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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Pastoralism</journal-id>
<journal-title-group>
<journal-title>Pastoralism: Research, Policy and Practice</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Pastoralism</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2041-7136</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">17175</article-id>
<article-id pub-id-type="doi">10.3389/past.2026.17175</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>Understanding social-ecological vulnerability in goat pastoral systems through a participatory multi-stakeholder spatial assessment</article-title>
<alt-title alt-title-type="left-running-head">Guzm&#x00E1;n-Miranda et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/past.2026.17175">10.3389/past.2026.17175</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Guzm&#x00E1;n-Miranda</surname>
<given-names>Andrea Valeria</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/3084118"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Huber-Sannwald</surname>
<given-names>Elisabeth</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>D&#xe1;vila-Ortiz</surname>
<given-names>Rodrigo</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Mart&#xed;nez-Tag&#xfc;e&#xf1;a</surname>
<given-names>Natalia</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Alvarado</surname>
<given-names>Fredy</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/3740639"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Mora-Ledesma</surname>
<given-names>Mar&#xed;a Isabel</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Vel&#xe1;zquez-Mart&#xed;nez</surname>
<given-names>Mauricio</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<label>1</label>
<institution>Divisi&#xf3;n de Ciencias Ambientales, Instituto Potosino de Investigaci&#xf3;n Cient&#xed;fica y Tecnol&#xf3;gica (IPICYT)</institution>, <city>San Luis Potos&#xed;</city>, <country country="MX">Mexico</country>
</aff>
<aff id="aff2">
<label>2</label>
<institution>Universidad Nacional Rosario Castellanos, Soledad de Graciano S&#xe1;nchez</institution>, <city>San Luis Potos&#xed;</city>, <country country="MX">Mexico</country>
</aff>
<aff id="aff3">
<label>3</label>
<institution>Centro de Investigaci&#xf3;n en Ciencias Sociales y Estudios Regionales, Universidad Aut&#xf3;noma del Estado de Morelos (UAEM)</institution>, <city>Cuernavaca</city>, <country country="MX">Mexico</country>
</aff>
<aff id="aff4">
<label>4</label>
<institution>El Colegio de San Luis (COLSAN)</institution>, <city>San Luis Potos&#xed;</city>, <country country="MX">Mexico</country>
</aff>
<aff id="aff5">
<label>5</label>
<institution>Instituto Nacional de Investigaciones Forestales, Agr&#x00ED;colas y Pecuarias (INIFAP), Campo Experimental San Luis</institution>, <city>San Luis Potos&#xed;</city>, <country country="MX">Mexico</country>
</aff>
<author-notes>
<corresp id="c001">
<label>&#x2a;</label>Correspondence: Elisabeth Huber-Sannwald, <email xlink:href="mailto:ehs@ipicyt.edu.mx">ehs@ipicyt.edu.mx</email>
</corresp>
<fn fn-type="present-address" id="fn001">
<label>&#x2020;</label>
<p>
<bold>Present address:</bold> Andrea Valeria Guzm&#x00E1;n-Miranda, Universidad Nacional Rosario Castellanos, Soledad de Graciano S&#x00E1;nchez, San Luis Potos&#x00ED;, Mexico</p>
<p>Rodrigo D&#x00E1;vila-Ortiz, Department Geociencias Aplicadas. Instituto Potosino de Investigaci&#x00F3;n Cient&#x00ED;fica y Tecnol&#x00F3;gica (IPICYT), San Luis Potos&#x00ED;, Mexico</p>
</fn>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-10-28">
<day>28</day>
<month>10</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>16</volume>
<elocation-id>17175</elocation-id>
<history>
<date date-type="received">
<day>19</day>
<month>06</month>
<year>2026</year>
</date>
<date date-type="rev-recd">
<day>24</day>
<month>09</month>
<year>2026</year>
</date>
<date date-type="accepted">
<day>30</day>
<month>09</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Guzm&#x00E1;n-Miranda, Huber-Sannwald, D&#xe1;vila-Ortiz, Mart&#xed;nez-Tag&#xfc;e&#xf1;a, Alvarado, Mora-Ledesma and Vel&#xe1;zquez-Mart&#xed;nez.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Guzm&#x00E1;n-Miranda, Huber-Sannwald, D&#xe1;vila-Ortiz, Mart&#xed;nez-Tag&#xfc;e&#xf1;a, Alvarado, Mora-Ledesma and Vel&#xe1;zquez-Mart&#xed;nez</copyright-holder>
<license>
<ali:license_ref start_date="2026-10-28">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>
<p>Dryland pastoral systems are increasingly affected by the interrelation between socioenvironmental variability and change with land degradation. In Mexico, goat pastoralism (CaprinoCultura) represents a key social-ecological system (SES) that sustains rural livelihoods under highly constrained conditions. This study examined how social-ecological drivers operating across household, ejido and regional scales shape the vulnerability of CaprinoCultura in the Altiplano Potosino. It also questioned how different stakeholder groups perceive and prioritize these drivers. Thus, we developed a novel Participatory Vulnerability Assessment Framework (PVAF) that combined SES characterization, stakeholder-based criteria selection, and weighting and spatial multi-criteria analysis. The assessment integrated biophysical, socio-economic and institutional dimensions co-defined by pastoralists, academics, government representatives and civil society organizations. Results revealed marked spatial heterogeneity in the convergence of vulnerability-associated conditions in the integrated assessment, with northern and eastern municipalities showing greater concentrations of conditions like ecosystem degradation, high grazing pressure, migration, limited access to resources, and governance and institutional constraints. In contrast, southwestern municipalities generally showed lower and more heterogeneous levels of convergence across these conditions. Stakeholder-specific assessments showed broadly similar spatial patterns but differed in the relative importance assigned to individual conditions. Pastoralists tended to prioritize drivers directly affecting daily herd management, such as grazing pressure and ecosystem degradation, whereas government, academics and civil society organizations placed greater emphasis on broader institutional, ecological and social processes, including communal land-governance constraints and migration. Despite these differences, stakeholder perspectives converged on several key challenges affecting CaprinoCultura&#x2019;s long-term viability. These findings underscore the importance of using participatory knowledge in spatial analysis to coproduce more context-specific and socially informed strategies for the management and sustainability of pastoral systems. Therefore, by integrating stakeholder knowledge and priorities into spatial analysis, this study provides a novel operational approach for a participatory vulnerability assessment that enhances adaptive governance in dryland pastoral systems.</p>
</abstract>
<kwd-group>
<kwd>caprinocultura</kwd>
<kwd>goat pastoralism</kwd>
<kwd>Mexico</kwd>
<kwd>multicriteria analysis</kwd>
<kwd>participatory mapping</kwd>
<kwd>pastoral system</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This study was supported by a graduate scholarship granted by SECIHTI. Additional funding for the organization and implementation of the multisectoral meetings was provided by the Consejo Potosino de Ciencia y Tecnolog&#xed;a (COPOCYT) through the 2023 &#x201c;23871-Multas Electorales&#x201d; call for proposal.</funding-statement>
</funding-group>
<counts>
<fig-count count="11"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="128"/>
<page-count count="26"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>Pastoral systems are inherent elements of most dryland regions worldwide (<xref ref-type="bibr" rid="B87">Reid et al., 2008</xref>). Pastoralist livelihoods have developed under resource scarcity by harnessing synergies between livestock, rangelands and adaptive management practices (<xref ref-type="bibr" rid="B104">Sharifian et al., 2023</xref>), while remaining deeply connected to their land (<xref ref-type="bibr" rid="B26">Fern&#xe1;ndez-Gim&#xe9;nez and Estaque, 2012</xref>; <xref ref-type="bibr" rid="B76">Oba, 2013</xref>). Herders adapt by adjusting livestock mobility, herd size or composition and diversifying livelihood activities (<xref ref-type="bibr" rid="B2">Amsidder et al., 2021</xref>; <xref ref-type="bibr" rid="B11">Bostedt et al., 2023</xref>). Place-based knowledge and adaptive capacity have enabled pastoral societies and dryland ecosystems to co-evolve as interconnected social-ecological systems (SES) (<xref ref-type="bibr" rid="B39">Huber-Sannwald et al., 2012</xref>; <xref ref-type="bibr" rid="B88">Reid et al., 2014</xref>). However, pastoral systems increasingly face megadroughts, agro-industrial expansion, migration, cultural transformations, land privatization, degradation and desertification (<xref ref-type="bibr" rid="B88">Reid et al., 2014</xref>; <xref ref-type="bibr" rid="B15">Cherlet et al., 2018</xref>; <xref ref-type="bibr" rid="B58">Manzano et al., 2021</xref>).</p>
<p>The Southern Chihuahua Desert in Mexico has a long-standing tradition of goat pastoralism (<xref ref-type="bibr" rid="B68">Urquijo Torres, 2017</xref>), supporting regional livelihoods and pastoral identities rooted in ecological knowledge, sociocultural values, and strong relationships with grazing territories (<xref ref-type="bibr" rid="B12">Brond&#xed;zio et al., 2021</xref>; <xref ref-type="bibr" rid="B27">Fern&#xe1;ndez-Gim&#xe9;nez and Wilmer, 2025</xref>). From now on, we will refer to this regional goat pastoral system as <italic>CaprinoCultura</italic>, a term intended to emphasize its cultural heritage, institutional relevance, and contribution to dryland livelihoods (<xref ref-type="bibr" rid="B67">Mora-Ledesma, 2011</xref>; <xref ref-type="bibr" rid="B68">Urquijo Torres, 2017</xref>; <xref ref-type="bibr" rid="B123">Wurzinger et al., 2013</xref>; <xref ref-type="bibr" rid="B9">Barrera-Perales et al., 2018</xref>; <xref ref-type="bibr" rid="B114">Trenti-Very et al., 2021</xref>).</p>
<p>These goat pastoral systems are extensively grazed under communal land tenure regimes (ejidos) in designated open rangelands (<xref ref-type="bibr" rid="B82">Pinos-Rodr&#xed;guez et al., 2013</xref>). Their functioning relies on interactions between community decision-making, communal land governance, local ecological knowledge and intrinsic social-ecological dynamics (<xref ref-type="bibr" rid="B67">Mora-Ledesma, 2011</xref>; <xref ref-type="bibr" rid="B68">Urquijo Torres, 2017</xref>; <xref ref-type="bibr" rid="B34">G&#xf3;mez-Ruiz et al., 2012</xref>; <xref ref-type="bibr" rid="B39">Huber-Sannwald et al., 2012</xref>; <xref ref-type="bibr" rid="B9">Barrera-Perales et al., 2018</xref>). As in other pastoral regions, CaprinoCultura is vulnerable to increasing environmental and socioeconomic pressures (<xref ref-type="bibr" rid="B9">Barrera-Perales et al., 2018</xref>; <xref ref-type="bibr" rid="B69">Mora-Ledesma, 2020</xref>). Yet, how these pressures interact with communal governance, household organization, and local knowledge to shape pastoral vulnerability remains insufficiently understood. Hence, a systematic assessment of multiple dimensions of vulnerability in these systems is needed to inform context-specific interventions towards sustainable solutions.</p>
<p>Vulnerability assessment in SES has evolved from approaches focused primarily on physical hazards toward more integrative frameworks emphasizing interactions among exposure, sensitivity and adaptive capacity (<xref ref-type="bibr" rid="B116">Turner et al., 2003</xref>; <xref ref-type="bibr" rid="B10">Bennett et al., 2016</xref>). Exposure refers to the extent to which a system experiences socio-environmental trends and shocks; sensitivity addresses the degree to which a system&#x2019;s socio-ecological components are affected by external pressures; and adaptive capacity considers the ability of a SES to respond and adjust to disturbance. From an SES perspective, vulnerability is not simply the presence or intensity of a hazard, but an emergent property arising from interactions between society and nature and shaped by the characteristics and organization of the system (<xref ref-type="bibr" rid="B20">Depietri, 2020</xref>; <xref ref-type="bibr" rid="B111">Thiault et al., 2021</xref>). These interactions occur across spatial and organizational scales and are influenced by institutional, financial, technological, cultural, and political conditions that shape the adaptive capacity (<xref ref-type="bibr" rid="B10">Bennett et al., 2016</xref>). Consequently, understanding vulnerability requires examining not only what stressors affect the system, but why it is susceptible to them, how responses are organized and how vulnerability is distributed across space. For analytical purposes, we distinguish vulnerability itself from vulnerability-associated conditions through which its dimensions become observable in SES. These conditions may relate to exposure, sensitivity, or adaptive capacity and can be spatially assessed when appropriate indicators are available.</p>
<p>Evaluating pastoral vulnerability serves not only to characterize susceptible areas but also to identify priorities for context-specific intervention (<xref ref-type="bibr" rid="B64">Metcalf et al., 2015</xref>; <xref ref-type="bibr" rid="B124">Yang et al., 2023</xref>). As it has been suggested previously, SES vulnerability assessments need to bridge ecological and cultural dimensions (<xref ref-type="bibr" rid="B55">Long and Steel, 2020</xref>) and adopt flexible methodological frameworks (<xref ref-type="bibr" rid="B106">Singh et al., 2020</xref>; <xref ref-type="bibr" rid="B111">Thiault et al., 2021</xref>) capable of capturing the plurality of realities experienced by actors within these systems (<xref ref-type="bibr" rid="B60">Masterson et al., 2017</xref>). Understanding the causes and spatial distribution of vulnerability requires context-specific spatial and temporal indicators capable of capturing how multiple stressors are distributed and where they converge across heterogeneous landscapes (<xref ref-type="bibr" rid="B48">Kok et al., 2016</xref>; <xref ref-type="bibr" rid="B53">Li et al., 2025</xref>). Multi-Criteria Analysis (MCA) integrates heterogeneous socioenvironmental information by standardizing and weighting multiple criteria within a common spatial framework (<xref ref-type="bibr" rid="B1">Amiri et al., 2014</xref>; <xref ref-type="bibr" rid="B7">Balew et al., 2022</xref>). Thus, combined with participatory approaches, MCA incorporates the knowledge and priorities of actors embedded within the system (<xref ref-type="bibr" rid="B10">Bennett et al., 2016</xref>; <xref ref-type="bibr" rid="B111">Thiault et al., 2021</xref>).</p>
<p>Pastoral systems require place-based approaches because social practices, ecological interactions, and local knowledge shape vulnerability contexts (<xref ref-type="bibr" rid="B46">Johnsen et al., 2019</xref>; <xref ref-type="bibr" rid="B58">Manzano et al., 2021</xref>; <xref ref-type="bibr" rid="B103">Sharifian et al., 2022</xref>). Hence, deep local understanding is fundamental for assessing vulnerability and enhancing sustainability (<xref ref-type="bibr" rid="B52">Levin et al., 2013</xref>). Understanding pastoral systems as SES calls for a transdisciplinary approach that accounts for weaving different knowledge systems (<xref ref-type="bibr" rid="B45">Johansson and Isgren, 2017</xref>; <xref ref-type="bibr" rid="B43">Jamsranjav et al., 2019</xref>), diversity of local contexts (<xref ref-type="bibr" rid="B2">Amsidder et al., 2021</xref>; <xref ref-type="bibr" rid="B100">Scoones, 2023</xref>), and joint exploration of resilience or vulnerability (<xref ref-type="bibr" rid="B54">Linst&#xe4;dter et al., 2016</xref>; <xref ref-type="bibr" rid="B102">Semplici et al., 2024</xref>). Engaging with this complexity through multi-stakeholder knowledge co-production foster social innovation and collective learning, support co-adaptive management, and reduce uncertainty in decision-making (<xref ref-type="bibr" rid="B121">Wilmer et al., 2018</xref>; <xref ref-type="bibr" rid="B122">2022</xref>; <xref ref-type="bibr" rid="B25">Fern&#xe1;ndez-Gim&#xe9;nez, 2020</xref>; <xref ref-type="bibr" rid="B89">Reid et al., 2021</xref>; <xref ref-type="bibr" rid="B96">Roche, 2021</xref>; <xref ref-type="bibr" rid="B61">Mata-P&#xe1;ez et al., 2025</xref>).</p>
<p>Effective transdisciplinary collaboration (i.e., <xref ref-type="bibr" rid="B90">Reid-Shaw et al., 2021</xref>), requires participatory approaches that foster inclusive intercultural dialogue and trust-building (<xref ref-type="bibr" rid="B18">Coppock, 2016</xref>; <xref ref-type="bibr" rid="B80">Pappagallo and Semplici, 2020</xref>). For pastoral systems, participatory methodologies are sensitive to the intertwined territorial, social, and ecological realities of each community, while drawing on the expertise of the main actors, the herders (<xref ref-type="bibr" rid="B46">Johnsen et al., 2019</xref>; <xref ref-type="bibr" rid="B100">Scoones, 2023</xref>). Through mobility and close interaction with nature, pastoralists garner extensive knowledge of the spatial and temporal characteristics of their rangelands (<xref ref-type="bibr" rid="B24">Fern&#xe1;ndez-Gim&#xe9;nez, 2000</xref>; <xref ref-type="bibr" rid="B76">Oba, 2013</xref>). Acknowledging pastoralists&#x2019; land-based knowledge affirms their cultural identity and sense of place linked to grazing territories, key aspects of community wellbeing and livelihoods (<xref ref-type="bibr" rid="B31">Frank et al., 2018</xref>; <xref ref-type="bibr" rid="B29">Fern&#xe1;ndez-Gim&#xe9;nez et al., 2021</xref>).</p>
<p>Vulnerability assessments of pastoral systems adopting a SES framework remain relatively scarce (<xref ref-type="bibr" rid="B124">Yang et al., 2023</xref>; <xref ref-type="bibr" rid="B33">Gatew and Guyo, 2024</xref>). While participatory studies demonstrate the value of local knowledge (<xref ref-type="bibr" rid="B6">Ayantunde et al., 2015</xref>; <xref ref-type="bibr" rid="B46">Johnsen et al., 2019</xref>), and spatial assessments increasingly integrate indicators of pastoral vulnerability (<xref ref-type="bibr" rid="B124">Yang et al., 2023</xref>), but systematic integration of multiple stakeholder perspectives into the selection and prioritization of spatial vulnerability criteria remains limited. This gap is important because vulnerability in pastoral SES is shaped by ecological, territorial, institutional, and social processes that are perceived and prioritized differently by actors occupying different positions within the system. To address this gap, we developed a Participatory Vulnerability Assessment Framework (PVAF) combining social-ecological characterization, stakeholder-derived vulnerability criteria and priorities, and spatial MCA to examine the spatial differentiation of vulnerability-associated conditions in the Altiplano Potosino. Integrating multiple stakeholder perspectives into their identification and prioritization allows vulnerability to be examined as both spatially differentiated and socially situated.</p>
<p>Therefore, we asked how environmental, territorial, social, and institutional drivers operating across household, ejido, and regional scales shape vulnerability in CaprinoCultura. Specifically, we asked how stakeholder groups perceive and prioritize these drivers and how these can inform a participatory spatial assessment of vulnerability-associated conditions. Our objectives were to: (1) identify and characterize the main vulnerability drivers through a multi-stakeholder participatory process; (2) integrate pastoralist, academic, governmental, and civil society knowledge into their identification and prioritization; and (3) develop a participatory spatial multi-criteria assessment to identify areas where multiple vulnerability-associated conditions converge and where context-specific interventions may be prioritized.</p>
<p>This study contributes conceptually by showing how vulnerability-associated conditions are spatially differentiated in relation to the social, ecological, territorial, and institutional processes shaping pastoral SES, while recognizing that actors perceive and prioritize these conditions differently. Rather than treating vulnerability as a directly measurable property, we approach it as an emergent and socially situated property whose spatial expression can be examined through stakeholder-informed indicators. Methodologically, the study expands participatory multi-criteria approaches by incorporating stakeholder-derived priorities rather than relying solely on researcher-defined criteria and weights, linking multiple knowledge systems with spatial decision support for more inclusive and context-specific processes of planning and governance.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>Materials and methods</title>
<sec id="s2-1">
<title>Study area</title>
<p>The Altiplano Potosino is located in the Southern Chihuahua Desert in San Luis Potosi, Mexico (<xref ref-type="fig" rid="F1">Figure 1</xref>), covering approximately 21,510&#xa0;km<sup>2</sup> within the Mesa Central physiographic province (<xref ref-type="bibr" rid="B40">Instituto Nacional de Estad&#xed;stica y Geograf&#xed;a [INEGI], 2001</xref>). The region comprises intermountain plains, tectonic depressions and north-south-oriented mountain ranges at 1,500&#x2013;2,000&#xa0;m a.s.l., shaped by a geological history of Mesozoic sedimentary basins overlain by Cenozoic volcanic sequences. Soils range from calcareous xerosols in western and northern areas to shallow lithosols and more fertile pheozems in the south.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Study area of the CaprinoCultura system with land use and vegetation patterns in the Altiplano Potosino, Mexico.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g001.tif">
<alt-text content-type="machine-generated">Municipal map of northern San Luis Potos&#xED;, Mexico, displaying land cover types with colors distinguishing agriculture, urbanized areas, forest or woodland, chaparral, water, areas without vegetation, shrubland, grassland, and secondary vegetation; municipalities and boundaries are labeled, with an inset showing the regional location in Mexico.</alt-text>
</graphic>
</fig>
<p>The predominant climate is temperate dry (BS1) with seasonal rainfall concentrated between June and October and occasional precipitation events in December and January (<xref ref-type="bibr" rid="B32">Garc&#xed;a, 2004</xref>). Mean annual precipitation is below 400&#xa0;mm, and the average annual temperature is approximately 18&#xa0;&#xb0;C, with extremes ranging from 8.4&#xa0;&#xb0;C to 32&#xa0;&#xb0;C (<xref ref-type="bibr" rid="B16">CONAGUA, 2023</xref>). The Altiplano Potosino falls within the administrative hydrological region of El Salado, the driest in the country, with an estimated annual runoff of 10&#x2013;20&#xa0;mm (<xref ref-type="bibr" rid="B72">Negrete, 2020</xref>).</p>
<p>Vegetation varies along gradients of altitude, water availability and topography. Xerophytic vegetation dominates most of the region, particularly microphyllous and rosetophyllous desert scrublands (<xref ref-type="bibr" rid="B98">Rzedowski, 1961</xref>), including species such as <italic>Larrea tridentata</italic>, <italic>Flourensia cernua</italic>, <italic>Parthenium incanum</italic>, <italic>Agave lechuguilla</italic>, and <italic>Yucca filifera</italic>. Microphyllous scrublands and grasslands cover the intermountain plains and lowlands, whereas rosetophyllous scrublands are more common on rocky slopes and mountainous areas. In higher elevations, these vegetation types gradually transition into temperate woodlands and conifer forests. Halophytic grasslands and mesquite woodlands occur locally depending on soil salinity, soil depth, and topographic conditions (<xref ref-type="bibr" rid="B42">Instituto Nacional de Estad&#xed;stica y Geograf&#xed;a [INEGI], 2018</xref>).</p>
<p>Goat pastoralism is concentrated in microphyllous and rosetophyllous scrublands, where goats are morphologically and behaviorally adapted to consume thorny and fibrous vegetation (<xref ref-type="bibr" rid="B23">Echavarr&#xed;a-Ch&#xe1;irez and G&#xf3;mez-Ruiz, 2013</xref>). Pastoral mobility follows seasonal vegetation and rainfall dynamics: herds use grasslands and lowlands during the dry season and shift toward mountainous areas during the dry season (<xref ref-type="bibr" rid="B69">Mora-Ledesma, 2020</xref>). These movements are constrained by the limits of communal grazing territories and land-tenure arrangements (<xref ref-type="bibr" rid="B73">Negrete-S&#xe1;nchez et al., 2016</xref>; <xref ref-type="bibr" rid="B92">Rivera et al., 2020</xref>). Unlike cattle production, which is commonly associated with fenced properties, goat pastoralism is predominantly practiced by ejidal smallholders under communal open-grazing regimes (<xref ref-type="bibr" rid="B114">Trenti-Very et al., 2021</xref>; <xref ref-type="bibr" rid="B109">Tajonar et al., 2022</xref>).</p>
<p>The Altiplano Potosino has dispersed rural settlements and high levels of marginalization, poverty, and inequality (<xref ref-type="bibr" rid="B17">CONEVAL, 2020</xref>). Over recent decades, it has undergone rapid territorial transformation driven by irrigated agriculture, mining, renewable energy projects, horticultural agro-industries and the automotive sector (<xref ref-type="bibr" rid="B66">Montiel Torres, 2019</xref>). These processes have fragmented rangelands, reduced rainfed farming areas, altered labor dynamics, and contributed to changes in communal tenure systems and land-use patterns (<xref ref-type="bibr" rid="B77">Ortega and Mor&#xe1;n, 2020</xref>; <xref ref-type="bibr" rid="B70">Mor&#xe1;n et al., 2023</xref>).</p>
<p>Mexican agricultural policy organizes farming and livestock activities into &#x201c;production units,&#x201d; which are operational entities comprising one or more land parcels and farming infrastructure managed under a shared household or collective decision-making structure (<xref ref-type="bibr" rid="B99">SADER, 2021</xref>). In the Altiplano Potosino, goat herding is largely organized through these units, which constitute an important operational scale for herd management, grazing mobility, labor organization, and resource allocation. Goat production has a long history in the region, dating back to the sixteenth century, when herding was carried out by laborers working on haciendas within colonial production systems (<xref ref-type="bibr" rid="B62">Mellado, 1997</xref>; <xref ref-type="bibr" rid="B78">Oseguera Montiel et al., 2014</xref>). Following the Mexican Revolution, agrarian reforms established ejidal communal tenure, reshaping pastoral territorial organization. In 1992, PROCEDE (in Spanish: &#x201c;<italic>Programa de Certificaci&#xf3;n de Derechos Ejidales y Titulaci&#xf3;n de Solares&#x201d;)</italic> enabled the certification of ejidal rights and opened possibilities for changes in tenure and privatization, contributing to subsequent social-ecological transformations in pastoral systems (<xref ref-type="bibr" rid="B39">Huber-Sannwald et al., 2012</xref>; <xref ref-type="bibr" rid="B69">Mora-Ledesma, 2020</xref>).</p>
</sec>
<sec id="s2-2">
<title>Participatory vulnerability assessment framework</title>
<p>This study adopts a social-ecological systems (SES) approach (<xref ref-type="bibr" rid="B88">Reid et al., 2014</xref>), to characterize goat pastoral systems in the Altiplano Potosino and spatially assess their multidimensional vulnerability. A literature review was conducted on pastoral SES in drylands worldwide, focusing on pastoral mobility, rangeland governance, livelihood diversification and vulnerability dynamics (<xref ref-type="bibr" rid="B37">Guilherme et al., 2017</xref>; <xref ref-type="bibr" rid="B118">Vil&#xe1; et al., 2020</xref>; <xref ref-type="bibr" rid="B109">Tajonar et al., 2022</xref>; <xref ref-type="bibr" rid="B117">Vargas et al., 2022</xref>; <xref ref-type="bibr" rid="B104">Sharifian et al., 2023</xref>), as well as the socio-economic, socio-political and socio-cultural dimensions of goat pastoralism in the Altiplano Potosino (<xref ref-type="bibr" rid="B67">Mora-Ledesma, 2011</xref>; <xref ref-type="bibr" rid="B69">2020</xref>; <xref ref-type="bibr" rid="B68">Urquijo Torres, 2017</xref>; <xref ref-type="bibr" rid="B8">Potos&#xed;, 2013</xref>; <xref ref-type="bibr" rid="B9">Barrera-Perales et al., 2018</xref>; <xref ref-type="bibr" rid="B77">Ortega and Mor&#xe1;n, 2020</xref>). This review informed the participatory research design and provided contextual information on pastoral characteristics, challenges, and adaptive responses. Consultations with goat pastoralism specialists from Argentina, Chile and Mexico provided additional comparative insights.</p>
<p>For clarity, we distinguish among vulnerability, vulnerability-associated conditions, vulnerability drivers, vulnerability criteria, and vulnerability indicators. Vulnerability is understood as an emergent, relational, and context-specific property of a social-ecological system. Vulnerability-associated conditions refer to environmental, social, territorial, and institutional conditions through which vulnerability becomes observable in a particular context. Vulnerability drivers refer to stressors, changes, or constraints identified by stakeholders as influencing these vulnerability-associated conditions, without implying causal relationships. Vulnerability criteria are broader analytical categories synthesized from recurring participatory evidence, while vulnerability indicators are measurable variables used to represent these criteria spatially when suitable data are available. For example, stakeholders identified drought, land-use change, migration, and limited access to resources as factors influencing vulnerability-associated conditions. These participatory findings were synthesized into vulnerability criteria such as ecosystem degradation, high migration intensity, and limited access to watering points, which were then represented using measurable spatial indicators where data allowed.</p>
<p>The Participatory Vulnerability Assessment Framework (PVAF) comprises two phases (<xref ref-type="fig" rid="F2">Figure 2</xref>). Phase 1 characterizes CaprinoCultura as an SES across three interconnected spatial/institutional scales: (1) household/production unit, (2) ejido/shared territory, and (3) regional/shared landscape governance (Altiplano Potosino) (<xref ref-type="fig" rid="F3">Figure 3</xref>). Phase 2 organizes stakeholder-identified vulnerability-associated conditions into conceptual criteria, operationalizes them using spatially explicit indicators, and integrates them through Multi-Criteria Analysis (MCA) within a Geographic Information System (GIS) framework (<xref ref-type="fig" rid="F4">Figure 4</xref>). The MCA does not directly measure vulnerability or model causal interactions; rather, it provides an integrative spatial representation of the relative convergence of vulnerability-associated conditions based on stakeholder-derived priorities. Details of each phase are described below.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Conceptual representation of the Participatory Vulnerability Assessment Framework (PVAF) applied to CaprinoCultura in the Altiplano Potosino. The framework conceptualizes vulnerability as an emergent, relational and context-specific property of a social-ecological system, arising from interactions among exposure, sensitivity and adaptive capacity. In Phase 1, participatory methods were used to identify recurrent social-ecological stressors and constraints affecting CaprinoCultura, which were synthesized into vulnerability-associated criteria and interpreted according to their predominant relationship with the three vulnerability dimensions. In Phase 2, spatially operationalizable criteria were represented through geospatial indicators and combined with multistakeholder-derived weights using Multi-Criteria Analysis (MCA). The resulting spatial assessment represents the relative distribution and convergence of vulnerability-associated conditions rather than a direct measure of vulnerability.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g002.tif">
<alt-text content-type="machine-generated">Circular infographic illustrating a participatory and spatial assessment framework for social-ecological vulnerability, centered on a Venn diagram with Exposure, Sensitivity, and Adaptive Capacity, surrounded by contextual stressors and a two-phase process: participatory characterization and spatial prioritization and analysis, leading to vulnerability-associated spatial conditions.</alt-text>
</graphic>
</fig>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Phase 1 of the Participatory Vulnerability Assessment Framework: multi-scale participatory social-ecological characterization of goat pastoral systems in the Altiplano Potosino, showing the three spatial/institutional scales, participatory methodologies, objectives, and references.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g003.tif">
<alt-text content-type="machine-generated">Three-tiered infographic outlines analysis of goat herding systems at local (household), community (ejido), and regional (Altiplano Potosino) scales, showing visually distinct segments for each scale, corresponding methods, objectives, and references; includes icons of livestock, houses, and a mapped region to visually reinforce analytical levels.</alt-text>
</graphic>
</fig>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>Phase 2 of Participatory Vulnerability Assessment Framework: conceptual and analytical workflow for assessing vulnerability-associated conditions in CaprinoCultura through stakeholder-derived weights and standardized geospatial indicators.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g004.tif">
<alt-text content-type="machine-generated">Five-step flowchart illustrating a vulnerability assessment methodology: Step 1 identifies vulnerability criteria from participatory analysis; Step 2 develops spatial indicator layers; Step 3 applies multistakeholder weighting; Step 4 uses multi-criteria analysis in QGIS to compute a composite spatial index; Step 5 presents regional spatial assessment maps showing overall and stakeholder-specific results.</alt-text>
</graphic>
</fig>
<sec id="s2-2-1">
<title>Phase 1: participatory social-ecological characterization of goat pastoral systems</title>
<p>The participatory approach combined qualitative and multi-stakeholder methods to characterize CaprinoCultura as an SES across multiple scales and identify environmental, economic, social, institutional and territorial drivers considered relevant to its vulnerability. At the household/production-unit level, participants identified herd management, mobility, livelihood diversification, and family participation; at the ejido level, communal grazing practices, collective land-use arrangements and rangeland governance; and at the regional scale, broader environmental, institutional and socio-economic dynamics (<xref ref-type="fig" rid="F3">Figure 3</xref>).</p>
<p>At the household/production unit level, we conducted semi-structured interviews in 2023 with 115 pastoralists (97 men and 18 women) managing goat production units (regardless of formal registration) from 17 ejidos in six municipalities of the Altiplano Potosino. Snowball sampling was used to broaden representation across pastoral and grazing contexts (<xref ref-type="bibr" rid="B5">Atkinson and Flint, 2001</xref>). Interviews addressed herding strategies, livelihood diversification, pastoral routes within communal grazing territories, family participation in pastoral activities, and experiences and projections regarding drivers jeopardizing pastoral development and territorial access (<xref ref-type="bibr" rid="B130">INEGI, 2020</xref>; <xref ref-type="bibr" rid="B69">Mora-Ledesma et al., 2020</xref>; <xref ref-type="bibr" rid="B2">Amsidder et al., 2021</xref>; <xref ref-type="bibr" rid="B114">Trenti-Very et al., 2021</xref>; <xref ref-type="bibr" rid="B103">Sharifian et al., 2022</xref>; <xref ref-type="bibr" rid="B61">Mata-Paez et al., 2022</xref>). They also explored cultural meanings and local knowledge associated with goat pastoralism, as well as perceived environmental, institutional and socioeconomic stressors.</p>
<p>Because interviews revealed ejido-specific territorial arrangements, grazing rules, and mobility patterns, then a participatory mapping was conducted between late 2023 and early 2024 with 11 pastoralist focus groups, one per ejido, in Catorce, Charcas, Vanegas, Villa de Guadalupe, Cedral and Matehuala (<xref ref-type="fig" rid="F1">Figure 1</xref>). Participants mapped grazing territories, seasonal routes, management practices, mobility constraints, and areas considered constrained, degraded, threatened, or important for CaprinoCultura. These exercises also examined collective governance and the role of local ecological knowledge in pastoral decision-making (<xref ref-type="bibr" rid="B85">Rajala et al., 2020</xref>; <xref ref-type="bibr" rid="B84">Rajala and Sorice, 2022</xref>; <xref ref-type="bibr" rid="B131">Basupi et al., 2017</xref>; <xref ref-type="bibr" rid="B132">Cho and Mutanga, 2021</xref>).</p>
<p>To examine regional heterogeneity across municipalities of the Altiplano Potosino, two multi-stakeholder workshops were organized in Matehuala, San Luis Potos&#xed; (<xref ref-type="table" rid="T1">Table 1</xref>; <xref ref-type="sec" rid="s11">Supplementary Material S2</xref>). The first, conducted in late 2023, included 75 participants: 52 pastoralists (42 men, 10 women), 8 academics, 11 government representatives, and 4 NGOs. Participants reconstructed the historical trajectory of CaprinoCultura through six &#x201c;Rivers of Life&#x201d; (<xref ref-type="bibr" rid="B71">Moussa, 2009</xref>; <xref ref-type="bibr" rid="B50">Lauterio-Mart&#xed;nez et al., 2021</xref>), identifying different major social-environmental drivers, understood here as stressors, changes, or constraints perceived by participants as influencing the conditions of CaprinoCultura. Three Rivers of Life were produced by male pastoralists, one by female pastoralists, one by academics and NGOs, and one by government representatives. A collective Fuzzy Cognitive Map (FCM), based on <xref ref-type="bibr" rid="B36">Gray et al. (2015)</xref>, was then developed to identify key social-ecological drivers influencing CaprinoCultura.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Social-ecological indicators used for the spatial assessment of CaprinoCultura in the Altiplano Potosino.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">Vulnerability criterion</th>
<th rowspan="2" align="left">SES dimension</th>
<th rowspan="2" align="left">Geospatial indicator</th>
<th rowspan="2" align="left">Data source</th>
<th colspan="5" align="left">Vulnerability-associated condition level</th>
</tr>
<tr>
<th align="left">Very low (1)</th>
<th align="left">Low (2)</th>
<th align="left">Moderate (3)</th>
<th align="left">High (4)</th>
<th align="left">Very high (5)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Limited access to urban centers</td>
<td align="left">Market access</td>
<td align="left">Distance to municipal urban centers (km)</td>
<td align="left">INEGI&#x2a; topographic data (2022)</td>
<td align="left">0&#x2013;10</td>
<td align="left">11&#x2013;20</td>
<td align="left">21&#x2013;30</td>
<td align="left">31&#x2013;40</td>
<td align="left">&#x3e;40</td>
</tr>
<tr>
<td align="left">Low suitability of land-use and vegetation conditions</td>
<td align="left">Biophysical suitability</td>
<td align="left">Land use/Vegetation type</td>
<td align="left">INEGI&#x2a; series VII land use and vegetation dataset (2022)</td>
<td align="left">Desert shrubland</td>
<td align="left">Natural grassland</td>
<td align="left">Cultivated grassland, mesquite woodland</td>
<td align="left">Oak forest</td>
<td align="left">Irrigated agriculture</td>
</tr>
<tr>
<td align="left">Exposure to megaprojects</td>
<td align="left">Land-use pressure</td>
<td align="left">Distance to agroindustrial, mining and wind energy projects (km)</td>
<td align="left">Participatory mapping and georeferencing</td>
<td align="left">&#x3e;40</td>
<td align="left">31&#x2013;40</td>
<td align="left">21&#x2013;30</td>
<td align="left">11&#x2013;20</td>
<td align="left">0&#x2013;10</td>
</tr>
<tr>
<td rowspan="2" align="left">Ecosystem degradation</td>
<td align="left">Vegetation condition</td>
<td align="left">Soil-adjusted vegetation index (SAVI)</td>
<td align="left">Google earth Engine (2024)</td>
<td align="left">&#x2265;0.58</td>
<td align="left">&#x3e;0.40 - &#x3c;0.58</td>
<td align="left">&#x3e;0.231&#x2013;0.40</td>
<td align="left">&#x3e;0.05&#x2013;0.230</td>
<td align="left">&#x2212;0.10&#x2013;0.05</td>
</tr>
<tr>
<td align="left">Soil degradation</td>
<td align="left">Degree of soil degradation</td>
<td align="left">CONABIO&#x2a; national degradation datasets (2012)</td>
<td align="left">Very low</td>
<td align="left">Low</td>
<td align="left">Moderate</td>
<td align="left">High</td>
<td align="left">Very high</td>
</tr>
<tr>
<td align="left">Communal land governance constraints</td>
<td align="left">Governance and institutional capacity</td>
<td align="left">Ratio of communal land area to private land area</td>
<td align="left">RAN&#x2a; ejido land tenure data (2024)</td>
<td align="left">0&#x2013;0.20</td>
<td align="left">0.21&#x2013;0.40</td>
<td align="left">0.41&#x2013;0.60</td>
<td align="left">0.61&#x2013;0.80</td>
<td align="left">0.81</td>
</tr>
<tr>
<td align="left">Terrain steepness</td>
<td align="left">Topographic constraint</td>
<td align="left">Slope (%)</td>
<td align="left">INEGI&#x2a; digital elevation models (15&#xa0;m) (2022)</td>
<td align="left">0&#x2013;10</td>
<td align="left">11&#x2013;20</td>
<td align="left">21&#x2013;30</td>
<td align="left">31&#x2013;40</td>
<td align="left">&#x3e;40</td>
</tr>
<tr>
<td align="left">High grazing pressure</td>
<td align="left">Grazing pressure</td>
<td align="left">Stocking rate to carrying capacity ratio</td>
<td align="left">SIAP&#x2a; livestock data (2022) and COTECOCA&#x2a; carrying capacity estimates</td>
<td align="left">0&#x2013;0.50</td>
<td align="left">&#x3e;0.50&#x2013;1.0</td>
<td align="left">&#x3e;1.0&#x2013;1.50</td>
<td align="left">&#x3e;1.50&#x2013;2.0</td>
<td align="left">&#x3e;2.0</td>
</tr>
<tr>
<td align="left">High migration intensity</td>
<td align="left">Socio-demographic pressure</td>
<td align="left">Migration intensity index</td>
<td align="left">CONABIO&#x2a;, migration intensity index (2020)</td>
<td align="left">Very low</td>
<td align="left">Low</td>
<td align="left">Moderate</td>
<td align="left">High</td>
<td align="left">Very high</td>
</tr>
<tr>
<td align="left">Limited access to watering points</td>
<td align="left">Resource availability</td>
<td align="left">Distance to livestock watering points (km)</td>
<td align="left">CONABIO&#x2a;, water bodies dataset (2022)</td>
<td align="left">0&#x2013;5</td>
<td align="left">6&#x2013;10</td>
<td align="left">11&#x2013;15</td>
<td align="left">16&#x2013;20</td>
<td align="left">&#x3e;20</td>
</tr>
<tr>
<td align="left">Restrictions associated with protected natural areas</td>
<td align="left">Institutional support</td>
<td align="left">Distance to federal or state PNA (km)</td>
<td align="left">CONANP&#x2a; spatial data&#x2a; (2025)</td>
<td align="left">0-20</td>
<td align="left">21&#x2013;40</td>
<td align="left">41&#x2013;60</td>
<td align="left">61&#x2013;80</td>
<td align="left">&#x3e;80</td>
</tr>
<tr>
<td align="left">Low eligibility for technological support</td>
<td align="left">Adaptive capacity</td>
<td align="left">Participation in goat development programs</td>
<td align="left">SEDARH&#x2a;, Goat Regional Program (2016)</td>
<td align="left">Received support</td>
<td align="left">-</td>
<td align="left">-</td>
<td align="left">-</td>
<td align="left">No support</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>&#x2a;INEGI, Instituto Nacional de Estad&#xed;stica y Geograf&#xed;a - National Institute of Statistics and Geography in Mexico.</p>
</fn>
<fn>
<p>&#x2a;CONABIO, Comisi&#xf3;n Nacional para el Conocimiento y Uso de la Biodiversidad - National Commission for the Knowledge and Use of Biodiversity.</p>
</fn>
<fn>
<p>&#x2a;RAN, Registro Agrario Nacional - National Agrarian Register.</p>
</fn>
<fn>
<p>&#x2a;SIAP, Servicio de Informaci&#xf3;n Agroalimentaria y Pesquera - Agri-Food and Fisheries Information Service.</p>
</fn>
<fn>
<p>&#x2a;COTECOCA, Comisi&#xf3;n T&#xe9;cnico Consultiva de Coeficientes de Agostadero - Technical Advisory Commission on Grazing Coefficients.</p>
</fn>
<fn>
<p>&#x2a;CONANP, Comisi&#xf3;n Nacional de &#xc1;reas Naturales Protegidas - National Commission of Natural Protected Areas.</p>
</fn>
<fn>
<p>&#x2a;SEDARH, Secretar&#xed;a de Desarrollo Agropecuario y Recursos Hidr&#xe1;ulicos - Secretariat of Agricultural Development and Water Resources.</p>
</fn>
<fn>
<p>Indicator thresholds were defined based on participatory inputs, social-ecological literature, and statistical classification of spatial datasets. Indicators were standardized to a five-level ordinal scale prior to integration into the multi-criteria assessment; binary indicators were coded according to their observed categories.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>The second workshop, organized in 2024, gathered 68 participants: 50 pastoralists (38 men and 12 women), 10 academics, 5 government representatives and 3 NGO members. Participants used printed regional maps at a scale of 1:50,000 derived from high-resolution Google Earth imagery to identify spatial similarities and differences in pastoral systems across the Altiplano Potosino. Stakeholder groups first discussed how landscapes, pastoral practices, environmental conditions, and threats vary throughout the region. They then identified core drivers causing these differences, including vegetation patterns, land-use change, water access, institutional constraints, market pressures and environmental degradation. Five maps were produced: two by male pastoralists, one by female pastoralists, one by government representatives, and one by academics and NGOs.</p>
</sec>
<sec id="s2-2-2">
<title>Phase 2: participatory vulnerability assessment of pastoral systems</title>
<p>Building on Phase 1, vulnerability drivers and associated conditions were identified across interviews, participatory mapping exercises, Rivers of Life, and multi-stakeholder workshops, where participants discussed the principal environmental, territorial, institutional and socio-economic stressors and constraints affecting the development and sustainability of CaprinoCultura.</p>
<p>Twelve vulnerability-associated criteria were derived from these complementary participatory sources through methodological triangulation (<xref ref-type="bibr" rid="B81">Patton, 1999</xref>). The research team compared evidence across methods and stakeholder groups to identify shared and complementary accounts of vulnerability drivers and associated conditions, grouping conceptually related concerns into broader social-ecological criteria. For example, concerns about excessive livestock use and limited regulation of herd sizes were considered together when defining a broader criterion related to grazing pressure. This interpretive synthesis did not involve formal thematic coding or counts of response frequencies. The resulting criteria were aligned with the vulnerability framework and operationalized using spatially explicit information (<xref ref-type="fig" rid="F4">Figure 4</xref>).</p>
<p>The twelve vulnerability criteria are: (1) reduced annual precipitation, (2) limited access to urban centers, (3) low suitability of land-use and vegetation conditions for goat pastoralism, (4) exposure to megaprojects, (5) ecosystem degradation, (6) high grazing pressure, (7) communal land governance constraints, (8) terrain steepness limiting pastoral accessibility, (9) high migration intensity, (10) limited access to watering points, (11) restrictions associated with nearby Protected Natural Areas, and (12) low eligibility for technological support programs. Criteria were classified according to their relationship within the vulnerability framework as representing exposure, sensitivity and adaptive capacity (<xref ref-type="table" rid="T2">Table 2</xref>). Although some criteria may relate to more than one vulnerability dimension, particularly those associated with adaptive capacity, they were assigned according to their predominant conceptual role.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Derivation of vulnerability criteria from participatory evidence and their conceptual classification within the vulnerability framework.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Evidence from participatory process</th>
<th align="center">Vulnerability criterion</th>
<th align="center">Conceptual dimension</th>
<th align="center">Explanation</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">&#x201c;There is less rain, and the droughts are becoming longer and harsher&#x201d;</td>
<td align="center">Reduced annual precipitation</td>
<td align="center">Exposure</td>
<td align="left">Represents a climatic stressor experienced by pastoral systems that directly affects water availability and rainfall-dependent vegetation productivity</td>
</tr>
<tr>
<td align="center">&#x201c;Being far from Matehuala (closest urban center) affects sales and access to services&#x201d;</td>
<td align="center">Limited access to urban centers</td>
<td align="center">Adaptive capacity</td>
<td align="left">Represents constraints on pastoral households&#x2019; access to urban services, markets, institutional support, and other resources that may facilitate responses to environmental or socioeconomic disturbances</td>
</tr>
<tr>
<td align="center">&#x201c;There are types of vegetation and soil that are not suitable for goat pastoralism&#x201d;</td>
<td align="center">Low suitability of land-use and vegetation conditions</td>
<td align="center">Sensitivity</td>
<td align="left">Represents the susceptibility of pastoral production to land-use, soil and vegetation conditions that provide limited suitability for goat pastoralism</td>
</tr>
<tr>
<td align="center">&#x201c;Greenhouses take away our grazing lands &#x2026; as do wind farms and mining companies&#x201d;</td>
<td align="center">Exposure to megaprojects</td>
<td align="center">Exposure</td>
<td align="left">Represents exposure to large-scale territorial transformations that can reduce access to communal grazing areas and modify the spatial availability of resources for pastoral activities</td>
</tr>
<tr>
<td align="center">&#x201c;Rangelands with poor vegetation are not good for grazing &#x2026; the soil is very degraded, and nothing grows there anymore&#x201d;</td>
<td align="center">Ecosystem degradation</td>
<td align="center">Sensitivity</td>
<td align="left">Represents the degraded condition of ecosystems and their reduced capacity to sustain forage resources and pastoral production under environmental and production pressures. This criterion was operationalized through two complementary indicators: vegetation condition and soil degradation</td>
</tr>
<tr>
<td align="center">&#x201c;There are always conflicts about how to manage communal area &#x2026; we can&#x2019;t agree on how to limit animal numbers for different livestock types to control overgrazing&#x201d;</td>
<td align="center">Communal land governance constraints</td>
<td align="center">Adaptive capacity</td>
<td align="left">Represents institutional and collective-action constraints that may limit the ability of communities to coordinate resource use, establish rules and collectively respond to changing environmental and production conditions</td>
</tr>
<tr>
<td align="center">&#x201c;There are very steep areas that limit where we can herd the goats&#x201d;</td>
<td align="center">Terrain steepness</td>
<td align="center">Sensitivity</td>
<td align="left">Represents physical landscape constraints that limit herd mobility and access to grazing areas, increasing the sensitivity of pastoral production to heterogeneous terrain conditions</td>
</tr>
<tr>
<td align="center">&#x201c;There is a lot of overgrazing &#x2026; people don&#x2019;t regulate the number of their animals and monopolize all the vegetation in the rangeland&#x201d;</td>
<td align="center">High grazing pressure</td>
<td align="center">Sensitivity</td>
<td align="left">Represents the intensity of livestock use relative to the capacity of rangeland resources to sustain grazing, which may reduce forage availability and contribute to soil and ecosystem degradation</td>
</tr>
<tr>
<td align="center">&#x201c;There is a lot of migration &#x2026; young people no longer want to continue &#x2026; this activity will eventually be forgotten&#x201d;</td>
<td align="center">High migration intensity</td>
<td align="center">Adaptive capacity</td>
<td align="left">Represents demographic and labor dynamics that may reduce household labor availability and weaken the intergenerational continuity of pastoral knowledge and practices</td>
</tr>
<tr>
<td align="center">&#x201c;If you have access to an earthen dam or a well, you can keep more animals &#x2026; if you don&#x2019;t have an earthen dam or it&#x2019;s too far away, you have to adjust the size of your herd&#x201d;</td>
<td align="center">Limited access to watering points</td>
<td align="center">Sensitivity</td>
<td align="left">Represents the susceptibility of pastoral production to limited availability or accessibility of water resources required for livestock management</td>
</tr>
<tr>
<td align="center">&#x201c;Being close to protected natural areas gives us access to more training &#x2026; we have to take better care of the vegetation; it encourages better conservation&#x201d;</td>
<td align="center">Restrictions associated with protected natural areas</td>
<td align="center">Adaptive capacity</td>
<td align="left">Represents institutional and land-use conditions associated with proximity to protected natural areas that may either constrain pastoral flexibility through land-use restrictions or enhance adaptive capacity through access to conservation programs and technical support. For the spatial assessment, this criterion was operationalized through distance to PNAs, with greater distance representing higher levels of vulnerability-associated conditions based on the participatory prioritization of access to institutional and conservation support</td>
</tr>
<tr>
<td align="center">&#x201c;The more support and technology we have, the better the production &#x2026; the training sessions have taught us how to improve rangeland use and increase milk and cheese production&#x201d;</td>
<td align="center">Low eligibility for technological support</td>
<td align="center">Adaptive capacity</td>
<td align="left">Represents constraints on access to technological, institutional and technical support that can limit opportunities to improve pastoral management and respond to environmental and socioeconomic changes</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>The participatory characterization identified adaptive capacity processes, including pastoral mobility, local ecological knowledge, livelihood and product diversification, family organization, and flexible herd management. Processes that could not be systematically assessed or spatially extrapolated across the region informed the contextual interpretation, while spatially measurable constraints and enabling drivers, such as access to urban centers and institutional support, were incorporated into the MCA (<xref ref-type="table" rid="T1">Table 1</xref>).</p>
<p>Each criterion was operationalized using one or more measurable spatial indicators derived from publicly available geospatial datasets, initially resulting in 13 spatial indicators. Ecosystem degradation was represented by two complementary indicators: vegetation condition and soil degradation. Reduced annual precipitation was excluded from the spatial analysis and the stakeholder weighting exercise because it showed limited spatial differentiation across the study area, but it was retained as a regional background condition influencing CaprinoCultura. Thus, 11 criteria represented by 12 spatial indicators were retained for the spatial analysis and weighting exercise (<xref ref-type="table" rid="T1">Table 1</xref>).</p>
<p>MCA was used to integrate socioenvironmental indicators through weighted combinations of standardized values (<xref ref-type="bibr" rid="B1">Amiri et al., 2014</xref>; <xref ref-type="bibr" rid="B7">Balew et al., 2022</xref>; <xref ref-type="bibr" rid="B86">Rana and Moniruzzaman, 2023</xref>). This approach was considered adequate because the conditions identified through the participatory process are heterogeneous and cannot be represented by a single environmental or socioeconomic variable. MCA allowed indicators with different units, spatial distributions and conceptual dimensions to be standardized and integrated within a common spatial framework. The resulting index does not directly measure vulnerability or establish causal relationships, rather, it represents the relative spatial convergence of vulnerability-associated conditions and provides decision-support information to identify areas where context-specific interventions should be prioritized (<xref ref-type="bibr" rid="B7">Balew et al., 2022</xref>).</p>
<p>For each spatial indicator, datasets were prioritized that corresponded as closely as possible to the 2023&#x2013;2024 participatory research period. When data were not available, we used the most recent dataset with adequate spatial coverage, methodological consistency and reliability. Since the participatory characterization captured processes occurring over time rather than conditions at a single point in time, the spatial indicators represent the most recent available expression of these conditions rather than vulnerability for a single reference year. The reference year and selection rationale for each dataset are reported in <xref ref-type="table" rid="T1">Table 1</xref> and detailed in <xref ref-type="sec" rid="s11">Supplementary Material S1</xref>.</p>
<p>All spatial processing was conducted using QGIS v3.40.6. To ensure spatial comparability, all layers were projected into a common coordinate reference system. Raster datasets were standardized to 15&#xa0;m, while vector datasets were rasterized to maintain consistency in spatial structure. Indicators were reclassified into five-class ordinal classes representing increasing vulnerability-associated conditions: (1) very low vulnerability, (2) low vulnerability, (3) medium vulnerability, (4) high vulnerability, and (5) very high vulnerability. This classification facilitates spatial comparison in multicriteria analyses (<xref ref-type="bibr" rid="B63">Mena et al., 2012</xref>; <xref ref-type="bibr" rid="B7">Balew et al., 2022</xref>).</p>
<p>To determine the relative importance assigned to the 12 spatial indicators, a structured survey was conducted with 80 stakeholders: pastoralists (60), academics (10), government representatives (7), and NGOs (3). The survey was administered online and in person in 2025. Participants ranked the 12 spatial indicators retained for the MCA from highest (1) to lowest (12) according to the extent to which they considered each condition to affect CaprinoCultura. Thus, participants expressed their relative priorities through ordinal rankings rather than directly assigning numerical weights. Participants were instructed to assign a unique rank to each indicator; tied rankings were not permitted and all 12 indicators were required to receive a rank. Because ordinal rankings indicate the order of priority but not the magnitude of differences between ranks, resulting weights were interpreted as relative priorities rather than interval-scale measures of preference (<xref ref-type="bibr" rid="B93">Roberts and Goodwin, 2002</xref>).</p>
<p>The four stakeholder categories, herders, government, academia and civil society organizations, were selected to represent distinct forms of knowledge, responsibilities, and institutional relationships with the CaprinoCultura system. Herders contributed place-based and experiential knowledge from direct engagement with pastoral production and territories; government representatives contributed institutional and policy perspectives; academic participants contributed scientific and analytical knowledge; and civil society organizations contributed experience in community-based initiatives and rural development. These categories were therefore used as analytical stakeholder perspectives rather than as statistically representative populations.</p>
<p>Because group sizes differed substantially, individual rankings were first aggregated within each stakeholder category using mean ranks. This prevented the larger pastoralist group from determining composite weighting solely through sample size. Mean ranks summarized relative priorities within each stakeholder category. The resulting mean ranks were converted into surrogate weights using an inverse-rank procedure, whereby higher-priority indicators (lower mean rank) received larger weights. Values were then normalized so that weights of the 12 spatial indicators summed to one. Rank-based procedures for deriving surrogate weights from ordinal rankings are established in multi-criteria decision analysis (<xref ref-type="bibr" rid="B108">Stillwell and Seaver, 1981</xref>; <xref ref-type="bibr" rid="B93">Roberts and Goodwin, 2002</xref>; <xref ref-type="bibr" rid="B13">Burk and Nehring, 2023</xref>).</p>
<p>The four stakeholder-specific weighting schemes were applied through weighted linear combination in QGIS to generate four spatial maps. A fifth, integrated map was produced by averaging the four weighting schemes, giving each stakeholder perspective equal influence regardless of group size. The integrated map reflects their combined priorities, while the stakeholder-specific maps show differences in spatial patterns arising from their respective priorities. Values ranged from 1 (very low) to 5 (very high), indicating increasing convergence of vulnerability-associated conditions. These maps were interpreted as relative spatial gradients rather than direct measures of absolute vulnerability.</p>
<p>Three complementary sensitivity analyses assessed the robustness of the spatial MCA to changes in criterion weights, criterion inclusion, and stakeholder aggregation. First, each criterion weight was increased and decreased by 20% relative to its baseline value, one criterion at a time. The remaining weights were proportionally rescaled to preserve a total weight of one. This procedure was repeated for all criteria within each stakeholder group, and each resulting surface was compared with its corresponding baseline using Spearman&#x2019;s rank correlation coefficient (&#x3c1;). Second, a leave-one-criterion-out analysis assessed the influence of individual criteria on spatial patterns. Each criterion was removed in turn, and the remaining weights were proportionally rescaled to sum to one. The resulting surfaces were compared with their corresponding baselines using Spearman&#x2019;s &#x3c1;, with lower correlations indicating greater changes in the spatial ranking of MCA values. Third, sensitivity to stakeholder aggregation was evaluated by comparing the primary integrated assessment, which assigned equal weight to each stakeholder group (25%), with an alternative weighted by group sample size (60 pastoralists, 10 academics, 7 government representatives, and 3 NGO representatives). The two integrated surfaces were compared using Spearman&#x2019;s &#x3c1; to assess similarity in spatial rankings and root mean square error (RMSE) to quantify differences in MCA values.</p>
</sec>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec id="s3-1">
<title>Historical dynamics of goat populations in San Luis Potos&#xed;</title>
<p>Goat populations in San Luis Potos&#xed; (<xref ref-type="fig" rid="F5">Figure 5</xref>) increased steadily starting in 1980 and reached over 1.2 million heads by 1994 (<xref ref-type="bibr" rid="B105">SIAP, 2022</xref>). This expansion coincided with economic restructuring associated with the General Agreement on Tariffs and Trade (GATT) in 1986 and the North American Free Trade Agreement (NAFTA) in 1994; it integrated Mexican agriculture into global markets and altered incentives for small-scale farmers. Despite these changes, goat numbers sharply declined after 1996, because of market exposure and broader structural pressures (<xref ref-type="bibr" rid="B66">Montiel Torres, 2019</xref>) and out-migration and aging of the rural population thereby reducing labor availability and weakening generational continuity within pastoral systems (<xref ref-type="bibr" rid="B34">G&#xf3;mez-Ruiz et al., 2012</xref>).</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption>
<p>Temporal trend of goat population in San Luis Potos&#xed;, Mexico (1980&#x2013;2022). The time series shows sustained growth through the 1980s and early 1990s, followed by a sharp drop after 1996, which extended until 2007; since 2016, goat population has been gradually recovering. Data source: (<xref ref-type="bibr" rid="B105">SIAP, 2022</xref>).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g005.tif">
<alt-text content-type="machine-generated">Line graph showing goat population from 1980 to 2022, with population rising to over one million by 1996, significantly declining after 1999, and stabilizing around eight hundred thousand from 2004 onward.</alt-text>
</graphic>
</fig>
<p>During the early 2000s, the nationwide livestock support program <italic>Programa Pecuario Sustentable y Ordenamiento Ganadero y Ap&#xed;cola</italic> (PROGAN) helped stabilize goat production; however, numbers declined after 2006 (<xref ref-type="fig" rid="F5">Figure 5</xref>). Beyond policy and market factors, pronounced climate variability, particularly droughts in 1998, 2000&#x2013;2001, 2005, and 2011, likely placed additional pressure on pastoral systems. Since 2016, goat numbers have shown moderate recovery, coinciding with the implementation of the Regional Goat Project (Proyecto Regional Caprino) promoted by the Secretar&#xed;a de Desarrollo Agropecuario y Recursos Hidr&#xe1;ulicos (SEDARH) in San Luis Potos&#xed;. This project aimed to strengthen goat production through genetic improvement, market development, and animal health management (<xref ref-type="bibr" rid="B3">Anzaldo Montoya, 2024</xref>). More favorable conditions may also have contributed to this recovery. The latest available estimate reported approximately 772,075 goats in San Luis Potos&#xed; in 2022, with most production units concentrated in the Altiplano Potosino (<xref ref-type="bibr" rid="B105">SIAP, 2022</xref>).</p>
</sec>
<sec id="s3-2">
<title>Phase 1: participatory characterization of vulnerability-associated conditions in CaprinoCultura</title>
<p>CaprinoCultura in the Altiplano Potosino constitutes a complex social-ecological system shaped by ecological, social, cultural and political interaction dynamics across multiple spatial and temporal scales (<xref ref-type="fig" rid="F6">Figure 6</xref>). Participatory characterization identified vulnerability-associated conditions operating across household, ejido and regional levels, including environmental variability, territorial transformations, governance constraints and changes in household organization and resource access. These conditions informed the vulnerability criteria developed in Phase 2.</p>
<fig id="F6" position="float">
<label>FIGURE 6</label>
<caption>
<p>Multi-scale social-ecological system of CaprinoCultura in the Altiplano Potosino. The diagram represents interactions between biophysical, social, and institutional components across regional (Altiplano Potosino), community (ejido), and local (LPU and Family) scales. Regional drivers such as climate variability, markets, and public policy shape resource availability and land-use dynamics. At the community level, ejido governance, rangeland conditions, and social organization regulate access to communal grazing areas. At the local level, herd management, household characteristics, and knowledge systems determine pastoral practices and mobility. Arrows indicate cross-scale interactions, including policy, market, and extension influences. The main drivers inducing change are grouped by category at the community and local scales. The figure emphasizes the importance of mobility, local ecological knowledge, and family-based management in sustaining CaprinoCultura systems.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g006.tif">
<alt-text content-type="machine-generated">Infographic illustrating spatial scales in pastoral systems of the Altiplano Potosino, depicting three interconnected levels: regional, community, and local. Each level lists drivers and factors such as climate, government, geology, land use, local knowledge, management practices, and household roles, with circular insets detailing main drivers including biophysical, socio-economic, herd management, and knowledge systems.</alt-text>
</graphic>
</fig>
<sec id="s3-2-1">
<title>Regional environmental and territorial conditions associated with vulnerability</title>
<p>The Altiplano Potosino provides the broader socioenvironmental context in which CaprinoCultura has developed over decades. Participants consistently identified rainfall variability and recurrent droughts as the major environmental constraints affecting forage availability and water access. Herders also described how heterogeneous topography shapes pastoral mobility, expressing a preference for gentle slopes with shrub vegetation over steep hills dominated by succulent vegetation. These observations indicate that grazing activities are spatially concentrated in areas perceived as more suitable for pastoral use.</p>
<p>The region contains three Protected Natural Areas (PNAs), including the Sierra La Mojonera, Wirikuta, and the Guadalc&#xe1;zar State Reserve. Participants described proximity to PNAs having constraining and enabling effects. Designated areas limit intensive livestock practices, land transformation and agrochemical use; while neighboring ejidos may benefit from conservation programs and alternative livelihood opportunities. Participants also associated land-use change, agro-industrial expansion, mining, and wind farms with the loss of communal grazing areas and the fragmentation of traditional pastoral territories following the implementation of PROCEDE in 1992 (<xref ref-type="bibr" rid="B66">Montiel Torres, 2019</xref>). This reduction in grazing space reportedly concentrated livestock pressure on the remaining rangelands and constrained traditional mobility. Out-migration among younger generations was likewise associated with reduced household labor availability, disrupted intergenerational knowledge transmission, and an aging herding population (<xref ref-type="bibr" rid="B70">Mor&#xe1;n et al., 2023</xref>).</p>
</sec>
<sec id="s3-2-2">
<title>Ejido governance and communal resource management</title>
<p>Participants identified communal land governance as a vulnerability-associated condition that varied substantially among ejidos. Governance structures include ejido assemblies and committee meetings. Relevant actors include <italic>ejidatarios</italic> (formal land rights holders), <italic>posesionados</italic> (possessory rights holders recognized by the ejidal assembly) and <italic>avecinados</italic> (recognized residents with no ejido or possessory rights), whose rights and roles in decision-making differ. Collective decisions address livestock numbers permitted in communal grazing areas, conservation practices, and access to designated areas, such as the &#x201c;<italic>pasta</italic>&#x201d;, a communal livestock exclosure reserved for periods of forage scarcity. Some herders also participate in regional organizations such as the Federation of Goat Producers, which integrates cooperatives across ejidos.</p>
<p>Participants described contrasting experiences of rule enforcement, grazing access and conflict resolution. Some reported that effective collective organization facilitated access to communal grazing areas and agreement on grazing rules, while others described conflicts that undermined coordination and rule enforcement. Women and younger generations were also described as having limited participation in ejidal decision-making despite their active involvement in pastoral systems. These accounts highlight both differences in collective governance among ejidos and inequalities of participation within them.</p>
<p>Access to water and the organization of grazing routes further illustrated how communal resource are used within ejidos. Water bodies within communal lands, including natural sources associated with local geological conditions and artificial structures such as troughs and small reservoirs (<italic>bordos</italic>) constructed through government support programs, serve as critical gathering points for livestock. Multiple herders within the same ejido share these sites, where herd convergence can increase grazing pressure in surrounding areas. Participatory mapping showed that herders often share grazing areas while following different routes. Route use varied with time of day, resource availability and internal agreements; some herders followed stable routes, while others adjusted their movements across grazing areas.</p>
<p>Herders described route selection as shaped by inherited knowledge, environmental conditions, and production objectives. Many followed routes established by previous generations, reflecting the intergenerational transmission of territorial knowledge. Overall, herders associated areas containing highly palatable forage species were associated with milk production, whereas areas with more drought-tolerant and fibrous vegetation serve for meat production. Alongside local knowledge and collective decision-making, external actors also influence pastoral practices. Interviewees reported receiving occasional technical advice on animal health and dairy processing, but noted that comparatively little support addressed on rangeland management or grazing practices.</p>
</sec>
<sec id="s3-2-3">
<title>Livestock production units and family-based management</title>
<p>At the household level, pastoral production combines herd management, grazing mobility, household labor and livelihood diversification. Livestock Production Unit (LPU) are the household-level unit through which livestock production is formally registered and managed, and represent the smallest operational unit considered in the analysis. Official records identify approximately 2,071 LPUs across 140 ejidos and 15 municipalities of the Altiplano Potosino. Registration provides access to animal health and traceability systems, facilitates livestock movement and marketing, and enables participation in government support programs. However, many herders reported remaining unregistering due to administrative barriers, costs, or limited trust in external regulations, indicating that official LPU records do not capture the full extent of CaprinoCultura.</p>
<p>Within these household-based production systems, a division of labor by gender and generational lines was described, with roles varying among households. Men are generally responsible for herding, while women play a central role in milking, processing dairy products such as cheese and traditional sweets, and selling these products. Elderly individuals and children also assist with herding, product preparation, or sales. These shared responsibilities underscore the importance of family organization in sustaining CaprinoCultura.</p>
<p>Rainfed agriculture, particularly the <italic>milpa</italic> system, is a central component of livelihood diversification and is closely integrated with goat husbandry. Herds are brought onto agricultural plots to fertilize soils with manure, while crop residues provide feed after harvest. Households also collect and sell locally valued natural resources (<xref ref-type="sec" rid="s11">Supplementary Table S2</xref>), including edible and medicinal plants, and <italic>escamoles</italic> (<italic>Liometopum sp</italic>., ant larvae, a prized delicacy in Mexican cuisine), which constitute an important seasonal source of income in some communities (<xref ref-type="bibr" rid="B49">Lara-Ju&#xe1;rez et al., 2018</xref>). Temporary off-farm employment in construction, agro-industrial activities, and other rural sectors provides additional income. Remittances from family members who have migrated to other regions of Mexico or the United States also help households manage economic uncertainty and sustain pastoral production.</p>
<p>Goat breed selection and herd size are central household management decisions. Herders select breeds according to milk or meat production objectives and adaptability to local environmental conditions. Herd size is influenced by communal grazing regulations, household labor availability, and climatic variability. During droughts many herders reduce their herds to minimize losses and adjust to declining forage availability. In more favorable years, herds may expand as resources and management capacity allow. Goat herds typically range from 5 to 100 animals per herder, with breeds including Nubian, Alpine, Boer, Toggenburg, Saanen, and Creole. Herders expressed renewed interest in the original Granadina breed, valuing its adaptation to arid conditions and suitability for both milk and meat production. They also reported that animals retaining its original characteristics had become increasingly rare following successive cross-breeding.</p>
<p>Pastoral mobility also involves the use of <italic>majadas,</italic> remote and semi-permanent corrals within grazing areas. Their use depends on herd size, herder&#x2019;s ability to travel long distances, and available household labor. Younger herders may remain with their animals in <italic>majadas</italic> near grazing sites for extended periods (months), whereas older herders, particularly those with limited household support or competing livelihood responsibilities, may avoid distant grazing areas. Access to labor and the capacity to use <italic>majadas</italic> therefore shape households grazing range.</p>
</sec>
<sec id="s3-2-4">
<title>Institutional interventions and external support (cross-scale interactions)</title>
<p>External interventions have strongly influenced CaprinoCultura across scales. Programs such as the Regional Goat Program (2016) and PROGAN (2003-2018) promoted technological adoption, improved breeding, infrastructure, and financial support. Participants acknowledge short-term benefits but identified a poor fit to local conditions, insufficient follow-up, and weak alignment with pastoral priorities. They emphasized that limited coordination among government agencies, academic institutions, and civil-society organizations undermined the long-term effectiveness of these interventions and their potential to strengthen adaptive capacity (<xref ref-type="bibr" rid="B91">R&#xed;os-Renter&#xed;a and Rivera, 2017</xref>).</p>
<p>In parallel, initiatives promoted by producer organizations and academic institutions, such as those supported by the Instituto Nacional de Investigaciones Forestales, Agr&#xed;colas y Pecuarias <bold>(</bold>INIFAP) and the Universidad Aut&#xf3;noma de San Luis Potos&#xed; (UASLP), contributed with alternatives to address livestock feed shortages, animal health, and infrastructure for production (<xref ref-type="bibr" rid="B22">Echavarr&#xed;a and G&#xf3;mez-Ruiz, 2013</xref>; <xref ref-type="bibr" rid="B3">Anzaldo Montoya, 2024</xref>). However, poor alignment with local needs and limited continuity constrained their longer-term benefits (<xref ref-type="bibr" rid="B3">Anzaldo Montoya, 2024</xref>). These findings suggest that external interventions strengthen adaptive capacity when they respond to territorial, institutional, and household conditions of pastoral systems.</p>
<p>Overall, these findings suggest that the effects of environmental variability are mediated by processes operating across scales. Similar environmental conditions did not necessarily translate into similar pastoral conditions across the Altiplano Potosino. Rather, their effects were differentiated through interactions among territorial configuration, local governance, household organization and adaptive practices. These cross-scale interactions provide context for interpreting the spatial differentiation of vulnerability-associated conditions explored in Phase 2.</p>
</sec>
</sec>
<sec id="s3-3">
<title>Phase 2: multi-stakeholder prioritization of vulnerability conditions of CaprinoCultura</title>
<p>Throughout the participatory characterization, stakeholders identified and discussed the principal socioenvironmental factors affecting the development and long-term sustainability of CaprinoCultura. Analysis and triangulation across interviews, participatory mapping, Rivers of Life, and multi-stakeholder workshops revealed a range of perceived vulnerability-associated conditions that informed the development of the 12 criteria used in the spatial assessment.</p>
<p>
<italic>Herders</italic> highlighted declining precipitation, overgrazing and soil degradation as their main challenges. Recent droughts (2020, 2022 and 2023) forced reductions in herd size and changes in grazing routes. Rangeland degradation is concentrated near communities, reflecting both historical grazing pressures from larger herds (<xref ref-type="bibr" rid="B34">G&#xf3;mez-Ruiz et al., 2012</xref>) and declining use of remote grazing areas associated with livelihood diversification, the disuse of <italic>majadas</italic>, and mobility constraints among older herders. Herders identified weak regulation of communal grazing as a further contributor to overgrazing and soil degradation. They also acknowledged limited knowledge of rangelands&#x2019; carrying capacity despite recognizing its importance for sustainable production. In some ejidos, stocking rates are nearly three times the recommended level of one Animal Unit (AU) per 17&#xa0;ha, where one AU equals six productive goats (<xref ref-type="bibr" rid="B9">Barrera-Perales et al., 2018</xref>). Participants described changes in the ejido land use as slow and complex because they require collective decisions by the ejidatarios, many of whom live elsewhere or participate infrequently.</p>
<p>Government representatives identified prolonged rainfall deficits as a major constraint, even in areas served by earthen dams with a larger reservoir. They also emphasized limited access to milk collection and preservation technologies, linking these deficiencies to lower product quality and restricted market access (consistent with <xref ref-type="bibr" rid="B8">Potos&#xed;, 2013</xref>). They noted that effective technology adoption depends on the capacity and willingness to collaborate within each ejido. Soil degradation associated with livestock and other agricultural activities was another common concern.</p>
<p>Academic participants emphasized changes in land-tenure and management practices. They argued that, under certain conditions, a transition from communal to private tenure could encourage more sustainable rangeland management by strengthening ownership incentives (similarly to <xref ref-type="bibr" rid="B73">Negrete-S&#xe1;nchez et al., 2016</xref>). Nevertheless, they cautioned that land sales could enable acquisition by agribusinesses and mining companies, potentially reducing grazing areas and compromising water availability and quality, concerns also documented in previous studies (<xref ref-type="bibr" rid="B78">Oseguera Montiel et al., 2014</xref>; <xref ref-type="bibr" rid="B69">Mora-Ledesma, 2020</xref>; <xref ref-type="bibr" rid="B77">Ortega and Mor&#xe1;n, 2020</xref>).</p>
<p>
<italic>Civil society organizations</italic> also identified declining precipitation as a critical concern, but emphasized youth out-migration. Limited economic opportunities and adverse environmental conditions were perceived to threaten generational continuity, consistent with previous studies documenting the growing dependance of CaprinoCultura on older producers (<xref ref-type="bibr" rid="B34">G&#xf3;mez-Ruiz et al., 2012</xref>; <xref ref-type="bibr" rid="B78">Oseguera Montiel et al., 2014</xref>; <xref ref-type="bibr" rid="B114">Trenti-Very et al., 2021</xref>).</p>
<p>These perceptions were reflected in the relative weights assigned to the 12 spatial indicators across stakeholder groups (<xref ref-type="fig" rid="F7">Figure 7</xref>). Vegetation condition and soil degradation received the highest average weights (0.12 each), followed by grazing pressure and migration intensity (0.11 each). These averages highlight the overall prominence of rangeland conditions, grazing pressure, and demographic change in stakeholders&#x2019; priorities.</p>
<fig id="F7" position="float">
<label>FIGURE 7</label>
<caption>
<p>Heatmap showing the weights assigned by different stakeholder groups to the spatial indicators used to assess vulnerability-associated conditions in CaprinoCultura in the Altiplano Potosino. Colors represent the relative importance assigned to each indicator, ranging from red (higher weight) to green (lower weight).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g007.tif">
<alt-text content-type="machine-generated">Heatmap comparing perceived challenges among Herders, Government, Academia, and NGOs for rangeland management, with color intensity indicating higher values. Key issues include high grazing pressure, ecosystem degradation, and low land-use suitability, with averages provided.</alt-text>
</graphic>
</fig>
<p>Stakeholder priorities reflected their distinct role within the SES, Pastoralists emphasized day-to-day herd and rangeland management, government representatives focused on technological support and production constraints, academics highlighted governance and territorial processes, and civil society organizations stressed demographic continuity and resource access. Shared concerns about rangeland degradation and grazing pressure suggest opportunities for collaborative action. Stakeholder-specific weights were then incorporated into the Multi-Criteria Analysis (MCA) to assess how differences in priorities shaped the resulting spatial patterns.</p>
</sec>
<sec id="s3-4">
<title>Spatial patterns of vulnerability-associated conditions in CaprinoCultura</title>
<p>According to SIAP database, the largest numbers of registered livestock production units (LPUs) occur in Villa de Guadalupe (n &#x3d; 336), Charcas (n &#x3d; 311), Matehuala (n &#x3d; 273), and Cedral (n &#x3d; 269). Because many goat producers remain unregistered, the spatial assessment covered ejidos where CaprinoCultura is known to occur rather than relying on registered LPU locations. Each criterion was mapped independently to capture its specific spatial expression and relative contribution to pastoral vulnerability (<xref ref-type="fig" rid="F8">Figure 8</xref> panel).</p>
<fig id="F8" position="float">
<label>FIGURE 8</label>
<caption>
<p>Spatial distribution of vulnerability-associated indicators for CaprinoCultura in the Altiplano Potosino: <bold>(A)</bold> Limited access to urban centers, <bold>(B)</bold> Low suitability of land-use and vegetation conditions for goat pastoralism, <bold>(C)</bold> Terrain steepness, <bold>(D)</bold> Exposure to megaprojects, <bold>(E)</bold> Communal land governance constraints, <bold>(F)</bold> High grazing pressure, <bold>(G)</bold> Ecosystem degradation - vegetation Condition, <bold>(H)</bold>, Ecosystem degradation - soil degradation, <bold>(I)</bold> High migration intensity, <bold>(J)</bold> Limited access to watering points, <bold>(K)</bold> Distance to federal or state PNA, <bold>(L)</bold> Low eligibility for technological support.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g008.tif">
<alt-text content-type="machine-generated">Twelve-panel graphic displays maps of a region assessing vulnerability by different factors using color-coded ranks from one to five. Panels include limited access to urban centers, goat pastoralism land use, terrain steepness, exposure to megaprojects, communal land governance constraints, high grazing pressure, vegetation and soil degradation, migration intensity, access to watering points, distance from protected natural areas, and technological support. Each map visually distinguishes varying vulnerability levels, references geographic features like urban centers, water resources, and protected areas, and incorporates boundaries and key locations for spatial context. North orientations and color legends are provided on each panel.</alt-text>
</graphic>
</fig>
<p>Reduced annual precipitation: All stakeholder groups identified low rainfall as a major environmental stressor. The SPEI24 data indicated drought episodes across the Altiplano Potosino during 1998, 2000&#x2013;2001, 2005, 2011, and 2022&#x2013;2023 (<xref ref-type="fig" rid="F9">Figure 9</xref>). Similar SPEI trends among municipalities indicate that drought was a broadly shared regional stressor. Given its limited spatial differentiation at the scale of analysis, drought was retained as contextual information and excluded from the MCA and stakeholder weighting, as described in the Methods.</p>
<fig id="F9" position="float">
<label>FIGURE 9</label>
<caption>
<p>Temporal variation of the Standardized Precipitation-Evapotranspiration Index (SPEI24) in four municipalities of the Altiplano Potosino (Vanegas, Cedral, Matehuala, and Charcas) between 1981 and 2023. The dashed horizontal line indicates average climatic conditions (SPEI &#x3d; 0), whereas negative and positive values represent drier- and wetter-than-average conditions, respectively. The solid grey line represents the regional average SPEI24 across the four municipalities.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g009.tif">
<alt-text content-type="machine-generated">Line chart depicting SPEI24 trends from 1981 to 2023 for Vanegas, Cedral, Matehuala, Charcas, and the regional mean, showing periodic fluctuations above and below the zero SPEI threshold.</alt-text>
</graphic>
</fig>
<p>Limited access to urban centers: Distance to urban centers shapes access to markets and services. Matehuala, with 86,686 inhabitants, is the main regional market for goat meat and cheese. Remote herders face higher transportation costs and fewer opportunities to commercialize perishable products, often relying on local or informal markets with limited income opportunities. Animal movement across administrative boundaries requires compliance with animal health standards, traceability and official permits (e.g., NOM-041-ZOO-1995 for brucellosis control in goats or the registers in SINIIGA) (<xref ref-type="fig" rid="F8">Figure 8A</xref>).</p>
<p>Low suitability of land-use and vegetation conditions for goat pastoralism: Participants identified desert scrub vegetation and rainfed agriculture as the most favorable for goat production because they provide forage and crop residues. These land-cover types occupy much of the Altiplano Potosino, resulting in relatively low scores for this criterion across large areas. Higher scores occurred where vegetation and land were less suitable for pastoral production (<xref ref-type="fig" rid="F8">Figure 8B</xref>).</p>
<p>Terrain steepness: Steep, rugged terrain constrains pastoral mobility. The highest scores ocurred in the municipalities of Catorce, Villa de la Paz, Villa de Guadalupe, Charcas, Guadalc&#xe1;zar, and Villa Hidalgo (<xref ref-type="fig" rid="F8">Figure 8C</xref>).</p>
<p>Exposure to megaprojects: Large-scale agricultural, mining, and energy developments were associated with rangeland fragmentation, restricted grazing areas, disrupted mobility routes, and reduced resource access. The highest vulnerability-associated conditions occurred in Vanegas, Villa de la Paz, Cedral, Santo Domingo, Villa de Guadalupe, Matehuala, and Charcas (<xref ref-type="fig" rid="F8">Figure 8D</xref>). Although these developments may provide temporary employment, participants emphasized longer-term threats to pastoral livelihoods, consistent with previous studies (<xref ref-type="bibr" rid="B67">Mora-Ledesma, 2011</xref>; <xref ref-type="bibr" rid="B69">2020</xref>; <xref ref-type="bibr" rid="B68">Urquijo Torres, 2017</xref>; <xref ref-type="bibr" rid="B70">Mor&#xe1;n et al., 2023</xref>).</p>
<p>Communal land governance constraints: Scores varied across the region, with the highest values in Vanegas, Venado, Catorce, Charcas, Villa de Guadalupe, and Villa Hidalgo (<xref ref-type="fig" rid="F8">Figure 8E</xref>). Participants described difficulties coordinating resource use, enforcing local agreements, and regulating grazing pressure. However, cases such as the ejido El Casta&#xf1;&#xf3;n illustrate how strong internal organization can support sustainable rangeland management (<xref ref-type="bibr" rid="B73">Negrete-S&#xe1;nchez et al., 2016</xref>).</p>
<p>Ecosystem degradation and high grazing pressure: Cedral, Matehuala and Villa de Guadalupe, exhibited the highest grazing pressure, with stocking rates exceeding recommended thresholds (<xref ref-type="fig" rid="F8">Figure 8F</xref>). These municipalities together with Guadalc&#xe1;zar<italic>,</italic> also had the lowest SAVI values (<xref ref-type="fig" rid="F8">Figure 8G</xref>). CONABIO data indicated moderate soil degradation across much of the region, with high to extreme degradation in Charcas, Villa de Guadalupe, Villa Hidalgo, and Guadalc&#xe1;zar (<xref ref-type="fig" rid="F8">Figure 8H</xref>). The convergence of grazing pressure, reduced vegetation cover, and soil degradation was particularly evident in Villa de Guadalupe.</p>
<p>High migration intensity: Participants associated youth out-migration with reduced household labor and disrupted intergenerational knowledge transmission, leaving herding increasingly in the hands of older family members, often over 70 years of age. Reported consequences include smaller herds, shorter grazing routes, and reduced capacity to maintain labor-intensive practices. Migration was highest in Cedral, Santo Domingo, Villa de Ramos, Venado, Moctezuma, and Villa de Guadalupe (<xref ref-type="fig" rid="F8">Figure 8I</xref>).</p>
<p>Limited access to watering points: Livestock water sources include seasonal ponds, small reservoirs (<italic>bordos</italic>), wells, and water-storage infrastructure. Water bodies suitable for livestock use occupied the largest portions of territory in Matehuala (0.71%), Santo Domingo (0.68%), and Vanegas (0.60%), and the smallest in Villa de la Paz (0.019%), Villa de Arista (0.025%), and Guadalc&#xe1;zar (0.04%) (<xref ref-type="fig" rid="F8">Figure 8J</xref>). However, this measure does not fully capture effective access, as water sources may be unevenly distributed, seasonal, or restricted by land-tenure arrangements.</p>
<p>Restrictions associated with Protected Natural Areas: Sierra La Mojonera, Wirikuta, and the Guadalc&#xe1;zar State Reserve influence pastoral activities through land-use restrictions and opportunities for conservation support (<xref ref-type="fig" rid="F8">Figure 8K</xref>). While these areas provide opportunities for conservation and restoration programs, may also restrict land use and grazing expansion. The highest levels of vulnerability-associated conditions occurred in Cedral, Matehuala, Villa de Guadalupe, Santo Domingo, Venado, Moctezuma, and Villa de Arista.</p>
<p>Low eligibility for technological support programs: The Regional Goat Program, introduced in 2016, primarily benefited larger producers, particularly those managing more than 100 goats. Reported improvements in animal health and milk processing were limited by insufficient follow-up and technologies poorly suited to local production systems. Equipment underuse, discontinued practices and occasional conflicts over shared infrastructure further reduced program benefits. The highest levels of this vulnerability-associated condition occurred in Santo Domingo, Salinas, Villa de Ramos, Villa Hidalgo, Guadalc&#xe1;zar, and Vanegas (<xref ref-type="fig" rid="F8">Figure 8L</xref>).</p>
<p>The integrated map, based on equally weighted stakeholder perspectives showed clear spatial variation in the convergence of vulnerability-associated conditions (<xref ref-type="fig" rid="F10">Figure 10</xref>). Higher scores occurred in Vanegas, Cedral, Matehuala, Villa de Guadalupe, Guadalc&#xe1;zar, and Villa Hidalgo. Charcas, Catorce, Venado, Moctezuma, Santo Domingo, Villa de Ramos, and Salinas, exhibited lower and more heterogeneous scores. Contrasts among neighboring ejidos in Matehuala and Charcas also revealed within-municipality variation in grazing pressure, governance, vegetation condition, and resource access.</p>
<fig id="F10" position="float">
<label>FIGURE 10</label>
<caption>
<p>Composite spatial assessment of vulnerability-associated conditions across ejidos in the Altiplano Potosino derived from the multi-criteria analysis. The gradient (1.79&#x2013;4.25) represents relative levels of vulnerability-associated conditions, with higher values indicating areas where multiple conditions converge under the integrated weighting scheme. These areas may therefore represent potential priorities for further assessment and context-specific intervention. Only ejidos with available data and/or registered goat production units were included in the analysis; white areas indicate non-evaluated units.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g010.tif">
<alt-text content-type="machine-generated">Map illustrating general vulnerability levels of Ejidos in a specific region, using a color gradient from green (least vulnerable) to red (most vulnerable) with labeled municipalities and a scale bar indicating distance in kilometers.</alt-text>
</graphic>
</fig>
<p>Stakeholder-specific maps showed broadly similar patterns, with substantial overlap in high-scoring areas in the central-eastern and northern Altiplano Potosino (<xref ref-type="fig" rid="F11">Figure 11</xref> panel). Differences in stakeholder weighting nevertheless affected MCA score magnitude and distribution. Pastoralists&#x2019; emphasis on grazing pressure and soil degradation produced higher scores near population centers, particularly in Matehuala, Villa de Guadalupe, Cedral, and Vanegas. Government priorities yielded a more homogeneous distribution of moderate-to-high scores, while academic priorities produced greater spatial differentiation. NGOs weight areas with high migration and limited access to resources and institutional support.</p>
<fig id="F11" position="float">
<label>FIGURE 11</label>
<caption>
<p>Stakeholder-specific spatial assessments of vulnerability-associated conditions across ejidos in the Altiplano Potosino, generated through Multi-Criteria Analysis (MCA) using stakeholder-specific weighting schemes. The maps represent the spatial configuration of relative vulnerability-associated conditions based on the priorities assigned by different stakeholder groups: <bold>(A)</bold> pastoralists, <bold>(B)</bold> government, <bold>(C)</bold> academia, and <bold>(D)</bold> NGOs.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="past-16-17175-g011.tif">
<alt-text content-type="machine-generated">Figure with four colored maps labeled A through D compares spatial vulnerability ranks in ejidos of a region in Mexico as assessed by herders, government, academia, and NGOs; each map uses a green to red gradient to show vulnerability values, includes town boundaries, orientation north arrows, scale bars, and labeled municipalities.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-5">
<title>Sensitivity of spatial assessment results</title>
<p>Sensitivity analyses indicated that spatial MCA patterns were highly robust to moderate changes in criterion weights (&#xb1;20%), with Spearman&#x2019;s &#x3c1; generally above 0.98. The leave-one-criterion-out analysis revealed that some criteria, particularly ecosystem degradation and overgrazing, had a stronger influence on the spatial organization of results, although their influence varied among stakeholder groups. Alternative stakeholder aggregation produced highly consistent spatial patterns, with equal- and sample-size-proportional weighting yielding high spatial agreement with the integrated assessment. Detailed sensitivity analysis results are provided in <xref ref-type="sec" rid="s11">Supplementary Material S4</xref>.</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>Pastoral vulnerability emerges from interactions among climatic variability, land degradation, governance, and socio-economic change across scales (<xref ref-type="bibr" rid="B89">Reid et al., 2021</xref>; <xref ref-type="bibr" rid="B100">Scoones, 2023</xref>). Social-ecological systems (SES) frameworks and spatial analyses help examine these interactions (<xref ref-type="bibr" rid="B19">de Sherbinin et al., 2019</xref>; <xref ref-type="bibr" rid="B111">Thiault et al., 2021</xref>; <xref ref-type="bibr" rid="B7">Balew et al., 2022</xref>; <xref ref-type="bibr" rid="B124">Yang et al., 2023</xref>); yet indicator selection and weighting remain largely researcher- or expert-driven, limiting stakeholders&#x2019; influence over how vulnerability is assessed. Participation thus informed both what was assessed and how conditions were prioritized. This contribution complements GIS-based vulnerability assessments (<xref ref-type="bibr" rid="B19">de Sherbinin et al., 2019</xref>; <xref ref-type="bibr" rid="B111">Thiault et al., 2021</xref>; <xref ref-type="bibr" rid="B7">Balew et al., 2022</xref>; <xref ref-type="bibr" rid="B124">Yang et al., 2023</xref>) by making different stakeholder perspectives explicit, including concerns that may be overlooked in expert assessments but influence adaptation responses (Nelson et al., 2023).</p>
<p>Shared priorities can function as &#x201c;theme bridges&#x201d; among actors with different responsibilities and knowledge systems (<xref ref-type="bibr" rid="B38">Hern&#xe1;ndez-Valdez et al., 2025</xref>). Their value lies in providing a basis for dialogue and collective action without requiring agreement on all aspects of vulnerability (<xref ref-type="bibr" rid="B101">Seiferth et al., 2024</xref>). Such dialogue supports social learning while preserving differences among knowledge systems (<xref ref-type="bibr" rid="B97">Roux et al., 2017</xref>; <xref ref-type="bibr" rid="B107">Souza et al., 2020</xref>).</p>
<p>Multi-stakeholder learning platforms could sustain this dialogue beyond the assessment, enabling participants to interpret spatial priorities, monitor change and negotiate locally appropriate responses (<xref ref-type="bibr" rid="B59">Mart&#xed;nez-Tag&#xfc;e&#xf1;a et al., 2024</xref>). Although establishing these platforms is beyond the study&#x2019;s scope, the emergence of a multisectoral partnership following discussion of the results suggests potential for continued collaboration. Whether this partnership produces sustained collective action and strengthens adaptive governance remains to be assessed.</p>
<sec id="s4-1">
<title>CaprinoCultura as a pastoral social-ecological system</title>
<p>The findings suggest that adaptive capacity in CaprinoCultura depends on conditions that allow households to put their knowledge and management strategies into practice. Pastoral households are embedded within broader territorial, institutional and ecological processes that shape their capacity to respond to socioenvironmental change (<xref ref-type="bibr" rid="B54">Linst&#xe4;dter et al., 2016</xref>; <xref ref-type="bibr" rid="B112">Tolera and Senbeta, 2020</xref>; <xref ref-type="bibr" rid="B83">Postigo, 2021</xref>).</p>
<p>Mobility illustrates this relationship: enables responses to variability in forage and water, but depends on ecological knowledge and arrangements governing access to grazing areas (<xref ref-type="bibr" rid="B47">Kakinuma et al., 2019</xref>; <xref ref-type="bibr" rid="B115">Turner and Schlecht, 2019</xref>; <xref ref-type="bibr" rid="B21">D&#x2019;Abramo et al., 2021</xref>; <xref ref-type="bibr" rid="B104">Sharifian et al., 2023</xref>). In the Mexican ejido context, its adaptive value is therefore closely tied to communal resource governance. Territorial fragmentation and demographic change appear to constrain this capacity jointly. While privatization and competing land uses restrict accessible grazing areas, migration and population aging reduce the household labor available to use them. These processes have also been documented in other pastoral systems (<xref ref-type="bibr" rid="B95">Robinson and Flintan, 2022</xref>; <xref ref-type="bibr" rid="B75">Ntombela et al., 2024</xref>).</p>
<p>Local ecological knowledge is similarly dependent on opportunities for its continued use and transmission. It provides detailed information relevant to herd management and territorial planning, like forage quality, seasonal resource availability, grazing suitability, animal health, and production potential (<xref ref-type="bibr" rid="B51">Le&#xf3;n Villalobos et al., 2018</xref>; <xref ref-type="bibr" rid="B103">Sharifian et al., 2022</xref>), but its adaptive role may weaken when access to familiar grazing territories is lost or intergenerational participation declines. Participatory territorial planning offers one means of bringing this knowledge into dialogue with technical assessments and land-use decisions (<xref ref-type="bibr" rid="B4">Arteaga Aguilar et al., 2014</xref>). These findings shift attention from the presence of adaptive practices to the conditions that sustain them. Ejido governance is central to this distinction because collective rules and decisions shape whether households can access and manage the resources on which those practices depend.</p>
</sec>
<sec id="s4-2">
<title>Ejido governance as a key social-ecological process</title>
<p>Variation among ejidos suggests that communal tenure should not itself be interpreted as a vulnerability factor. Its implications depend on how collective institutions regulate grazing, negotiate resource access and enforce agreements. This interpretation is consistent with studies showing that collective institutions can support adaptive capacity through collective action and flexible resource management (<xref ref-type="bibr" rid="B28">Fern&#xe1;ndez-Gim&#xe9;nez et al., 2015</xref>; <xref ref-type="bibr" rid="B35">Gongbuzeren et al., 2021</xref>; <xref ref-type="bibr" rid="B79">Pappagallo, 2024</xref>). The ejido is therefore a governance arena in which household interests, ecological variability, and external pressures are negotiated.</p>
<p>
<xref ref-type="bibr" rid="B94">Robinson, (2019)</xref> similarly shows that pastoral tenure systems often involve flexible and overlapping arrangements of access and use that do not conform to conventional communal&#x2013;private distinctions. <xref ref-type="bibr" rid="B79">Pappagallo, (2024)</xref> likewise shows how collective institutions can maintain connectivity and flexible access to heterogeneous resources across tenure arrangements. Together, these studies suggest that the adaptive value of pastoral institutions depends less on formal tenure categories than on their capacity to maintain connectivity, negotiate access, and adjust resource-use arrangements under changing conditions.</p>
<p>Evidence from El Casta&#xf1;on associates rangeland parcelization with improved rangeland condition, livestock production, and individual stewardship (<xref ref-type="bibr" rid="B73">Negrete-S&#xe1;nchez et al., 2016</xref>). Our findings do not rule out such benefits, but caution against attributing outcomes to tenure categories alone. Pastoral access arrangements often extend beyond communal-private distinctions, and their adaptive value depends on maintaining connectivity and negotiating access to heterogeneous resources (<xref ref-type="bibr" rid="B94">Robinson, 2019</xref>; <xref ref-type="bibr" rid="B79">Pappagallo, 2024</xref>). Strengthening local governance may therefore support adaptation without necessarily requiring changes in tenure.</p>
<p>This perspective favors support tailored to local institutional capacities over uniform prescriptions. Research across pastoral contexts worldwide highlights the importance of collaborative institutions and governance networks to coordinate communities, governments, and other actors under changing conditions like climate-related pressures (<xref ref-type="bibr" rid="B113">Tolera and Senbeta, 2023</xref>; <xref ref-type="bibr" rid="B120">Weng et al., 2023</xref>; <xref ref-type="bibr" rid="B124">Yang et al., 2023</xref>; <xref ref-type="bibr" rid="B125">Zhang, 2023</xref>). Thus, while institutional arrangements are various a common principle is that pastoral adaptive capacity depends partly on institutions&#x2019; ability to maintain flexible and collectively negotiated access to heterogeneous resources while connecting local knowledge and decision-making with broader institutional support. In our study, we show that differences in local governance effectiveness become spatially differentiated across a pastoral landscape. For CaprinoCultural, this implies attending to how ejido rules operate in practice and whether households can participate in, negotiate, and implement collective decisions.</p>
</sec>
<sec id="s4-3">
<title>Household organization and the adaptive capacity of CaprinoCultura</title>
<p>The household is both a productive unit and a social setting through which labor, knowledge, resource management and production and risk are organized. This helps explain how pastoral families combine livelihood activities to respond to changing conditions, as documented in other pastoral and smallholder goat systems (<xref ref-type="bibr" rid="B78">Oseguera Montiel et al., 2014</xref>; <xref ref-type="bibr" rid="B57">Mairomi and Kimengsi, 2021</xref>). Livelihood diversification can buffer income fluctuations, but its adaptive benefits depend partly on whether households retain sufficient labor and knowledge to sustain pastoral practices. Migration and demographic aging may weaken these adaptive capacities (<xref ref-type="bibr" rid="B75">Ntombela et al., 2024</xref>).</p>
<p>Household continuity also has a sociocultural and territorial dimension. Herders&#x2019; descriptions of grazing areas as places of family history and learning suggest that these territories sustain relationships beyond production and are rooted in memory, identity, and social meaning. This interpretation is consistent with research linking pastoral knowledge to landscapes, intergenerational transmission, and cultural identity and heritage (<xref ref-type="bibr" rid="B103">Sharifian et al., 2022</xref>; <xref ref-type="bibr" rid="B14">Chao et al., 2025</xref>). Consequently, migration and territorial fragmentation affect not only production but also relationships through which CaprinoCultura is maintained and renewed.</p>
</sec>
<sec id="s4-4">
<title>From vulnerability assessment to adaptive governance</title>
<p>The spatial assessment represents the relative convergence of selective vulnerability-associated conditions rather than an absolute measure of vulnerability. Its interpretation depends on the indicators, scale, and aggregation procedures used (<xref ref-type="bibr" rid="B19">de Sherbinin et al., 2019</xref>; <xref ref-type="bibr" rid="B111">Thiault et al., 2021</xref>). Mobility, livelihood diversification and household organization were identified through participatory activities but could not be consistently represented spatially. Their omission from the spatial model reflects methodological scope rather than the lack of relevance to adaptive capacity.</p>
<p>The maps should therefore guide further inquiry and locally negotiated responses rather than serve as definitive classifications of territories. Areas with higher scores warrant closer examination of how mapped conditions interact with capacities not captured by the indicators. Sensitivity analyses support the stability of spatial rankings under the tested weighting changes, but do not establish that the indicators capture all dimensions of vulnerability. This limitation also highlights a broader contribution of the study. Rather than treating vulnerability as a fixed territorial attribute, our results distinguish between the spatial distribution of selected vulnerability conditions and the broader processes shaping adaptive capacity.</p>
<p>Equal weighting balanced the contribution of stakeholder sectors to the integrated map but did not eliminate differences in representation within them, including the limited participation of women and younger generations. Spatial indicators also only partially capture the governance arrangements and adaptive practices identified through participatory research. Although sensitivity analyses supported the stability of spatial rankings under the tested scenarios, future research could examine how these patterns relate to observed livelihood outcomes and changes in pastoral continuity.</p>
<p>Stakeholder-specific maps also remain important alongside the integrated assessment. Although their broad patterns were similar, differences in priorities reveal distinct concerns that averaging can obscure. These differences provide information for deliberation rather than simply uncertainty to be eliminated (<xref ref-type="bibr" rid="B30">Findlater et al., 2022</xref>). Reading the maps together can support dialogue among complementary knowledge systems while preserving their distinct perspectives (similarly to <xref ref-type="bibr" rid="B110">Teng&#xf6; et al., 2017</xref>; <xref ref-type="bibr" rid="B25">Fern&#xe1;ndez-Gim&#xe9;nez, 2020</xref>; <xref ref-type="bibr" rid="B90">Reid-Shaw et al., 2021</xref>; <xref ref-type="bibr" rid="B101">Seiferth et al., 2024</xref>). In pastoral systems, collaborative research has similarly shown that co-production, integration of knowledges, social learning, networking, and collective action can strengthen connections between knowledge generation and governance (<xref ref-type="bibr" rid="B89">Reid et al., 2021</xref>).</p>
<p>Shared priorities may function as &#x201c;theme bridges&#x201d; around which stakeholders begin this dialogue (<xref ref-type="bibr" rid="B38">Hern&#xe1;ndez-Valdez et al., 2025</xref>). Our approach links co-produced criteria, stakeholder priorities, and spatial analysis to examine vulnerability-associated conditions within their local social-ecological contexts (as mentioned previously by <xref ref-type="bibr" rid="B6">Ayantunde et al., 2015</xref>; <xref ref-type="bibr" rid="B124">Yang et al., 2023</xref>). Beyond mapping these conditions, this integration can support joint learning, priority setting, and dialogue to inform adaptive governance (<xref ref-type="bibr" rid="B111">Thiault et al., 2021</xref>).</p>
</sec>
<sec id="s4-5">
<title>Policy implications for place-based pastoral development</title>
<p>These findings support context-specific policies that coordinate actions across households, ejido authorities, government, academia, and civil society across various scales. Production-oriented interventions should account for the governance arrangements, household capacities, and resource constraints that shape their feasibility and adoption. This is particularly relevant where programs have incorporated pastoralists&#x2019; priorities and knowledge only to a limited extent (<xref ref-type="bibr" rid="B3">Anzaldo Montoya, 2024</xref>) and is consistent with calls for differentiated pastoral policies and coordination across scales (<xref ref-type="bibr" rid="B125">Zhang, 2023</xref>).</p>
<p>For territorial planning, stakeholder-informed assessments can complement existing information on environmental suitability, livestock production, infrastructure, land use, and resource availability In Mexico, combining INEGI and SIAP datasets with participatory diagnosis could help distinguish biophysical suitability from the social-ecological conditions needed to sustain pastoral activities. This would inform decisions about which interventions are appropriate, where, and for whom.</p>
<p>At the ejido level, support should strengthen capacities to negotiate grazing access, regulate grazing pressure, resolve conflicts, and monitor rangelands. Communal tenure should not be treated as a constraint; attention should focus on how community-based institutions organize resource access and collective management, strengthening adaptive capacity through knowledge exchange, social capital, and collective action (<xref ref-type="bibr" rid="B28">Fern&#xe1;ndez-Gim&#xe9;nez et al., 2015</xref>; <xref ref-type="bibr" rid="B35">Gongbuzeren et al., 2021</xref>; <xref ref-type="bibr" rid="B79">Pappagallo, 2024</xref>). At the household level, productive support should be accompanied by measures that enable women&#x2019;s and younger generations&#x2019; participation, intergenerational learning and livelihood diversification.</p>
<p>At the regional level, the maps can identify areas requiring closer diagnosis. Where grazing pressure and ecosystem degradation converge, restoration and grazing management may warrant consideration; elsewhere, water access, institutional/technological support or demographic change may require different responses like infrastructure, mobility, market access, training, diversification, and generational strategies. These options should be evaluated locally, since the spatial assessment neither prescribes interventions nor implies an absence of adaptive capacity (<xref ref-type="bibr" rid="B111">Thiault et al., 2021</xref>; <xref ref-type="bibr" rid="B7">Balew et al., 2022</xref>). In this way, vulnerability assessment can contribute not only to territorial analysis, but also to dialogue, priority setting, and adaptive governance (<xref ref-type="bibr" rid="B64">Metcalf et al., 2015</xref>; <xref ref-type="bibr" rid="B124">Yang et al., 2023</xref>).</p>
<p>Monitoring vulnerability-associated conditions over time could strengthen the policy relevance of the assessment by tracking whether selected conditions improve, persist, or intensify. Such comparisons would require consistent methods and explicit attention to dataset reference years. Interpreting changes jointly with pastoralists, ejido authorities, and other stakeholders could connect monitoring with locally informed decisions without treating indicator trends as direct measures of changing vulnerability.</p>
</sec>
<sec id="s4-6">
<title>Conceptual contribution and broader implications</title>
<p>This study supports a relational understanding of pastoral vulnerability as an emergent, relational, and spatially differentiated property of social-ecological systems. In which environmental pressures acquire different implications through their interaction with resource access, governance, household organization and local knowledge (<xref ref-type="bibr" rid="B116">Turner et al., 2003</xref>; <xref ref-type="bibr" rid="B124">Yang et al., 2023</xref>). In CaprinoCultura, this directs attention to the social and institutional conditions that enable pastoralists to exercise adaptive capacity, rather than solely to the pressures they face.</p>
<p>The methodological contribution lies in connecting this contextual understanding with spatial assessment while distinguishing mapped conditions from adaptive processes that require qualitative interpretation. This is particularly relevant in pastoral systems, where mobility, livelihood diversification, household organization, and local knowledge may be central to adaptive capacity but difficult to consistently spatialize (<xref ref-type="bibr" rid="B6">Ayantunde et al., 2015</xref>; <xref ref-type="bibr" rid="B111">Thiault et al., 2021</xref>). The resulting framework identifies where selected conditions converge and how stakeholders prioritize them, providing a basis for further diagnosis and negotiation. Its broader relevance lies in supporting place-based decisions that sustain pastoralists&#x2019; capacity to mobilize knowledge, labor, mobility, collective institutions, and external support in response to change (as described in (<xref ref-type="bibr" rid="B121">Wilmer et al., 2018</xref>; <xref ref-type="bibr" rid="B122">2022</xref>; <xref ref-type="bibr" rid="B89">Reid et al., 2021</xref>).</p>
<p>Beyond its analytical contribution, participatory vulnerability assessment can create opportunities for dialogue by connecting spatial evidence with different knowledge systems and stakeholder priorities (as suggested by <xref ref-type="bibr" rid="B89">Reid et al., 2021</xref>; <xref ref-type="bibr" rid="B101">Seiferth et al., 2024</xref>). Its value therefore lies not only in identifying where vulnerability-associated conditions converge, but also in providing a shared basis for negotiating responses that sustain CaprinoCultura and the capacities of those who maintain it.</p>
</sec>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s5">
<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 sec-type="ethics-statement" id="s6">
<title>Ethics statement</title>
<p>Ethical approval was not required for this study under applicable institutional and national guidelines. The Instituto Potosino de Investigaci&#xf3;n Cient&#xed;fica y Tecnol&#xf3;gica does not have an ethics committee, and the study involved non-invasive participatory methods, including interviews, participatory mapping, focus groups, workshops, and surveys. It did not involve experimental interventions or the collection of sensitive personal information. The research focused on documenting knowledge, perceptions, and experiences related to pastoral systems and was conducted in accordance with applicable local legislation and institutional requirements, respecting the principles of voluntary participation, confidentiality, respect for participants, and responsible use of information. Written informed consent for participation was not obtained because literacy levels vary in rural pastoral communities and participants may be reluctant to sign formal documents. Instead, verbal informed consent was obtained before all research activities. Participants were informed about the study&#x2019;s objectives, the intended use of the information, their right to decline participation or withdraw at any time, and their right to withhold any information they preferred to keep confidential. Written consent for the publication of potentially identifiable images or data was also not obtained. Before photographs were taken, participants were informed about their intended use, and verbal permission for photography and publication was requested during the multistakeholder workshops. The photographs included in the Supplementary Material were taken during these workshops.</p>
</sec>
<sec sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>AG-M: Conceptualization, investigation, data analysis, interpretation, and manuscript writing. EH-S: Conceptualization, data analysis, interpretation, manuscript writing and supervision. RD-O: Data analysis and interpretation. NM-T: Conceptualization, manuscript review and editing, and supervision. FA: Conceptualization, manuscript review, and supervision. MM-L: Conceptualization, manuscript review, and supervision. MV-M: Conceptualization, manuscript review, and supervision. All authors contributed to the article and approved the submitted version.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>The authors sincerely thank the goat herders, academics, government representatives, and local stakeholders who participated in the interviews, workshops, surveys, and participatory mapping activities conducted throughout this research. We are especially grateful to the Federaci&#xf3;n de Caprinocultores del Altiplano Mexicano for their support and collaboration during the development of this study. We also acknowledge the valuable technical assistance provided by Alejandro Malagamba, as well as the contributions of the facilitators who supported the multistakeholder workshops: Roberto I. M&#xe1;rquez Hern&#xe1;ndez, Luis D. Cruz Gonz&#xe1;lez, Gerardo Esquivel Arriaga, Esmeralda N. L&#xf3;pez Lozano, Marcela Corpus Hern&#xe1;ndez, and Fidel I. Garc&#xed;a Ch&#xe1;vez. Finally, we acknowledge the institutional and logistical support provided by the Instituto Potosino de Investigaci&#xf3;n Cient&#xed;fica y Tecnol&#xf3;gica (IPICYT) and the Consejo Potosino de Ciencia y Tecnolog&#xed;a (COPOCYT), whose collaboration contributed significantly to the development of this research.</p>
</ack>
<sec sec-type="COI-statement" id="s9">
<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 sec-type="ai-statement" id="s10">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was used in the creation of this manuscript. Generative artificial intelligence (AI) tools were used to support language editing and improve the clarity of the manuscript. However, all scientific content, data analysis, interpretation of results, and conclusions were developed by the authors, who take full responsibility for the integrity and accuracy of the work.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="supplementary-material" id="s11">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontierspartnerships.org/articles/10.3389/past.2026.17175/full#supplementary-material">https://www.frontierspartnerships.org/articles/10.3389/past.2026.17175/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet1.pdf" id="SM1" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2164157/overview">Palden Tsering</ext-link>, Qinghai Nationalities University, China</p>
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