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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Amphib. Reptile Sci.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Amphibian and Reptile Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Amphib. Reptile Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2813-6780</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/famrs.2026.1758509</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Ecophysiology and vulnerability to warming of Whorl-tail Iguanas (Tropidurinae: <italic>Stenocercus</italic>) from the Tropical Andes of Ecuador</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Guerra-Correa</surname><given-names>Estefany S.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name><surname>Guayasamin</surname><given-names>Juan M.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
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<contrib contrib-type="author">
<name><surname>Peters</surname><given-names>Richard A.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<aff id="aff1"><label>1</label><institution>Animal Behaviour Group, La Trobe University</institution>, <city>Melbourne</city>, <state>VIC</state>,&#xa0;<country country="au">Australia</country></aff>
<aff id="aff2"><label>2</label><institution>Laboratorio de Biolog&#xed;a Evolutiva, Colegio de Ciencias Biol&#xf3;gicas y Ambientales, Universidad San Francisco de Quito, Cumbay&#xe1;</institution>, <city>Quito</city>,&#xa0;<country country="ec">Ecuador</country></aff>
<aff id="aff3"><label>3</label><institution>Galapagos Science Center, Universidad San Francisco de Quito (USFQ) and University of North Carolina at Chapel Hill</institution>, <city>Puerto Baquerizo Moreno</city>,&#xa0;<country country="ec">Ecuador</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Estefany S. Guerra-Correa, <email xlink:href="mailto:estefy92guerra@gmail.com">estefy92guerra@gmail.com</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-26">
<day>26</day>
<month>01</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>4</volume>
<elocation-id>1758509</elocation-id>
<history>
<date date-type="received">
<day>01</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>06</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="rev-recd">
<day>04</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Guerra-Correa, Guayasamin and Peters.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Guerra-Correa, Guayasamin and Peters</copyright-holder>
<license>
<ali:license_ref start_date="2026-01-26">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Environmental changes can significantly affect the performance of ectotherms, as nearly all aspects of their life history are intricately linked to temperature conditions in their habitats. One approach to quantify ectothermic physiological performance is to assess traits that define their thermal tolerance. Research integrating thermophysiological traits of terrestrial ectotherms with environmental data has shown that tropical ectothermic species face a higher risk of extinction compared to their temperate counterparts because they live near their physiological thermal optimum and exhibit limited plasticity to adapt to changing conditions.</p>
</sec>
<sec>
<title>Methods</title>
<p>In this study we measured the preferred body temperature (<italic>T</italic><sub>pref</sub>), critical thermal minimum (CT<sub>min</sub>), and critical thermal maximum (CT<sub>max</sub>) of seven <italic>Stenocercus</italic> populations inhabiting high-altitude tropical ecosystems in the Ecuadorian Andes, between 2093 and 4046 m asl. Field-based experiments were conducted on adult lizards to determine these thermophysiological traits. We combined these data with environmental records and  operative temperature models (OTMs) to characterise the thermal conditions of each population's microhabitat and to evaluate vulnerabilty under current and future warming scenarios.</p>
</sec>
<sec>
<title>Results</title>
<p>Our findings support the hypothesis that habitats with greater daily temperature variability and structurally complex vegetation allow lizards to exhibit broader thermal tolerance ranges and higher tolerance to warming. For instance, <italic>Stenocercus</italic> lizards from paramo ecosystems are unlikely to be physiologically constrained by projected temperature increases. In contrast, warming is likely to restrict the activity of Inter-Andean lizards because their microhabitats already reach temperatures close to their physiological optimum.</p>
</sec>
<sec>
<title>Discussion</title>
<p>These results highlight the importance of access to suitable thermal microhabitats and the role of behavioural strategies in reducing the risk of overheating.</p>
</sec>
</abstract>
<kwd-group>
<kwd>ecophysiology</kwd>
<kwd>ecosystem</kwd>
<kwd>high altitude</kwd>
<kwd>lizards</kwd>
<kwd>microhabitat</kwd>
<kwd>tropical Andes hotspot</kwd>
<kwd>vulnerability</kwd>
</kwd-group>
<funding-group>
<award-group id="gs1">
<funding-source id="sp1">
<institution-wrap>
<institution>La Trobe University</institution>
<institution-id institution-id-type="doi" vocab="open-funder-registry" vocab-identifier="10.13039/open_funder_registry">10.13039/501100001215</institution-id>
</institution-wrap>
</funding-source>
</award-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This work received financial support from two funding sources: internal funds provided by the School of Agriculture, Biomedicine &amp; Environment, of La Trobe University, Melbourne, Australia, and the Australian Research Council Discovery Project (grant number: DP170102370).</funding-statement>
</funding-group>
<counts>
<fig-count count="6"/>
<table-count count="5"/>
<equation-count count="0"/>
<ref-count count="78"/>
<page-count count="17"/>
<word-count count="8705"/>
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<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Physiology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Climate-driven impacts on species vary widely in both direction and magnitude on a global scale (<xref ref-type="bibr" rid="B73">Williams and Jackson, 2007</xref>). For most ectothermic species, environmental changes can adversely affect their performance, as nearly all aspects of their life history are closely influenced by temperature conditions in their habitats (<xref ref-type="bibr" rid="B5">Angilletta et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B34">Ibarg&#xfc;engoyt&#xed;a et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B39">Kubisch et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B78">Zhu et&#xa0;al., 2025</xref>). One method for quantifying ectothermic physiological responses is to examine their thermal performance curves, which describe how body temperature affects their performance or fitness (<xref ref-type="bibr" rid="B32">Huey and Stevenson, 1979</xref>; <xref ref-type="bibr" rid="B31">Huey and Kingsolver, 1989</xref>; <xref ref-type="bibr" rid="B38">Kingsolver et&#xa0;al., 2013</xref>). In brief, an organism&#x2019;s thermal performance increases gradually from a critical thermal minimum (CT<sub>min</sub>) to an optimal temperature (<italic>T</italic><sub>opt</sub>) and then declines rapidly as body temperature approaches the critical thermal maximum (CT<sub>max</sub>) (<xref ref-type="bibr" rid="B5">Angilletta et&#xa0;al., 2002</xref>). These thermal traits are traditionally measured in terrestrial ectotherms, revealing geographic patterns of local adaptation and responses to climate variations (<xref ref-type="bibr" rid="B13">Chown and Terblanche, 2007</xref>; <xref ref-type="bibr" rid="B38">Kingsolver et&#xa0;al., 2013</xref>). For instance, species from higher latitudes typically exhibit greater thermal breadth (the difference between CT<sub>max</sub> and CT<sub>min</sub>) and lower CT<sub>min</sub> values compared to tropical species (<xref ref-type="bibr" rid="B14">Clusella-Trullas et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B38">Kingsolver et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B65">Sunday et&#xa0;al., 2011</xref>).</p>
<p>Several studies have integrated physiological thermal tolerance metrics with environmental data, using correaltive or mechanistic modelling approaches, to predict population declines and local extinctions of ectotherms across latitudinal and elevational gradients (<xref ref-type="bibr" rid="B12">Chen et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B24">Garc&#xed;a-Robledo et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B63">Sinervo et&#xa0;al., 2010</xref>). Based on these approaches, tropical ectothermic species are often considered at greater risk of extinction than their temperate counterparts because they tend to operate close to their physiological thermal optima and are assumed to have limited physiological and behavioural plasticity (<xref ref-type="bibr" rid="B18">Deutsch et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B29">Huey et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B47">Morley et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B56">Polato et&#xa0;al., 2018</xref>). Despite their widespread use, these approaches can yield inaccurate or incomplete predictions, particularly in tropical systems, for three main reasons. First, they commonly rely on ambient air temperature as a proxy for the organismal habitat temperature, overlooking the fact that ectotherms can experience substantially different thermal conditions within their microhabitats (<xref ref-type="bibr" rid="B54">Pincebourde and Suppo, 2016</xref>; <xref ref-type="bibr" rid="B57">Potter et&#xa0;al., 2013</xref>). Second, tropical environments, are characterised by strong spatial and temporal thermal heterogeneity at fine scales, which can directly influence the thermal physiology and thermoregulatory opportunities of small ectotherms (<xref ref-type="bibr" rid="B54">Pincebourde and Suppo, 2016</xref>). Third, much of the empirical support underlying predictions of tropical ectotherm vulnerability, especially in lizards, comes from low- and mid-altitude tropical ecosystems, such as tropical rainforests, resulting in a strong elevational bias (<xref ref-type="bibr" rid="B8">Brusch et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B29">Huey et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B51">Mu&#xf1;oz et&#xa0;al., 2014</xref>, <xref ref-type="bibr" rid="B50">2022</xref>). Consequently, the thermal responses of high-altitude tropical mountain species remain poorly understood, limiting our ability to accurately predict their vulnerability to climate change.</p>
<p>The rapid uplift of the Andes created complex and diverse ecosystems with distinct climate conditions that vary by altitude (<xref ref-type="bibr" rid="B21">Esquerr&#xe9; et&#xa0;al., 2019</xref>). High-elevation tropical Andean ecosystems, for example, exhibit steep altitudinal gradients with marked macroclimate variations, which interact with abiotic and biotic factors to create a mosaic of thermal microclimates (<xref ref-type="bibr" rid="B6">Arroyo and Cavieres, 2013</xref>; <xref ref-type="bibr" rid="B74">Woods et&#xa0;al., 2015</xref>). When first formed, these heterogeneous and fragmented Andean ecosystems provided new habitats for some groups to explosively diversify (<xref ref-type="bibr" rid="B20">Drummond et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B33">Hutter et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B42">Losos, 2009</xref>). This is true for <italic>Stenocercus</italic> lizards, which inhabit various South American landscapes, including dry and humid tropical forests, montane forests, and paramo, at elevations between 0 and 4000 m <italic>asl</italic> (<xref ref-type="bibr" rid="B67">Torres-Carvajal, 2000</xref>).</p>
<p>Two studies have examined aspects of the thermal biology of high-altitude tropical montane <italic>Stenocercus</italic> species. <xref ref-type="bibr" rid="B3">Andrango et&#xa0;al. (2016)</xref> conducted the first study to model local extinction risks for the Ecuadorian tropical Andean species <italic>S. guentheri</italic>. By integrating temperatures recorded with physical models placed in various microhabitats (i.e. operative temperature), the species&#x2019; preferred body temperature, and air temperatures from weather stations at georeferenced points within the species&#x2019; distribution, they predicted that 26.7% of this species&#x2019; populations will be extinct by 2050. In the only other study, <xref ref-type="bibr" rid="B25">Guerra-Correa et&#xa0;al. (2020)</xref> reported that tropical&#xa0;Andean <italic>Stenocercus</italic> lizards exploit diverse thermal microenvironments, allowing them shelter and remain active without experiencing thermal stress or reduced performance. Their findings emphasise the importance of microhabitat structure for these species and highlighted the need to investigate additional thermal adaptations, many of which remain poorly understood.</p>
<p>In this study, we aim to examine how vegetation structure and composition combined with local environmental conditions influence key thermophysiological traits of multiple <italic>Stenocercus</italic> populations from the Ecuadorian Andes, and how these interactions translate into differences in thermal vulnerability. We hypothesise that the interplay between pronounced daily temperature fluctuations, characteristic of high-altitude tropical montane ecosystems, and local vegetation assemblages plays a central role in shaping these lizards&#x2019; thermal preferences and tolerances. Specifically, we predict that lizards inhabiting areas with greater daily temperature variability and more complex vegetation structure will exhibit broader thermal tolerance ranges and more flexible thermal preferences than those in areas with lower temperature variability and less vegetative landscapes. This assumption is grounded in the climatic variability hypothesis and theories of phenotypic plasticity, which states that ectotherms inhabiting environments with large diurnal temperature fluctuations and structurally complex microhabitats promote broader thermal physiological responses, especially when coupled with behavioural thermoregulation (<xref ref-type="bibr" rid="B35">Janzen, 1967</xref>; <xref ref-type="bibr" rid="B5">Angilletta, 2009</xref>; <xref ref-type="bibr" rid="B49">Mu&#xf1;oz and Bodensteiner, 2019</xref>). To test these hypotheses, we assessed three thermophysiological traits including the preferred body temperature (<italic>T</italic><sub>pref</sub>), critical thermal minimum (CT<sub>min</sub>) and maximum (CT<sub>max</sub>) across six <italic>Stenocercus</italic> species inhabiting three high-altitude ecosystems. These physiological data were then integrated with climate records and spatially distributed operative temperature models to quantify thermal vulnerability using established indices, including thermal safety margins (TSM) and warming tolerance (WT) under present and future warming scenarios.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Focal species and collection</title>
<p>Six closely related <italic>Stenocercus</italic> species inhabiting high-altitude montane ecosystems in the Ecuadorian Andes were evaluated (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>). <italic>Stenocercus angel</italic> occurs in southern Colombia and northern Ecuador and primarily inhabits high evergreen montane forests, humid montane shrublands, <italic>Espeletia</italic>-dominated paramos, and highland grasslands at elevations ranging from 2400 to 3875 m <italic>asl</italic>. <italic>Stenocercus chota</italic> is restricted to the inter-Andean valleys of northern Ecuador, where it occupies dry highland shrublands and human-disturbed areas between 1574 and 1940 m <italic>asl</italic>. <italic>Stenocercus guentheri</italic>, distributed in southern Colombia and northern Ecuador, inhabits both dry and humid ecosystems, including evergreen montane forests, highland shrublands, paramos, and altered landscapes across an elevational range of 2135 to 3890 m <italic>asl</italic>. In central Ecuador, <italic>S. cadlei</italic> occurs in inter-Andean valleys across grasslands, croplands, montane forests, shrublands, and paramos at elevations ranging from 1956 to 4024 m <italic>asl</italic>. <italic>Stenocercus festae</italic> is distributed in southern Ecuador, inhabiting undisturbed shrub-dominated areas as well as disturbed habitats such as pine plantations, pastures, and rural gardens between 1050 and 3200 m <italic>asl</italic>. Finally, <italic>S. ornatus</italic> occurs in inter-Andean basins of southern Ecuador, occupying humid and dry montane shrublands, evergreen high montane forests, paramos, and disturbed areas at elevations between 1500 to 3000 m <italic>asl</italic> (<xref ref-type="bibr" rid="B67">Torres-Carvajal, 2000</xref>, <xref ref-type="bibr" rid="B68">2007</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p><italic>Stenocercus</italic> species included in this study: <bold>(A)</bold><italic>S. angel</italic>, <bold>(B)</bold><italic>S. chota</italic>, <bold>(C)</bold><italic>S. guentheri</italic>, <bold>(D)</bold><italic>S. cadlei</italic>, <bold>(E)</bold><italic>S. festae</italic>, and <bold>(F)</bold><italic>S. ornatus</italic>. Asterisks (*) indicate endemic species.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="famrs-04-1758509-g001.tif">
<alt-text content-type="machine-generated">Side-by-side comparison of female and male lizards from six different groups labeled A to F. Each lizard exhibits distinct coloration and patterns, with males generally on the left and females on the right. A scale indicates a measurement reference of 2 centimeters.</alt-text>
</graphic></fig>
<p>These species were sampled across seven tropical montane sites distributed along the Ecuadorian Andes, spanning elevations from 2095 to 4046 m <italic>asl</italic>. To assess intraspecific differences in thermophysiological traits, two <italic>S. guentheri</italic> populations inhabiting the range margins of this species distribution were included (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2</bold></xref>; <xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>). Based on the local-scale plant community composition, study sites were classified into three ecosystem categories: inter-Andean scrubs, high montane evergreen shrublands, and upper montane paramos (<xref ref-type="bibr" rid="B46">Ministerio del Ambiente del Ecuador, 2013</xref>) (<xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3</bold></xref>). Inter-Andean scrubs, henceforth inter-Andean, are vegetation formations adapted to prolonged and severe droughts, characterised by low stature trees and spiny plants resistant to long dry seasons and low annual precipitation (<xref ref-type="bibr" rid="B76">Young et&#xa0;al., 2011</xref>) (<xref ref-type="fig" rid="f3"><bold>Figures&#xa0;3A, B</bold></xref>). High montane evergreen shrublands, henceforth evergreen, cover a wide range of vegetation types, from woody plant species less than 5 metres in height to epiphytes such as orchids, ferns, and bryophytes (<xref ref-type="bibr" rid="B46">Ministerio del Ambiente del Ecuador, 2013</xref>). This vegetation structure creates a low and open canopy that allows high light penetration, supporting relatively high diversity in the herbaceous layer (<xref ref-type="bibr" rid="B46">Ministerio del Ambiente del Ecuador, 2013</xref>) (<xref ref-type="fig" rid="f3"><bold>Figures&#xa0;3C, D</bold></xref>). Upper montane paramos, henceforth paramo, are characterised by average temperatures below 10&#xb0;C, persistent cloud cover, high precipitation, intense UV radiation, low atmospheric pressure, and strong winds. These harsh environmental conditions result in landscapes dominated by grasslands and shrublands with unique adaptations (<xref ref-type="bibr" rid="B60">Ruiz et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B76">Young et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B11">CEPF, 2021</xref>) (<xref ref-type="fig" rid="f3"><bold>Figures&#xa0;3E&#x2013;G</bold></xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Geographic location of the seven study sites examined in this study, each representing a different <italic>Stenocercus</italic> population in Ecuador.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="famrs-04-1758509-g002.tif">
<alt-text content-type="machine-generated">Map showing study sites in Ecuador with altitude shaded in grayscale. Colored dots represent study sites: El Angel ER, Pisquer, Jerusalem RPPF, Cotopaxi NP, Chimborazo WPR, El Gullan SS, Madrigal PR. Inset shows Ecuador's location in South America.</alt-text>
</graphic></fig>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p><italic>Stenocercus</italic> species and sampling sites in the Northern Andes of Ecuador.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Species</th>
<th valign="middle" align="left">Study site (Abbreviation name)</th>
<th valign="middle" align="left">GPS coordinates</th>
<th valign="middle" align="left">Elevation range (m asl)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left"><italic>S. angel</italic></td>
<td valign="middle" align="left">El Angel Ecological Reserve (<bold>El Angel ER</bold>)</td>
<td valign="middle" align="left">0&#xb0;42&#x2032;21.866&#x2033; N 77&#xb0;58&#x2032;56.661&#x2033; W</td>
<td valign="middle" align="left">3500 &#x2013; 3685</td>
</tr>
<tr>
<td valign="middle" align="left"><italic>S. chota</italic></td>
<td valign="middle" align="left">Pisquer (<bold>Pisquer</bold>)</td>
<td valign="middle" align="left">0&#xb0;30&#x2032;42.296&#x2033; N 78&#xb0;5&#x2032;5.827&#x2033; W</td>
<td valign="middle" align="left">2093 &#x2013; 2235</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left"><italic>S. guentheri</italic></td>
<td valign="middle" align="left">Jerusalem Recreational Park and Protected Forest (<bold>Jerusalem RPPF</bold>)</td>
<td valign="middle" align="left">0&#xb0;0&#x2032;29.47&#x2033; S 78&#xb0;21&#x2032;31.305&#x2033; W</td>
<td valign="middle" align="left">2193 &#x2013; 2289</td>
</tr>
<tr>
<td valign="middle" align="left">Cotopaxi National Park (<bold>Cotopaxi NP</bold>)</td>
<td valign="middle" align="left">0&#xb0;36&#x2032;35.604&#x2033; N 78&#xb0;28&#x2032;51.718&#x2033; W</td>
<td valign="middle" align="left">3700 &#x2013; 3897</td>
</tr>
<tr>
<td valign="middle" align="left"><italic>S. cadlei</italic></td>
<td valign="middle" align="left">Chimborazo Wildlife Production Reserve (<bold>Chimborazo WPR</bold>)</td>
<td valign="middle" align="left">1&#xb0;31&#x2032;28.409&#x2033; S 78&#xb0;50&#x2032;44.199&#x2033; W</td>
<td valign="middle" align="left">3889 &#x2013; 4046</td>
</tr>
<tr>
<td valign="middle" align="left"><italic>S. festae</italic></td>
<td valign="middle" align="left">El Gullan Scientific Station (<bold>El Gullan SS</bold>)</td>
<td valign="middle" align="left">3&#xb0;20&#x2032;17.83&#x2033; S 79&#xb0;10&#x2032;18.195&#x2033; W</td>
<td valign="middle" align="left">2918 &#x2013; 3028</td>
</tr>
<tr>
<td valign="middle" align="left"><italic>S. ornatus</italic></td>
<td valign="middle" align="left">Madrigal of Podocarpus Reserve (<bold>Madrigal PR</bold>)</td>
<td valign="middle" align="left">4&#xb0;2&#x2032;48.527&#x2033; S 79&#xb0;10&#x2032;46.714&#x2033; W</td>
<td valign="middle" align="left">2295 &#x2013; 2509</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Abbreviation names of study sites and ecosystem types in bold will be used in subsequent sections of this article.</p></fn>
</table-wrap-foot>
</table-wrap>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Vegetation structure at each study site. <bold>(A)</bold> Pisquer and <bold>(B)</bold> Jerusalem RPPF are in inter-Andean ecosystems; <bold>(C)</bold> Madrigal PR and <bold>(D)</bold> El Gullan SS are part of evergreen ecosystems; and <bold>(E)</bold> Cotopaxi NP, <bold>(F)</bold> Chimborazo WPR, and <bold>(G)</bold> El Angel ER are situated in paramo ecosystems.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="famrs-04-1758509-g003.tif">
<alt-text content-type="machine-generated">A: Expansive savanna with acacia trees and vegetation, mountains in the background. B: Open grassland with shrubs and distant mountain range. C: Dense forested hills under a clear sky. D: Diverse shrubland with various grasses and bushes. E: High-altitude landscape with fields, seen from a viewpoint, with two large plants in the foreground. F: Volcanic mountain with snow-capped peak, surrounded by grassy terrain. G: Rocky, barren landscape with sparse vegetation, leading to a snow-covered, mountainous horizon.</alt-text>
</graphic></fig>
<p>Fieldwork was conducted during eight sampling sessions between June and October in each of the years 2021, 2022, and 2023 (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S1</bold></xref>). Sampling took place from 0800 to 1700 hours at each study site, targeting active adult females and males in their habitats using noose-capture techniques. Immediately upon capture, a K-type thermocouple connected to a 51-II Single Input Digital Thermometer (Fluke Corporation) was used to measure the body temperature (<italic>T</italic><sub>b</sub>) and substrate temperature (<italic>T</italic><sub>sub</sub>). The thermocouple was inserted into the lizard&#x2019;s cloaca to measure <italic>T</italic><sub>b</sub>, while <italic>T</italic><sub>sub</sub> was measured by placing the thermocouple probe onto the substrate where the lizard was captured. Care was taken to shield individuals from direct sunlight to prevent inaccuracies in <italic>T</italic><sub>b</sub> measurements. Weather parameters such as air temperature (<italic>T</italic><sub>air</sub>), wind speed (WS), and relative humidity (RH), were measured immediately upon capture using a Kestrel 3000 meter (Nielsen Kellerman Inc.). Captured lizards were temporarily held in collection bags for transporting to the field base camp for thermophysiological experimentation.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Thermophysiological experiments</title>
<p>Thermophysiological experiments were conducted at the field base camp at each site to minimise suffering and stress caused by lengthy travel times. Lizards were housed in individual terrariums (28 cm long x 17.5 cm wide x 17 cm high) with ad libitum water for a maximum of three days before being released at each capture site. The experimentation process began with measurements of preferred body temperature (<italic>T</italic><sub>pref</sub>), followed by assessments of critical thermal minimum (CT<sub>min</sub>) and maximum (CT<sub>max</sub>), with a 24-hour interval between each experiment to allow the lizard to recover. The sample size for <italic>S.festae</italic> was smaller than that of the other populations due to unforeseen circumstances encountered during sampling that forced us to stop fieldwork.</p>
<p>For <italic>T</italic><sub>pref</sub> experiments, a temporary outdoor field enclosure was utilised. Wooden enclosures measuring 1 m long x 0.12 m wide x 0.2 m high were placed on the ground, with a 100-watt light bulb installed at one end to create a thermal gradient (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure S1</bold></xref>) (<xref ref-type="bibr" rid="B25">Guerra-Correa et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B53">Paranjpe et&#xa0;al., 2012</xref>). Body temperatures were recorded in real time using the Omega Logging Recorder program (OMEGA Engineering Inc.) every 30 seconds for 2 hours, with a K-type thermocouple placed anteriorly to the cloacal area and secured with Micropore surgery tape. Lizards were released in the middle of the enclosure at the start of each experiment with a 15-minute period of acclimatation. <italic>T</italic><sub>pref</sub> was determined by averaging the body temperature recorded for the two hours of experimentation.</p>
<p>For CT<sub>min</sub> and CT<sub>max</sub> experiments, we built a custom-controlled thermal system capable of increasing or decreasing temperature at a rate of 1.5-2&#xb0;C per minute. The system consisted of an enclosed experimental chamber in which individual lizards were placed, allowing precise control of ambient temperature while minimising external thermal interference. Temperature within the chamber was continuously monitored using a thermocouple temperature sensor positioned on the thermal system wall, which provided real-time feedback to an Arduino microcontroller. The Arduino board regulated temperature changes by controlling both heating and cooling elements through a solid-state relay (DC 3-32V) and an amplifier transistor mounted on a heatsink to dissipate excess heat and ensure stable power delivery. Cooling was achieved using Peltier cells coupled with cooling fans, which facilitated efficient heat dissipation and prevented thermal accumulation within the system. Heating was provided by a ceramic air heater that delivered uniform warm airflow into the chamber. An adapter converter regulator supplied and stabilised voltage to all electronic components, ensuring consistent system performance. Temperature adjustments were programmed in the Arduino to produce gradual, linear changes at the target rate of 1.5-2&#xb0;C per minute, reducing thermal shock to the animals. A camera was mounted inside the thermal system to continuously record lizard behaviour during trails, allowing precise identification of loss-of-function endpoints associated with critical thermal minima and maxima (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure S2</bold></xref>).</p>
<p>Body temperatures were recorded using the same procedure as in <italic>T</italic><sub>pref</sub> experiments. CT<sub>min</sub> trials concluded when the lizard was unable to right itself after flipping onto its back, while for CT<sub>max</sub>, the end of the experiment was determined by the first mouth-opening response exhibited by the lizard. This response, known as panting, is a thermoregulatory mechanism used by lizards to cool their body temperature under heat stress and is typically exhibited before losing their righting response (<xref ref-type="bibr" rid="B15">Clusella-Trullas et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B27">Heatwole et&#xa0;al., 1973</xref>). All lizards were released at the end of the experimental period.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Operative temperature models and climate data</title>
<p>Ten operative temperature models (OTMs) were used to measure the available temperatures within the lizards&#x2019; microhabitat. These models consisted of 3D-printed lizards connected to a two-channel HOBO Pro V2 U23&#x2013;003 data logger (Onset Computer Corporation) (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure S3</bold></xref>). We followed the 3D digitisation protocol established by <xref ref-type="bibr" rid="B45">Medina et&#xa0;al. (2020)</xref> to build 3D lizards from a well-preserved specimen of <italic>S. cadlei</italic> from the Zoology Museum of Pontificia Universidad Cat&#xf3;lica del Ecuador (QCAZ). The scanned specimen accurately replicated the shape and the average adult size of the studied <italic>Stenocercus</italic> species (SVL = 83 mm, body height = 17 mm, body width = 18 mm, tail length = 65 mm) (<xref ref-type="bibr" rid="B7">Behm et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B70">Watson and Francis, 2015</xref>) (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S2</bold></xref>). The 3D lizards were printed using polylactic acid (PLA) in a posture with extended hind and forelimbs and a completely flat ventral surface. PLA is an affordable material for 3D printing and was tested against other materials and shown to have high accuracy in relation to temperature of a live organism in its habitat (<xref ref-type="bibr" rid="B1">Alujevi&#x107; et&#xa0;al., 2024</xref>). All models were printed at DLab, Universidad San Francisco de Quito (USFQ), using a MK3S printer (Prusa Research A.S.) with a shell thickness of 1.2 mm, a layer height of 0.16 mm, and an infill density of 10% with a lighting fill pattern (i.e. models were 90% hollow). The 3D-printed lizards were painted with dark brown synthetic paint on the dorsum and pale beige synthetic paint on the belly to match lizards&#x2019; colour background. The two external probes of the HOBO Pro V2 U23&#x2013;003 data logger were inserted 4 cm into the 3D-printed lizards and secure with cloth tape.</p>
<p>The OTMs were placed in randomly selected microhabitats representative of each species and recorded temperature every 5 minutes throughout the sampling period at each study site. Dates of sampling are shown in <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S1</bold></xref>, which correspond to dry conditions at each study site. Five models were positioned on the ground in shaded refuge sites, while the remaining models were placed in open areas exposed to direct sunlight.</p>
<p>Additionally, air temperature and relative humidity data were recorded every 5 minutes using a HOBO micro&#x2013;Station Data Logger IC-H21- USB (Onset Computer Corporation) for at least a one-year period at each study site.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Data analysis</title>
<sec id="s2_4_1">
<label>2.4.1</label>
<title>Climate data</title>
<p>Air temperature data recorded from the weather stations installed at each study site for at least a one-year period (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S3</bold></xref>) was summarised by computing the mean and 95% CI in one-hour time blocks across a 24-hour time interval.</p>
</sec>
<sec id="s2_4_2">
<label>2.4.2</label>
<title>Thermophysiological traits</title>
<p>The analysis of variation in <italic>T</italic><sub>pref</sub>, CT<sub>min</sub>, and CT<sub>max</sub> involved two main steps: (i) testing for sex differences within each population to obtain outcomes comparable with other studies, and (ii) evaluating the effects of snout-vent length (SVL), sex, and ecosystem type to explore the influence of these factors on the variation of thermal traits. All statistical analyses were performed in R (v. 4.4.0, <xref ref-type="bibr" rid="B58">R Core Team, 2024</xref>).</p>
<p>Before testing for sex differences within populations, the Levene and Shapiro-Wilk&#x2019;s tests were used to assess for homogeneity of variances and normality of each thermophysiological trait respectively. If the data met the assumptions of normality and homogeneity, independent <italic>t</italic>-tests were performed to examine sex-based differences in the variables of interest. The non-parametric Kruskal-Wallis test was employed for data that violated these assumptions.</p>
<p>Linear models were built using the <italic>lm</italic> function from the STATS package (<xref ref-type="bibr" rid="B58">R Core Team, 2024</xref>), with each thermal trait as the response variable, and SVL, sex, and ecosystem as fixed factors. Ecosystem classification was based on the vegetation structure and composition in each lizard population and included three categories: paramo, evergreen, and inter-Andean. Pairwise <italic>post-hoc</italic> comparisons between ecosystems were performed using estimated margin means at 95% confidence level, with a <italic>p</italic>-value adjustment following the Tukey method (<xref ref-type="bibr" rid="B41">Lenth, 2019</xref>).</p>
</sec>
<sec id="s2_4_3">
<label>2.4.3</label>
<title>Assessment of vulnerability to changes in temperature</title>
<p>The thermal vulnerability of tropical Andean <italic>Stenocercus</italic> populations was assessed using three complementary approaches: (1) a graphical and descriptive analysis of lizards&#x2019; thermophysiological traits in relation to the maximum and minimum micro-environmental temperatures available in their habitat, along with the calculation of two thermal vulnerability metrics &#x2013; (2) warming tolerance, and (3) thermal safety margins. The first approach was chosen to contextualise the thermal environments these lizards experience and, when combined with quantitative vulnerability assessments, provide a more comprehensive evaluation of how temperature variation may affect&#xa0;their survival from both micro-environmental and thermophysiological perspectives.</p>
<p>First, we explored graphically the relationship between thermal physiological traits of lizards and the temperature present in their microhabitats (<xref ref-type="bibr" rid="B25">Guerra-Correa et&#xa0;al., 2020</xref>). For each population, the temperature of OTMs placed in sun-exposed and shaded areas were averaged within hourly blocks and plotted along with the average critical thermal limits (CT<sub>max</sub> and CT<sub>min</sub>) and <italic>T</italic><sub>pref</sub>. In addition, the body temperatures of captured lizards at the corresponding hour of capture were included as a proxy of lizard activity across temperature ranges. Mean and ranges of <italic>T</italic><sub>b</sub> and <italic>T</italic><sub>sub</sub> values were calculated for each population, providing further insight into the temperature ranges of their activity.</p>
<p>Next, we examined the warming tolerance and thermal safety margin metrics to further evaluate vulnerability to temperature changes. Warming tolerance (WT) was calculated to estimate the extent of environmental warming that <italic>Stenocercus</italic> lizards can tolerate before their performance declines to lethal levels (<xref ref-type="bibr" rid="B18">Deutsch et&#xa0;al., 2008</xref>). Species with small WT values have limited physiological tolerances to temperature increases, whereas species with large WT values can tolerate warmer condition before their physiological performance declines to critical or fatal levels (<xref ref-type="bibr" rid="B18">Deutsch et&#xa0;al., 2008</xref>). In this context, the average CT<sub>max</sub> of each population was subtracted from the 95<sup>th</sup> percentile of the maximum annual air temperature recorded at each site with micro weather stations (WT=CT<sub>max-avg</sub> &#x2013; T<sub>air-P95</sub>) and projected under two warming scenarios: an increase of 1.5&#xb0;C and 2&#xb0;C (<xref ref-type="bibr" rid="B28">Hoegh-Guldberg et&#xa0;al., 2018</xref>). The 95<sup>th</sup> percentile was used to provide an accurate representation of the maximum air temperatures experienced by the lizards, while excluding recordings that otherwise may be atypical.</p>
<p>The thermal safety margin (TSM), on the other hand, was determined by calculating the difference between the maximum body temperature of active lizards and the 95<sup>th</sup> percentile of shaded microhabitat temperatures recorded by OTMs, as these values more accurately represent the thermal microenvironment available to lizards for avoiding overheating (<xref ref-type="bibr" rid="B10">Camacho et&#xa0;al., 2015</xref>) (TSM=T<sub>b-max</sub> &#x2013; T<sub>e-shade-P95</sub>). Small TSM values indicate that a species maintains an active body temperature close to the temperature available in its micro-environment to avoid overheating. This narrow margin suggests a reduced capacity to buffer against rising environmental temperatures, making the species potentially more vulnerable to climate warming. In contrast, a species with large TSM values inhabits micro-environments with a wider range of thermal conditions, allowing the organisms to effectively escape extreme heat exposure (<xref ref-type="bibr" rid="B18">Deutsch et&#xa0;al., 2008</xref>).</p>
</sec>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Daily temperature variation</title>
<p>For the inter-Andean ecosystems, Pisquer exhibited more stable air temperatures conditions compared to Jerusalem RPPF, remaining ~10&#xb0;C during the night and early morning, reaching a maximum of ~25&#xb0;C around midday, and gradually decreasing to ~15&#xb0;C by 5-6 PM (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4A</bold></xref>). At Jerusalem RPPF, early morning temperatures were colder than nighttime temperatures, reaching under 10&#xb0;C, and midday temperatures peaked at 30&#xb0;C and declining to ~20&#xb0;C by late afternoon (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4B</bold></xref>). At Madrigal PR, air temperatures exhibited moderate fluctuations, remaining above 10&#xb0;C during most of the night and early morning, peaking just over 20&#xb0;C at midday, and remaining relatively stable throughout the afternoon (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4C</bold></xref>). In contrast, El Gullan SS showed greater temperature variability, with air temperatures dropping below 10&#xb0;C at night and early morning, peaking above 30&#xb0;C at midday, and decreasing to under 20&#xb0;C by late afternoon (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4D</bold></xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Air temperature across a 24-hour period averaged across a year for our seven tropical montane sites. <bold>(A)</bold> Pisquer, <bold>(B)</bold> Jerusalem RPPF, <bold>(C)</bold> Madrigal PR, <bold>(D)</bold> El Gullan SS, <bold>(E)</bold> El Angel ER, <bold>(F)</bold> Cotopaxi NP, <bold>(G)</bold> Chimborazo WPR.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="famrs-04-1758509-g004.tif">
<alt-text content-type="machine-generated">Graphs depict air temperature variations across different ecosystems at varying times of day. Inter-Andean ecosystem graphs (A, B) show a peak around midday. Evergreen ecosystem graphs (C, D) peak slightly higher midday. Paramo ecosystem graphs (E, F, G) display similar, lower peaks. Error bars indicate variability.</alt-text>
</graphic></fig>
<p>Paramo ecosystems showed the coldest air temperature conditions of all the ecosystem types. In El Angel ER and Chimborazo WPR, daily temperature patterns were similar, peaking at ~15&#xb0;C around midday (<xref ref-type="fig" rid="f4"><bold>Figures&#xa0;4E, G</bold></xref>). In Cotopaxi NP, however, air temperatures reached ~20&#xb0;C at noon (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4F</bold></xref>). Night and early morning temperatures in Chimborazo WPR dropped to 0&#xb0;C, while in El Angel ER and Cotopaxi NP, temperatures remained slightly above freezing.</p>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Thermophysiological traits</title>
<p>A summary of thermophysiological trait measurements is provided in <xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>. Only one of the seven <italic>Stenocercus</italic> populations produced significant differences between males and females, with a different species exhibiting sex differences for each measure. Significant sex differences in <italic>T</italic><sub>pref</sub> were observed in <italic>S. guentheri</italic> from Jerusalem RPPF, with females exhibiting higher <italic>T</italic><sub>pref</sub> than males (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2a</bold></xref>). In <italic>S. festae</italic>, sex differences were found in CT<sub>min</sub> values, with males showing greater cold tolerance than females (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2b</bold></xref>). Finally, <italic>S. ornatus</italic> yielded sex-specific differences for CT<sub>max</sub>, with females being less tolerant of high temperatures than males (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2c</bold></xref>).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Average (Standard deviation) <italic>T</italic><sub>pref</sub>, CT<sub>min</sub>, and CT<sub>max</sub> values of <italic>Stenocercus</italic> species/populations assessed.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Measure</th>
<th valign="middle" align="center"><italic>S. angel</italic></th>
<th valign="middle" align="center"><italic>S. guentheri</italic> (Cotopaxi NP)</th>
<th valign="middle" align="center"><italic>S. cadlei</italic></th>
<th valign="middle" align="center"><italic>S. festae</italic></th>
<th valign="middle" align="center"><italic>S. ornatus</italic></th>
<th valign="middle" align="center"><italic>S. chota</italic></th>
<th valign="middle" align="center"><italic>S. guentheri</italic> (Jerusalem RPPF)</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="8" align="left">a. <italic>T</italic><sub>pref</sub> (&#xb0;C)</th>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;N <sup>1</sup></td>
<td valign="middle" align="center">24 (12)</td>
<td valign="middle" align="center">24 (12)</td>
<td valign="middle" align="center">26 (12)</td>
<td valign="middle" align="center">16 (8)</td>
<td valign="middle" align="center">26 (13)</td>
<td valign="middle" align="center">24 (12)</td>
<td valign="middle" align="center">24 (12)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;All</td>
<td valign="middle" align="center">28.13 (1.52)</td>
<td valign="middle" align="center">27.70 (2.03)</td>
<td valign="middle" align="center">26.60 (3.50)</td>
<td valign="middle" align="center">25.77 (2.48)</td>
<td valign="middle" align="center">30.12 (1.89)</td>
<td valign="middle" align="center">29.77 (1.95)</td>
<td valign="middle" align="center">30.71 (2.05)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Males<sup>2</sup></td>
<td valign="middle" align="center">28.16 (1.61)</td>
<td valign="middle" align="center">27.31 (2.26)</td>
<td valign="middle" align="center">26.13 (4.45)</td>
<td valign="middle" align="center">25.57 (2.02)</td>
<td valign="middle" align="center">30.48 (1.79)</td>
<td valign="middle" align="center">30.38 (1.70)</td>
<td valign="middle" align="center">29.68 (1.67)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Females<sup>2</sup></td>
<td valign="middle" align="center">28.10 (1.50)</td>
<td valign="middle" align="center">28.09 (1.79)</td>
<td valign="middle" align="center">27.14 (1.97)</td>
<td valign="middle" align="center">25.97 (2.99)</td>
<td valign="middle" align="center">29.76 (2.00)</td>
<td valign="middle" align="center">29.15 (2.06)</td>
<td valign="middle" align="center">31.73 (1.92)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Sex difference <sup>3</sup></td>
<td valign="middle" align="center">t = -0.09</td>
<td valign="middle" align="center">t = 0.94</td>
<td valign="middle" align="center">t = 0.76</td>
<td valign="middle" align="center">t = 0.31</td>
<td valign="middle" align="center">t = 0.98</td>
<td valign="middle" align="center">t = -1.61</td>
<td valign="middle" align="center"><bold>t = 2.79</bold></td>
</tr>
<tr>
<td valign="middle" align="center"/>
<td valign="middle" align="center">p = 0.93</td>
<td valign="middle" align="center">p = 0.36</td>
<td valign="middle" align="center">p = 0.46</td>
<td valign="middle" align="center">p = 0.76</td>
<td valign="middle" align="center">p = 0.34</td>
<td valign="middle" align="center">p = 0.12</td>
<td valign="middle" align="center"><bold>p = 0.01</bold></td>
</tr>
<tr>
<th valign="middle" colspan="8" align="left">b. CT<sub>min</sub> (&#xb0;C)</th>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;N <sup>1</sup></td>
<td valign="middle" align="center">24(12)</td>
<td valign="middle" align="center">24(12)</td>
<td valign="middle" align="center">26(12)</td>
<td valign="middle" align="center">12 (7)</td>
<td valign="middle" align="center">26 (13)</td>
<td valign="middle" align="center">25 (12)</td>
<td valign="middle" align="center">24 (12)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;All</td>
<td valign="middle" align="center">5.89 (0.83)</td>
<td valign="middle" align="center">7.05 (1.03)</td>
<td valign="middle" align="center">6.38 (0.94)</td>
<td valign="middle" align="center">6.80 (0.87)</td>
<td valign="middle" align="center">7.32 (0.61)</td>
<td valign="middle" align="center">7.14 (0.63)</td>
<td valign="middle" align="center">7.47 (0.61)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Males<sup>2</sup></td>
<td valign="middle" align="center">5.97 (0.68)</td>
<td valign="middle" align="center">6.82 (1.16)</td>
<td valign="middle" align="center">6.36 (0.88)</td>
<td valign="middle" align="center">6.12 (0.32)</td>
<td valign="middle" align="center">7.46 (0.71)</td>
<td valign="middle" align="center">7.06 (0.63)</td>
<td valign="middle" align="center">7.54 (0.64)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Females<sup>2</sup></td>
<td valign="middle" align="center">5.81 (0.99)</td>
<td valign="middle" align="center">7.19 (0.86)</td>
<td valign="middle" align="center">6.41 (1.05)</td>
<td valign="middle" align="center">7.28 (0.81)</td>
<td valign="middle" align="center">7.16 (0.45)</td>
<td valign="middle" align="center">7.22 (0.64)</td>
<td valign="middle" align="center">7.40 (0.60)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Sex difference <sup>3</sup></td>
<td valign="middle" align="center">t = -0.475</td>
<td valign="middle" align="center">t = 1.16</td>
<td valign="middle" align="center">chi-sq = 0.003</td>
<td valign="middle" align="center"><bold>t = 3.422</bold></td>
<td valign="middle" align="center">t = -1.32</td>
<td valign="middle" align="center">chi-sq = 0.758</td>
<td valign="middle" align="center">t = -0.57</td>
</tr>
<tr>
<td valign="middle" align="center"/>
<td valign="middle" align="center">p = 0.64</td>
<td valign="middle" align="center">p = 0.26</td>
<td valign="middle" align="center">p = 0.96</td>
<td valign="middle" align="center"><bold>p = 0.009</bold></td>
<td valign="middle" align="center">p = 0.20</td>
<td valign="middle" align="center">p = 0.38</td>
<td valign="middle" align="center">p = 0.571</td>
</tr>
<tr>
<th valign="middle" colspan="8" align="left">c. CT<sub>max</sub> (&#xb0;C)</th>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;N <sup>1</sup></td>
<td valign="middle" align="center">24 (12)</td>
<td valign="middle" align="center">24 (12)</td>
<td valign="middle" align="center">26 (12)</td>
<td valign="middle" align="center">16 (8)</td>
<td valign="middle" align="center">27 (13)</td>
<td valign="middle" align="center">25 (12)</td>
<td valign="middle" align="center">24 (12)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;All</td>
<td valign="middle" align="center">39.45 (1.34)</td>
<td valign="middle" align="center">39.93 (2.07)</td>
<td valign="middle" align="center">38.74 (2.33)</td>
<td valign="middle" align="center">38.94 (1.31)</td>
<td valign="middle" align="center">39.33 (1.52)</td>
<td valign="middle" align="center">41.61 (1.62)</td>
<td valign="middle" align="center">39.94 (1.15)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Males<sup>2</sup></td>
<td valign="middle" align="center">39.53 (1.40)</td>
<td valign="middle" align="center">40.71 (1.92)</td>
<td valign="middle" align="center">38.88 (2.73)</td>
<td valign="middle" align="center">38.71 (1.62)</td>
<td valign="middle" align="center">39.92 (1.16)</td>
<td valign="middle" align="center">41.80 (1.60)</td>
<td valign="middle" align="center">39.80 (0.92)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Females<sup>2</sup></td>
<td valign="middle" align="center">39.37 (1.32)</td>
<td valign="middle" align="center">39.16 (1.99)</td>
<td valign="middle" align="center">38.58 (1.86)</td>
<td valign="middle" align="center">39.16 (0.96)</td>
<td valign="middle" align="center">38.70 (1.65)</td>
<td valign="middle" align="center">41.40 (1.69)</td>
<td valign="middle" align="center">40.08 (1.38)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Sex difference <sup>3</sup></td>
<td valign="middle" align="center">t = -0.30</td>
<td valign="middle" align="center">t = -1.95</td>
<td valign="middle" align="center">t = -0.33</td>
<td valign="middle" align="center">t = 0.68</td>
<td valign="middle" align="center"><bold>t = -2.20</bold></td>
<td valign="middle" align="center">t = -0.62</td>
<td valign="middle" align="center">t = 0.57</td>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="center">p = 0.76</td>
<td valign="middle" align="center">p = 0.06</td>
<td valign="middle" align="center">p = 0.74</td>
<td valign="middle" align="center">p = 0.51</td>
<td valign="middle" align="center"><bold>p = 0.04</bold></td>
<td valign="middle" align="center">p = 0.543</td>
<td valign="middle" align="center">p = 0.57</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p><sup>1</sup>Number of lizards with number of females in parentheses. <sup>2</sup>Values shown for each sex when sex differences reported. <sup>3</sup>T-test or Kruskal Wallis test (see methods). The sample size for <italic>S.festae</italic> was smaller than that of the other populations due to unforeseen circumstances encountered during sampling that forced us to stop fieldwork. Significant differences are in bold.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>The linear model examining <italic>T</italic><sub>pref</sub> as a function of SVL, sex, and ecosystem was highly significant (F = 8.861, df=4,159, <italic>p</italic> = 0.001), explaining 16.2% of the variation in <italic>T</italic><sub>pref</sub> (<xref ref-type="table" rid="T3"><bold>Table&#xa0;3a</bold></xref>). The model indicated that neither SVL nor sex had a significant effect on <italic>T</italic><sub>pref</sub>. However, significant differences were observed between ecosystems (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5A</bold></xref>). Pairwise comparisons indicated that lizards inhabiting the evergreen ecosystems had significantly lower <italic>T</italic><sub>pref</sub> compared to those from inter-Andean ecosystems. No significant difference was found between evergreen and paramo ecosystems, but there was a marked difference between inter-Andean and paramo, where lizards from inter-Andean ecosystems had significantly higher <italic>T</italic><sub>pref</sub>.</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Linear model outcomes for three thermal traits (<italic>T</italic><sub>pref</sub>, CT<sub>min</sub>, CT<sub>max</sub>) with SVL, sex, and ecosystem as fixed variables.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Thermal trait</th>
<th valign="middle" align="left"><italic>R</italic><sub>m</sub><sup>2</sup></th>
<th valign="middle" align="left"><italic>R</italic><sub>c</sub>&gt;
<sup>2</sup></th>
<th valign="middle" align="left">Estimate (&#xb0;C)</th>
<th valign="middle" align="left">Std. Error</th>
<th valign="middle" align="left"><italic>t</italic>-value</th>
<th valign="middle" align="left"><italic>p-</italic>value</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" align="left">a. <italic>T</italic><sub>pref</sub></th>
<th valign="middle" align="left">0.18</th>
<th valign="middle" align="left">0.16</th>
<th valign="middle" align="left"/>
<th valign="middle" align="left"/>
<th valign="middle" align="left"/>
<th valign="middle" align="left">0.001
</th>
</tr>
<tr>
<td valign="middle" align="left">SVL</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.02</td>
<td valign="middle" align="left">0.03</td>
<td valign="middle" align="left">0.62</td>
<td valign="middle" align="left">0.54</td>
</tr>
<tr>
<td valign="middle" align="left">Sex</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">-0.59</td>
<td valign="middle" align="left">0.58</td>
<td valign="middle" align="left">-1.01</td>
<td valign="middle" align="left">0.31</td>
</tr>
<tr>
<td valign="middle" align="left">Evergreen &#x2013; Inter-Andean</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">-1.87</td>
<td valign="middle" align="left">0.56</td>
<td valign="middle" align="left">-3.32</td>
<td valign="middle" align="left"><bold>0.003</bold></td>
</tr>
<tr>
<td valign="middle" align="left">Evergreen &#x2013; Paramo</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">1.06</td>
<td valign="middle" align="left">0.50</td>
<td valign="middle" align="left">2.11</td>
<td valign="middle" align="left">0.09</td>
</tr>
<tr>
<td valign="middle" align="left">Inter-Andean &#x2013; Paramo</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">2.93</td>
<td valign="middle" align="left">0.54</td>
<td valign="middle" align="left">5.47</td>
<td valign="middle" align="left"><bold>&lt;0.0001</bold></td>
</tr>
<tr>
<th valign="middle" align="left">b. CT<sub>min</sub></th>
<th valign="middle" align="left">0.19</th>
<th valign="middle" align="left">0.17</th>
<th valign="middle" align="left"/>
<th valign="middle" align="left"/>
<th valign="middle" align="left"/>
<th valign="middle" align="left">0.001
</th>
</tr>
<tr>
<td valign="middle" align="left">SVL</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">-0.02</td>
<td valign="middle" align="left">0.01</td>
<td valign="middle" align="left">-1.43</td>
<td valign="middle" align="left">0.15</td>
</tr>
<tr>
<td valign="middle" align="left">Sex</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.13</td>
<td valign="middle" align="left">0.20</td>
<td valign="middle" align="left">0.65</td>
<td valign="middle" align="left">0.52</td>
</tr>
<tr>
<td valign="middle" align="left">Evergreen &#x2013; Inter-Andean</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">-0.05</td>
<td valign="middle" align="left">0.19</td>
<td valign="middle" align="left">-0.25</td>
<td valign="middle" align="left">0.97</td>
</tr>
<tr>
<td valign="middle" align="left">Evergreen &#x2013; Paramo</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.68</td>
<td valign="middle" align="left">0.17</td>
<td valign="middle" align="left">3.92</td>
<td valign="middle" align="left"><bold>0.0004</bold></td>
</tr>
<tr>
<td valign="middle" align="left">Inter-Andean &#x2013; Paramo</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.73</td>
<td valign="middle" align="left">0.18</td>
<td valign="middle" align="left">4.02</td>
<td valign="middle" align="left"><bold>0.0003</bold></td>
</tr>
<tr>
<th valign="middle" align="left">c. CT<sub>max</sub></th>
<th valign="middle" align="left">0.15</th>
<th valign="middle" align="left">0.13</th>
<th valign="middle" align="left"/>
<th valign="middle" align="left"/>
<th valign="middle" align="left"/>
<th valign="middle" align="left">0.003
</th>
</tr>
<tr>
<td valign="middle" align="left">SVL</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.004</td>
<td valign="middle" align="left">0.023</td>
<td valign="middle" align="left">0.19</td>
<td valign="middle" align="left">0.85</td>
</tr>
<tr>
<td valign="middle" align="left">Sex</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.41</td>
<td valign="middle" align="left">0.396</td>
<td valign="middle" align="left">1.04</td>
<td valign="middle" align="left">0.30</td>
</tr>
<tr>
<td valign="middle" align="left">Evergreen &#x2013; Inter-Andean</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">-1.63</td>
<td valign="middle" align="left">0.38</td>
<td valign="middle" align="left">-4.24</td>
<td valign="middle" align="left"><bold>0.0001</bold></td>
</tr>
<tr>
<td valign="middle" align="left">Evergreen &#x2013; Paramo</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">-0.16</td>
<td valign="middle" align="left">0.34</td>
<td valign="middle" align="left">-0.47</td>
<td valign="middle" align="left">0.89</td>
</tr>
<tr>
<td valign="middle" align="left">Inter-Andean &#x2013; Paramo</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">1.47</td>
<td valign="middle" align="left">0.37</td>
<td valign="middle" align="left">3.99</td>
<td valign="middle" align="left"><bold>0.0003</bold></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Significant differences are in bold.</p></fn>
</table-wrap-foot>
</table-wrap>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Pairwise comparisons between ecosystem types for each thermophysiological trait evaluated. <bold>(A)</bold> Preferred body temperature (<italic>T</italic><sub>pref</sub>), <bold>(B)</bold> critical thermal minimum (CT<sub>min</sub>), <bold>(C)</bold> critical thermal maximum (CT<sub>max</sub>). Ev, Evergreen; IA, Inter-Andean; Pa, Paramo. a- no significant differences, b - significant differences.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="famrs-04-1758509-g005.tif">
<alt-text content-type="machine-generated">Bar charts labeled A, B, and C, showing temperature in degrees Celsius for ecosystems Ev, IA, and Pa. Chart A shows IA highest with 30&#xb0;C, Chart B has Ev and IA both at 7&#xb0;C, and Chart C displays IA highest at 41&#xb0;C. Error bars indicate variability.</alt-text>
</graphic></fig>
<p>The linear model for CT<sub>min</sub>, was also significant (F = 9.228, df=4,156, <italic>p</italic> = 0.001), explaining 17.1% of the variance (<xref ref-type="table" rid="T3"><bold>Table&#xa0;3b</bold></xref>). As above, neither SVL nor sex significantly affected CT<sub>min</sub> of <italic>Stenocercus</italic> lizards, but significant variation was found among ecosystems (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5B</bold></xref>). Pairwise comparisons between ecosystem categories revealed that CT<sub>min</sub> of lizards from the evergreen and inter-Andean ecosystems was not significantly different. However, paramo lizards had significantly lower CT<sub>min</sub> than those from the evergreen and inter-Andean ecosystems.</p>
<p>As with the other two measures, the linear model for CT<sub>max</sub> was significant (F = 7.035, df=4,161, <italic>p</italic> = 0.03), explaining 12.8% of the variance, with only ecosystems significantly impacting CT<sub>max</sub> (<xref ref-type="table" rid="T3"><bold>Table&#xa0;3c</bold></xref>). Pairwise comparisons showed no significant difference&#xa0;between lizards from evergreen and paramo ecosystems.&#xa0;In&#xa0;contrast, lizards from inter-Andean ecosystems had significantly&#xa0;higher CT<sub>max</sub> than to those from the other two ecosystems (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5C</bold></xref>).</p>
<p>Despite the statistical differences observed between sexes within some populations, the linear models did not show a significant effect of sex on <italic>T</italic><sub>pref</sub>, CT<sub>min</sub>, or CT<sub>max</sub>. Therefore, the average values of each thermophysiological traits were used for downstream analysis (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>).</p>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Thermal vulnerability</title>
<sec id="s3_3_1">
<label>3.3.1</label>
<title>Thermophysiological traits in relation to micro-environmental temperatures</title>
<p>Average and ranges of <italic>T</italic><sub>b</sub>, <italic>T</italic><sub>air</sub>, and <italic>T</italic><sub>sub</sub> for each population are summarised in <xref ref-type="table" rid="T4"><bold>Table&#xa0;4</bold></xref>. Graphical depiction of the relationship between thermal physiological traits and environmental temperatures are presented in <xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6</bold></xref>, separately for each species/population and organised by ecosystem type: inter-Andean (<xref ref-type="fig" rid="f6"><bold>Figures&#xa0;6A, B</bold></xref>), evergreen (<xref ref-type="fig" rid="f6"><bold>Figures&#xa0;6C, D</bold></xref>) and paramo (<xref ref-type="fig" rid="f6"><bold>Figures&#xa0;6E&#x2013;G</bold></xref>).</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Average and range <italic>T</italic><sub>b</sub>, <italic>T</italic><sub>sub</sub>, and <italic>T</italic><sub>air</sub> recorded for <italic>Stenocercus</italic> species/populations from high-altitude tropical montane ecosystems.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Species/Populations</th>
<th valign="middle" align="right"><italic>T</italic><sub>b</sub> (&#xb0;C)</th>
<th valign="middle" align="right"><italic>T</italic><sub>sub</sub> (&#xb0;C)</th>
<th valign="middle" align="right"><italic>T</italic><sub>air</sub> (&#xb0;C)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left"><italic>a. S. guentheri</italic> (Jerusalem RPPF) (N = 24)</td>
<td valign="middle" align="right">29.7<break/>(20.5 &#x2013; 35.1)</td>
<td valign="middle" align="right">29.11<break/>(20.8 &#x2013; 38.4)</td>
<td valign="middle" align="right">27.74<break/>(20.7 &#x2013; 31.6)</td>
</tr>
<tr>
<td valign="middle" align="left">b. <italic>S. chota</italic><break/>(N = 24)</td>
<td valign="middle" align="right">28.45<break/>(21.7 &#x2013; 34.8)</td>
<td valign="middle" align="right">26.52<break/>(18.2 &#x2013; 43.5)</td>
<td valign="middle" align="right">24.29<break/>(18.9 &#x2013; 30.3)</td>
</tr>
<tr>
<td valign="middle" align="left">c. <italic>S. ornatus</italic><break/>(N = 26)</td>
<td valign="middle" align="right">27.51<break/>(18.5 &#x2013; 34.9)</td>
<td valign="middle" align="right">24.56<break/>(18.9 &#x2013; 31.2)</td>
<td valign="middle" align="right">25.38<break/>(19.4 &#x2013; 29.9)</td>
</tr>
<tr>
<td valign="middle" align="left">d. <italic>S. festae</italic><break/>(N = 16)</td>
<td valign="middle" align="right">26.94<break/>(18.2 &#x2013; 34.8)</td>
<td valign="middle" align="right">25<break/>(16.8 &#x2013; 46.5)</td>
<td valign="middle" align="right">22.71<break/>(15.7 &#x2013; 27)</td>
</tr>
<tr>
<td valign="middle" align="left">e. <italic>S. angel</italic><break/>(N = 24)</td>
<td valign="middle" align="right">26.75<break/>(20.1 &#x2013; 32.3)</td>
<td valign="middle" align="right">25.38<break/>(13.5 &#x2013; 38.2)</td>
<td valign="middle" align="right">17.39<break/>(12.5 &#x2013; 21.7)</td>
</tr>
<tr>
<td valign="middle" align="left">f. <italic>S. guentheri</italic> (Cotopaxi)<break/>(N = 24)</td>
<td valign="middle" align="right">25.79<break/>(16.5 &#x2013; 31.8)</td>
<td valign="middle" align="right">23.86<break/>(14.4 &#x2013; 32.4)</td>
<td valign="middle" align="right">19.14<break/>(15.2 &#x2013; 22.5)</td>
</tr>
<tr>
<td valign="middle" align="left">g. <italic>S. cadlei</italic><break/>(N = 24)</td>
<td valign="middle" align="right">22.81<break/>(10.3 &#x2013; 33.7)</td>
<td valign="middle" align="right">23.01<break/>(10.8 &#x2013; 49.3)</td>
<td valign="middle" align="right">15.45<break/>(7.4 &#x2013; 21.3)</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Relationship between thermal physiological traits and operative temperature for each assessed population. The red curves represent the hourly average of OTMs placed in sun-exposed microhabitats, while blue curves show the hourly average of OTMs in shaded microhabitats. Black dots represent the body temperature of active individuals plotted against the corresponding hour of capture. The dashed lines show the average <italic>T</italic><sub>pref</sub>, CT<sub>min</sub>, and CT<sub>max</sub> for each population. <bold>(A)</bold><italic>S. guentheri</italic> from Jerusalem RPPF, <bold>(B)</bold><italic>S. chota</italic> from Pisquer, <bold>(C)</bold><italic>S. ornatus</italic> from Madrigal PR, <bold>(D)</bold><italic>S. festae</italic> from El Gullan SS, <bold>(E)</bold><italic>S. angel</italic> from El Angel ER, <bold>(F)</bold><italic>S. guentheri</italic> Cotopaxi NP, <bold>(G)</bold><italic>S. cadlei</italic> from Chimborazo WPR.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="famrs-04-1758509-g006.tif">
<alt-text content-type="machine-generated">Seven line graphs labeled A to G show temperature fluctuations throughout the day. Each graph displays critical temperature maximum (CTmax), preferred temperature (Tpref), and critical temperature minimum (CTmin) as reference lines. Averages are depicted with black dots, showing different patterns on each graph.</alt-text>
</graphic></fig>
<p>Inter-Andean sites revealed similar patterns. At Jerusalem RPPF, and between 0900 and 1500 hours, sun exposed microhabitats reached temperatures exceeding the average CT<sub>max</sub> of <italic>S. guentheri</italic> (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6A</bold></xref>). Moreover, around midday, shaded areas warmed to values close to the population&#x2019;s average <italic>T</italic><sub>pref</sub>, which also aligned closely with the average <italic>T</italic><sub>b</sub> (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4a</bold></xref>). In contrast, early morning temperatures were below the average CT<sub>min</sub> (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6A</bold></xref>). At Pisquer, midday temperatures in sun-exposed microhabitats peaked above the average CT<sub>max</sub> of <italic>S. chota</italic>, while shaded areas approached the average <italic>T</italic><sub>pref</sub> (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6B</bold></xref>). <italic>T</italic><sub>b</sub> of this population ranged between 21.7&#xb0;C and 34.8&#xb0;C (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4b</bold></xref>), with an average lower than the species&#x2019; average <italic>T</italic><sub>pref</sub>. Additionally, shaded microhabitats also remained above the average CT<sub>min</sub> (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6B</bold></xref>).</p>
<p>Evergreen sites showed broadly similar patterns, but with some key differences between them. Between 1000 and 1200 hours at El Madrigal PR, sun-exposed microhabitats exceeded the average CT<sub>max</sub> of <italic>S. ornatus</italic> (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6C</bold></xref>). During the same period, shaded areas were about 10&#xb0;C cooler than the average <italic>T</italic><sub>pref</sub>. This thermal contrast enabled lizards to maintain <italic>T</italic><sub>b</sub> values between 18.5&#xb0;C and 34.9&#xb0;C (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4c</bold></xref>). The average CT<sub>min</sub> was also lower than the minimum recorded micro-environmental temperature. At El Gullan SS, sun-exposed areas reached peak temperatures before midday, matching the average CT<sub>max</sub> of <italic>S. festae</italic> (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6D</bold></xref>). In early morning, the coolest shaded temperatures were near the average CT<sub>min</sub>. Lizards here exhibited <italic>T</italic><sub>b</sub> values ranging from 18.2&#xb0;C to 34.8&#xb0;C (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4d</bold></xref>), with a mean close to their average <italic>T</italic><sub>pref</sub>.</p>
<p>Nighttime temperatures were a challenge in paramos ecosystems. At El Angel ER, sun-exposed microhabitats peaked at 1200 hours, reaching temperatures close to the population&#x2019;s average <italic>T</italic><sub>pref</sub> and approximately 10&#xb0;C below the average CT<sub>max</sub> of <italic>S. angel</italic> (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6E</bold></xref>). Shaded areas were often cooler than the average CT<sub>min</sub>, especially at night. Despite this, average <italic>T</italic><sub>b</sub> remained above 26&#xb0;C (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4e</bold></xref>). At Cotopaxi NP, maximum temperatures in sun-exposed areas never reached the average CT<sub>max</sub> of <italic>S. guentheri</italic> (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6F</bold></xref>). From 1800 to 0800 hours, microhabitat temperatures fell below the average CT<sub>min</sub>. Lizards showed <italic>T</italic><sub>b</sub> values ranging from 16.5&#xb0;C to 31.8&#xb0;C (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4f</bold></xref>), reflecting the highly variable thermal environment. Finally, at Chimborazo WPR, sun-exposed microhabitats reached the average CT<sub>max</sub> of <italic>S. cadlei</italic> around midday (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6G</bold></xref>). At night, temperatures dropped below the average CT<sub>min</sub>. The consistently cold conditions resulted in <italic>T</italic><sub>b</sub> values ranging from 10.3&#xb0;C to 33.7&#xb0;C, with an average lower than the species&#x2019; <italic>T</italic><sub>pref</sub> (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4g</bold></xref>).</p>
</sec>
<sec id="s3_3_2">
<label>3.3.2</label>
<title>Thermal safety margins and warming tolerance</title>
<p>Thermal safety margins (TSM) and warming tolerance (WT) under three scenarios (present, +1.5&#xb0;C, and +2&#xb0;C) for each species/population are presented in <xref ref-type="table" rid="T5"><bold>Table&#xa0;5</bold></xref>.</p>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>Thermal safety margins (TSM) and warming tolerance (WT) under three scenarios for <italic>Stenocercus</italic> species/populations assessed.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Species/populations</th>
<th valign="middle" align="right">TSM (&#xb0;C)</th>
<th valign="middle" align="right">WT (present)</th>
<th valign="middle" align="right">WT (+1.5 &#xb0;C)</th>
<th valign="middle" align="right">WT (+2&#xb0;C)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">a. <italic>S. guentheri</italic> (Jerusalem RPPF)</td>
<td valign="middle" align="right">-1.43</td>
<td valign="middle" align="right">5.63</td>
<td valign="middle" align="right">4.13</td>
<td valign="middle" align="right">3.63</td>
</tr>
<tr>
<td valign="middle" align="left">b. <italic>S. chota</italic></td>
<td valign="middle" align="right">0.73</td>
<td valign="middle" align="right">15.69</td>
<td valign="middle" align="right">14.19</td>
<td valign="middle" align="right">13.69</td>
</tr>
<tr>
<td valign="middle" align="left">c. <italic>S. ornatus</italic></td>
<td valign="middle" align="right">6.73</td>
<td valign="middle" align="right">12.78</td>
<td valign="middle" align="right">11.28</td>
<td valign="middle" align="right">10.78</td>
</tr>
<tr>
<td valign="middle" align="left">d. <italic>S. festae</italic></td>
<td valign="middle" align="right">8.67</td>
<td valign="middle" align="right">-3.68</td>
<td valign="middle" align="right">-5.18</td>
<td valign="middle" align="right">-5.68</td>
</tr>
<tr>
<td valign="middle" align="left">e. <italic>S. angel</italic></td>
<td valign="middle" align="right">17.75</td>
<td valign="middle" align="right">22.75</td>
<td valign="middle" align="right">21.25</td>
<td valign="middle" align="right">20.75</td>
</tr>
<tr>
<td valign="middle" align="left">f. <italic>S. guentheri</italic> (Cotopaxi)</td>
<td valign="middle" align="right">18.3</td>
<td valign="middle" align="right">17.02</td>
<td valign="middle" align="right">15.52</td>
<td valign="middle" align="right">15.02</td>
</tr>
<tr>
<td valign="middle" align="left">g. <italic>S. cadlei</italic></td>
<td valign="middle" align="right">22.09</td>
<td valign="middle" align="right">20.5</td>
<td valign="middle" align="right">19</td>
<td valign="middle" align="right">18.5</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Species inhabiting inter-Andean ecosystems appear to be the most vulnerable to rising temperatures in their habitats. The negative TSM values and small WT scores of <italic>S. guentheri</italic> from Jerusalem RPPF place this population at the highest risk among all focal populations. Meanwhile, <italic>S. chota</italic> is close to the limit of its physiological capacity to buffer high temperatures in its microhabitats but can still tolerate current and projected warming scenarios.</p>
<p>Lizards from evergreen ecosystems show that their microhabitats remain more than 6&#xb0;C below the point at which activity becomes restricted. However, the negative WT values of <italic>S. festae</italic> indicate that these lizards may still be at risk. A completely different pattern emerges for species inhabiting paramo ecosystems. The three populations evaluated in this ecosystem type (<italic>S. angel</italic> from El Angel ER, <italic>S. guentheri</italic> from Cotopaxi NP, and <italic>S. cadlei</italic> from Chimborazo WPR) show positive TSM and WT values, implying sufficient physiological resilience to avoid overheating.</p>
</sec>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>Across the studied tropical Andean ecosystems, pronounced differences in daily temperature variability and microhabitat thermal conditions were closely associated with variation in lizard thermal preferences, tolerances, and vulnerability, supporting our hypothesis that local climate and vegetation interactions shape thermophysiological traits of high-altitude <italic>Stenocercus</italic> populations. For instance, lizards inhabiting ecosystems characterised by high diurnal temperature conditions, such as Inter-Andean ecosystems, exhibit the highest CT<sub>max</sub> and <italic>T</italic><sub>pref</sub> values. In contrast, paramo lizards show the lowest CT<sub>min</sub> values due to the cold conditions they are exposed in their microenvironments. Furthermore, microhabitat analyses revealed that structurally complex vegetation in tropical montane ecosystems created diverse thermal mosaics, allowing lizards to behaviourally thermoregulate by exploiting sun-exposed or shaded areas. Despite this buffering capacity, thermal safety margins and warming tolerance varied markedly among populations. Inter-Andean populations were the most vulnerable to warming due to frequent exposure to temperatures near or above their critical thermal maximum, whereas paramo populations maintained positive safety margins and warming tolerance, indicating greater resilience to overheating. Overall, these results demonstrate that daily temperature variability and vegetation-driven microclimatic heterogeneity jointly influence thermal flexibility and vulnerability in high-altitude tropical montane lizards.</p>
<p>Various physical mechanisms in the Tropical Andes, such as the El Ni&#xf1;o-Southern Oscillation and the presence of trade winds to the north, drive temporal variability that shapes the region&#x2019;s climate (<xref ref-type="bibr" rid="B44">Mart&#xed;nez et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B75">Young et&#xa0;al., 2007</xref>). This climatic variability, combined with the complex topography of the Andes, has created a diverse array of climatic niches, promoting physiological specialisation in response to differing thermal and rainfall regimes (<xref ref-type="bibr" rid="B61">Salazar et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B62">Sheldon, 2019</xref>). For example, macroclimate conditions in high-altitude tropical Andean ecosystems show marked daily temperature fluctuations (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4</bold></xref>), which we propose directly influence the thermal exposure of <italic>Stenocercus</italic> lizards at the microhabitat scale. Additionally, the uplift of the Andes led to the formation of isolated land areas, each hosting distinct ecosystems with representative vegetation assemblages.</p>
<p>One such ecosystem is the inter-Andean valleys, where precipitation is limited due to the rain shadow effect caused by the surrounding high cordilleras (<xref ref-type="bibr" rid="B52">Neill, 1999</xref>). These arid valleys are dominated by xerophytic plant species from the families Cactaceae and Agavaceae, along with small shrubs and trees from the Euphorbiaceae and Fabaceae families (<xref ref-type="bibr" rid="B52">Neill, 1999</xref>; <xref ref-type="bibr" rid="B71">Werner, 2009</xref>). This distinctive vegetation composition results in open microhabitats with reduce shaded areas, thereby exposing lizards to intense solar radiation and elevated temperatures, especially during midday hours. Consequently, <italic>S. guentheri</italic> and <italic>S. chota</italic> populations inhabiting inter-Andean ecosystems exhibit higher <italic>T</italic><sub>pref</sub> and CT<sub>max</sub> values compared to those living in evergreen and paramo ecosystems.</p>
<p>In contrast, evergreen ecosystems, now reduced to highly localised and increasingly fragmented remnants, are under severe threat from burning, grazing, and the relentless expansion of the agricultural frontier (<xref ref-type="bibr" rid="B46">Ministerio del Ambiente del Ecuador, 2013</xref>). Despite their vulnerability, these ecosystems provide a markedly different thermal environment for lizards. Characterised by a low and open canopy, evergreen ecosystems support a rich assemblage of epiphytes, particularly from the Orchidaceae and Bromeliaceae families (<xref ref-type="bibr" rid="B46">Ministerio del Ambiente del Ecuador, 2013</xref>). This complex vertical structure contributes to a cooler and more thermally buffered microclimate, offering lizards access to shaded refuges and reduced exposure to extreme heat. As a result, lizard populations in these ecosystems (<italic>S. ornatus</italic> and <italic>S. festae</italic>) tended to exhibit lower thermal preferences and heat tolerances than those in the more exposed inter-Andean valleys.</p>
<p>Finally, paramo ecosystems, situated at even higher elevations, present a unique suite of environmental conditions. These ecosystems are shaped by intense daily temperature fluctuations, strong winds, high ultraviolet radiation, frequent precipitation, and low atmospheric pressure (<xref ref-type="bibr" rid="B60">Ruiz et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B76">Young et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B16">Cuesta et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B11">CEPF, 2021</xref>). The vegetation in these landscapes consists of dense shrub-herbaceous assemblages dominated by sclerophyllous shrubs such as <italic>Chuquiraga</italic> and <italic>Diplostephium</italic>, cushion-forming plants like <italic>Xenophyllum</italic> and <italic>Azorella</italic>, and low-growing grasses of the genus <italic>Calamagrostis</italic> (<xref ref-type="bibr" rid="B16">Cuesta et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B59">Romoleroux et&#xa0;al., 2023</xref>). These plant forms create microhabitats that are both thermally challenging and spatially heterogeneous. Lizards inhabiting paramo ecosystems (<italic>S. guentheri</italic>, <italic>S. angel</italic>, and <italic>S. cadlei</italic>) are therefore adapted to withstand cold temperatures and tend to prefer lower body temperatures than their counterparts in drier, sun-exposed inter-Andean environments. Additionally, the unique structural and climatic features of paramo ecosystems contribute to shaping distinct physiological tolerances, highlighting the critical role of habitat-specific environmental pressures in driving thermal adaptation in high-altitude tropical Andean <italic>Stenocercus</italic> lizards.</p>
<p>According to the thermal adaptation hypothesis, the minimum and maximum temperatures of an organism&#x2019;s microenvironment should align with its thermal limits, thereby minimising the physiological costs associated with maintaining thermal tolerances (<xref ref-type="bibr" rid="B4">Angilleta, 2009</xref>; <xref ref-type="bibr" rid="B35">Janzen, 1967</xref>; <xref ref-type="bibr" rid="B36">Kaspari et&#xa0;al., 2015</xref>). This framework may help explain the observed variation in thermophysiological traits among high-altitude tropical montane <italic>Stenocercus</italic> populations, which differ according to the ecosystem types they inhabit. However, considering the relatively recent diversification of this lizard group in the northern Andes (<xref ref-type="bibr" rid="B69">Torres-Carvajal, 2007b</xref>), further research is needed to determine whether their physiological traits result from short-term phenotypic plasticity, longer-term thermal acclimation, or genetic adaptation, as documented in other taxa (<xref ref-type="bibr" rid="B9">Bujan et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B43">Martin et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B64">S&#xf8;rensen et&#xa0;al., 2016</xref>). The isolated land formations created by the uplift of the Andes may have further promoted the divergence of thermophysiological traits within this lizard clade by facilitating climate niche specialisation at the microhabitat scale (<xref ref-type="bibr" rid="B17">Dangles, 2023</xref>; <xref ref-type="bibr" rid="B22">Flantua and Hooghiemstra, 2018</xref>; <xref ref-type="bibr" rid="B26">Hazzi et&#xa0;al., 2018</xref>). Yet, this degree of specialisation may come at a cost, increasing these lizards&#x2019; vulnerability to ongoing climate warming. The extent to which <italic>Stenocercus</italic> lizards can buffer against this threat likely depends on the availability of suitable microhabitats that reduce overheating risk, as well as behavioural strategies that allow them to effectively regulate their body temperature.</p>
<p>Daylight ambient temperatures in tropical montane microhabitats begin to rise around 0800 hours and decreased by 1700 hours, defining the activity period of <italic>Stenocercus</italic> lizards. However, microenvironmental temperature conditions within and beyond this activity window vary across tropical Andean ecosystems, exposing each lizard population to differing levels of vulnerability (<xref ref-type="bibr" rid="B54">Pincebourde and Suppo, 2016</xref>). Simple vulnerability indices, such as thermal safety margins (TSM) and warming tolerance (WT), are widely used to evaluate species vulnerability to rising temperatures (<xref ref-type="bibr" rid="B18">Deutsch et&#xa0;al., 2008</xref>). These indices quantify how close a species&#x2019; thermal limits and optimal body temperatures are to projected warming scenarios, offering insights into their capacity to cope with rising temperatures (<xref ref-type="bibr" rid="B15">Clusella-Trullas et&#xa0;al., 2021</xref>). This framework is based on the premise that temperature sensitivity of physiological performance plays a critical role in determining species distributions and survival (<xref ref-type="bibr" rid="B66">Sunday et&#xa0;al., 2012</xref>). Consequently, these indices serve as valuable tools for comparing vulnerability across different species or populations.</p>
<p>Although <italic>S. chota</italic> and <italic>S. guentheri</italic> inhabit inter-Andean ecosystems, their microhabitats presented contrasting thermal characteristics, leading to opposing thermal vulnerability outcomes. The <italic>S. guentheri</italic> population from Jerusalem RPPF experienced the most severe thermal stress of all evaluated populations. On the one hand, they suffered from cold physiological stress during some hours of nighttime, as their CT<sub>min</sub> is higher than the lowest temperatures available in their microhabitats. On the other hand, daytime temperatures in their microhabitats exceeded their average CT<sub>max</sub>, being greater at midday when temperatures are more than 10&#xb0;C higher compared to the average CT<sub>max</sub>. As a result, they exhibited negative thermal safety margins and minimal warming tolerance, which may increase mortality rates and decrease population growth (<xref ref-type="bibr" rid="B37">Kearney, 2013</xref>; <xref ref-type="bibr" rid="B48">Munch and Salinas, 2009</xref>). Conversely, <italic>S. chota</italic> showed no evidence of thermal stress from either cold or heat based on the thermal conditions in their microhabitats. However, their narrow thermal safety margin indicates that they inhabit environments near their physiological optimum (<xref ref-type="bibr" rid="B18">Deutsch et&#xa0;al., 2008</xref>). Therefore, warming is likely to cause these lizards to retreat to cool refuges limiting their activity and constraining other functions such as foraging and reproduction (<xref ref-type="bibr" rid="B63">Sinervo et&#xa0;al., 2010</xref>).</p>
<p>Lizard species inhabiting evergreen ecosystems, such as <italic>S. festae</italic> and <italic>S. ornatus</italic>, exhibited average CT<sub>min</sub> values below the minimum temperatures of their microhabitats. However, midday temperatures in their micro-environments approached or exceeded their average CT<sub>max</sub>. Despite this, these populations maintained favourable thermal safety margins, suggesting positive physiological responses to cope with high temperatures in their microhabitats. Interestingly, <italic>S. festae</italic> exhibited negative warming tolerance under current temperature conditions and across the two projected warming scenarios, suggesting an inability to tolerate even slightly higher temperatures than those currently experienced (<xref ref-type="bibr" rid="B2">Anderson et&#xa0;al., 2022</xref>). Conversely, <italic>S. ornatus</italic> showed no physiological limitations under any of the three assessed warming scenarios, indicating a greater capacity to cope with rising temperatures. Although evergreen ecosystems typically offer suitable thermal microhabitats that lizards to avoid overheating, ongoing habitat fragmentation is diminishing these refuges and increasing exposure to high temperatures. This phenomenon is evident at El Gullan SS, where large portions of the surrounding landscape have been converted into pine plantations, grazing areas, and agricultural lands. Such extensive alteration is suggested to intensify thermal stress for <italic>S. festae</italic> populations. Therefore, urgent action is needed to halt the continued degradation of these ecosystems and to preserve the thermal habitats essential for the survival of this species.</p>
<p><italic>Stenocercus</italic> species from paramo ecosystems, including <italic>S. angel</italic>, <italic>S. guentheri</italic>, and <italic>S. cadlei</italic>, inhabit the coldest environments among all analysed populations. The extremely low nighttime temperature in their microhabitats fall below their average CT<sub>min</sub> for substantial periods, increasing their dependence on thermal refuges to avoid extreme cold and enhancing their cold tolerance (<xref ref-type="bibr" rid="B55">Pintanel et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B61">Salazar et&#xa0;al., 2024</xref>). In contrast, the maximum temperatures in their microhabitats remained below their average CT<sub>max</sub>, suggesting they are unlikely to experience physiological stress from heat exposure. Additionally, thermal safety margins indicate that these lizards possess sufficient physiological resilience to avoid overheating. This is further supported by warming tolerance calculations, showing that even under the highest projected warming scenario of +2&#xb0;C, paramo lizards will not be physiologically constrained. These findings align with other studies, which suggest that lizards inhabiting thermally variable environments exhibit greater physiological tolerance to warming, making them less vulnerable to rising temperatures compared to populations in more thermally stable conditions (<xref ref-type="bibr" rid="B40">Lara-Resendiz et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B77">Yuan et&#xa0;al., 2018</xref>).</p>
<p>In the context of climate change, terrestrial ectotherms must rapidly respond to novel thermal environments without prolonged exposure to suboptimal temperatures that could impair their performance. By either adapting physiologically, adjusting their behaviour or employing both strategies, organisms can mitigate potential impacts of climate change on their populations (<xref ref-type="bibr" rid="B5">Angilletta et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B51">Mu&#xf1;oz et&#xa0;al., 2014</xref>). Behavioural thermoregulation is an effective short-term strategy to minimise exposure to extreme climate conditions (<xref ref-type="bibr" rid="B5">Angilletta et&#xa0;al., 2002</xref>). Additionally, studies on tropical anole species suggest that behavioural thermoregulation can shield organisms from selective pressures on upper physiological thermal limits, while cold tolerance remains under stronger selection (<xref ref-type="bibr" rid="B51">Mu&#xf1;oz et&#xa0;al., 2014</xref>). Thus, examining how organisms interact with the available microthermal habitats can help elucidate patterns of physiological divergence in tropical montane species as well as support predictions of vulnerability to climate change (<xref ref-type="bibr" rid="B4">Angilleta, 2009</xref>; <xref ref-type="bibr" rid="B30">Huey et&#xa0;al., 2003</xref>).</p>
<p>In conclusion, the microscale environmental conditions experienced by high-altitude tropical Andean <italic>Stenocercus</italic> populations have shaped specialised thermophysiological profiles tailored to the thermal variability in their habitats. However, thermophysiological responses vary among populations depending on their exposure to environmental changes. Particular attention should be given to populations such as <italic>S. guentheri</italic> (inter-Andean) and <italic>S. festae</italic>, which face challenges due to either reduced performance under high temperature conditions in their habitats or limited physiological tolerances to warming. For these populations, thermoregulatory behaviours may be the primary mechanism to cope with rising temperatures, given the constraints ectotherm tropical Andean species face in shifting their elevational ranges (<xref ref-type="bibr" rid="B23">Forero-Medina et&#xa0;al., 2010</xref>). Long-term monitoring of these populations is important for understanding their adaptative strategies in behaviour and physiology, as well as the implications for their ecological niches. Moreover, such monitoring could inform conservation policies that advocate for the protection of high-elevation climate refugia. While it is evident that global warming poses significant risks to populations like <italic>S. festae</italic> and <italic>S. guentheri</italic>, other <italic>Stenocercus</italic> populations, such as those inhabiting paramo ecosystems may not be as adversely affected by rising temperatures as reported for other cold-adapted lizard species (<xref ref-type="bibr" rid="B19">Doan et&#xa0;al., 2022</xref>). However, further research into the mechanisms of cold tolerance in these lizards is essential to better understand how these traits might evolve or constraint adaptation to warming scenarios. Finally, exploring the adaptive significance of thermal developmental phenotypic plasticity (an area currently unexplored in <italic>Stenocercus</italic> lizards) could enhance predictions of vulnerability in the face of climate change. This mechanism, which has been suggested to have organisational effects that potentially constrain phenotypic development later in life (<xref ref-type="bibr" rid="B72">While et&#xa0;al., 2018</xref>), may hold key insights into the resilience of tropical Andean species in a warming world.</p>
</sec>
</body>
<back>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p></sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The animal study was approved by La Trobe University Animal Ethics Committee. Project No.: AEC-21-028. Fieldwork permits were issued by the Ministry of Environment, Water, and Ecological Transition (MAAE-ARSFC-2021-1463, MAATE-ARSFC-2022-2330, MAATE-ARSFC-2023-3250, MAAE-DBI-CM-2022-0229). The study was conducted in accordance with the local legislation and institutional requirements.</p></sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>EG-C: Formal analysis, Project administration, Data curation, Investigation, Writing &#x2013; review &amp; editing, Methodology, Conceptualization, Writing &#x2013; original draft. JG: Writing &#x2013; review &amp; editing, Supervision, Resources. RP: Resources, Funding acquisition, Formal analysis, Writing &#x2013; review &amp; editing, Methodology, Supervision.</p></sec>
<ack>
<title>Acknowledgments</title>
<p>Thanks to all fieldwork assistants for their dedication and hard work: Sebasti&#xe1;n Mena, Marek Castel, Salom&#xe9; Pillajo, Erick Troncoso, Sof&#xed;a Gonz&#xe1;lez, Malki Bustos, Jefferson Mora, Michelle Est&#xe9;vez, and Kerly Tr&#xe1;vez. To the park rangers for welcoming us with respect and generously shared their facilities: &#xd3;scar Mu&#xf1;oz, Edwin Taipe, Eduardo Quinga, Giovanni Tocto, and Miguel Paguay. To the National Parks authorities: Dami&#xe1;n Ponce, Mario Jarr&#xed;n, and Pa&#xfa;l Tito, as well as the community members of Pulingu&#xed; San Pablo and Patricia Vizuete, for granting us the space and authorisation to conduct this research. To Andr&#xe9;s M&#xe1;rmol and Esteban Ponguillo, for dedicating time to build the 3D models as well as to Omar Torres-Carvajal and Andr&#xe9;s Merino Viteri for granting access to preserve specimens and providing necessary workspace. Special thanks to Lily Leahy and Vanessa Kellermann for their guidance and expertise on data analysis. We are also grateful to Maria Thaker and Geoff While for their comments on an early version of this manuscript.</p>
</ack>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p></sec>
<sec id="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
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<supplementary-material xlink:href="Image1.pdf" id="SM1" mimetype="application/pdf"/>
<supplementary-material xlink:href="Table1.docx" id="ST1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/></sec>
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<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1094966">Luisa Maria Diele Viegas</ext-link>, Federal University of Bahia (UFBA), Brazil</p></fn>
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<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3060229">Hugo Andrade</ext-link>, Federal University of Sergipe, Brazil</p></fn>
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