td>19</td><td>23</td><td>17</td><td></td><td>10</td><td></td><td></td><td>81</td><td>39</td></tr><tr><td>Austrochaperina</td><td></td><td></td><td></td><td>17</td><td>17</td><td>12</td><td></td><td>11</td><td></td><td></td><td>40</td><td>28</td></tr><tr><td>Sphenophryne</td><td></td><td>1</td><td>7</td><td>9</td><td>16</td><td>13</td><td></td><td>7</td><td></td><td></td><td>37</td><td>53</td></tr><tr><td>Copiula</td><td></td><td></td><td>7</td><td>14</td><td>21</td><td>11</td><td></td><td></td><td></td><td></td><td>32</td><td>53</td></tr><tr><td>Barygenys</td><td>1</td><td>5</td><td>3</td><td></td><td>3</td><td>7</td><td>1</td><td></td><td></td><td></td><td>17</td><td>78</td></tr><tr><td>Paedophryne</td><td>3</td><td>4</td><td></td><td></td><td></td><td>8</td><td></td><td></td><td></td><td></td><td>15</td><td>86</td></tr><tr><td>Aphantophryne</td><td></td><td></td><td>1</td><td></td><td>1</td><td>7</td><td></td><td></td><td></td><td></td><td>8</td><td>20</td></tr><tr><td><strong>Hylidae</strong></td><td>87</td><td>19</td><td>79</td><td>147</td><td>226</td><td>4</td><td>3</td><td>15</td><td></td><td></td><td>354</td><td>42</td></tr><tr><td>Litoria</td><td>58</td><td>7</td><td>37</td><td>71</td><td>110</td><td></td><td>3</td><td>2</td><td></td><td></td><td>180</td><td>40</td></tr><tr><td>Nyctimystes</td><td>18</td><td>12</td><td>18</td><td>42</td><td>60</td><td>4</td><td></td><td>7</td><td></td><td></td><td>101</td><td>40</td></tr><tr><td>Ranoidea</td><td>11</td><td></td><td>24</td><td>34</td><td>58</td><td></td><td></td><td>6</td><td></td><td></td><td>75</td><td>45</td></tr><tr><td><strong>Ceratobatrachidae</strong></td><td>44</td><td>54</td><td>33</td><td>122</td><td>155</td><td>5</td><td>1</td><td>39</td><td></td><td></td><td>298</td><td>69</td></tr><tr><td>Cornufer</td><td>44</td><td>54</td><td>33</td><td>122</td><td>155</td><td>5</td><td>1</td><td>39</td><td></td><td></td><td>298</td><td>69</td></tr><tr><td><strong>Ranidae</strong></td><td>7</td><td>28</td><td>27</td><td>39</td><td>66</td><td></td><td></td><td>14</td><td></td><td></td><td>115</td><td>86</td></tr><tr><td>Papurana</td><td>7</td><td>28</td><td>27</td><td>39</td><td>66</td><td></td><td></td><td>14</td><td></td><td></td><td>115</td><td>86</td></tr><tr><td><strong>Myobatrachidae</strong></td><td></td><td></td><td>2</td><td>4</td><td>6</td><td></td><td></td><td>1</td><td></td><td></td><td>7</td><td>67</td></tr><tr><td>Platylectrum</td><td></td><td></td><td>2</td><td>4</td><td>6</td><td></td><td></td><td>1</td><td></td><td></td><td>7</td><td>67</td></tr><tr><td><strong>Dicroglossidae</strong></td><td></td><td></td><td></td><td>4</td><td>4</td><td></td><td></td><td></td><td></td><td></td><td>4</td><td>100</td></tr><tr><td>Limnonectes</td><td></td><td></td><td></td><td>4</td><td>4</td><td></td><td></td><td></td><td></td><td></td><td>4</td><td>100</td></tr><tr><td><strong>Total</strong></td><td>484</td><td>466</td><td>267</td><td>534</td><td>801</td><td>375</td><td>8</td><td>167</td><td></td><td></td><td>2301</td><td>51</td></tr></tbody></table>

The majority of the georeferenced sequences are from the eastern half of New Guinea (1177 sequences; Fig. 2), mainly from the Papuan Peninsula (367 sequences, 32 unique localities) and the eastern central range (CRE) (274 sequences, 37 unique localities). Conversely, in the western half of New Guinea and its surrounding islands (963 sequences), most sequences were from specimens collected in the Bird's Neck and Bird's Head subregions (393 and 312 sequences from 27 and 11 unique localities, respectively). Across subregions, microhylids are best represented in the dataset (175, 342, 259 and 145 sequences in the eastern central range, Papuan Peninsula, Bird's Neck and Bird's Head, respectively).

Most recognised species of Ceratobatrachidae and Ranidae in our study region are represented by molecular data (69% and 86% of 58 and 15 recognised species, respectively). By contrast, molecular data are available for only half of the recognised species in Microhylidae and Hylidae (Table 1). With the exception of *Aphantophryne* and *Callulops*, species-poor genera (*sensu* Frost (2024)) tend to have the highest taxonomic coverage: *Mantophryne*, *Paedophryne*, *Barygenys* and *Hylophorbus* (78–100%).

## Species delimitation

The number of "species" delimited by the different methods ranged from 263 (PTP) to nearly 400 (386 (ABGD), 371 (GMYC)), with a majority-rule consensus of 372 MOTUs in our focal area. This count was reduced to 369 with our integrative approach, comprising 179 species recognised by current taxonomy and 190 MOTUs that could not be assigned to any taxon (i.e., unidentified or undescribed candidate species). Microhylidae are dominant in our dataset in every measure: total number of sequences (Table 1), all 16Sb sequences (Fig. 3A), MOTU counts and proportion of candidate species (Fig. 3B).

Acoustic data were available for 38 MOTUs (Suppl. material 1: appendix S3, table S1), amongst which 30 were supported as distinct species, with 11 recognised and 19 (63%) unrecognised species. The mean p-distance between the MOTUs confirmed as valid species by acoustic data is 4.0% (1.0–13.0%) for Microhylidae and 2.7% (2.0–3.0%) for Ceratobatrachidae; limited bioacoustic data prevented comparisons between related MOTUs in other families.
Adding the 560 recognised species known to be res-
ident in our study region to our 190 candidate species
suggests that a minimum of 750 species inhabit the re-
gion. Most candidate species (123) originate from the
western half of New Guinea where 215 species are cur-
rently recognised. Based on the ratio between the candi-
date species (190) and the recognised species included
in our dataset (179; thus ratio = 1.1) (Fig. 3B), we can
extrapolate the total number of species remaining to be
described from the number of recognised species (560)
if we assume: 1) that all candidate species are confirmed;
2) that we have evenly sampled total taxonomic diversity;
and 3) that taxonomic gaps are evenly distributed across
the region. Extrapolated to all groups, there would be a
total of 1176 frog species across New Guinea and its
neighbouring islands (Fig. 3C), of which 616 would be

unrecognised at present (560*1.1 = 616). However, can-
didate species richness is unbalanced across families,
being mostly driven by Microhylidae, with 1.5 times more
candidate species than recognised species (97 vs. 68).
The same extrapolation in this family alone would lead to
501 unrecognised species in addition to the current 334
recognised species.

The Bird's Head and Bird's Neck subregions contain the highest number of MOTUs (75 and 61 respectively; Fig. 3D), MOTUs assigned to recognised species (24 and 34, respectively), 16Sb sequences (223 and 175, Suppl. material 1: fig. S7) and are occupied by species of all families, except Dicroglossidae. By contrast, the western central range is represented by no 16Sb sequences at all, but one 12S, two 16Sa and three cytb sequences (Suppl. material 1: fig. S7A).

<figure><img src="image_5.png" /><figcaption>**Figure 3.** A) Ultrametric tree used for the GMYC analysis, based on all 16Sb sequences. Numbers in parentheses indicate the number of sequences. The detailed tree is presented in Suppl. material 1: fig. S8; B) Final number of recognised species and candidate species amongst MOTUs across families; C) Global number of recognised species, candidate species from this study and extrapolation of unrecognised species per family. The extrapolation is based on the proportion of putative candidate species in B (details in Results: Species delimitation); D) Total number of MOTUs per subregion (grey shading). Pie charts indicate the proportion of each family in the final MOTUs delimitation (colours presented in A), for the eight richest subregions. Abbreviations: Mic, Microhylidae; Hyl, Hylidae; Cer, Ceratobatrachidae; Ran, Ranidae; Myo, Myobatrachidae; Dic, Dicroglossidae.</figcaption></figure>
## Species diversity and endemism

Out of the 369 delimited MOTUs, 294 are represented by one or two occurrence points and 75 by three or more occurrence points. The evaluation of our taxonomic sampling across subregions, based on the richness of MOTUs assigned to recognised species vs. richness derived from IUCN data (Fig. 4A), revealed that the Papuan Peninsula and eastern central range were the most deficient, with 151

and 126 recognised species missing in the MOTU dataset, respectively (Fig. 4B). This deficit was less pronounced in the Solomon Islands, Seram and Halmahera (two, four and eight recognised species missing) and the Bird's Neck and Bird's Head (21 and 25 recognised species missing). When comparing species richness between IUCN data and all MOTUs regardless of their correspondence to recognised or candidate species, the molecular dataset missed species the most in eastern New Guinea (Fig. 4C). In contrast,

<figure><img src="image_6.png" /><figcaption>**Figure 4.** A) Regional species richness based on IUCN data; B) Number of missing recognised species in the MOTU dataset based on the difference between the count of MOTUs assigned to recognised species and IUCN data presented in A; C) Difference in species richness, between the total MOTUs dataset and IUCN data. Negative values indicate a species-deficit in the DNA-based dataset, as compared to IUCN data.</figcaption></figure>
the westernmost peninsula of New Guinea and the Island of Halmahera displayed levels of species diversity higher than those published by IUCN, with the Bird's Head in particular having an excess of 18 MOTUs over the number of taxonomically known species (Fig. 4C).

When looking at the degree of endemism per subregion, distributional data for both MOTUs and IUCN range maps suggested higher levels of endemism in archipelagos (e.g. Bismarck and Solomon Isl.) and in the eastern half of New Guinea (Suppl. material 1: fig. S9). However, estimates of endemism rates for MOTUs were much more homogeneous across subregions and higher on average (85%) than those obtained for species in the IUCN dataset (35%).

## Discussion

Gaps in knowledge of species diversity and distribution hinder our understanding of the ecological and evolutionary processes driving species diversification and geographic variation in species diversity (Giller and O'Donovan 2002; Utami et al. 2022). As these gaps alter our perception of diversity patterns, they also hamper our capacity to address the ongoing extinction crisis (Baranzelli et al. 2023). This particularly applies to tropical rainforest areas such as the New Guinea region, which possibly host the least-studied fauna and flora of all terrestrial biomes (Dinerstein and Wikramanayake 1993; Di Marco et al. 2017; Cámara-Leret et al. 2020). Molecular-based inventories represent a fast and efficient way to estimate species diversity and they can foster subsequent taxonomic efforts (Padial et al. 2010). Here, we used this approach by collating data from existing repositories and new data to improve our current understanding of species diversity in frogs in the New Guinea region, a fauna for which the taxonomic impediment is expected to be very high. We provided 534 new DNA sequences of specimens mainly collected from the Bird's Head and the Bird's Neck, two of the most poorly studied regions on New Guinea. Using our dataset, we delimited MOTUs to assess geographic variation in species diversity across the region and to compare our diversity estimates with IUCN counts that are based on recognised species. Our results show that frog species richness in the New Guinea region is vastly underestimated, with the strongest taxonomic impediment located in the western half of New Guinea, where large areas still remain unsurveyed by biologists.

## Sampling gaps and geographic bias

Although DNA sequencing has been increasingly accessible, with the rate of publication of new sequences rocketing over the last two decades (Smith 2016), the New Guinea region still remains poorly represented in DNA sequence repositories. Our georeferenced dataset highlighted that most (81%) of the mtDNA sequences from New Guinean amphibians published before this study (GenBank) originate from the eastern half of the island,

in the country of Papua New Guinea (Fig. 2). This sampling bias is also apparent in other taxa (e.g. ants; Kass et al. (2022)). We partially filled this gap by providing newly acquired sequences from specimens recently collected in western New Guinea and we encourage others to pursue efforts to document species diversity in this part of the island by combining field surveys and molecular identification protocols (Arida et al. 2021).

Despite relatively intensive frog sampling in the eastern half of New Guinea, where 75% of all recognised species from our study region occur, 49% of these are not yet represented by molecular data (Table 1). Missing data are most prevalent in Microhylidae and Hylidae and especially in species having narrow ranges (Suppl. material 1: table S3). Studies focusing on specific genera have already started to fill these gaps (e.g. Oliver et al. (2017); Ferreira et al. (2023)) and work on the Hylidae is in progress (S.C. Donnellan, pers. comm.).

## Barcoding and the amphibian Linnean shortfall

Using 16S mtDNA, we delimited 369 MOTUs in the study region and a significant fraction of these (179) are named and considered taxonomically valid. Overall, the ABGD and GMYC delimitations were congruent with one another and mainly drove our final consensus (Suppl. material 1: table S4), while PTP tended to be more conservative, except for Microhylidae. A similar pattern between delimitation methods was also found by Arida et al. (2021), who analysed variation at the COI locus in a subset of samples included in our study (Suppl. material 1: table S5). The MOTU consensus in Arida et al. (2021) only partially overlaps with ours (Suppl. material 1: table S5), highlighting the benefits of integrating additional data (e.g. bioacoustics, morphometrics) to define robust candidate species hypotheses (Padial et al. 2010).

Thirty of the 38 MOTUs, for which acoustic data were available, displayed notable differences in call features and we consider 19 of these to represent confirmed candidate species. MOTUs supported by acoustic data display mean p-distances at the 16S locus of 2.75–4% (minimum of 1% between *Asterophrys pullifer* and *Asterophrys cf. pullifer*), broadly overlapping with the 3–5% distances that have been advocated as useful thresholds to flag "candidate species" in amphibians (Vences et al. 2005; Fouquet et al. 2007). Hence, a 3% threshold would be relatively conservative with our 16S dataset, since 69, 56 and 26 pairs of MOTUs in Microhylidae, Hylidae and Ceratobatrachidae display p-distances below 3% (including eight that were supported by acoustic data). Yet, because mtDNA-based approaches can lead to either species-oversplitting or lumping (Sukumaran and Knowles 2017; Dellicour and Flot 2018), the true extent of unrecognised diversity remains uncertain in the absence of bioacoustic data and the lack of morphological data prevents further characterisation that could strengthen the candidate species hypotheses. Nevertheless, because Microhylidae and
Ceratobatrachidae are direct-developing frogs that often have narrow distributions and climatic niches (Oliver et al. 2022), we consider it likely that a very large portion of allopatric MOTUs in these groups correspond to distinct species. Conversely, we advise caution regarding Hylidae, for which species diversity remains ambiguous in our dataset due to sampling gaps and because numerous species complexes have been documented (e.g. Sulaeman et al. (2021); Günther et al. (2023)).

Microhylidae, Hylidae and Ceratobatrachidae together include 93% of all our MOTUs and 91% of the MOTUs assigned to recognised species. This proportion mirrors the proportion of taxonomically known species from these families (94%; Frost (2024)) and supports the idea that our sampling is representative of actual species diversity in the region. Following this assumption and assuming that the ratio between candidate and recognised species within our MOTU dataset is representative of the whole region (see Results), we obtained an estimate of 1,200 frog species in the New Guinea region. This estimate is subject to uncertainty and could well be an overestimate due to the nature of mtDNA (cf. paragraph above) and also because

unsurveyed or poorly surveyed areas could be home to higher proportions of previously-known species (i.e. low beta diversity). On the other hand, our estimate could also be an underestimate if our dataset contains false negatives (species undelimited by mtDNA) or there is overlooked high beta diversity, as suggested by recent work in eastern New Guinea (Kraus 2021; Dahl et al. 2024).

Although the validity of our estimate of frog species richness across all of the New Guinea region remains to be confirmed, we argue that a two-fold increase in species diversity seems reasonable in the western half of New Guinea where most of our candidate species occur (Fig. 5). However, major uncertainties persist in areas where data remain substantially lacking, such as the western portion of the central range, which is thought to be highly biodiverse (Fig. 4A). This part of the island is the least sampled of all New Guinea both for molecular data and for most taxa, except perhaps some arthropod groups and birds (Toussaint et al. 2021; Kennedy et al. 2022; Letsch et al. 2023).

We delimited a total of 190 candidate species, of which 123 occur in western New Guinea (mainly in the Bird's Head and Bird's Neck subregions; Fig. 5). Amongst those,

<figure><img src="image_7.png" /><figcaption>Oreophryne cf. roedeli 2</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Oreophryne sp. 'small Kaimana'</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>Oreophryne sp. 'small Kumawa'</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>Xenohrina sp. 'Lengguru'</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>Xenohrina sp. 'Kaimana'</figcaption></figure>

<figure><img src="image_12.png" /><figcaption>Xenohrina sp. 'Lobo'</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>Cornufer sp. 'BW'</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>Cornufer cf. bimaculatus 1</figcaption></figure>

<figure><img src="image_15.png" /><figcaption>Cornufer sp. 'Urisa'</figcaption></figure>

<figure><img src="image_16.png" /><figcaption>Nyctimystes cf. pallidofemora</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>Ranoidea sp. 'Kumawa'</figcaption></figure>

<figure><img src="image_18.png" /><figcaption>Ranoidea sp. 'Kumawa'</figcaption></figure>

<caption>**Figure 5.** Examples of candidate species from the Bird's Head and Bird's Neck subregions (West Papua, Indonesia). The full list of candidate species is presented in the Suppl. material 2.</caption>
only six overlap with the ~ 200 candidate species identified by Oliver et al. (2022) from the New Guinea region. This gap derives from the differing sources of data used: mtDNA data in this study vs. expert surveys in Oliver et al. (2022). We can further highlight the geographic unbalance across datasets, i.e. most candidate species of Oliver et al. (2022) are from eastern New Guinea and many candidates from western New Guinea were not considered. These two largely non-overlapping datasets illustrate the scale of the Linnean shortfall for frogs in this region; while estimating a total of 700 species, Oliver et al. (2022) did not include at least 117 species identified here. Combining these two candidate species datasets, both incomplete and patchy in different ways, generates a minimum estimate of 800 species (~ 240 currently undescribed).

## Investigating the amphibian Wallacean shortfall

Due to large geographic and taxon sampling gaps for the 16Sb locus in several regions on New Guinea (e.g. Microhylidae in the central range, Hylidae in southern New Guinea and Ceratobatrachidae in the central portion of northern New Guinea), assessments of species distribution and endemism are necessarily limited. The Papuan Peninsula stands out as being the most sampled subregion when considering all mtDNA sequences (Fig. 1) and the most species-rich according to the IUCN (Fig. 4A), but one of the least sampled and least diverse in our MOTUs dataset (Fig. 3D and Suppl. material 1: fig. S7). This discrepancy derives from the positive correlation between the number of available 16Sb sequences per subregion and the number of delimited MOTUs (Figs 3D, 4B, 7B). How the correlation between species richness and geographic area varies across the study region remains to be tested with more data. However, we suspect that most areas of New Guinea show high levels of species richness, as suggested by the similar areal extents and species diversity of: 1) the Papuan Peninsula (85,000 km²) where 162 species are resident according to the IUCN and 2) the combined Bird's Head and Bird's Neck (90,000 km²) that are our best 16Sb-sampled subregions and have 110 delimited MOTUs in our analyses. Such diversity levels in western New Guinea are in line with recent studies that uncovered high levels of undocumented diversity in numerous taxa in this part of the island (Kadarusman et al. 2012; Cámara-Lerret et al. 2020; Natusch et al. 2020; Arida et al. 2021; Milá et al. 2021; Ferreira et al. 2023; Oliver et al. 2025).

Our regional endemism rates for MOTUs may be overestimates for some regions due to sparse sampling of species that may be more widely distributed. This is particularly true for Hylidae (also Ranidae, Dicroglossidae and Myobatrachidae) that tend to have wider ranges than microhylids and may occur throughout unsampled areas. This contrast in distribution patterns is probably tightly linked to reproductive features and habitat, i.e. between species breeding in waterbodies, which are abundant in the lowlands and the direct-developing Microhylidae that can breed virtually

anywhere humidity is sufficient (Duellman et al. 1999; Bickford 2004). Endemism is generally high for amphibians in tropical mountains that act as habitat islands, which ultimately favours biological diversification (Anthelme et al. 2014; Stein et al. 2014). This pattern has been reported for frogs in eastern New Guinea (Oliver et al. 2017; Tallowin et al. 2017; Dahl et al. 2024) and undoubtedly occurs in western New Guinea, which harbours similar topographic heterogeneity (Oliver et al. 2022; Ferreira et al. 2023).

Estimated and recognised levels of regional frog species richness on New Guinea (e.g. 100–150 species in the Bird's Head and the Papuan Peninsula) are similar to comparably sized areas in Amazonia (eastern Guiana Shield) (Vacher et al. 2020) and Madagascar (Central plateau) (Brown et al. 2016). However, the diversification of the Amazonian and Malagasy amphibian fauna has a long history throughout the Cenozoic, whereas terrestrial ecosystems of New Guinea may only date back to the early Oligocene (e.g. Jønsson et al. (2011)). These differences of context are clearly exemplified when comparing the crown age of Microhylidae from these regions; ~ 60 vs. 20 Ma (Feng et al. 2017; Hime et al. 2021; Portik et al. 2023). The New Guinean clade of Microhylidae (at least 14 genera and more than 300 species; Frost (2024)) would then have rapidly diversified during the island's recent orogenic development and adapted to fossorial, terrestrial, scansorial and arboreal habitats (Rivera et al. 2017; Hill et al. 2023), a pattern typical of an adaptive radiation (Moen et al. 2021).

## Phylogenetic insights on New Guinean amphibians

The Maximum-Likelihood and ultrametric phylogenetic trees obtained from the analysis of 580 bp of 16S mtDNA are mostly congruent and revealed numerous lineages from western New Guinea that are new to science (Suppl. material 1: fig. S8). Since our phylogenetic inferences are based on a single mtDNA locus only, we refrain from discussing node age estimates or interrelationships further than for the most external branches. We note, however, that our tree topologies are largely congruent with recent phylogenetic hypotheses that focused on Ranidae and Ceratobatrachidae (Brown et al. 2015; Chan et al. 2020). Interestingly, the addition of new *Cornufer* lineages revealed overlooked diversity in western New Guinea that could be very important for understanding the evolutionary history of that group (Suppl. material 1: fig. S8).

Most incongruences between our trees and previously published phylogenies occur within Hylidae and especially within *Litoria* (*sensu* Frost (2024)). Most discrepancies concern weakly supported clades that are also unresolved in literature (Portik et al. 2023). On the other hand, microhylid phylogenetic relationships are difficult to evaluate herein due to insufficient sequence data and limited species sampling. This echoes the long-standing challenge of resolving microhylid phylogenetic relationships in the region (Rivera et al. 2017; Hill et al. 2022).
# Amphibian conservation in the New Guinea region

New Guinea's forests are still relatively extensive compared to many other tropical areas (Vancutsem et al. 2021) and their amphibian faunas remains substantially intact (Oliver et al. 2022). The region has been considered a "wilderness area" (Mittermeier et al. 2003); consequently, it has received little conservation attention compared to other regions that face much more extensive and imminent threats (e.g. Madagascar; Ralimanana et al. (2022)). Yet, a quarter of recognised amphibians from the New Guinea region still awaits an IUCN conservation status assessment and might already be subject to some threats (Oliver et al. 2022). In addition, we showed here that the region hosts an important and undocumented cryptic amphibian diversity, a large portion of which may consist of species confined to restricted geographical areas and, therefore, likely to be more sensitive to both land-use and climate changes. At a minimum, this indicates that the conservation status of many species will need to be re-assessed as distributions become better known, as highlighted by Kraus (2021) for the south-easternmost part of New Guinea and its archipelagos. More generally, there is a crucial need to hasten formal species descriptions in the New Guinea region (best achieved using integrative approaches), in order to facilitate conservation while also providing a more robust foundation for future research. The significant extent of the Linnean and Wallacean shortfalls of this region should also emphasise the importance of taking early conservation measures for amphibians to mitigate the risks of destructive land-use change (Cordier et al. 2021) and potential biotic invasions (e.g. chytrid fungus; Bower et al. (2019)) and to address the vulnerability and resilience of locally endemic upland species to threats from climate change (Lenoir et al. 2020). This rationale also applies to other tropical regions that are subject to significant amphibian Linnean shortfalls (e.g. Neotropics and Madagascar) (Vacher et al. 2020; Carné and Vieites 2024) and already face massive threats to biodiversity (Luedtke et al. 2023).

# Acknowledgements

We are grateful to Laurent Pouyaud, Gono Semiadi, Régis Hocdé, Jacques Slembrouck and Kadarusman who organised the Lengguru expedition in 2014, and Iqbal Setiadi and Philippe Gaucher for their contribution to the sampling in Maluku and west Papua, respectively. We thank the staff from the Museum Zoologicum Bogoriense (MZB) and the South Australian Museum (SAMA), Molly Hagemann from the Bernice Pauahi Bishop Museum (BPBM) and Frank Tillack from the Berlin Museum of Natural History (ZMB), who processed and shipped biological samples and showed great support over many years. We are also thankful to Uxue Suescun and Lucie Moreau from the Centre de la Recherche sur la Biodiversité et l'Environnement (CRBE) and Rachel Fourdin from

the Génomique & Transcriptomique Plateforme Génotoul (GeT-PlaGe) for their help in generating molecular data. We thank Rafe Brown and Jimmy McGuire for their courtesy in providing *Oreophryne anulata* and *O. variabilis* call recordings. Finally, we thank Robert Whittaker, Christopher Burridge, Aurélien Miralles, David Vieites and an anonymous reviewer for their suggestions and support for this work.

# Funding

The first author was supported by a PhD scholarship from the Ministère de l'Enseignement Supérieur et de la Recherche (FR) through SEVAB graduate school. Fieldwork in west Papua was conducted under the RISTEK research permit number 304/SIP/FRP/SM/X/2014, supported by the Lengguru Project conducted by the French Institut de Recherche pour le Développement (IRD), the Indonesian Institute of Sciences (LIPI), with the Research Center for Biology (RCB) and the Research Center for Oceanography (RCO), the University of Papua (UNIPA), the University of Cendrawasih (UNCEN), the University of Musamus (UNMUS) and the Polytechnic KP Sorong, with corporate sponsorship from COLAS and TIPCO groups, Veolia Water and the Total Foundation, and assistance from the Institut Français in Indonesia (IFI) and the French embassy in Jakarta. C.T. acknowledges support from the IRD.

# Conflicts of interest

The authors declare they have no conflict of interest.

# Author contributions

Flavien Ferreira (Data curation and collection, Methodology, Formal analysis, Visualisation, Writing – Original draft and editing), Antoine Fouquet (Data curation and collection, Methodology, Writing – Review and editing), Paul Oliver (Writing – Review and editing), Stephen Richards (Data curation and collection, Writing – Review and editing), Fred Kraus (Data curation and collection, Writing – Review and editing), Rainer Günther (Data curation and collection, Writing – Review and editing), Burhan Tjaturadi (Data collection, Review), Evy Ayu Arida (Data collection, Review), Amir Hamidy (Data curation, Review), Awal Riyanto (Data curation, Review), Wahyu Trilaksono (Data collection, Review) and Christophe Thébaud (Data collection, Writing – Review and editing).

# Data accessibility statement

Molecular data used in the analyses are available in online repositories: GenBank (newly generated sequences are available under the accessions PQ334073-PQ334606) and OSF (the 16S sequences alignment used in the species delimitation are available at https://osf.io/ezg9y/).
Unpublished call recordings analysed in Suppl. materials 1, 2 are available upon request to the corresponding author and have been uploaded on iNaturalist.

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**Supplementary materials**

**Supplementary material 1**

appendix S1: DNA extraction and sequencing protocol.
appendix S2: Species-delimitation method. appendix
S3: Integrative delimitations: fig. S1. Integrative
delimitations for an Oreophryne and Cornufer clade.
fig. S2. Integrative delimitations for four Oreophryne
clades. fig. S3. Integrative delimitations for a Xenorhina
and Oreophryne clade. fig. S4. Integrative delimitations for
two Cornufer clades. fig. S5. Integrative delimitations for
a Hylophorbus and Nyctimystes clade. fig. S6. Integrative
delimitations for a Choerophryne and Oreophryne clade.
Appendix S4: Subregions choice. fig. S7. Distribution
of GenBank mitochondrial DNA sequences, per locus.
fig. S8. Ultrametric tree of amphibians from New Guinea
and neighbouring islands (16S rRNA). fig. S9. Endemism
rate of amphibian species based on the different datasets.
table S1. Summary of the acoustic data analysed in
appendix S3. table S2. Summary of the number of total
mitochondrial DNA sequences, recognised species
and candidate species. table S3. List of available
mitochondrial DNA sequences for amphibians of the New
Guinea region, per species. table S4. Congruence matrix
between our different species-delimitation methods.
table S5. Congruence matrix between different species-
delimitation methods, for the 16S and COI locus. (.docx)
Link: https://doi.org/10.21425/fob.18.137988.suppl1

**Supplementary material 2**

List of all samples and available molecular data, per
specimen and species, with detailed results of the
species-delimitation methods (.xlsex)

Link: https://doi.org/10.21425/fob.18.137988.suppl2