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<article xmlns:tp="http://www.plazi.org/taxpub" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" article-type="research-article" xml:lang="en">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">127</journal-id>
      <journal-id journal-id-type="index">urn:lsid:arphahub.com:pub:15f175fc-9690-5d13-a2ea-114d8a2e74bd</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">Frontiers of Biogeography</journal-title>
        <abbrev-journal-title xml:lang="en">biogeography</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">1948-6596</issn>
      <publisher>
        <publisher-name>Pensoft Publishers</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.21425/fob.19.208301</article-id>
      <article-id pub-id-type="publisher-id">208301</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group subj-group-type="biological_taxon">
          <subject>Animalia</subject>
          <subject>Leptodactylidae</subject>
        </subj-group>
        <subj-group subj-group-type="scientific_subject">
          <subject>Biogeography</subject>
          <subject>Distribution modelling</subject>
          <subject>Diversity</subject>
          <subject>Genetics</subject>
        </subj-group>
        <subj-group subj-group-type="geological_era">
          <subject>Cenozoic</subject>
        </subj-group>
        <subj-group subj-group-type="geographical_area">
          <subject>Americas</subject>
          <subject>South America</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Biogeographic origins of the disjunct distribution of the chacoan Neotropical frog <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic></article-title>
      </title-group>
      <contrib-group content-type="authors">
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Carné</surname>
            <given-names>Albert</given-names>
          </name>
          <email xlink:type="simple">albert.carne@mncn.csic.es</email>
          <uri content-type="orcid">https://orcid.org/0000-0002-7920-8159</uri>
          <xref ref-type="aff" rid="A1">1</xref>
          <xref ref-type="aff" rid="A2">2</xref>
          <role content-type="http://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
          <role content-type="http://credit.niso.org/contributor-roles/writing-original-draft/">Writing - original draft</role>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
          <role content-type="http://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
          <role content-type="http://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
          <role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
          <role content-type="http://credit.niso.org/contributor-roles/methodology/">Methodology</role>
          <role content-type="http://credit.niso.org/contributor-roles/validation/">Validation</role>
          <role content-type="http://credit.niso.org/contributor-roles/visualization/">Visualization</role>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Gonzales</surname>
            <given-names>Lucindo</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0009-0007-0324-1407</uri>
          <xref ref-type="aff" rid="A3">3</xref>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
          <role content-type="http://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
          <role content-type="http://credit.niso.org/contributor-roles/validation/">Validation</role>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>De la Riva</surname>
            <given-names>Ignacio</given-names>
          </name>
          <email xlink:type="simple">iriva@mncn.csic.es</email>
          <uri content-type="orcid">https://orcid.org/0000-0001-5064-4507</uri>
          <xref ref-type="aff" rid="A2">2</xref>
          <role content-type="http://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
          <role content-type="http://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
          <role content-type="http://credit.niso.org/contributor-roles/supervision/">Supervision</role>
          <role content-type="http://credit.niso.org/contributor-roles/validation/">Validation</role>
        </contrib>
      </contrib-group>
      <aff id="A1">
        <label>1</label>
        <addr-line content-type="verbatim">Science and Business S.L., Edificio CITEXVI, Campus Universitario de Vigo, Rúa Fonte das Abelleiras s/n, 36210 Vigo, Galicia, Spain</addr-line>
        <institution>Science and Business S.L., Edificio CITEXVI, Campus Universitario de Vigo</institution>
        <addr-line content-type="city">Vigo</addr-line>
        <country>Spain</country>
        <uri content-type="ror">https://ror.org/02v6zg374</uri>
      </aff>
      <aff id="A2">
        <label>2</label>
        <addr-line content-type="verbatim">Department of Biodiversity and Evolutionary Biology, Museo Nacional de Ciencias Naturales (MNCN), CSIC, C. de José Gutiérrez Abascal, 2, 28006, Madrid, Spain</addr-line>
        <institution>Department of Biodiversity and Evolutionary Biology, Museo Nacional de Ciencias Naturales</institution>
        <addr-line content-type="city">Madrid</addr-line>
        <country>Spain</country>
        <uri content-type="ror">https://ror.org/05rdf8595</uri>
      </aff>
      <aff id="A3">
        <label>3</label>
        <addr-line content-type="verbatim">Museo de Historia Natural Noel Kempff Mercado, Avda. Irala 565, Santa Cruz de la Sierra, Santa Cruz, Bolivia</addr-line>
        <institution>Museo de Historia Natural Noel Kempff Mercado</institution>
        <addr-line content-type="city">Santa Cruz</addr-line>
        <country>Bolivia</country>
        <uri content-type="ror">https://ror.org/006y63v75</uri>
      </aff>
      <author-notes>
        <fn fn-type="corresp">
          <p>Corresponding authors: Albert Carné (<email xlink:type="simple">albert.carne@mncn.csic.es</email>); Ignacio De la Riva (<email xlink:type="simple">iriva@mncn.csic.es</email>)</p>
        </fn>
        <fn>
          <p><bold>Editor</bold> Larry Heaney</p>
        </fn>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2026</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>24</day>
        <month>09</month>
        <year>2026</year>
      </pub-date>
      <volume>19</volume>
      <elocation-id>e208301</elocation-id>
      <uri content-type="arpha" xlink:href="http://openbiodiv.net/521C0175-DFFD-5C2A-AFB2-A7BFC86740BD">521C0175-DFFD-5C2A-AFB2-A7BFC86740BD</uri>
      <history>
        <date date-type="received">
          <day>21</day>
          <month>07</month>
          <year>2026</year>
        </date>
        <date date-type="accepted">
          <day>01</day>
          <month>09</month>
          <year>2026</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Albert Carné, Lucindo Gonzales, Ignacio De la Riva</copyright-statement>
        <license license-type="creative-commons-attribution" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">
          <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
        </license>
      </permissions>
      <abstract>
        <label>Abstract</label>
        <p>Disjunct distributions, in which populations of a putative species are separated by large distances, represent an important, albeit poorly understood pattern in biogeography. Detailed study of these populations often reveals that they actually comprise more than one species resulting from prolonged restricted gene flow. The leptodactylid chacoan frog <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> exhibits a striking disjunct distribution. Populations are well known to occur in north-central Argentina, whereas records from southern Bolivia are separated by ca. 820 km gap lacking confirmed records despite extensive surveys. In this study, we integrate molecular and paleoclimatic data to assess, 27 years after their discovery, whether the Bolivian populations are conspecific with Argentine populations and to explore the historical processes that shaped their current distribution. Despite the large geographical distance, our phylogenetic analyses based on two mitochondrial gene fragments revealed minimal divergence between Bolivian and Argentine populations, which do not form reciprocally monophyletic lineages. These results support the hypothesis that the Bolivian and Argentine populations are conspecific and present a true disjunct (i.e., bicentric) distribution resulting from recent range fragmentation rather than an ancient split. Paleoclimatic niche projections suggest a dynamic history of habitat connectivity and fragmentation. Suitable habitats were more continuous during the Last Glacial Maximum, became fragmented afterward, and then reconnected between ca. 8–13 ka; however, fragmentations during later climatic oscillations likely led to further range contractions and local extinctions that produced the current disjunct pattern observed in the species. Overall, our results support an intriguing case of conspecific disjunct distribution driven by historical climatic oscillations.</p>
        <sec sec-type="Highlights" id="sec1">
          <title>Highlights</title>
          <boxed-text position="float">
            <list list-type="bullet">
              <list-item>
                <p>We report a true disjunct distribution in amphibians.</p>
              </list-item>
              <list-item>
                <p>Molecular data confirm that Bolivian populations of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> are conspecific with Argentine populations.</p>
              </list-item>
              <list-item>
                <p><italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> exhibits a true disjunct distribution, whose geographical clusters are separated by ca. 800 km.</p>
              </list-item>
              <list-item>
                <p>This disjunct distribution is best explained by climatic oscillations during the Last Glacial Maximum and Holocene.</p>
              </list-item>
            </list>
          </boxed-text>
        </sec>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Amphibians</kwd>
        <kwd>Argentina</kwd>
        <kwd>Bolivia</kwd>
        <kwd>Chaco</kwd>
        <kwd>Distributions</kwd>
        <kwd>
          <tp:taxon-name>
            <tp:taxon-name-part taxon-name-part-type="family" reg="Leptodactylidae">Leptodactylidae</tp:taxon-name-part>
          </tp:taxon-name>
        </kwd>
        <kwd>Paleoclimate</kwd>
        <kwd>Phylogeny</kwd>
        <kwd>
          <italic>
            <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name>
          </italic>
        </kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="Introduction" id="sec2">
      <title>Introduction</title>
      <p>Species are the fundamental unit for measuring and conserving biodiversity. Delimiting species and mapping their distributions are the first steps toward their conservation. However, we are still far from fully understanding how many species are on Earth, where they occur, and the mechanisms that shape this diversity and its biogeographic patterns (<xref ref-type="bibr" rid="B52">Lomolino 2004</xref>; <xref ref-type="bibr" rid="B88">Whittaker et al. 2005</xref>).</p>
      <p>A striking and intriguing pattern in the biogeography of species is the disjunct distribution, where otherwise closely related populations are separated by large distances, even with no evident geographical or ecological barriers. Sampling biases can be behind an apparent but not real disjunct distribution, which is perceived as such due to incomplete sampling in intermediate areas or species having low detectability (<xref ref-type="bibr" rid="B83">Taylor 2017</xref>). Once these artifacts are tested and discarded, a clustered geographical pattern may be due to three processes: vicariance, local extinction, or long-distance dispersal events (<xref ref-type="bibr" rid="B83">Taylor 2017</xref>; <xref ref-type="bibr" rid="B60">Owen and Taylor 2023</xref>). Natural vicariance (i.e., not due to human intervention through habitat fragmentation and other barriers of anthropogenic origin) may be caused by physical barriers and historical climatic changes that create unsuitable habitats (e.g., <xref ref-type="bibr" rid="B47">Kropf et al. 2006</xref>; <xref ref-type="bibr" rid="B62">Pârvulescu et al. 2019</xref>), potentially extirpating populations and dividing the species’ once-continuous range into geographical clusters. Local extinction may result from historical changes in ecological conditions, either abiotic or biotic, leading to the extirpation of populations from otherwise apparently current suitable habitats (<xref ref-type="bibr" rid="B35">Harrison 1991</xref>). Finally, long-distance dispersal events can also lead to disjunctions when jump dispersal processes establish new populations in suitable habitats that are geographically isolated from the main distribution range (<xref ref-type="bibr" rid="B54">Marin da Fonte et al. 2019</xref>).</p>
      <p>The three mentioned drivers can promote allopatric speciation if the spatial or temporal gap between population clusters sufficiently restricts gene flow. Indeed, molecular data have frequently revealed that disjunct populations previously considered conspecific actually represent distinct species (e.g., <xref ref-type="bibr" rid="B15">Carranza and Amat 2005</xref>), especially when such populations had been at some point previously recognized as subspecies (e.g., <xref ref-type="bibr" rid="B29">Fok et al. 2002</xref>). Thus, assessing the specific identity of clusters within a disjunct-distributed taxon can lead to the discovery and description of new species or confirm such disjunct distribution.</p>
      <p>Amphibians constitute valuable, yet little studied models for biogeographic research: most species are small and tightly tied to humid environments, which limits their dispersal and makes their distributions especially informative of environmental constraints, while some taxa retain enough vagility to colonize new areas, offering insight into range-expansion dynamics. Our knowledge of the taxonomy and distributions of amphibians—the most endangered class of vertebrates (<xref ref-type="bibr" rid="B53">Luedtke et al. 2023</xref>)—, has improved significantly in recent times, partly due to the integration of molecular data into systematic studies (e.g., <xref ref-type="bibr" rid="B86">Veith 1996</xref>; <xref ref-type="bibr" rid="B31">Frost et al. 2006</xref>; <xref ref-type="bibr" rid="B65">Pyron and Wiens 2011</xref>). This has enabled the description of ca. 100 new species of frogs per year in the last decades (<xref ref-type="bibr" rid="B45">Köhler et al. 2005</xref>; <xref ref-type="bibr" rid="B30">Frost 2026</xref>) and the resolution of numerous species complexes, thereby improving our understanding of species ranges (<xref ref-type="bibr" rid="B81">Streicher et al. 2020</xref>; <xref ref-type="bibr" rid="B30">Frost 2026</xref>). However, despite these recent advances, knowledge of amphibian distributions remains fragmentary in many regions (<xref ref-type="bibr" rid="B9">Brito 2010</xref>), particularly in tropical and sub-tropical areas —the most biodiverse and imperiled on Earth (<xref ref-type="bibr" rid="B6">Barlow et al. 2018</xref>). This is largely caused by three reasons: (1) Even in the best-studied tropical biodiversity hotspots, species inventories remain incomplete and taxonomic uncertainty continues to obscure what is actually being mapped (<xref ref-type="bibr" rid="B12">Carné and Vieites 2024</xref>); (2) amphibians are typically small, secretive, and often exhibit seasonal activity patterns, which reduces their detectability —particularly in strongly seasonal habitats where active periods are short (<xref ref-type="bibr" rid="B20">Dubos et al. 2020</xref>); and (3) field trips are logistically complex, costly, and time-consuming, leading surveys to focus on the most accessible or attractive-to-sample sites (<xref ref-type="bibr" rid="B71">Sastre and Lobo 2009</xref>), while less appealing habitats (e.g., plantations) are often overlooked —despite their potential to provide a more complete picture of species’ distributions and ecologies (e.g., <xref ref-type="bibr" rid="B13">Carné et al. 2025</xref>). Furthermore, DNA barcoding is not yet widely implemented (<xref ref-type="bibr" rid="B14">Carné et al. 2026</xref>), creating uncertainty when assigning localities to certain species based solely on morphology. This is especially problematic when closely related species exhibit intraspecific morphological variability or phenotypic conservatism in relation to their congeners.</p>
      <p>The anuran genus <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> Tschudi, 1838 comprises 15 described species of leptodactylid frogs distributed across the Neotropics (used here in its classical sense; but see <xref ref-type="bibr" rid="B39">Holt et al. 2013</xref>), from Panama to southern Argentina and Chile, and occurring from sea level up to 5,000 m a.s.l. (<xref ref-type="bibr" rid="B24">Faivovich et al. 2012</xref>; <xref ref-type="bibr" rid="B30">Frost 2026</xref>). Most species primarily inhabit open environments, often in arid and/or cold, or highly seasonal temperate regions (<xref ref-type="bibr" rid="B26">Ferraro and Casagranda 2009</xref>; <xref ref-type="bibr" rid="B24">Faivovich et al. 2012</xref>). Due to these harsh conditions, the breeding season is short, with optimal mating and egg-laying opportunities sometimes limited to just a few days per year, thus leading most species to exhibit explosive breeding behavior (<xref ref-type="bibr" rid="B38">Hödl 1992</xref>; <xref ref-type="bibr" rid="B26">Ferraro and Casagranda 2009</xref>; <xref ref-type="bibr" rid="B24">Faivovich et al. 2012</xref>).</p>
      <p>Several studies have been carried out on the phylogeny of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> (<xref ref-type="bibr" rid="B22">Duellman and Veloso 1977</xref>; <xref ref-type="bibr" rid="B24">Faivovich et al. 2012</xref>; <xref ref-type="bibr" rid="B25">Ferraro 2022</xref>). All of them recover a clade containing two sister, morphologically similar species from northwestern Argentina, <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="nebulosum">nebulosum</tp:taxon-name-part></tp:taxon-name></italic> (<xref ref-type="bibr" rid="B11">Burmeister 1861</xref>) and <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> Barrio, 1964. <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> was distinguished from <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="nebulosum">nebulosum</tp:taxon-name-part></tp:taxon-name></italic> based on clear bioacoustic differences and the absence of an external tympanum; hybridization near the type locality was documented (<xref ref-type="bibr" rid="B7">Barrio 1964</xref>). These two species have been hypothesized to have diverged during the Pleistocene due to barriers such as rivers carrying glacial runoff or the uplift of N–S mountain ranges (<xref ref-type="bibr" rid="B22">Duellman and Veloso 1977</xref>), but this has not been corroborated.</p>
      <p><italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> (Fig. <xref ref-type="fig" rid="F1">1</xref>) is a species that typically inhabits saline flat environments and semidesert regions of the Dry Chaco ecoregion, and was originally known from the convergence zone of the Argentine provinces of Catamarca, Córdoba, La Rioja, San Juan, San Luis, and Santiago del Estero (<xref ref-type="bibr" rid="B16">Cei 1980</xref>; <xref ref-type="bibr" rid="B34">Guerreiro et al. 2005</xref>; <xref ref-type="bibr" rid="B26">Ferraro and Casagranda 2009</xref>; <xref ref-type="bibr" rid="B66">Quiroga and Sanabria 2009</xref>). Surprisingly, <xref ref-type="bibr" rid="B18">De la Riva and Gonzales (1998)</xref> reported morphologically identified <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> specimens from four nearby localities in anthropogenic habitats of Bolivia’s Santa Cruz department, approximately 1000 km north of the nearest Argentine population known at that time. Subsequent surveys since 1998 have expanded the species’ known Argentine distribution northward but, despite extensive sampling efforts in intervening areas, a significant 820 km distributional gap persists between the northernmost Argentine records (Santiago del Estero Province) and the Bolivian populations. The unexpected discovery of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> in Bolivia raised questions concerning the taxonomic status of Bolivian populations (<xref ref-type="bibr" rid="B18">De la Riva and Gonzales 1998</xref>; <xref ref-type="bibr" rid="B19">De la Riva et al. 2000</xref>; <xref ref-type="bibr" rid="B24">Faivovich et al. 2012</xref>). If Argentine and Bolivian populations were conspecific, we could consider <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> a proven example of confirmed disjunct distribution in amphibians.</p>
      <fig id="F1">
        <object-id content-type="doi">10.21425/fob.19.208301.figure1</object-id>
        <object-id content-type="arpha">AC944ACA-2891-5456-921F-AE05DE597F5A</object-id>
        <label>Figure 1.</label>
        <caption>
          <p>Phylogenetic relationships and haplotype networks of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> species. The Bayesian phylogenetic tree (top) is based on the concatenated dataset (<italic><abbrev xlink:title="16S rRNA">16S</abbrev> RNA</italic> + <italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic>) and includes all sequenced species of the genus <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic>. Haplotype networks (bottom) display mutational connections among individuals of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> and <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="nebulosum">nebulosum</tp:taxon-name-part></tp:taxon-name></italic>. Circle sizes are proportional to sample sizes, and hash marks indicate mutational steps. Blue and yellow shading highlight Bolivian and Argentinian samples, respectively.</p>
        </caption>
        <graphic xlink:href="biogeography-19-001_article-208301__-g001.jpg" id="oo_1788931.jpg">
          <uri content-type="original_file">https://binary.pensoft.net/fig/1788931</uri>
        </graphic>
      </fig>
      <p>In this study, we use molecular data to evaluate —twenty-seven years after their discovery— the taxonomic identity of the Bolivian populations morphologically attributed to <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic>. Our main goal was to determine whether the Bolivian specimens are conspecific with those from Argentina and thus confirm a hypothesized bicentric species distribution (i.e., geographically separated but genetically undifferentiated populations), or whether they constitute a distinct vicariant taxon (i.e., geographically and genetically differentiated). Additionally, we explore the potential ecological and historical factors that might have shaped the biogeographic patterns.</p>
    </sec>
    <sec sec-type="materials|methods" id="sec3">
      <title>Materials and methods</title>
      <sec sec-type="Sampling and genetic analysis" id="sec4">
        <title>Sampling and genetic analysis</title>
        <p>We sampled five <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> specimens from the Bolivian populations, held at the Museo de Historia Natural Noel Kempff Mercado (<named-content content-type="dwc:institutional_code" xlink:title="Museo de Historia Natural Noel Kempff Mercado" xlink:href="https://scientific-collections.gbif.org/institution/0174acbe-20f4-4b56-9a4c-6353038ef1f9">MHNNKM</named-content>; Santa Cruz de la Sierra, Bolivia) (see Suppl. material <xref ref-type="supplementary-material" rid="S1">1</xref> for localities and coordinates). We extracted DNA from leg muscle tissue using the Qiagen DNeasy extraction kit (Qiagen, Valencia, CA, USA). We PCR-amplified two mitochondrial gene fragments following standard protocols, using the primers MVZ15 (<xref ref-type="bibr" rid="B56">Moritz et al. 1992</xref>) and H15149 (<xref ref-type="bibr" rid="B44">Kocher et al. 1989</xref>) for the c<italic>ytochrome-b</italic> (<italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic>) and 16Ar-L and 16Br-H for the <italic><abbrev xlink:title="16S rRNA">16S</abbrev> rRNA</italic> (<italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic>) (<xref ref-type="bibr" rid="B61">Palumbi et al. 1991</xref>). PCR products were Sanger-sequenced in both directions at Macrogen (Madrid, Spain). Additionally, we incorporated from GenBank (<xref ref-type="bibr" rid="B72">Sayers et al. 2025</xref>) all available <italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic> and <italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic> sequences of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> and <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="nebulosus">nebulosus</tp:taxon-name-part></tp:taxon-name></italic>, one specimen of each described <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> species with available sequences for both target genes, and one specimen of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Physalaemus">Physalaemus</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="cuvieri">cuvieri</tp:taxon-name-part></tp:taxon-name></italic> as outgroup (see Suppl. material <xref ref-type="supplementary-material" rid="S1">1</xref> for specimen data and GenBank accession numbers).</p>
        <p>We trimmed, assembled, and edited the raw sequences using GENEIOUS 2021.2.2 (available at: <ext-link xlink:href="https://www.geneious.com" ext-link-type="uri">https://www.geneious.com</ext-link>). We incorporated the newly generated sequences, along with those from GenBank, into two separate datasets, one for each gene. We aligned the sequences using MAFFT v.7 (<xref ref-type="bibr" rid="B43">Katoh et al. 2019</xref>) with default parameters, and manually inspected, edited the resulting alignments, and then concatenated the two gene fragments using GENEIOUS. For each gene fragment independently and for the concatenated dataset, we inferred phylogenetic trees using Bayesian inference (<abbrev xlink:title="Bayesian inference">BI</abbrev>). We performed <abbrev xlink:title="Bayesian inference">BI</abbrev> analyses with BEAST v1.10.4 (<xref ref-type="bibr" rid="B82">Suchard et al. 2018</xref>), applying the best-fitting substitution model selected by PARTITIONFINDER (<xref ref-type="bibr" rid="B49">Lanfear et al. 2017</xref>) —GTR+I+G in <italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic> and GTR+G in C<italic>yt-b</italic>. We ran the BEAST analyses under a Yule speciation process and a strict molecular clock, conducting three independent runs of 100 million generations each. We assessed convergence and effective sample sizes (<abbrev xlink:title="effective sample sizes">ESS</abbrev>) of the three independent runs using TRACER v1.7.1 (<xref ref-type="bibr" rid="B69">Rambaut et al. 2018</xref>). We combined the resulting tree files using LOGCOMBINER, discarding the first 10% of trees as burn-in, and generated ultrametric trees using TREEANOTATOR (both software provided with the BEAST package).</p>
        <p>We calculated uncorrected <italic>p-distances</italic> in MEGA v. 10 (<xref ref-type="bibr" rid="B48">Kumar et al. 2018</xref>) using pairwise deletion and accounting for transitions and transversions. Finally, we constructed a haplotype network for both mitochondrial genes in POPART using the TCS option (<xref ref-type="bibr" rid="B51">Leigh and Bryant 2015</xref>).</p>
      </sec>
      <sec sec-type="Species distribution modelling" id="sec5">
        <title>Species distribution modelling</title>
        <p>We compiled distribution data for <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> populations from multiple sources: <xref ref-type="bibr" rid="B26">Ferraro and Casagranda (2009)</xref>, <xref ref-type="bibr" rid="B66">Quiroga and Sanabria (2009)</xref>, <xref ref-type="bibr" rid="B4">Baldo and Gutiérrez (1997)</xref>, <xref ref-type="bibr" rid="B18">De la Riva and Gonzales (1998)</xref>, <xref ref-type="bibr" rid="B73">Schalk (2012)</xref>, GBIF (<ext-link xlink:href="http://www.gbif.org" ext-link-type="uri">http://www.gbif.org</ext-link>), and iNaturalist (<ext-link xlink:href="https://www.inaturalist.org/" ext-link-type="uri">https://www.inaturalist.org/</ext-link>). For iNaturalist data, we only considered research-grade records with geolocation uncertainty of less than 5 km. For GBIF data, we downloaded all records considering human observations, samples, and preserved specimens, excluding occurrences with geolocation uncertainty exceeding 5 km (link to data: <xref ref-type="bibr" rid="B32">GBIF.org 2025a</xref>); from this GBIF dataset we deleted records redundant with those extracted from the literature. We compiled a dataset of 91 georeferenced occurrence records, after discarding some previously published records based on potential locality redundancy and misidentifications (see details in the caption of Suppl. material <xref ref-type="supplementary-material" rid="S2">2</xref>). After removing duplicates per pixel (with a spatial resolution of ~1 km; see below), we used 46 occurrence records to build the models (see Suppl. material <xref ref-type="supplementary-material" rid="S2">2</xref> for the complete dataset).</p>
        <p>We obtained all bioclimatic variables from PaleoClim (<xref ref-type="bibr" rid="B10">Brown et al. 2018</xref>) at 30 arc-second resolution (~1 km) for both current conditions and the Last Glacial Maximum (<abbrev xlink:title="Last Glacial Maximum">LGM</abbrev>), and at 2.5-minute resolution for the rest of paleoclimatic layers. These included eight Pleistocene periods (Late-Holocene, Meghalayan [4.2 to 0.3 ka], Mid-Holocene, Northgrippian [8.326 to 4.2 ka], Early-Holocene, Greenlandian [11.7 to 8.326 ka], Younger Dryas Stadial [12.9 to 11.7 ka], Bølling-Allerød [14.7 to 12.9 ka], Heinrich Stadial 1 [17 to 14.7 ka], Last Glacial Maximum, <abbrev xlink:title="Last Glacial Maximum">LGM</abbrev> [ca 21 ka], and Last Interglacial, LIG [ca. 130 ka]. Following <xref ref-type="bibr" rid="B8">Booth (2022)</xref>, we removed all variables that exhibited unusual spatial patterns suggesting artefacts in the study area (i.e., bio 2, 3, 8, 9, 12, 13, 14, 18, and 19). We evaluated multicollinearity effects among remaining variables based on the pairwise Pearson’s correlation coefficient and the Variance Inflation Factor (<abbrev xlink:title="Variance Inflation Factor">VIF</abbrev>) using the R packages ‘stats’ (<xref ref-type="bibr" rid="B67">R Core Team 2023</xref>) and ‘usdm’ (<xref ref-type="bibr" rid="B58">Naimi et al. 2014</xref>), respectively. We selected the variables to be used as model predictors according to the low multicollinearity values presented by both tests (Pearson’s correlation coefficient &lt; 0.75 and <abbrev xlink:title="Variance Inflation Factor">VIF</abbrev> &lt; 5; see Suppl. material <xref ref-type="supplementary-material" rid="S3">3</xref>). Our final dataset for model building contained five variables: mean daily maximum air temperature of the warmest month (bio5), annual range of air temperature (bio7), precipitation seasonality (bio15), mean monthly precipitation amount the wettest quarter (bio16), and mean monthly precipitation amount of the driest quarter (bio17).</p>
        <p>Absence data were unavailable for this study and, despite a large portion of the study area has been relatively well sampled, especially in Argentina, occurrence data might contain sampling biases (see Suppl. material <xref ref-type="supplementary-material" rid="S4">4</xref>). We reduced the impact of bias on model building using a background with the same sampling bias as the occurrence records. We followed the ‘target-group background’ approach suggested by <xref ref-type="bibr" rid="B5">Barber et al. (2022)</xref>, which uses the collective records of similar taxa across the study area to estimate the sampling effort for the focal species. As reptiles and amphibians are commonly sampled together using similar methodologies, we merged 32,912 reptile and 29,538 amphibian occurrence records from GBIF (link to data: <xref ref-type="bibr" rid="B33">GBIF.org 2025b</xref>), excluding occurrences with an error &gt; 1 km and considering human observations, samples, and preserved specimens. We subsequently created a two-dimensional kernel density raster to convert single presence points into a continuous probability surface, reflecting the sampling intensity conducted in the study area (i.e., the number of specimens per pixel). Finally, we randomly sampled 10,000 background points according to the probability given by the density raster (i.e., more sampling intensity and more background samples at a given locality).</p>
        <p>We modelled the species’ realized niche (<italic>sensu</italic><xref ref-type="bibr" rid="B75">Sillero 2011</xref>) following standard procedures (<xref ref-type="bibr" rid="B77">Sillero et al. 2021</xref>; <xref ref-type="bibr" rid="B76">Sillero and Barbosa 2021</xref>), using the Maximum Entropy (<abbrev xlink:title="Maximum Entropy">MaxEnt</abbrev>) algorithm in the ‘predicts’ R package (<xref ref-type="bibr" rid="B37">Hijmans 2023</xref>; <xref ref-type="bibr" rid="B78">Sillero et al. 2023</xref>). <abbrev xlink:title="Maximum Entropy">MaxEnt</abbrev> is a presence-background machine learning method that predicts the species’ habitat suitability (the most similar environmental conditions of the study area to the training data; <xref ref-type="bibr" rid="B59">Osorio-Olvera et al. 2019</xref>) with the highest entropy (i.e., the most uniform or least biased distribution) while still satisfying the known constraints or observations (<xref ref-type="bibr" rid="B63">Phillips et al. 2006</xref>, <xref ref-type="bibr" rid="B64">2017</xref>). <abbrev xlink:title="Maximum Entropy">MaxEnt</abbrev> estimates the realized niche in the environmental space based on a set of predictor variables included in the model. This niche is then projected onto the geographic space as a habitat suitability index. Because it is impossible to incorporate all variables that define a species’ niche, the realized niche is always a partial estimate. Therefore, we use the term ‘habitat suitability’ (e.g., gain/loss of suitable habitat) to refer to the geographic expression of the species’ modelled ecological niche (i.e., <abbrev xlink:title="Maximum Entropy">MaxEnt</abbrev> output maps). <abbrev xlink:title="Maximum Entropy">MaxEnt</abbrev> is one of the most effective modelling procedures for generating environmental niche predictions from presence-background data (<xref ref-type="bibr" rid="B23">Elith et al. 2006</xref>; <xref ref-type="bibr" rid="B84">Valavi et al. 2022</xref>) and is capable of producing reliable models with few records (<xref ref-type="bibr" rid="B36">Hernandez et al. 2006</xref>; <xref ref-type="bibr" rid="B46">Kremen et al. 2008</xref>). <abbrev xlink:title="Maximum Entropy">MaxEnt</abbrev> output forecasts the habitat suitability and ranges from 0 (unsuitable environmental conditions) to 1 (suitable). We applied Maxent’s default parametrization. We ran 10 replicates of each model, keeping only one occurrence per climatic pixel (i.e., removing duplicates). We defined the background as the whole study regions and obtained the background points using the density kernel as a covariate to account for sampling bias (see above). We clamped the response to prevent projecting (extrapolating) the models onto conditions outside the training data range.</p>
        <p>We used the bootstrapping method for model evaluation. We left 30% of occurrence data for testing (<xref ref-type="bibr" rid="B77">Sillero et al. 2021</xref>). We used two discrimination metrics: the area under the curve (<abbrev xlink:title="area under the curve">AUC</abbrev>) of the Receiver Operating Characteristic (ROC; <xref ref-type="bibr" rid="B89">Zweig and Campbell 1993</xref>; <xref ref-type="bibr" rid="B28">Fielding and Bell 1997</xref>) and the True Statistical Skill (<abbrev xlink:title="True Statistical Skill">TSS</abbrev>; <xref ref-type="bibr" rid="B2">Allouche et al. 2006</xref>) to evaluate the accuracy of our models (<xref ref-type="bibr" rid="B77">Sillero et al. 2021</xref>). <abbrev xlink:title="area under the curve">AUC</abbrev> ranges from 0 to 1, and a random model has a value of 0.5; <abbrev xlink:title="True Statistical Skill">TSS</abbrev> ranges from -1 to 1, and a random model has a value of 0. These two discrimination metrics are correlated (<xref ref-type="bibr" rid="B2">Allouche et al. 2006</xref>). Additionally, we compared the discrimination metrics of the empirical models with those obtained from null models (<xref ref-type="bibr" rid="B68">Raes and ter Steege 2007</xref>). To calculate the null models, we randomly generated pseudo-presence data across the study area, maintaining the same sample size as the species’ occurrence data while keeping all other model parameters unchanged. We analyzed whether the discrimination metrics from the empirical models were significantly higher than those from the null models with independent two-sample t-tests from the stats R package (<xref ref-type="bibr" rid="B67">R Core Team 2023</xref>).</p>
        <p>We assessed the importance of each explanatory variable by estimating its average percentage contribution across model replicates. Next, we used the Jackknife test (<xref ref-type="bibr" rid="B63">Phillips et al. 2006</xref>), which involves recalculating the model in three ways: excluding one explanatory variable at a time, using only that variable, and using all variables together to compare <abbrev xlink:title="area under the curve">AUC</abbrev> and gain for both the training and test data. Finally, to determine the model’s dependence on each variable, we calculated the permutation importance by randomly changing the variable values among the training points and measuring the decrease in <abbrev xlink:title="area under the curve">AUC</abbrev>.</p>
        <p>We projected the obtained replicated models into the current and past periods. We averaged the ten current model replicates into a single habitat suitability map. We binarized the continuous predictions into habitat suitable, or unsuitable, classes to assess the origin of the current disjunct distribution of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> using the threshold that maximizes the sum of sensitivity and specificity, as it tends to reﬂect the species’ prevalence well (<xref ref-type="bibr" rid="B42">Jiménez-Valverde and Lobo 2007</xref>).</p>
      </sec>
    </sec>
    <sec sec-type="Results" id="sec6">
      <title>Results</title>
      <sec sec-type="Phylogenetic relationships" id="sec7">
        <title>Phylogenetic relationships</title>
        <p>From the five sampled <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> individuals from Bolivia, we successfully sequenced 571 base pairs (<abbrev xlink:title="base pairs">bp</abbrev>) of the <italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic> in three individuals and 384 <abbrev xlink:title="base pairs">bp</abbrev> of the <italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic> in all five individuals (Suppl. material <xref ref-type="supplementary-material" rid="S1">1</xref>). Our phylogenetic analysis of the concatenated dataset (955 <abbrev xlink:title="base pairs">bp</abbrev>) yielded well-supported relationships among major clades (pp &gt; 0.9), recovering all described species with strong support (Fig. <xref ref-type="fig" rid="F1">1</xref>).</p>
        <p>We did not recover the monophyly of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic>, due to one Argentine individual (MACN 38766), assigned to <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="nebulosum">nebulosum</tp:taxon-name-part></tp:taxon-name></italic>, grouping with the <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> clade. This pattern, consistently supported across the <italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic>, <italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic>, and concatenated datasets (Fig. <xref ref-type="fig" rid="F1">1</xref>; Suppl. material <xref ref-type="supplementary-material" rid="S5">5</xref>), was previously noted and discussed by <xref ref-type="bibr" rid="B24">Faivovich et al. (2012)</xref>, indicating that the identity and phylogenetic relationships of these two species deserve further investigations. Additionally, we did not recover the <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> populations from Bolivia and Argentina as reciprocally monophyletic in the <italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic> or concatenated datasets, although we found them monophyletic in the <italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic> when excluding the introgressed <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="nebulosum">nebulosum</tp:taxon-name-part></tp:taxon-name></italic> individual (Fig. <xref ref-type="fig" rid="F1">1</xref>, Suppl. material <xref ref-type="supplementary-material" rid="S5">5</xref>). Excluding the introgressed individual (MACN 38766)— which shows a mean divergence of 0.29% in <italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic> and 1.39% in <italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic> against <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic>, and 1.07% in <italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic> and 2.7% in <italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic> against <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="nebulosum">nebulosum</tp:taxon-name-part></tp:taxon-name></italic>, the mean divergence between <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> and <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="nebulosum">nebulosum</tp:taxon-name-part></tp:taxon-name></italic> is 1.15% and 2.14% in <italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic> and <italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic>, respectively.</p>
      </sec>
      <sec sec-type="Species distribution models" id="sec8">
        <title>Species distribution models</title>
        <sec sec-type="Model evaluation and variable importance" id="sec9">
          <title>Model evaluation and variable importance</title>
          <p>We produced reliable models for all replicates. The overall empirical mean values were as follows: <abbrev xlink:title="area under the curve">AUC</abbrev><sub>Train</sub> = 0.988 ± 0.002, <abbrev xlink:title="area under the curve">AUC</abbrev><sub>Test</sub> = 0.980 ± 0.005, <abbrev xlink:title="True Statistical Skill">TSS</abbrev><sub>Train</sub> = 0.877 ± 0.023, and <abbrev xlink:title="True Statistical Skill">TSS</abbrev><sub>Test</sub> = 0.837 ± 0.059. All empirical models presented significantly higher discrimination metrics than null models (p-value<sub>AUC</sub> = &lt; 0.001; p-value<sub>TSS</sub> = &lt; 0.001), confirming that the empirical model significantly outperformed the null model (Suppl. material <xref ref-type="supplementary-material" rid="S6">6</xref>).</p>
          <p>The daily maximum air temperature of the warmest month (bio5) was the most influential predictor variable (mean contribution: 31.4%) during model training, followed by the mean monthly precipitation amount of the driest quarter (bio17: 19.7%) and precipitation seasonality (bio15: 17.0%). The annual range of air temperature (bio7: 16.3%) and the mean monthly precipitation amount of the wettest quarter (bio16: 15.7%) showed lower but still notable contributions. Permutation importance showed a different pattern, with bio16 (37.3%), bio5 (34.2%), and bio15 (22.2%) having the greatest influence on model stability, whereas bio17 (5.3%) and bio7 (0.9%) the lowest (Suppl. material <xref ref-type="supplementary-material" rid="S7">7</xref>).</p>
        </sec>
        <sec sec-type="Past range shifts on Pleurodema guayapae" id="sec10">
          <title>Past range shifts on <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic></title>
          <p>Our species distribution modelling results suggest a dynamic history of habitat connectivity and fragmentation for <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> since the <abbrev xlink:title="Last Glacial Maximum">LGM</abbrev>. During the <abbrev xlink:title="Last Glacial Maximum">LGM</abbrev> (ca. 21 ka), our projections show a nearly continuous and potentially connected distribution extending from Paraguay and Bolivia southward to Córdoba city in Argentina, with a central zone exhibiting slightly lower habitat suitability (ca. 0.5). In the subsequent Heinrich Stadial (17–14.7 ka), habitat suitability decreased sharply across the entire study area, reaching a maximum of only 0.5. During this period, two isolated clusters of suitable habitat emerged: one near Parque Nacional Translasierra close to Córdoba in Argentina and the second —representing the most suitable conditions— near the current border between Argentina, Paraguay, and Bolivia. During the Bølling-Allerød period (14.7–12.9 ka), habitat suitability generally increased within the clusters, particularly in the Argentine-Paraguayan-Bolivian cluster, which expanded northward into Bolivia and Paraguay. A third suitable habitat cluster also emerged near the present-day southeastern border between Bolivia and Brazil. More recently, during the Younger Dryas (12.9–11.7 ka) and Greenlandian (11,7–8.3 ka), habitat suitability rose in these transborder clusters, forming a continuous cluster of suitable habitats across Bolivia, Paraguay, and Brazil. The Córdoba cluster, which appeared during the Heinrich Stadial and persisted during the Bølling-Allerød, also expanded and increased its suitability near Córdoba. From the Greenlandian onward, these two clusters (i.e., transborder and Córdoba cluster) consolidated into a single suitable cluster according to the binary models. However, while the transborder cluster was once uniform in habitat suitability during the Greenlandian, it gradually fragmented, showing regions with significantly higher suitability than others. This pattern may reflect a stepping-stone process during the Northgrippian (around 4,200 years ago), ultimately leading to the current disjunct distribution. Although our binary models indicate that suitable habitat for <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> currently extends from Bolivia to Argentina, suitability in the intervening regions is relatively low (ca. 0.4; see Fig. <xref ref-type="fig" rid="F2">2</xref>).</p>
          <fig id="F2">
            <object-id content-type="doi">10.21425/fob.19.208301.figure2</object-id>
            <object-id content-type="arpha">8F80DEC2-3E5A-555C-9BCB-54588311B033</object-id>
            <label>Figure 2.</label>
            <caption>
              <p>Maxent heat maps showing the habitat suitability of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> today and through past climatic periods. The black boundary line in each map represents the area predicted as suitable as in the binary maps. The upper left map shows the study area in South America along with the sampling localities.</p>
            </caption>
            <graphic xlink:href="biogeography-19-001_article-208301__-g002.jpg" id="oo_1788932.jpg">
              <uri content-type="original_file">https://binary.pensoft.net/fig/1788932</uri>
            </graphic>
          </fig>
        </sec>
      </sec>
    </sec>
    <sec sec-type="Discussion" id="sec11">
      <title>Discussion</title>
      <p>Despite the substantial ~ 820 km geographic gap between the two known population clusters of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> —an area lacking occurrence records of the species even after decades of field surveys (see Suppl. material <xref ref-type="supplementary-material" rid="S4">4</xref>)— Bolivian and Argentine populations show no significant genetic divergence in the mitochondrial markers analyzed (<italic><abbrev xlink:title="16S rRNA">16S</abbrev></italic> and <italic><abbrev xlink:title="cytochrome-b">Cyt-b</abbrev></italic>) and do not form reciprocally monophyletic clades. These findings suggest that the observed disjunct distribution likely reflects a relative recent process rather than prolonged isolation. The fact that these populations do not represent genetically distinct lineages at mitochondrial level primarily supports the hypothesized true disjunct (i.e., bicentric) distribution of a single species. Nonetheless, data from nuclear genes are needed to test whether population structure or isolation exists but is obscured by mitochondrial introgression.</p>
      <p>The most intuitive explanation would be to attribute the disjunct distribution to a sampling bias. Many <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> species, among them <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic>, spend much of the year buried, which hampers detectability outside of explosive breeding events that occur during brief and unpredictable windows of optimal environmental conditions (<xref ref-type="bibr" rid="B18">De la Riva and Gonzales 1998</xref>; <xref ref-type="bibr" rid="B85">Valetti et al. 2014</xref>). It would seem therefore plausible that undetected populations might occur in the intermediate areas. However, this appears unlikely because the regions between the known population clusters of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> have been relatively well surveyed from a herpetological standpoint (e.g., <xref ref-type="bibr" rid="B50">Lavilla and Scrocchi 1991</xref>; <xref ref-type="bibr" rid="B17">Cruz et al. 1992</xref>), with survey intensity (i.e., number of reptile and amphibian specimen records) comparable to, or greater than, that of the localities where the species has actually been recorded (see Suppl. material <xref ref-type="supplementary-material" rid="S4">4</xref> for distribution and sampling intensity maps of amphibian and reptile records within the study area). Furthermore, despite the species’ secretive habits, <xref ref-type="bibr" rid="B74">Schalk and Saenz (2016)</xref> reported calling activity from January to May and again in October —thus substantially extending the potential detection window. Moreover, <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> lays eggs in floating foam nests and has exotrophic tadpoles that develop in lentic water bodies (<xref ref-type="bibr" rid="B85">Valetti et al. 2014</xref>), both of which are conspicuous and increase the likelihood of detection. These factors strongly suggest that the species is genuinely absent from the intervening region, and thus we can assume that the mentioned gap is real and not a human artifact due to lack of surveys. However, in order to confirm this hypothesis, we recommend that future herpetological surveys in the intervening area put a special focus on the species by searching in appropriate environments, especially during explosive breeding events of other chacoan amphibians, and by checking the identity of the tadpoles found at temporal water bodies.</p>
      <p>Once the sampling bias is discarded, the disjunct distribution pattern of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> may have two alternative explanations: long recent dispersal, or a complex history shaped by climate changes and including local extinctions.</p>
      <p>The first hypothesis is that the observed distribution results from a recent long-distance dispersal event. Amphibians are generally poor long-distance dispersers (<xref ref-type="bibr" rid="B21">Duellman and Trueb 1986</xref>) due to small body size, physiological constraints, habitat specificity, and phylopatry, making such events rare and typically passive (<xref ref-type="bibr" rid="B54">Marin da Fonte et al. 2019</xref>; <xref ref-type="bibr" rid="B60">Owen and Taylor 2023</xref>). If such a dispersal occurred, it was likely human-mediated. This hypothesis gains some support from the fact that all known Bolivian populations of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> occur in anthropogenic habitats (<xref ref-type="bibr" rid="B18">De la Riva and Gonzales 1998</xref>), suggesting that human-altered landscapes may have facilitated the passive transport and establishment of individuals—possibly through the movement of soil or agricultural materials where frogs could have been concealed. The fact that most Bolivian localities of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> are along the railway connecting Bolivia and Argentina might support this possibility; however, the trains do not continue southwards from the Bolivian border, and from that point (Yacuiba) there is still a gap &gt; 550 km airline to the closest <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> localities in Santiago del Estero. Thus, the plausibility of a human introduction is limited, as transporting material from rural areas over more than 800 km with no direct connections and across international borders is logistically unlikely.</p>
      <p>According to our results, the most plausible explanation for the current disjunct distribution is that past climate fluctuations triggered multiple episodes of range fragmentation, contraction, and expansion since the <abbrev xlink:title="Last Glacial Maximum">LGM</abbrev> (Fig. <xref ref-type="fig" rid="F2">2</xref>). During the Heinrich Stadial and Bølling-Allerød periods, several isolated but climatically suitable habitat clusters emerged (see Results). However, declines in habitat suitability in subsequent periods suggest that any populations occupying many of these clusters may have undergone local extinction. Throughout all periods, the most suitable habitat cluster occurred near the borders between Argentina, Paraguay, and Bolivia, suggesting that this region may have acted as a source cluster for the species’ present distribution. Habitat suitability patterns during the Northgrippian (8.3–4.2 ka) further suggest that the formerly monocentric core became fragmented in multiple clusters, and that this fragmentation, combined with subsequent range contractions to the centers of these clusters ultimately shaped the current disjunct distribution.</p>
      <p>In our area of study, some investigations have dealt with disjunct distributions shown by populations of non-chacoan species now occupying different biogeographic domains or main ecosystems, for which the Pleistocene climatic fluctuations meant distributional shifts across what is today the chacoan realm—for example, the harvestmen <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Geraeocormobius">Geraeocormobius</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="sylvarum">sylvarum</tp:taxon-name-part></tp:taxon-name></italic> and <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Discocyrtus">Discocyrtus</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="dilatatus">dilatatus</tp:taxon-name-part></tp:taxon-name></italic> (<xref ref-type="bibr" rid="B1">Acosta et al. 2007</xref>; <xref ref-type="bibr" rid="B87">Vergara et al. 2017</xref>). Likewise, many chacoan organisms experienced distributional shifts during those climatic fluctuations, as the ecosystem moved northwards during cool periods and recovered during warm ones, causing range expansions and contractions and leading to the disjunct or patchy distributional patterns observed today. Some examples include certain leguminous plants (<xref ref-type="bibr" rid="B70">Robbiati et al. 2021</xref>; <xref ref-type="bibr" rid="B80">Sinani et al. 2022</xref>), palms (<xref ref-type="bibr" rid="B79">Silva et al. 2023</xref>), and mammals (<xref ref-type="bibr" rid="B27">Ferreiro et al. 2022</xref>). Among amphibians, the most striking case of disjunct distribution is that of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> reported herein. However, it is not an isolated case: within the same study area, <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Chacophrys">Chacophrys</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="pierottii">pierottii</tp:taxon-name-part></tp:taxon-name></italic> shows a similar pattern that warrants further investigation (<xref ref-type="bibr" rid="B40">IUCN SSC Amphibian Specialist Group 2021a</xref>), and so does <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Lepidobatrachus">Lepidobatrachus</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="llanensis">llanensis</tp:taxon-name-part></tp:taxon-name></italic> (<xref ref-type="bibr" rid="B41">IUCN SSC Amphibian Specialist Group 2021b</xref>), whose disjunct populations have already been genetically confirmed to be conspecific (<xref ref-type="bibr" rid="B24">Faivovich et al. 2012</xref>).</p>
      <p>The Gran Chaco ecoregion, which expands over more than one million square kilometers across Argentina, Bolivia, Brazil, and Paraguay, is suffering a catastrophic rate of deforestation and alteration, mostly due to the expansion of intensive agriculture, cattle ranching, and fires (see <xref ref-type="bibr" rid="B57">Mosciaro et al. 2022</xref>, and references therein). Altered habitats can act as ecological filters, modulating the response of amphibian communities to land-use conversion in a way that does not necessarily follow a simple richness-decline pattern (<xref ref-type="bibr" rid="B3">Assmann et al. 2026</xref>). Some species of amphibians like <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> seem to tolerate a certain degree of human perturbation, and likely have not been as drastically affected by land use changes as others (see <xref ref-type="bibr" rid="B55">Medina et al. 2016</xref>). In the future, the systematic and rapid destruction of this rich ecosystem might extirpate many organisms characteristic of it, including species that remain poorly studied, thus precluding the understanding of their distributional patterns and the past processes that shaped them. In such an undesirable scenario, questions as intriguing as the disjunct distribution of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> might never be addressed.</p>
    </sec>
    <sec sec-type="Conclusion" id="sec12">
      <title>Conclusion</title>
      <p>Twenty-seven years after the discovery of the Bolivian populations of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic>, we demonstrate that, despite the ca. 800 km separating the two geographic clusters and the absence of records from the intervening areas notwithstanding extensive sampling efforts, the Bolivian populations are conspecific with those from Argentina. This represents a striking example of a true disjunct distribution in amphibians, likely resulting from repeated range expansions and contractions driven by past climatic oscillations.</p>
    </sec>
  </body>
  <back>
    <ack>
      <title>Acknowledgments</title>
      <p>We thank Dolores Casagranda and Daiana Ferraro for providing precise locality coordinates of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic> in Argentina, and to Julián Faivovich for his useful comment and insights on <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> systematics. We are grateful to Esther Langan (USNM) for providing data and pictures on the specimens under her care, and to Esteban O. Lavilla for his timely comments about the distribution and ecology of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Pleurodema">P.</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="guayapae">guayapae</tp:taxon-name-part></tp:taxon-name></italic>. Finally, we also thank Lourdes Alcaraz for her work at the laboratory and to Malena Vaca for her help transporting specimens. Loan and exportation of specimens was authorized by Kathia Rivero and Luzmila Arroyo (MHNNKM). We thank the editor-in-chief, Rob Whittaker, the subject editor, Larry Heaney, as well as Stefan Lötters, and one anonymous reviewer for their valuable comments and suggestions.</p>
    </ack>
    <ref-list>
      <title>References</title>
      <ref id="B1">
        <mixed-citation>Acosta LE, Kury AB, Juárez ML (2007) New records of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Geraeocormobius</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">sylvarum</tp:taxon-name-part></tp:taxon-name></italic> (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="class">Arachnida</tp:taxon-name-part></tp:taxon-name>, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Opiliones</tp:taxon-name-part></tp:taxon-name>, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Gonyleptidae</tp:taxon-name-part></tp:taxon-name>), with a remarkable disjunction in northwestern Argentina. Boletín de la Sociedad Entomológica Aragonesa 41: 303–306.</mixed-citation>
      </ref>
      <ref id="B2">
        <mixed-citation>Allouche O, Tsoar A, Kadmon R (2006) Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology 43: 1223–1232. <ext-link xlink:href="10.1111/j.1365-2664.2006.01214.x" ext-link-type="doi">https://doi.org/10.1111/j.1365-2664.2006.01214.x</ext-link></mixed-citation>
      </ref>
      <ref id="B3">
        <mixed-citation>Assmann BR, Lima-Rezende CA, Loebens CM, Rezende RS (2026) Contrasting responses of amphibian taxonomic and functional diversity to agriculture and silviculture in subtropical fragmented landscapes. Agriculture, Ecosystems and Environment 412: 110701</mixed-citation>
      </ref>
      <ref id="B4">
        <mixed-citation>Baldo G, Gutiérrez M (1997) Sobre la presencia del género <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Anura</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leptodactylidae</tp:taxon-name-part></tp:taxon-name>) en el noroeste de la provincia de Córdoba, con especial referencia a <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">nebulosa</tp:taxon-name-part></tp:taxon-name></italic>. Cuadernos de Herpetología 11: 71–74.</mixed-citation>
      </ref>
      <ref id="B5">
        <mixed-citation>Barber RA, Ball SG, Morris RK, Gilbert F (2022) Target-group backgrounds prove effective at correcting sampling bias in Maxent models. Diversity and Distributions 28: 128–141. <ext-link xlink:href="10.1111/ddi.13442" ext-link-type="doi">https://doi.org/10.1111/ddi.13442</ext-link></mixed-citation>
      </ref>
      <ref id="B6">
        <mixed-citation>Barlow J, França F, Gardner TA, Hicks CC, Lennox GD, Berenguer E, Castello L, Economo EP, Ferreira J, Guénard B, Leal CG, Isaac V, Lees AC, Parr CL, Wilson SK, Young PJ, Graham NAJ (2018) The future of hyperdiverse tropical ecosystems. Nature 559: 517–526. <ext-link xlink:href="10.1038/s41586-018-0301-1" ext-link-type="doi">https://doi.org/10.1038/s41586-018-0301-1</ext-link></mixed-citation>
      </ref>
      <ref id="B7">
        <mixed-citation>Barrio A (1964) Especies crípticas del género <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> que conviven en una misma área identificadas por el canto nupcial (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Anura</tp:taxon-name-part></tp:taxon-name>, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leptodactylidae</tp:taxon-name-part></tp:taxon-name>). Physis 24: 471–489.</mixed-citation>
      </ref>
      <ref id="B8">
        <mixed-citation>Booth TH (2022) Checking bioclimatic variables that combine temperature and precipitation data before their use in species distribution models. Austral Ecology 47: 1506–1514. <ext-link xlink:href="10.1111/aec.13234" ext-link-type="doi">https://doi.org/10.1111/aec.13234</ext-link></mixed-citation>
      </ref>
      <ref id="B9">
        <mixed-citation>Brito D (2010) Overcoming the Linnean shortfall: Data deficiency and biological survey priorities. Basic and Applied Ecology 11: 709–713. <ext-link xlink:href="10.1016/j.baae.2010.09.007" ext-link-type="doi">https://doi.org/10.1016/j.baae.2010.09.007</ext-link></mixed-citation>
      </ref>
      <ref id="B10">
        <mixed-citation>Brown JL, Hill DJ, Dolan AM, Carnaval AC, Haywood AM (2018) PaleoClim, high spatial resolution paleoclimate surfaces for global land areas. Scientific Data 5: 1–9. <ext-link xlink:href="10.1038/sdata.2018.254" ext-link-type="doi">https://doi.org/10.1038/sdata.2018.254</ext-link></mixed-citation>
      </ref>
      <ref id="B11">
        <mixed-citation>Burmeister H (1861) Reise durch die La Plata-Staaten mit besonderer Rücksicht auf die physische Beschaffenheit und den Culturzustand der argentinischen Republik: Ausgeführt in den Jahren 1857, 1858, 1859 und 1860. Vol. 2. H. W. Schmidt.</mixed-citation>
      </ref>
      <ref id="B12">
        <mixed-citation>Carné A, Vieites DR (2024) A race against extinction: The challenge to overcome the Linnean amphibian shortfall in tropical biodiversity hotspots. Diversity and Distributions 30: e13912. <ext-link xlink:href="10.1111/ddi.13912" ext-link-type="doi">https://doi.org/10.1111/ddi.13912</ext-link></mixed-citation>
      </ref>
      <ref id="B13">
        <mixed-citation>Carné A, Vieites DR, Ferrer X, Moreno M, Ponz-Segrelles G, Rahagalala NA, Rakotomanaga SE, Ramon-Laca A, Ratsoavina FM, van den Burg MP (2025) Microendemism in Madagascar: Small ranges or sampling gaps? The case of the frog <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Wakea</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">madinika</tp:taxon-name-part></tp:taxon-name></italic>. Salamandra 61: 160–170.</mixed-citation>
      </ref>
      <ref id="B14">
        <mixed-citation>Carné A, Sánchez-Vialas A, Lansac C, Moreno-Orosa M, De la Riva I (2026) Croaking for haste: How long does it take to describe a frog species since its discovery? PLoS ONE 21: e0323855. <ext-link xlink:href="10.1371/journal.pone.0323855" ext-link-type="doi">https://doi.org/10.1371/journal.pone.0323855</ext-link></mixed-citation>
      </ref>
      <ref id="B15">
        <mixed-citation>Carranza S, Amat F (2005) Taxonomy, biogeography and evolution of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Euproctus</tp:taxon-name-part></tp:taxon-name></italic> (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="class">Amphibia</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Salamandridae</tp:taxon-name-part></tp:taxon-name>), with the resurrection of the genus <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Calotriton</tp:taxon-name-part></tp:taxon-name></italic> and the description of a new endemic species from the Iberian Peninsula. Zoological Journal of the Linnean Society 145: 555–582. <ext-link xlink:href="10.1111/j.1096-3642.2005.00197.x" ext-link-type="doi">https://doi.org/10.1111/j.1096-3642.2005.00197.x</ext-link></mixed-citation>
      </ref>
      <ref id="B16">
        <mixed-citation>Cei JM (1980) Amphibians of Argentina. Monitore Zoologico Italiano, New Series, Monograph 2: 1–609.</mixed-citation>
      </ref>
      <ref id="B17">
        <mixed-citation>Cruz FB, Perotti MG, Fitzgerald LA (1992) Lista de anfibios y reptiles colectados en una localidad del Chaco salteño. Acta Zoológica Lilloana 42: 101–107.</mixed-citation>
      </ref>
      <ref id="B18">
        <mixed-citation>De la Riva I, Gonzales L (1998) Sobre la presencia de <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">guayapae</tp:taxon-name-part></tp:taxon-name></italic> Barrio, 1964 (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Anura</tp:taxon-name-part></tp:taxon-name>, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leptodactylidae</tp:taxon-name-part></tp:taxon-name>) en Bolivia. Alytes 16: 68–76.</mixed-citation>
      </ref>
      <ref id="B19">
        <mixed-citation>De la Riva I, Köhler J, Lötters S, Reichle S (2000) Ten years of research on Bolivian amphibians: Updated checklist, distribution, taxonomic problems, literature, and iconography. Revista Española de Herpetología 14: 19–164.</mixed-citation>
      </ref>
      <ref id="B20">
        <mixed-citation>Dubos N, Morel L, Crottini A, Freeman K, Honoré J, Lava H, Noël J, Porton I, Rendrirednry G, Rosa GM, Andreone F (2020) High interannual variability of a climate-driven amphibian community in a seasonal rainforest. Biodiversity and Conservation 29: 893–912. <ext-link xlink:href="10.1007/s10531-019-01916-3" ext-link-type="doi">https://doi.org/10.1007/s10531-019-01916-3</ext-link></mixed-citation>
      </ref>
      <ref id="B21">
        <mixed-citation>Duellman WE, Trueb L (1986) Biology of amphibians. McGraw-Hill, New York. <ext-link xlink:href="10.2307/1445022" ext-link-type="doi">https://doi.org/10.2307/1445022</ext-link></mixed-citation>
      </ref>
      <ref id="B22">
        <mixed-citation>Duellman WE, Veloso A (1977) Phylogeny of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Anura</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leptodactylidae</tp:taxon-name-part></tp:taxon-name>): A biogeographic model. Occasional Papers of the Museum of Natural History, University of Kansas 64: 1–46.</mixed-citation>
      </ref>
      <ref id="B23">
        <mixed-citation>Elith J, Graham CH, Anderson RP, Dudík M, Ferrier S, Guisan A, Hijmans RJ, Huettmann F, Leathwick JR, Lehmann A, Li J, Lohmann LG, Loiselle BA, Manion G, Moritz C, Nakamura M, Nakazawa Y, Overton JMcC, Peterson AT, Phillips SJ, Richardson K, Scachetti-Pereira R, Schapire RE, Soberón J, Williams S, Wisz MS, Zimmermann NE (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29: 129–151. <ext-link xlink:href="10.1111/j.2006.0906-7590.04596.x" ext-link-type="doi">https://doi.org/10.1111/j.2006.0906-7590.04596.x</ext-link></mixed-citation>
      </ref>
      <ref id="B24">
        <mixed-citation>Faivovich J, Ferraro DP, Basso NG, Haddad CFB, Rodrigues MT, Wheeler WC, Lavilla EO (2012) A phylogenetic analysis of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Anura</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leptodactylidae</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="subfamily">Leiuperinae</tp:taxon-name-part></tp:taxon-name>) based on mitochondrial and nuclear gene sequences, with comments on the evolution of anuran foam nests. Cladistics 28: 460–482. <ext-link xlink:href="10.1111/j.1096-0031.2012.00406" ext-link-type="doi">https://doi.org/10.1111/j.1096-0031.2012.00406</ext-link></mixed-citation>
      </ref>
      <ref id="B25">
        <mixed-citation>Ferraro DP (2022) Combined phylogenetic analysis of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Anura</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leptodactylidae</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="subfamily">Leiuperinae</tp:taxon-name-part></tp:taxon-name>). Cladistics 38: 301–319. <ext-link xlink:href="10.1111/cla.12497" ext-link-type="doi">https://doi.org/10.1111/cla.12497</ext-link></mixed-citation>
      </ref>
      <ref id="B26">
        <mixed-citation>Ferraro DP, Casagranda MD (2009) Geographic distribution of the genus <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part></tp:taxon-name></italic> in Argentina (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Anura</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leiuperidae</tp:taxon-name-part></tp:taxon-name>). Zootaxa 2024: 33–55. <ext-link xlink:href="10.11646/zootaxa.2024.1.2" ext-link-type="doi">https://doi.org/10.11646/zootaxa.2024.1.2</ext-link></mixed-citation>
      </ref>
      <ref id="B27">
        <mixed-citation>Ferreiro AM, Soibelzon E, Pinotti JD, Poljak S, Chiappero MB (2022) Reconstructing the distribution of Chacoan biota from current and past evidence: The case of the southern three-banded armadillo <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Tolypeutes</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">matacus</tp:taxon-name-part></tp:taxon-name></italic> (Desmarest, 1804). Journal of Mammalian Evolution 29: 783–795. <ext-link xlink:href="10.1007/s10914-022-09627-3" ext-link-type="doi">https://doi.org/10.1007/s10914-022-09627-3</ext-link></mixed-citation>
      </ref>
      <ref id="B28">
        <mixed-citation>Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24: 38–49. <ext-link xlink:href="10.1017/S0376892997000088" ext-link-type="doi">https://doi.org/10.1017/S0376892997000088</ext-link></mixed-citation>
      </ref>
      <ref id="B29">
        <mixed-citation>Fok KW, Wade CM, Parkin DT (2002) Inferring the phylogeny of disjunct populations of the azure-winged magpie <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Cyanopica</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">cyanus</tp:taxon-name-part></tp:taxon-name></italic> from mitochondrial control region sequences. Proceedings of the Royal Society B: Biological Sciences 269: 1671–1678. <ext-link xlink:href="10.1098/rspb.2002.2057" ext-link-type="doi">https://doi.org/10.1098/rspb.2002.2057</ext-link></mixed-citation>
      </ref>
      <ref id="B30">
        <mixed-citation>Frost DR (2026) Amphibian species of the world: An online reference. Version 6.2. American Museum of Natural History. <ext-link xlink:href="https://amphibiansoftheworld.amnh.org" ext-link-type="uri">https://amphibiansoftheworld.amnh.org</ext-link> [Visited on 28/02/2026]</mixed-citation>
      </ref>
      <ref id="B31">
        <mixed-citation>Frost DR, Grant T, Faivovich J, Bain RH, Haas A, Haddad CFB, de Sá RO, Channing A, Wilkinson M, Donnellan SC, Raxworthy CJ, Campbell JA, Blotto BL, Moler P, Drewes RC, Nussbaum RA, Lynch JD, Green DM, Wheeler WC (2006) The amphibian tree of life. Bulletin of the American Museum of Natural History 297: 1–291. <ext-link xlink:href="10.1206/0003-0090(2006)297%5B0001:TATOL%5D2.0.CO;2" ext-link-type="doi">https://doi.org/10.1206/0003-0090(2006)297[0001:TATOL]2.0.CO;2</ext-link></mixed-citation>
      </ref>
      <ref id="B32">
        <mixed-citation>GBIF.org (2025a) GBIF Occurrence Download. <ext-link xlink:href="10.15468/dl.ppuxrq" ext-link-type="doi">https://doi.org/10.15468/dl.ppuxrq</ext-link></mixed-citation>
      </ref>
      <ref id="B33">
        <mixed-citation>GBIF.org (2025b) GBIF Occurrence Download. <ext-link xlink:href="10.15468/dl.kkczh5" ext-link-type="doi">https://doi.org/10.15468/dl.kkczh5</ext-link></mixed-citation>
      </ref>
      <ref id="B34">
        <mixed-citation>Guerreiro A, Baldoni JC, Brigada AM (2005) Herpetofauna de Sierra de las Quijadas (San Luis, Argentina). Gayana 69: 6–9. <ext-link xlink:href="10.4067/S0717-65382005000100002" ext-link-type="doi">https://doi.org/10.4067/S0717-65382005000100002</ext-link></mixed-citation>
      </ref>
      <ref id="B35">
        <mixed-citation>Harrison S (1991) Local extinction in a metapopulation context: An empirical evaluation. Biological Journal of the Linnean Society 42: 73–88. <ext-link xlink:href="10.1111/j.1095-8312.1991.tb00552.x" ext-link-type="doi">https://doi.org/10.1111/j.1095-8312.1991.tb00552.x</ext-link></mixed-citation>
      </ref>
      <ref id="B36">
        <mixed-citation>Hernandez PA, Graham CH, Master LL, Albert DL (2006) The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29: 773–785. <ext-link xlink:href="10.1111/j.0906-7590.2006.04700.x" ext-link-type="doi">https://doi.org/10.1111/j.0906-7590.2006.04700.x</ext-link></mixed-citation>
      </ref>
      <ref id="B37">
        <mixed-citation>Hijmans RJ (2023) predicts: Spatial prediction tools. R package version 0.1-11. <ext-link xlink:href="10.32614/CRAN.package.predicts" ext-link-type="doi">https://doi.org/10.32614/CRAN.package.predicts</ext-link></mixed-citation>
      </ref>
      <ref id="B38">
        <mixed-citation>Hödl W (1992) Reproductive behavior in the neotropical foam-nesting frog <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">diplolistris</tp:taxon-name-part></tp:taxon-name></italic> (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leptodactylidae</tp:taxon-name-part></tp:taxon-name>). <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="class">Amphibia</tp:taxon-name-part></tp:taxon-name>-<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="superclass">Reptilia</tp:taxon-name-part></tp:taxon-name> 13: 263–274. <ext-link xlink:href="10.1163/156853892X00472" ext-link-type="doi">https://doi.org/10.1163/156853892X00472</ext-link></mixed-citation>
      </ref>
      <ref id="B39">
        <mixed-citation>Holt BG, Lessard JP, Borregaard MK, Fritz SA, Araújo MB, Dimitrov D, Fabre PH, Graham CH, Graves GR, Jønsson KA, Nogués-Bravo D, Wang Z, Whittaker RJ, Fjeldså J, Rahbek C (2013) An update of Wallace’s zoogeographic regions of the world. Science 339: 74–78. <ext-link xlink:href="10.1126/science.1228282" ext-link-type="doi">https://doi.org/10.1126/science.1228282</ext-link></mixed-citation>
      </ref>
      <ref id="B40">
        <mixed-citation>IUCN SSC Amphibian Specialist Group (2021a) <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Chacophrys</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">pierottii</tp:taxon-name-part></tp:taxon-name></italic>. The IUCN Red List of Threatened Species 2021: e.T56343A101427950. <ext-link xlink:href="10.2305/IUCN.UK.2021-3.RLTS.T56343A101427950.en" ext-link-type="doi">https://doi.org/10.2305/IUCN.UK.2021-3.RLTS.T56343A101427950.en</ext-link> [Visited on 28/02/2026]</mixed-citation>
      </ref>
      <ref id="B41">
        <mixed-citation>IUCN SSC Amphibian Specialist Group (2021b) <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Lepidobatrachus</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">llanensis</tp:taxon-name-part></tp:taxon-name></italic>. The IUCN Red List of Threatened Species 2021: e.T57112A101428639. <ext-link xlink:href="10.2305/IUCN.UK.2021-3.RLTS.T57112A101428639.en" ext-link-type="doi">https://doi.org/10.2305/IUCN.UK.2021-3.RLTS.T57112A101428639.en</ext-link> [Visited on 28/02/2026]</mixed-citation>
      </ref>
      <ref id="B42">
        <mixed-citation>Jiménez-Valverde A, Lobo JM (2007) Threshold criteria for conversion of probability of species presence to either–or presence–absence. Acta Oecologica 31: 361–369. <ext-link xlink:href="10.1016/j.actao.2007.02.001" ext-link-type="doi">https://doi.org/10.1016/j.actao.2007.02.001</ext-link></mixed-citation>
      </ref>
      <ref id="B43">
        <mixed-citation>Katoh K, Rozewicki J, Yamada KD (2019) MAFFT online service: Multiple sequence alignment, interactive sequence choice and visualization. Briefings in Bioinformatics 20: 1160–1166. <ext-link xlink:href="10.1093/bib/bbx108" ext-link-type="doi">https://doi.org/10.1093/bib/bbx108</ext-link></mixed-citation>
      </ref>
      <ref id="B44">
        <mixed-citation>Kocher TD, Thomas WK, Meyer A, Edwards SV, Pääbo S, Villablanca FX, Wilson AC (1989) Dynamics of mitochondrial DNA evolution in animals: Amplification and sequencing with conserved primers. Proceedings of the National Academy of Sciences 86: 6196–6200. <ext-link xlink:href="10.1073/pnas.86.16.6196" ext-link-type="doi">https://doi.org/10.1073/pnas.86.16.6196</ext-link></mixed-citation>
      </ref>
      <ref id="B45">
        <mixed-citation>Köhler J, Vieites DR, Bonett RM, Hita García F, Glaw F, Steinke D, Vences M (2005) New amphibians and global conservation: A boost in species discoveries in a highly endangered vertebrate group. BioScience 55: 693–696. <ext-link xlink:href="10.1641/0006-3568(2005)055%5B0693:NAAGCA%5D2.0.CO;2" ext-link-type="doi">https://doi.org/10.1641/0006-3568(2005)055[0693:NAAGCA]2.0.CO;2</ext-link></mixed-citation>
      </ref>
      <ref id="B46">
        <mixed-citation>Kremen C, Cameron A, Moilanen A, Phillips SJ, Thomas CD, Beentje H, Dransfield J, Fisher BL, Glaw F, Good TC, Harper GJ, Hijmans RJ, Lees DC, Louis Jr E, Nussbaum RA, Raxworthy CJ, Razafimpahanana A, Schatz GE, Vences M, Vieites DR, Wright PC, Zjhra ML (2008) Aligning conservation priorities across taxa in Madagascar with high-resolution planning tools. Science 320: 222–226. <ext-link xlink:href="10.1126/science.1155193" ext-link-type="doi">https://doi.org/10.1126/science.1155193</ext-link></mixed-citation>
      </ref>
      <ref id="B47">
        <mixed-citation>Kropf M, Comes HP, Kadereit JW (2006) Long-distance dispersal vs vicariance: The origin and genetic diversity of alpine plants in the Spanish Sierra Nevada. New Phytologist 172: 169–184. <ext-link xlink:href="10.1111/j.1469-8137.2006.01795.x" ext-link-type="doi">https://doi.org/10.1111/j.1469-8137.2006.01795.x</ext-link></mixed-citation>
      </ref>
      <ref id="B48">
        <mixed-citation>Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) MEGA X: Molecular evolutionary genetics analysis across computing platforms. Molecular Biology and Evolution 35: 1547–1549. <ext-link xlink:href="10.1093/molbev/msy096" ext-link-type="doi">https://doi.org/10.1093/molbev/msy096</ext-link></mixed-citation>
      </ref>
      <ref id="B49">
        <mixed-citation>Lanfear R, Frandsen PB, Wright AM, Senfeld T, Calcott B (2017) PartitionFinder 2: New methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Molecular Biology and Evolution 34: 772–773. <ext-link xlink:href="10.1093/molbev/msw260" ext-link-type="doi">https://doi.org/10.1093/molbev/msw260</ext-link></mixed-citation>
      </ref>
      <ref id="B50">
        <mixed-citation>Lavilla EO, Scrocchi GJ (1991) Aportes a la herpetología del Chaco argentino. I. Lista comentada de los taxa colectados por la Expedición PRHERP 1985. Acta Zoológica Lilloana 60: 21–32.</mixed-citation>
      </ref>
      <ref id="B51">
        <mixed-citation>Leigh JW, Bryant D (2015) PopART: Full-feature software for haplotype network construction. Methods in Ecology and Evolution 6: 1110–1116. <ext-link xlink:href="10.1111/2041-210X.12410" ext-link-type="doi">https://doi.org/10.1111/2041-210X.12410</ext-link></mixed-citation>
      </ref>
      <ref id="B52">
        <mixed-citation>Lomolino MV (2004) Conservation biogeography. In: Lomolino MV, Heaney LR (Eds) Frontiers of biogeography: New directions in the geography of nature. Sinauer Associates, 293–296.</mixed-citation>
      </ref>
      <ref id="B53">
        <mixed-citation>Luedtke JA, Chanson J, Neam K, Hobin L, Maciel AO, Catenazzi A, Borzée A, Hamidy A, Aowphol A, Jean A, Sosa-Bartuano Á, Fong AFG, de Silva A, Fouquet A, Angulo A, Kidov AA, Muñoz Saravia A, Diesmos AC, Tominaga A, Shrestha B, Gratwicke B, Tjaturadi B, Martínez Rivera CC, Vásquez Almazán CR, Señaris C, Chandramouli SR, Strüssmann C, Cortez Fernández CF, Azat C, Hoskin CJ, Hilton-Taylor C, Whyte DL, Gower DJ, Olson DH, Cisneros-Heredia DF, Santana DJ, Nagombi E, Najafi-Majd E, Quah ESH, Bolaños F, Xie F, Brusquetti F, Álvarez FS, Andreone F, Glaw F, Castañeda FE, Kraus F, Parra-Olea G, Chaves G, Medina-Rangel GF, González-Durán G, Ortega-Andrade HM, Machado IF, Das I, Ribeiro Dias I, Urbina-Cardona JN, Crnobrnja-Isailović J, Yang JH, Jianping J, Wangyal JT, Rowley JJL, Measey J, Vasudevan K, Chan KO, Gururaja KV, Ovaska K, Warr LC, Canseco-Márquez L, Toledo LF, Díaz LM, Khan MMH, Meegaskumbura M, Acevedo ME, Napoli MF, Ponce MA, Vaira M, Lampo M, Yáñez-Muñoz MH, Scherz MD, Rödel M-O, Matsui M, Fildor M, Kusrini MD, Ahmed MF, Rais M, Kouamé NG, García N, Gonwouo NL, Burrowes PA, Imbun PY, Wagner P, Kok PJR, Joglar RL, Auguste RJ, Brandão RA, Ibáñez R, von May R, Hedges SB, Biju SD, Ganesh SR, Wren S, Das S, Flechas SV, Ashpole SL, Robleto-Hernández SJ, Loader SP, Incháustegui SJ, Garg SJ, Phimmachak S, Richards SJ, Slimani T, Osborne-Naikatini T, Abreu-Jardim TPF, Condez TH, de Carvalho TR, Cutajar TP, Pierson TW, Nguyen TQ, Kaya U, Yuan Z, Long B, Langhammer P, Stuart SN (2023) Ongoing declines for the world’s amphibians in the face of emerging threats. Nature 622: 308–314. <ext-link xlink:href="10.1038/s41586-023-06578-4" ext-link-type="doi">https://doi.org/10.1038/s41586-023-06578-4</ext-link></mixed-citation>
      </ref>
      <ref id="B54">
        <mixed-citation>Marin da Fonte LFMD, Mayer M, Lötters S (2019) Long-distance dispersal in amphibians. Frontiers of Biogeography 11: e44577. <ext-link xlink:href="10.21425/F5FBG44577" ext-link-type="doi">https://doi.org/10.21425/F5FBG44577</ext-link></mixed-citation>
      </ref>
      <ref id="B55">
        <mixed-citation>Medina RG, Ponssa ML, Aráoz E (2016) Environmental, land cover and land use constraints on the distributional patterns of anurans: <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Leptodactylus</tp:taxon-name-part></tp:taxon-name></italic> species (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Anura</tp:taxon-name-part></tp:taxon-name>, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leptodactylidae</tp:taxon-name-part></tp:taxon-name>) from Dry Chaco. PeerJ 4: e2605. <ext-link xlink:href="10.7717/peerj.2605" ext-link-type="doi">https://doi.org/10.7717/peerj.2605</ext-link></mixed-citation>
      </ref>
      <ref id="B56">
        <mixed-citation>Moritz C, Schneider CJ, Wake D (1992) Evolutionary relationships within the <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Ensatina</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">eschscholtzi</tp:taxon-name-part></tp:taxon-name></italic> complex confirm the ring species interpretation. Systematic Biology 41: 273–291. <ext-link xlink:href="10.1093/sysbio/41.3.273" ext-link-type="doi">https://doi.org/10.1093/sysbio/41.3.273</ext-link></mixed-citation>
      </ref>
      <ref id="B57">
        <mixed-citation>Mosciaro MJ, Calamari NC, Peri PL, Montes NF, Seghezzo L, Ortiz E, Rejalaga L, Barral P, Villarino S, Mastrangelo M, Volante J (2022) Future scenarios of land use change in the Gran Chaco: How far is zero-deforestation? Regional Environmental Change 22: 115. <ext-link xlink:href="10.1007/s10113-022-01965-5" ext-link-type="doi">https://doi.org/10.1007/s10113-022-01965-5</ext-link></mixed-citation>
      </ref>
      <ref id="B58">
        <mixed-citation>Naimi B, Hamm NA, Groen TA, Skidmore AK, Toxopeus AG (2014) Where is positional uncertainty a problem for species distribution modeling? Ecography 37: 191–203. <ext-link xlink:href="10.1111/j.1600-0587.2013.00205.x" ext-link-type="doi">https://doi.org/10.1111/j.1600-0587.2013.00205.x</ext-link></mixed-citation>
      </ref>
      <ref id="B59">
        <mixed-citation>Osorio-Olvera L, Soberón J, Falconi M (2019) On population abundance and niche structure. Ecography 42: 1415–1425. <ext-link xlink:href="10.1111/ecog.04442" ext-link-type="doi">https://doi.org/10.1111/ecog.04442</ext-link></mixed-citation>
      </ref>
      <ref id="B60">
        <mixed-citation>Owen MG, Taylor ZP (2023) Patterns of disjunction in western hemisphere birds, amphibians, crocodilians, and mammals. Physical Geography 44: 782–797. <ext-link xlink:href="10.1080/02723646.2023.2189074" ext-link-type="doi">https://doi.org/10.1080/02723646.2023.2189074</ext-link></mixed-citation>
      </ref>
      <ref id="B61">
        <mixed-citation>Palumbi SR, Martin A, Romano S, McMillan WO, Stice L, Grabowski G (1991) The simple fool’s guide to PCR. Version 2.0. Privately published, University of Hawaii.</mixed-citation>
      </ref>
      <ref id="B62">
        <mixed-citation>Pârvulescu L, Pérez-Moreno JL, Panaiotu C, Drăguț L, Schrimpf A, Popovici ID, Zaharia C, Weiperth A, Gál B, Schubart CD, Bracken-Grissom H (2019) A journey on plate tectonics sheds light on European crayfish phylogeography. Ecology and Evolution 9: 1957–1971. <ext-link xlink:href="10.1002/ece3.4888" ext-link-type="doi">https://doi.org/10.1002/ece3.4888</ext-link></mixed-citation>
      </ref>
      <ref id="B63">
        <mixed-citation>Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling 190: 231–259. <ext-link xlink:href="10.1016/j.ecolmodel.2005.03.026" ext-link-type="doi">https://doi.org/10.1016/j.ecolmodel.2005.03.026</ext-link></mixed-citation>
      </ref>
      <ref id="B64">
        <mixed-citation>Phillips SJ, Anderson RP, Dudík M, Schapire RE, Blair ME (2017) Opening the black box: An open-source release of Maxent. Ecography 40: 887–893. <ext-link xlink:href="10.1111/ecog.03049" ext-link-type="doi">https://doi.org/10.1111/ecog.03049</ext-link></mixed-citation>
      </ref>
      <ref id="B65">
        <mixed-citation>Pyron RA, Wiens JJ (2011) A large-scale phylogeny of <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="class">Amphibia</tp:taxon-name-part></tp:taxon-name> including over 2800 species, and a revised classification of extant frogs, salamanders, and caecilians. Molecular Phylogenetics and Evolution 61: 543–583. <ext-link xlink:href="10.1016/j.ympev.2011.06.012" ext-link-type="doi">https://doi.org/10.1016/j.ympev.2011.06.012</ext-link></mixed-citation>
      </ref>
      <ref id="B66">
        <mixed-citation>Quiroga LB, Sanabria EA (2009) Geographic Distribution: <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">guayapae</tp:taxon-name-part></tp:taxon-name></italic>. Herpetological Review 40: 234.</mixed-citation>
      </ref>
      <ref id="B67">
        <mixed-citation>R Core Team (2023) R: A language and environment for statistical computing. R Foundation for Statistical Computing. <ext-link xlink:href="https://www.R-project.org/" ext-link-type="uri">https://www.R-project.org/</ext-link> [Visited on 28/02/2026]</mixed-citation>
      </ref>
      <ref id="B68">
        <mixed-citation>Raes N, ter Steege H (2007) A null-model for significance testing of presence-only species distribution models. Ecography 30: 727–736. <ext-link xlink:href="10.1111/j.2007.0906-7590.05041.x" ext-link-type="doi">https://doi.org/10.1111/j.2007.0906-7590.05041.x</ext-link></mixed-citation>
      </ref>
      <ref id="B69">
        <mixed-citation>Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA (2018) Posterior summarisation in Bayesian phylogenetics using Tracer 1.7. Systematic Biology 67: 901–904. <ext-link xlink:href="10.1093/sysbio/syy032" ext-link-type="doi">https://doi.org/10.1093/sysbio/syy032</ext-link></mixed-citation>
      </ref>
      <ref id="B70">
        <mixed-citation>Robbiati FO, Nores MJ, Anton AM, Fortunato RH (2021) Stability and fragmentation versus demographic expansion: Different phylogeographic patterns in closely related sympatric legumes (Senna) from arid and semi-arid zones of mid-latitude South America. Botanical Journal of the Linnean Society 196: 364–383. <ext-link xlink:href="10.1093/botlinnean/boab003" ext-link-type="doi">https://doi.org/10.1093/botlinnean/boab003</ext-link></mixed-citation>
      </ref>
      <ref id="B71">
        <mixed-citation>Sastre P, Lobo JM (2009) Taxonomist survey biases and the unveiling of biodiversity patterns. Biological Conservation 142: 462–467. <ext-link xlink:href="10.1016/j.biocon.2008.11.002" ext-link-type="doi">https://doi.org/10.1016/j.biocon.2008.11.002</ext-link></mixed-citation>
      </ref>
      <ref id="B72">
        <mixed-citation>Sayers EW, Cavanaugh M, Frisse L, Pruitt KD, Schneider VA, Underwood BA, Yankie L, Karsch-Mizrachi I (2025) GenBank 2025 update. Nucleic Acids Research 53: D56–D61. <ext-link xlink:href="10.1093/nar/gkae1114" ext-link-type="doi">https://doi.org/10.1093/nar/gkae1114</ext-link></mixed-citation>
      </ref>
      <ref id="B73">
        <mixed-citation>Schalk C (2012) <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">guayapae</tp:taxon-name-part></tp:taxon-name></italic>. Egg predation. Herpetological Review 43: 509–667.</mixed-citation>
      </ref>
      <ref id="B74">
        <mixed-citation>Schalk CM, Saenz D (2016) Environmental drivers of anuran calling phenology in a seasonal Neotropical ecosystem. Austral Ecology 41: 16–27. <ext-link xlink:href="10.1111/aec.12281" ext-link-type="doi">https://doi.org/10.1111/aec.12281</ext-link></mixed-citation>
      </ref>
      <ref id="B75">
        <mixed-citation>Sillero N (2011) What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods. Ecological Modelling 222: 1343–1346. <ext-link xlink:href="10.1016/j.ecolmodel.2011.01.018" ext-link-type="doi">https://doi.org/10.1016/j.ecolmodel.2011.01.018</ext-link></mixed-citation>
      </ref>
      <ref id="B76">
        <mixed-citation>Sillero N, Barbosa AM (2021) Common mistakes in ecological niche models. International Journal of Geographical Information Science 35: 213–226. <ext-link xlink:href="10.1080/13658816.2020.1798968" ext-link-type="doi">https://doi.org/10.1080/13658816.2020.1798968</ext-link></mixed-citation>
      </ref>
      <ref id="B77">
        <mixed-citation>Sillero N, Arenas-Castro S, Enriquez-Urzelai U, Vale CG, Sousa-Guedes D, Martínez-Freiría F, Real R, Barbosa AM (2021) Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling. Ecological Modelling 456: 109671. <ext-link xlink:href="10.1016/j.ecolmodel.2021.109671" ext-link-type="doi">https://doi.org/10.1016/j.ecolmodel.2021.109671</ext-link></mixed-citation>
      </ref>
      <ref id="B78">
        <mixed-citation>Sillero N, Campos JC, Arenas-Castro S, Barbosa AM (2023) A curated list of R packages for ecological niche modelling. Ecological Modelling 476: 110242. <ext-link xlink:href="10.1016/j.ecolmodel.2022.110242" ext-link-type="doi">https://doi.org/10.1016/j.ecolmodel.2022.110242</ext-link></mixed-citation>
      </ref>
      <ref id="B79">
        <mixed-citation>Silva GC, Solis Neffa VG, Zuquim G, Balslev H (2023) Biogeography and environmental preferences of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Butia</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">yatay</tp:taxon-name-part></tp:taxon-name></italic> (Mart.) Becc. Ecology and Evolution 13: e10749. <ext-link xlink:href="10.1002/ece3.10749" ext-link-type="doi">https://doi.org/10.1002/ece3.10749</ext-link></mixed-citation>
      </ref>
      <ref id="B80">
        <mixed-citation>Sinani TRF, Sciamarelli A, Bueno ML, Sartori ÂLB (2022) <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leguminosae</tp:taxon-name-part></tp:taxon-name> endemic to the Chaco facing Quaternary climate fluctuations. Acta Botanica Brasilica 36: e2021abb0346.</mixed-citation>
      </ref>
      <ref id="B81">
        <mixed-citation>Streicher JW, Sadler R, Loader SP (2020) Amphibian taxonomy: Early 21<sup>st</sup> century case studies. Journal of Natural History 54: 1–13. <ext-link xlink:href="10.1080/00222933.2020.1777339" ext-link-type="doi">https://doi.org/10.1080/00222933.2020.1777339</ext-link></mixed-citation>
      </ref>
      <ref id="B82">
        <mixed-citation>Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ, Rambaut A (2018) Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evolution 4: vey016. <ext-link xlink:href="10.1093/ve/vey016" ext-link-type="doi">https://doi.org/10.1093/ve/vey016</ext-link></mixed-citation>
      </ref>
      <ref id="B83">
        <mixed-citation>Taylor ZP (2017) Identifying and quantifying disjunctions at multiple taxonomic levels in western hemisphere mammals. The Professional Geographer 69: 472–485. <ext-link xlink:href="10.1080/00330124.2016.1266952" ext-link-type="doi">https://doi.org/10.1080/00330124.2016.1266952</ext-link></mixed-citation>
      </ref>
      <ref id="B84">
        <mixed-citation>Valavi R, Guillera-Arroita G, Lahoz-Monfort JJ, Elith J (2022) Predictive performance of presence-only species distribution models: A benchmark study with reproducible code. Ecological Monographs 92: e01486. <ext-link xlink:href="10.1002/ecm.1486" ext-link-type="doi">https://doi.org/10.1002/ecm.1486</ext-link></mixed-citation>
      </ref>
      <ref id="B85">
        <mixed-citation>Valetti JA, Grenat PR, Baraquet M, Martino AL (2014) Reproductive biology of <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Pleurodema</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">guayapae</tp:taxon-name-part></tp:taxon-name></italic> (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order">Anura</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Leptodactylidae</tp:taxon-name-part></tp:taxon-name>: <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="subfamily">Leiuperinae</tp:taxon-name-part></tp:taxon-name>). Revista de Biología Tropical 62: 173–181. <ext-link xlink:href="10.15517/rbt.v62i1.7763" ext-link-type="doi">https://doi.org/10.15517/rbt.v62i1.7763</ext-link></mixed-citation>
      </ref>
      <ref id="B86">
        <mixed-citation>Veith M (1996) Molecular markers and species delimitation: Examples from the European batrachofauna. <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="class">Amphibia</tp:taxon-name-part></tp:taxon-name>-<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="superclass">Reptilia</tp:taxon-name-part></tp:taxon-name> 17: 303–314. <ext-link xlink:href="10.1163/156853896X00027" ext-link-type="doi">https://doi.org/10.1163/156853896X00027</ext-link></mixed-citation>
      </ref>
      <ref id="B87">
        <mixed-citation>Vergara J, Acosta LE, Gonzalez-Ittig RE, Vaschetto LM, Gardenal CN (2017) The disjunct pattern of the Neotropical harvestman <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus">Discocyrtus</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species">dilatatus</tp:taxon-name-part></tp:taxon-name></italic> (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family">Gonyleptidae</tp:taxon-name-part></tp:taxon-name>) explained by climate-driven range shifts in the Quaternary: Paleodistributional and molecular evidence. PLoS ONE 12: e0187983. <ext-link xlink:href="10.1371/journal.pone.0187983" ext-link-type="doi">https://doi.org/10.1371/journal.pone.0187983</ext-link></mixed-citation>
      </ref>
      <ref id="B88">
        <mixed-citation>Whittaker RJ, Araújo MB, Jepson P, Ladle RJ, Watson JEA, Willis KJ (2005) Conservation biogeography: Assessment and prospect. Diversity and Distributions 11: 3–23. <ext-link xlink:href="10.1111/j.1366-9516.2005.00143.x" ext-link-type="doi">https://doi.org/10.1111/j.1366-9516.2005.00143.x</ext-link></mixed-citation>
      </ref>
      <ref id="B89">
        <mixed-citation>Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: A fundamental evaluation tool in clinical medicine. Clinical Chemistry 39: 561–577. <ext-link xlink:href="10.1093/clinchem/39.4.561" ext-link-type="doi">https://doi.org/10.1093/clinchem/39.4.561</ext-link></mixed-citation>
      </ref>
    </ref-list>
    <sec sec-type="Additional information" id="sec13">
      <title>Additional information</title>
      <sec sec-type="Conflict of interest" id="sec14">
        <title>Conflict of interest</title>
        <p>The authors have declared that no competing interests exist.</p>
      </sec>
      <sec sec-type="Ethical statement" id="sec15">
        <title>Ethical statement</title>
        <p>No ethical statement was reported.</p>
      </sec>
      <sec sec-type="Artificial Intelligence (AI) use" id="sec16">
        <title>Artificial Intelligence (AI) use</title>
        <p>The authors accept full responsibility for the content of the manuscript, including the disclosure of any use of AI.</p>
        <p>No AI tools were used in the preparation of this manuscript.</p>
      </sec>
      <sec sec-type="Funding" id="sec17">
        <title>Funding</title>
        <p>No funding was reported.</p>
      </sec>
      <sec sec-type="Author contributions" id="sec18">
        <title>Author contributions</title>
        <p>Conceptualization: A. Carné, I. De la Riva. Sampling: L. Gonzales, I. De la Riva. Data Curation: A. Carné, I. De la Riva. Methodology: A. Carné, I. De la Riva. Formal Analysis: A. Carné. Supervision: I. De la Riva. Validation: A. Carné, L. Gonzales, I. De la Riva. Visualization: A. Carné. Original Draft Preparation: A. Carné. Review &amp; Editing: A. Carné, L. Gonzales, I. De la Riva.</p>
      </sec>
      <sec sec-type="Author ORCIDs" id="sec19">
        <title>Author ORCIDs</title>
        <p>A. Carné <ext-link xlink:href="https://orcid.org/0000-0002-7920-8159" ext-link-type="uri">https://orcid.org/0000-0002-7920-8159</ext-link></p>
        <p>L. Gonzales <ext-link xlink:href="https://orcid.org/0009-0007-0324-1407" ext-link-type="uri">https://orcid.org/0009-0007-0324-1407</ext-link></p>
        <p>I. De la Riva <ext-link xlink:href="https://orcid.org/0000-0001-5064-4507" ext-link-type="uri">https://orcid.org/0000-0001-5064-4507</ext-link></p>
      </sec>
      <sec sec-type="Data availability" id="sec20">
        <title>Data availability</title>
        <p>All of the data that support the findings of this study are available in the main text or Supplementary Information.</p>
      </sec>
    </sec>
    <sec sec-type="supplementary-material">
      <title>Supplementary materials</title>
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        <label>Supplementary materials
 Supplementary material 1</label>
        <caption>
          <p>Specimens included in the genetic analyses and their GenBank accession numbers (.pdf)</p>
        </caption>
        <media xlink:href="biogeography-19-001_article-208301__-s001.pdf" mimetype="application" mime-subtype="pdf" position="float" orientation="portrait" id="oo_1788933.pdf">
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        <label>Supplementary material 2</label>
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          <p>Geographic coordinates and locality names (.xlsx)</p>
        </caption>
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        <label>Supplementary material 3</label>
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          <p>Selection of climatic variables (.pdf)</p>
        </caption>
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          <p>Distribution and sampling intensity of amphibian and reptile records within the study area (.pdf)</p>
        </caption>
        <media xlink:href="biogeography-19-001_article-208301__-s004.pdf" mimetype="application" mime-subtype="pdf" position="float" orientation="portrait" id="oo_1788936.pdf">
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        <label>Supplementary material 5</label>
        <caption>
          <p>Gene trees (.pdf)</p>
        </caption>
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          <p>Model evaluation metrics (.pdf)</p>
        </caption>
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          <p>Variable contributions and permutation importance for the models (.pdf)</p>
        </caption>
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  </back>
</article>
