From Crisis to Capacity: What COVID-19 Teaches about Resilience in Iran’s Farming Systems

From Crisis to Capacity: What COVID-19 Teaches about Resilience in Iran’s Farming Systems | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article From Crisis to Capacity: What COVID-19 Teaches about Resilience in Iran’s Farming Systems Sadegh Rahmani, Davoud Rouzaneh, Ameneh Savari Mombeni, Pouria Liravi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8515225/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The COVID-19 pandemic exposed the structural fragility of agricultural systems in southern Iran by disrupting production, marketing, access to inputs, and essential services. This study aimed to analyze and compare the adaptive capacity and adaptive strategies of smallholder farmers and livestock keepers in Khuzestan Province in response to this widespread shock. Using a qualitative approach and a six-dimensional adaptive capacity framework (including resources, information and knowledge, policies, governance, infrastructure, and perception), data were collected through 57 semi-structured interviews and analyzed using deductive content analysis. The findings revealed that in the absence of effective institutional support, farmers and livestock keepers adopted divergent strategies. Farmers focused on value chain restructuring, market diversification, and product transformation, while livestock keepers engaged in herd management adjustments, cost reduction, and increased reliance on local resources. Both groups drew heavily on social capital and informal networks to compensate for institutional gaps. The key contribution of this study lies in providing a comparative analysis of these two groups and highlighting the critical role of social capital in local resilience. We conclude that locally driven responses, despite structural constraints, offer valuable lessons for designing anticipatory policies, strengthening adaptive infrastructure, and reconfiguring governance to enhance agricultural resilience. These insights are crucial for preparing rural systems to better withstand and recover from future shocks. Social science/Development studies Earth and environmental sciences/Environmental social sciences Adaptive Capacity Smallholder Farmers COVID-19 Pandemic Adaptation Strategies Agricultural Resilience Future Shocks Figures Figure 1 Figure 2 Figure 3 Introduction In today’s interconnected world, sustainable agricultural systems are vital for food production and security. They also play a critical role in public health and community resilience against climatic, economic, and social shocks. From a systems thinking perspective, agriculture is part of an interconnected network whose performance influences the security and health sectors. Disruptions in this sector during crises can trigger failures across the entire system, undermining crisis management policies, even if they control the crisis’s epicenter (Akpabio et al., 2025 ; Fanzo, 2019 ; Clark et al., 2020 ). However, food systems in many parts of the world, particularly in developing countries, lack the capacity to achieve sustainability and resilience goals. Challenges such as rapid population growth, internal conflicts, natural disasters, and climate change pose serious threats to these systems. Consequently, these disruptions have hindered the core pillars of food security—availability, access, utilization, stability, agency, and sustainability—highlighting the urgent need for transformative changes in agricultural and food systems (Clark et al., 2020 ; Karimi et al., 2022 ; Akpabio et al., 2025 ). Among the global shocks that have severely impacted agricultural systems in recent years are the COVID-19 pandemic and the war in Ukraine, both of which caused economic recessions, disrupted food supply chains, and exacerbated inequality, food insecurity, and social instability (Swinnen & Vos, 2021 ; Kubatko et al., 2023 ). This study focuses on local-level adaptive capacity, analyzing how smallholder farmers and livestock keepers in Khuzestan Province responded to the COVID-19 pandemic under severe institutional and economic constraints. A challenge that was particularly severe in developing countries facing chronic climatic, institutional, and economic constraints, disrupting production, processing, trade, food stocks, and purchasing power (Workie et al., 2020 ). In this context, smallholder farmers and pastoralists, who depend on local resources and lack adequate institutional support, were highly vulnerable. Their responses, including shifting production patterns, relying on family labor, and using indigenous tools, reflect a concept known in development literature as “adaptive capacity,” which is essential for enhancing the resilience of agricultural systems against multifaceted crises (Kubatko et al., 2023 ). Adaptive capacity, a key factor in agricultural system resilience, refers to the set of resources, knowledge, and processes that enable a system or community to adapt to changes while minimizing negative consequences (Folke et al., 2005). This capacity was evident in the active responses of farmers and local communities to the COVID-19 pandemic, which disrupted supply chains, markets, and labor mobility, necessitating flexible, locally based mechanisms (Meuwissen et al., 2021 ). Adaptive capacity was demonstrated through actions such as extensive use of family labor, adoption of digital infrastructures, adjustments in cropping patterns, development of local or online sales, and strengthened social and institutional networks for product distribution (Schreiber et al., 2022 ; Khan, 2022). These initiatives highlight communities’ ability to adapt creatively to crises, utilize limited resources, and overcome institutional barriers—core elements of this concept in academic literature (van Gameren and Zaccai, 2015 ). However, the realization and sustainability of such capacity depend on institutional structures, social capital, resource access, and supportive policies, which remain challenging in many developing countries (Williams et al., 2019 ; Lindner et al., 2010 ). Despite its critical role in addressing crises like COVID-19, local-level data on adaptive capacity remain limited. While its application in climate change research has grown, its role in health crises and other shocks is underexplored. Nevertheless, it is increasingly central to policymaking for food security, resilience, and sustainable development (Cinner et al., 2018 ; Asfaw et al., 2019 ). While the critical role of adaptive capacity in managing crises like the COVID-19 pandemic is widely acknowledged, research on specific local-level strategies and the contextual factors that enable resilience in agrarian communities remains limited, especially in regions facing institutional constraints. This study addresses this research gap by focusing on Khuzestan Province, Iran, and providing an in-depth qualitative analysis. The primary contribution of this paper is to offer a comparative analysis of the adaptive strategies of both smallholder farmers and pastoralists, revealing key differences in their responses. Furthermore, the research highlights the vital role of social capital and informal networks in compensating for institutional shortcomings, thereby enriching our understanding of local resilience dynamics. Ultimately, this study offers concrete policy lessons for designing anticipatory policies, strengthening adaptive infrastructure, and reconfiguring governance to help rural systems better withstand and recover from future shocks. Conceptual framework Adaptive capacity, often overlooked, is integral to human systems’ resilience, enabling responses to natural and societal changes (Hirschfeld et al., 2020 ; Chepkoech et al., 2020 ; Biesbroek & Wals, 2017 ). It shapes actors’ abilities to plan and execute adaptation while overcoming socio-political constraints (Biesbroek & Wals, 2017 ). Adaptive capacity is crucial for designing and implementing measures to adapt to risks and shocks (Chepkoech et al., 2020 ; Dapilah et al., 2020 ). Effective adaptation and risk mitigation require developing the adaptive capacity of communities and households (Matewos, 2020 ). Originating in biology, adaptive capacity refers to an organism’s ability to survive environmental changes (de Wildt-Liesveld et al., 2015 ). This concept later extended to other fields, notably the social sciences, where anthropologist Julian Steward introduced cultural ecology, defined as “the study of processes by which societies adapt to their environments” (Plummer and Armitage, 2010 ). Since then, its role in managing vulnerability and fostering social and environmental resilience has led to systematic applications in social-ecological and human-social systems, including studies on climate change (Mahfoud et al., 2021), water management (Bergsma et al., 2012 ), women’s roles in agricultural adaptation (Witinok-Huber and Radil, 2021 ), flood exposure (Thanvisitthpon et al., 2020 ), and resilience to environmental change (Brown and Westaway, 2011 ). Adaptive capacity has been defined variably in the literature (Jones et al., 2019 ). The IPCC Third (2001) and Fourth (2007) Assessment Reports describe it as “the ability of systems, institutions, humans, and other organisms to adapt to potential harms, seize opportunities, and respond to consequences” (Matewos, 2020 ; Bhowmik et al., 2021 ). Adger et al. ( 2007 ) emphasize its role in enabling systems to respond to change through modifications in behavior, resources, and technology, particularly in agriculture. Similarly, Witinok-Huber and Radil ( 2021 ) define it as the ability of farmers and agricultural communities to develop strategies using existing resources and knowledge to manage social and environmental stresses while sustaining livelihoods. adaptive capacity, the focus of this study, is a latent trait enabling individuals to anticipate, respond to, and recover from changes while minimizing their consequences (Cinner et al., 2015 ). However, it is unevenly distributed across regions and communities within a country (Mahfoud et al., 2021). According to the Sixth Assessment Report of the IPCC, climate resilience is conceptualized as the “result of capacities,” encompassing absorptive, adaptive, and transformative capacities. Accordingly, adaptive capacity is regarded as one of the central components of resilience, and its strengthening directly enhances resilience. In the AR6 conceptual framework, vulnerability is defined as the propensity to be adversely affected, which is linked to sensitivity and the lack of adaptive capacity; thus, higher adaptive capacity reduces vulnerability and consequently increases resilience. This logic is emphasized in the conceptual chapters as well as in the discussion on Climate Resilient Development (CRD), where enabling conditions such as governance, financial resources, knowledge, and technology are highlighted as direct means of strengthening adaptive capacity and, in turn, resilience (IPCC, 2022). To support policymakers and development planners in enhancing community adaptive capacity, it is essential to analyze its influencing factors, which are embedded in societal systems and vary across time and place (Witinok-Huber and Radil, 2021 ). Enhancing adaptive capacity is critical for reducing societal vulnerability to global environmental changes and building resilience, enabling communities to address a wide range of external threats (Engle, 2011 ; Quinlan et al., 2016 ; Witinok-Huber and Radil, 2021 ; Freduah et al., 2019 ; Cinner et al., 2015 ). Studies indicate that adaptive capacity is a prerequisite for designing and implementing effective adaptation strategies (Adger et al., 2007 ). In line with the IPCC's framework, agricultural systems’ adaptive capacity and resilience depend on post-disaster measures, recovery efforts, and adaptation to COVID-19 impacts (Štreimikienė et al., 2021 ). Policymakers face the complex task of building adaptive capacity to enhance agricultural productivity, as farmers’ challenges vary by spatial and temporal factors (Witinok-Huber and Radil, 2021 ). Although vulnerability determinants have been widely studied, those of adaptive capacity have received less attention, likely due to their context-specific nature (Engle, 2011 ; Warrick et al., 2017 ). Because adaptive capacity varies regionally, a framework is needed to assess it and develop structural and non-structural measures to address natural disasters (Freduah et al., 2019 ; Hirschfeld et al., 2020 ). To address this need, frameworks for assessing adaptive capacity have been proposed (Berke et al., 2015; Gupta et al., 2010 ). These frameworks should include components that reflect the system’s internal dynamics and its ability to adapt to new conditions (Dixon et al., 2014 ). However, no universal framework exists, as components depend on local systems and contexts, and selected determinants often fail to fully capture community conditions (Warrick et al., 2017 ). This limitation points to the need for tailored approaches to evaluating adaptive capacity at the local level. Frameworks typically emphasize social factors like technology, infrastructure, institutions, and knowledge, but their relative importance varies by context and time (Freduah et al., 2019 ). Two approaches to measuring adaptive capacity exist: inductive, data-driven methods, which rely on expert judgment but are criticized for oversimplification and limited spatial validity, and deductive, theory-guided methods, which map cause-and-effect relationships to identify leverage points (Bhowmik et al., 2021 ; Matewos, 2020 ). Adaptive capacity varies across regions, requiring context-specific evaluation of temporal and spatial factors (Engle, 2011 ). This study adopts a deductive qualitative approach, applying an existing adaptive capacity framework to interpret factors influencing resilience. Using six predefined dimensions, resources, information, governance, policies, infrastructure, and perceptions, we analyze local-level data to reveal how structural and non-structural determinants shaped farmers’ and livestock keepers’ adaptive responses during the COVID-19 pandemic(Fig. 1 ). Knowledge and Information Information is a key component of adaptive capacity (Freduah et al., 2019 ; Mahfoud et al., 2021). Knowledge, a critical aspect of information, drives public concern about risks and motivates preventive behaviors (Reser et al., 2012 ). Awareness, reflecting this knowledge, is a prerequisite for adaptive behaviors and adjusting to new situations (Sundblad et al., 2009 ; Grunblatt, 2020 ; Mahfoud et al., 2021). Access to information empowers communities by raising awareness of specific group needs (Ospina and Heeks, 2010 ). For example, Stanturf et al. ( 2015 ) highlight the role of information access in guiding government and donor investments to reduce social vulnerability to epidemics, such as Ebola, and strengthen adaptive capacity. Similarly, Tam et al. ( 2021 ) found that individuals with greater knowledge and awareness were more likely to adopt protective behaviors during the COVID-19 pandemic. Resources Access Access to resources is a critical driver of farmers’ adaptive capacity in responding to change (Witinok-Huber & Radil, 2021 ). The ability of individuals and communities to cope with change depends heavily on access to and control over diverse livelihood assets (Jones et al., 2019 ). Resource constraints pose significant challenges for smallholder farmers in adapting to disruptions (Fanadzo et al., 2021 ). Rozaki ( 2020 ) emphasizes that access to basic and food resources was essential during and after the COVID-19 pandemic to ensure food security and adaptive stability in rural agricultural communities. Lal ( 2020 ) identifies supply chain disruptions, physical and economic barriers, and limited labor access as key reasons for resource constraints during the pandemic. Among these resources, infrastructure plays a pivotal role in enabling adaptive capacity, particularly during crises like the COVID-19 pandemic. Governance Governance is a critical component of adaptive capacity, shaping individuals’ and communities’ ability to adapt through effective decision-making and resource management (Vincent, 2007 ; Engle, 2011 ; Lockwood et al., 2015 ). Brooks et al. ( 2005 ) identify governance as the primary determinant of adaptive capacity, while Engle ( 2011 ) emphasizes the influence of management and active institutions (Kruse, 2015). Despite its importance, empirical research on governance’s role in adaptation remains limited (Medema et al., 2008 ). Governance refers to formal and informal institutional arrangements that regulate resource use in society (Rodriguez, 2019 ). Effective governance and management approaches facilitate adaptations, thereby enhancing or diminishing adaptive capacity (Clarvis and Engle, 2015). Actors at various governance levels develop and implement adaptation policies, strengthening adaptive capacity (Plummer, 2013 ). Participatory approaches further support sustainable management of natural, financial, and human resources during adaptation (Mahfoud et al., 2021). For example, Dutta and Fischer ( 2020 ) argue that local governance was crucial during the COVID-19 pandemic for aligning policy-making with local realities to coordinate responses. Policies Policies refer to policy-making that shapes the effective use of resources like infrastructure, playing a vital role in building adaptive capacity for agricultural communities. Stakeholder participation in formulating policies and strategies is crucial for enhancing adaptive capacity and mitigating losses (Ceddia et al., 2017 ). Policies, programs, and projects that support adaptation efforts enable communities to manage risks and adapt effectively (Thanvisitthpon et al., 2020 ). Iglesias and Grout (year) identify effective policy-making as essential for enhancing the adaptive capacity of agricultural communities against environmental risks. Adger et al. ( 2007 ) note that policy-making guides critical components of adaptation, including technology, infrastructure, and knowledge. Tran et al. ( 2020 ) highlight that rural and low-income communities faced greater challenges during the COVID-19 pandemic due to inequitable support policies. Infrastructure Infrastructure, as a key resource, includes physical assets that help individuals meet basic needs and enhance productivity (Fanadzo et al., 2021 ). Tangible assets, particularly infrastructure, significantly influence adaptive capacity, often outweighing psychological factors (Chetri et al., 2021 ). Mortreux and Barnett ( 2017 ) view infrastructure as physical capital in adaptive capacity. Countries with weak infrastructure are highly vulnerable due to limited adaptive capacity (Biesbroek and Wals, 2017 ). For example, a study of the Ebola outbreak in Liberia highlighted how poor infrastructure reduced community resilience and adaptive capacity (source needed). Similarly, the Canadian National Advisory Committee ( 2003 ) noted that robust public health infrastructure is critical for managing epidemics like SARS (NAC, 2003). Tran et al. ( 2020 ) found that robust infrastructure supported local adaptive capacity during the COVID-19 pandemic. Perception Perception, shaped by policies and information, is a critical component of adaptive capacity (Quiroga et al., 2015 ). Farmers’ adaptive behavior is influenced by their perceptions of risk factors, particularly at the local level (Quiroga et al., 2015 ; Witinok-Huber & Radil, 2021 ). Perceptions often rely on intuitive, subconscious processing of information rather than logic or probability (Grunblatt and Alessa, 2017 ). Factors such as awareness and information shape these perceptions, contributing to adaptive capacity (Sudarmadi et al., 2001 ; Sherly et al., 2019 ; Tam et al., 2021 ). Providing knowledge to stakeholders enhances awareness and understanding of changing conditions, clarifying implications for diverse interests (Clarvis and Engle, 2015). For example, during the SARS pandemic, the Canadian National Advisory Committee ( 2003 ) emphasized factors that shaped public risk perception (NAC, 2003). Similarly, Tam et al. ( 2021 ) underscored the role of risk perception in driving adaptive behaviors during COVID-19 outbreaks. Materials and Methods This study employed a deductive qualitative design to examine how Iranian farmers’ adaptive behaviors aligned with the adaptive Capacity Framework during the COVID-19 pandemic. The findings aim to provide a conceptual foundation for future research on shocks and disruptions in agricultural societies. Study Design This study employed a theory-driven qualitative design with a deductive orientation, in which the adaptive capacity framework served as a predefined analytical model. The framework comprised six components: Resources, Information, Governance, Policy-Making, Infrastructure, and Perception. Using this deductive approach, the interview data were systematically coded and interpreted in relation to these six components, allowing us to assess farmers’ and livestock keepers’ adaptive capacity during the COVID-19 pandemic. This design ensured analytical consistency while also capturing contextual insights from rural communities in Khuzestan, Iran, a region characterized by complex socio-economic and environmental challenges. Study Area Southwest Iran's Khuzestan province served as the study's location (see Fig. 2 , Map of Study Area). With a total area of roughly 62,800 km 2 , Khuzestan Province is one of the primary agricultural centers of the nation. With major rivers like the Karun, Dez, Karkheh, Jarrahi, and Zohreh, which collectively supply almost one-third of Iran's surface water resources, this province serves as the foundation for the nation's irrigated agriculture (Ardebili and Khademalrasoul, 2018 ; Chaharmahali et al., 2022 ). About 10% of Iran's harvested croplands (1.22 million hectares) and 18% of its total crop production (16.7 million tons) come from Khuzestan, which is also the only producer of sugarcane in Iran (Savari et al. 2021 ). The province also contributes significantly to the production of rice, dates, wheat, and maize (Moradi-Majd et al., 2022 ). The climate in Khuzestan is mainly arid to semi-arid with less than 250 mm of precipitation per year and average annual temperatures of around 30 degrees Celsius, above the national average (Nejad et al., 2025 ). The main climate challenges are high evapotranspiration, recurrent droughts, and frequent heat waves (Salari et al., 2023 ). Despite its water-rich rivers, Khuzestan is increasingly vulnerable to water scarcity due to water transfers between basins, inefficient irrigation systems, and soil salinity (Mao et al., 2025 ). These pressures have led to frequent farmer protests, reflecting the precarious situation of agricultural livelihoods and national food security (Salari et al., 2023 ). The farming systems in Khuzestan are mainly smallholder and pastoral, with rice farming in the northern districts exceeding 3,000 hectares per year, making the province the third-largest rice-producing province in Iran (Moradi-Majd et al., 2022 ). Khuzestan has also historically been a major producer of wheat and continues to rank among the top producers of this strategic crop, along with maize and date production, which are important to rural livelihoods (Dehghanpir et al., 2025 ). These systems are particularly vulnerable to multiple stressors, including drought, floods, salinity, dust storms, and social crises. Khuzestan was one of the most hard-hit provinces during the COVID-19 pandemic, as high rural and agricultural population density, reliance on local labor markets, and limited access to health services made farmers and pastoralists particularly vulnerable to the impacts of COVID-19 on livelihoods, which were compounded by market closures, rising input costs, and mobility restrictions, along with the existing water and climate stresses (Savari et al., 2021 ). This is an example of the paradox of Iran's agricultural governance, where policies of national self-sufficiency have encouraged the production of water-intensive crops such as sugarcane in this arid region, but adaptive infrastructure and crisis management have been weak (Madani et al., 2016 ). Participant Sampling In the difficult socioeconomic environment of Khuzestan, the study focused on 57 participants, including 38 crop farmers and 19 livestock producers. Purposive sampling was used to choose people who had firsthand knowledge of how COVID-19 affected livestock and farming operations. Direct experience was defined in this study as (i) directly overseeing farming or livestock production during the pandemic; (ii) experiencing disruptions in labor, markets, input supply, extension, and veterinary services; and/or (iii) putting adaptive strategies into practice, such as changing cropping patterns, herd management, or depending on unofficial networks for support. Using this definition, the sampling process was designed to capture those who had first-hand experience with the impact of COVID-19 on their livelihoods, which was the case for purposively selected farmers and livestock keepers. This approach aligns with the goals of qualitative research to capture multiple perspectives and those that are based on experiences (Biernacki & Waldorf, 1981 ; Mishra et al., 2021 ). Data Collection Data were collected from spring to summer 2021, during the fourth and fifth waves of COVID-19 in Iran, when the pandemic continued to significantly impact agricultural activities in Khuzestan, using multiple methods of data collection to capture the adaptive capacity of the purposively selected participants: direct observation, semi-structured interviews, field notes, and evidence recording (see Table 1 ). Direct observations were made based on repeated field visits over several weeks, allowing the researchers to observe how farmers and livestock keepers adapted to pandemic-related disruptions. Semi-structured interviews with open-ended questions provided rich insights into farmers' perceptions, emotions, and adaptive strategies (see Table 1 , Interview Questions). Field notes and evidence recording complemented these methods by documenting contextual details and tangible observations. Data Analysis Using deductive content analysis, which is appropriate for theory-guided research, data from observations, field notes, interviews, and evidence recordings were examined (Elo and Kyngäs, 2008 ; Rouzaneh and Savari, 2024 ). Although the main source for coding and interpretation was interview transcripts, additional data sources, including field notes, direct observations, and evidence recordings, were methodically included to support and contextualize the interview results. Using the adaptive Capacity Framework as the conceptual framework, the study team created a structured coding scheme for interview transcripts and related materials, including meaning units that were coded into categories aligned with the six framework components (Resources, Information, Governance, Policy-Making, Infrastructure, and Perception), with the goal of aligning data with the framework, capturing both anticipated and emergent patterns, and using NVivo software to manage the data, systematically code, retrieve themes across participants, visualize the data, and compare patterns between crop and livestock farmers, thus increasing analytic rigor and transparency. This structured yet flexible approach ensured that each component’s influence on farmers’ adaptive strategies during the COVID-19 pandemic was analyzed in a conceptually grounded and contextually relevant manner, while the use of multiple data sources enhanced the validity of the findings. Table 1 Semi-Structured Interview Guide about adaptation capacity and adaptation Behavior components List of Questions Access to resources Did you personally face any changes in food availability and food prices since the outbreak of COVID-19? Information and Knowledge How have prices for your products changed between the outbreak of COVID-19 and today? Thinking about social distancing and communication constraints, how do you get information relevant to your farm activities (including input purchases, consulting, and market information, etc.) since the outbreak of COVID-19? (e.g., face-to-face personal network, social media, internet, mobile phone messages, TV, newspaper) Perceptions effects From your perspective, who benefits and who loses from the COVID-19 outbreak? Please explain. Policies Specifically for government support, what public policies and government subsidies could be created or improved to support farmers in handling the pandemic? Governance Which actors, rules, and regulations impact your decision–making in times of COVID-19? Services and Infrastructure What services and support would you wish to have in place to facilitate adaptation to COVID-19? And how should they be implemented? Ethics statement All methods were carried out in accordance with relevant guidelines and regulations. The study protocol was reviewed and approved by the Institutional Review Board (IRB) of the Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran. All interviewees were informed about data protection and study objectives, and oral informed consent was obtained from all participants prior to data collection. All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Results In this study, using the adaptive capacity model, the adaptive behaviors of two groups of agricultural operators (farmers and pastoralists) in the face of the shock caused by the COVID-19 pandemic were analyzed and compared (Fig. 2 ) . Data obtained from 57 qualitative interviews were categorized and analyzed in six main components of the model: access to resources, information and knowledge, policymaking, governance, infrastructure, and understanding of impacts. 1. Knowledge and Information Farmers Farmers’ awareness of the economic consequences of the COVID-19 pandemic strongly influenced their adaptive behaviors. They observed sharp declines in the selling prices of certain crops due to mobility restrictions, reduced consumer demand, and increased transportation costs. This awareness not only informed immediate reactions but also triggered deliberate strategic decisions to minimize losses and secure income. For example, several farmers transformed low-value raw materials into higher-value products or modified cropping patterns to capture better market opportunities. This pattern indicates that economic knowledge acted as a driver for adaptive strategies, particularly in terms of value addition, diversification, and market-oriented adjustments. The choice to innovate within production chains also reflects farmers’ reasoning that long-term income stability requires both resourcefulness and responsiveness to market signals. "We kept calling other farmers and asking, 'How are you managing your fields these days?' Little by little, we learned new tricks to keep the work going even with all the restrictions." Livestock farmers Among livestock keepers, economic knowledge similarly shaped adaptive behaviors, but the strategies differed due to the nature of livestock production. Awareness of falling prices and reduced sales opportunities led some to temporarily suspend operations, while others reallocated labor from hired workers to family members or sold part of their herd to mitigate losses. These responses reveal a multidimensional adaptation process. Shifting to family labor represents a social adjustment, reducing herd size is an economic decision, and altering daily production routines demonstrates technical adjustment. Compared to crop farmers, livestock keepers prioritized minimizing immediate losses over pursuing innovation, illustrating how context-specific constraints influence adaptive strategies. "Because of falling prices and fewer buyers, we had to rely more on family members for feeding and care, and in some cases, we sold a few animals to make ends meet." Comparative Insight Both groups adjusted behaviors based on economic knowledge, but the pathways differed: farmers leveraged knowledge to innovate and explore new opportunities, whereas livestock keepers focused on downscaling and reallocating existing resources. This contrast highlights how the type of production, available resources, and risk perception collectively shape the adaptive capacity of rural actors. Across both groups, access to timely and relevant economic information was a key enabler of strategic decision-making and short-term adaptation during the pandemic. 2. Resources Access Farmers During the COVID-19 pandemic, farmers faced substantial constraints on productive assets and essential resources, which directly shaped adaptive behaviors. Limited financial reserves, agricultural equipment, and institutional support forced farmers to rely heavily on family labor and small-scale, low-input production strategies. The absence of savings, insurance, or external safety nets heightened vulnerability and required careful prioritization of resource allocation. Farmers made strategic trade-offs between maintaining staple crops versus high-value crops, or between irrigation and conserving inputs for future seasons. These decisions reflect adaptive planning: rather than halting production, farmers optimized available resources, experimented with low-input or value-added strategies, and adjusted market-oriented practices to reduce losses and maintain income security. "Since the beginning of this virus outbreak, access to food has become more difficult because, on the one hand, it became difficult to go out, people entered the market very carefully and followed health protocols for shopping, and on the other hand, the costs of commuting by taxi for the purchase had doubled. We were also facing an increase in the price of food because we had to buy when we went out for shopping, and the shopkeepers had hidden some goods and doubled the price of their..." Livestock Keepers For livestock keepers, resource constraints were closely linked to feed availability, veterinary services, and access to live animal markets. The pandemic caused acute feed shortages, price inflation, and service interruptions, exposing production systems to immediate shocks. Without effective insurance or emergency support, livestock keepers had to implement rapid and multifaceted adaptive strategies. These strategies included reallocating labor from hired workers to family members, selling part of the herd to cover operational costs, and adjusting feeding and herd management routines to conserve scarce resources. Social and economic dimensions were intertwined: using family labor strengthened household cohesion while reducing dependence on external inputs, and downsizing herds minimized financial exposure to fluctuating markets. " All our assets are animals. In this situation, when prices fall and the price of animal feed rises, we have nothing to rely on. They are not buying our milk and dairy products due to quarantine restrictions and fear of disease transmission, and we don't know what to do with our daily production ." Comparative Insight Both farmers and livestock keepers experienced heightened vulnerability due to limited access to productive assets and essential household resources. However, farmers primarily confronted broader financial and market constraints, adapting through labor reallocation and low-input innovation, while livestock keepers faced acute disruptions in feed, veterinary services, and market access, leading to rapid adjustments in herd management and labor allocation. In both cases, access to resources functioned as a background stressor, framing the conditions under which adaptive behaviors emerged. The differential responses underscore how resource constraints interact with production type, household structure, and market dependencies to influence the nature, timing, and complexity of adaptive strategies. These findings highlight that while limited resources constrain options, they also actively shape the strategic pathways that farmers and livestock keepers adopt under crisis conditions. 3. Governance Farmers Governance, encompassing formal and informal institutions, regulations, policies, and actors that shape decision-making, played a pivotal role in determining farmers’ adaptive responses during the COVID-19 pandemic. Formal governance structures included national crisis management bodies such as the National Corona Headquarters, the Ministry of Health, and other government agencies responsible for implementing public health measures. Informal governance influences emerged from local leaders, cooperatives, and community networks, shaping farmers’ practical options in the field. The most impactful governance interventions were top-down regulations including curfews, market closures, and strict health protocols. While aimed at public safety, these measures disrupted agricultural operations by restricting market access, delaying input deliveries, and constraining labor availability. Farmers responded by strategically adjusting production and marketing behaviors: some developed alternative marketing channels, engaged in value addition through processing, or redistributed labor within the household to maintain farm productivity. Unfortunately, local authorities are not doing anything useful during these closures and restrictions. The governor and district administrations must find a solution for local businesses.. . These responses reflect a combination of reactive adaptation—responding to immediate regulatory shocks—and proactive adaptation, such as experimenting with new product chains or market-oriented solutions. The data reveal that farmers’ adaptive strategies were strongly shaped by the interplay between governance limitations and local problem-solving capacities. Livestock farmers Livestock producers experienced governance influences both through formal institutions—Veterinary Departments, Agricultural Departments, and Ministries of Health—and informal community actors such as family members and local influencers. Governance mechanisms affected multiple behavioral dimensions, including market participation, labor allocation (e.g., shifting from hired to family labor), herd management, and temporary withdrawal from livestock activities. Critical disruptions, such as veterinary clinic closures due to guild shutdowns or delayed institutional support, led to tangible negative outcomes, including increased livestock mortality and reduced herd productivity. Livestock keepers implemented adaptive strategies such as labor reallocation, herd downsizing, sharing veterinary knowledge within informal networks, and temporary suspension of certain production activities to cope with the governance-induced constraints. Due to the closure of guilds during the coronavirus restrictions, we have faced the closure of veterinary offices; hence, we have had animal deaths due to the lack of access to veterinary services during the epidemic . These behaviors highlight the multidimensional impact of governance: regulatory gaps or rigid top-down measures directly affected operational capacity, while informal networks mitigated some consequences, demonstrating the interaction between formal and informal governance structures in shaping adaptation. Comparative Insight Both farmers and livestock keepers were highly affected by governance-related constraints, but the nature of the impacts differed. Crop farmers primarily navigated market and input disruptions, fostering innovation in marketing and value addition. Livestock farmers confronted more acute service and health-related gaps, which forced them toward labor reduction, herd downsizing, or partial exit strategies. Overall, the findings underscore that governance failures—characterized by delayed, non-sector-specific, or top-down interventions—significantly limited the resilience of small-scale agricultural producers. Adaptive behaviors emerged not only as responses to environmental and economic stressors but were also mediated by the structural and functional effectiveness of governance institutions. 4. Policies Farmers The Policies component examines the role of formal public policies, government support mechanisms, and subsidy systems in shaping adaptive responses during the COVID-19 pandemic. The analysis revealed a substantial lack of targeted policy support for the agricultural sector, despite its pivotal role in national food security. Farmers consistently reported gaps in structured aid programs, demonstrating a policy vacuum that left them vulnerable during crisis conditions. Official assessments corroborate these shortcomings. For example, a report by the Iranian Parliament Research Center (IPRC) highlighted that while the government considered measures such as expanding agricultural insurance, providing direct subsidies, stimulating domestic consumption, and implementing food reserve policies, these initiatives were either delayed or insufficiently implemented (Iranian Parliament Research Center, 2020 ). Consequently, farmers faced a disconnect between announced measures and practical realities, requiring them to independently adopt technical and economic strategies to mitigate losses. From interviews, farmers articulated two main domains of priority policy support: Technical support: guaranteed purchase of agricultural products, subsidized inputs, access to agricultural insurance, and provision of veterinary and plant health services. Financial and economic support: concessional loans, grants, extension of credit repayments, and market price regulation. Additionally, social protection measures—such as health coverage, social security, and supplementary insurance schemes tailored to occupational risks—were emphasized as critical. " I propose that the government should first extend all facilities in the agricultural sector for at least one year, and provide agricultural insurance free of charge or with a discount. Also, the government should directly buy products from farmers... and control the prices so they don’t increase for no reason ." Livestock farmers Livestock producers reported similar gaps in policy support, but with a distinct focus reflecting their sector-specific challenges. Pastoralists faced feed shortages, market instability, and interruptions in veterinary services, yet no comprehensive policy mechanism addressed these vulnerabilities. Livestock farmers’ priorities included: Economic and financial support: deferrals on debt repayment, direct subsidies, and regulation of feed prices. Technical and veterinary support: affordable access to feed and medicines, regular veterinary visits, and effective disease control programs. Market interventions: government-facilitated purchasing systems for livestock products to stabilize prices and ensure market access. "The government can give us time to repay the loans... even though the price of meat has become more expensive, our livestock is not bought and is sold at a very low price. The country’s livestock affairs support company can buy heavy livestock from us and release it to the market at the right time." Comparative Insight Both farmers and livestock keepers experienced a pronounced policy gap during the pandemic, reflecting structural weaknesses in agricultural governance. Crop farmers were primarily concerned with input access, price regulation, and income security, while livestock producers emphasized service delivery, veterinary support, and market guarantees. The absence of proactive, context-sensitive policies significantly constrained adaptive capacity in both groups. These findings underscore that adaptive responses were not merely technical or behavioral; they were deeply mediated by the availability, timing, and effectiveness of policy interventions. Differences in sector-specific vulnerabilities shaped divergent priorities, revealing how nuanced policy design is essential for supporting resilient agricultural systems. 5. Infrastructure Farmers This component reflects the availability and adequacy of economic, agricultural, and health-related services and infrastructure during the COVID-19 crisis. Farmers faced significant challenges due to the limited availability and quality of essential services, particularly in rural areas. The absence of adequate financial services, market infrastructure, and healthcare access forced many to rely on personal resources and informal networks to maintain production and livelihoods. The study identified three priority areas of infrastructure needs: Economic : Access to financial credit and direct government purchases of produce. Agricultural : Continued provision of inputs and extension services. Health : Access to preventive health supplies and rural medical support. Government-imposed restrictions such as market closures, office shutdowns, and traffic bans disrupted supply chains and access to services. As a result, many farmers called for non-face-to-face administrative services, distribution of hygiene supplies, and targeted financial support to reduce economic pressure. In my opinion, in this situation, the government should provide hygiene items such as masks and alcohol through rural health centers, and provide financial assistance to the disadvantaged and weak... so as to avoid unnecessary travel to the city and at the same time, the work does not fall behind . Livestock farmers For livestock producers, the weaknesses in infrastructure similarly spanned three domains: Economic : Lack of stable access to inputs and credit. Agricultural : Shortages of feed, veterinary services, and reliable distribution channels. Health : Insufficient health facilities and supplies in rural areas. These deficiencies forced livestock keepers to adopt adaptive mechanisms such as reducing herd size, minimizing external labor, or even withdrawing from production. The need for coordinated delivery of essential inputs, accessible credit schemes, and local veterinary services emerged as critical to sustaining their operations. The government should provide health items to the villagers through health centers, provide financial assistance to the disadvantaged and vulnerable, make going to and from the offices non-face-to-face by phone and online to avoid unnecessary travel to the city . Comparative Insight Both groups experienced structural service gaps that undermined adaptive responses. Farmers emphasized access to markets and credit, while livestock keepers were more affected by supply-chain breakdowns and health service deficits. Across both, the lack of decentralized, accessible, and responsive infrastructure significantly limited their resilience during the pandemic. Synthesis of Adaptive Behaviors The six components, Information and Knowledge, Perceptions of Effects, Policies, Governance, Services and Infrastructure, collectively shaped the adaptive behaviors of farmers and livestock keepers during the COVID-19 shock. The observed adaptive responses can be classified into three major domains: 1. Economic Adaptive Behaviors Farmers : Processing raw products (e.g., horticultural goods), seeking alternative markets, and reducing costs by cutting inputs or labor. Livestock Keepers : Selling part or all of livestock herds, reducing operational expenses, and substituting hired labor with family labor. 2. Technical and Operational Adaptations Farmers : Modifying production cycles, changing crop patterns, storing products to wait for better prices. Livestock Keepers : Shifting grazing times, rotating pastures more intensively, and changing livestock diets. 3. Institutional and Social Strategies Farmers : Demanding government intervention (e.g., subsidies, direct purchase), avoiding travel to urban centers, using informal networks. Livestock Keepers : Engaging with local governance structures, calling for decentralized veterinary services, relying on social capital. 6. Perceptions Farmers Farmers’ perceptions of the COVID-19 pandemic shaped not only their understanding of immediate disruptions but also their anticipatory reasoning about potential future impacts. Key perceived disruptions included labor shortages coupled with rising wages, sharp declines in crop prices, income reductions, restricted access to markets, higher transportation costs, postharvest losses, and breakdowns in cooperative support networks. These perceptions triggered adaptive strategies that were both reactive and proactive. For example, farmers transformed raw crops into value-added products to secure income, explored alternative sales channels such as local cooperatives or online platforms, and reorganized work schedules to optimize limited labor. The decisions were informed by an integrated understanding of market dynamics, labor availability, and institutional responsiveness. This demonstrates that farmers’ adaptive behaviors were guided by a multi-dimensional awareness, which combined immediate problem-solving with anticipation of systemic disruptions. " The outbreak of COVID-19 has led to the imposition of restrictions, and this has increased the cost of our agricultural activities. Therefore, this problem has had a negative impact on farmers' income and has put farmers' livelihoods in danger." Livestock farmers Livestock keepers’ perceptions extended deeply into operational, economic, and ecological dimensions. Participants reported critical challenges such as closure of livestock markets, rising feed prices, mortality risks from disease, and limited access to veterinary and animal health services. These pressures created both short-term shocks and long-term uncertainties, which forced livestock farmers to reconsider herd size, grazing practices, and labor allocation. Adaptive responses were multidimensional: reallocating tasks from hired labor to family members, implementing small-scale automation for feeding and milking, processing livestock products to extend shelf life, and adjusting grazing rotations to balance nutrition and feed cost constraints. Notably, some interventions carried ecological trade-offs: for example, extending pasture grazing times to offset feed shortages risked long-term pasture degradation, highlighting the tension between immediate economic survival and sustainable resource management. " Due to the increase in feed prices during the corona epidemic, I have had to rotate the sheep for 2 more hours in the pastures to compensate for nutrition, which has weakened the capacity of the pastures ." Comparative Insight While both groups perceived multi-layered pandemic impacts, the nature and focus of their adaptations differed substantially. Farmers prioritized product handling, market innovation, and value addition as a response to market disruptions, whereas livestock keepers focused on herd management, labor reallocation, and operational sustainability under resource constraints. Across both groups, perception acted as a central driver: it not only informed immediate behavioral choices but also shaped strategic anticipations for managing risk under uncertainty. These findings underscore the critical role of perceived systemic pressures in guiding adaptive behaviors in agricultural and pastoral systems during crises. "The analysis highlights how the six dimensions of adaptive capacity—knowledge and information, access to resources, governance, policies, infrastructure, and perceptions—collectively shaped farmers’ and livestock keepers’ responses to the COVID-19 pandemic. Rather than focusing on the specific adaptive actions, the findings emphasize the underlying conditions, constraints, and enabling factors that influenced the emergence of adaptive strategies. In this way, the study underscores that the observed behaviors are manifestations of broader adaptive capacities, demonstrating how different vulnerabilities, institutional access, and production systems guided decision-making and strategy development under crisis conditions (Fig. 3 )." Discussion This study set out to analyze how smallholder farmers and livestock keepers in southern Iran adapted to the systemic disruptions caused by the COVID-19 pandemic, using a six-dimensional adaptive capacity framework. By applying this framework, rather than developing a new one, the study provides empirical insights into how adaptive capacity is enacted under crisis conditions and how resilience is shaped at the local scale. The findings demonstrate that adaptive capacity is not a static attribute but a dynamic process shaped by both structural constraints and lived experiences. Farmers and livestock keepers drew on local knowledge, informal networks, and experimental practices when formal institutions and governance structures failed to provide timely support. These adaptive behaviors—such as diversifying products, reallocating labor, modifying grazing practices, and exploring alternative markets—represent concrete manifestations of adaptive capacity. At the same time, they reveal the limits of resilience when adaptive actions are improvised under conditions of weak infrastructure and policy support, often leading to short-term coping at the expense of long-term sustainability. The distinction between adaptive capacity and adaptive behaviors is central to interpreting the results. While adaptive capacity refers to the enabling conditions captured through six dimensions (resources, information and knowledge, governance, policies, infrastructure, and perceptions), adaptive behaviors are the observable responses that emerge when those capacities are activated under stress. This study shows how weaknesses in systemic dimensions—such as inadequate rural infrastructure, centralized governance, and fragmented policies—restricted the scope of adaptive behaviors and sometimes generated maladaptive outcomes. Conversely, where information, social capital, and local organization were relatively strong, adaptive responses were more effective and resilient. In relation to resilience, our results suggest that local resilience cannot be achieved through individual coping alone but requires institutional and structural reinforcement. COVID-19 exposed the fragility of agricultural livelihoods in Khuzestan: short-term adaptive actions helped households survive, but without systemic support they risk undermining future adaptive capacity. Thus, resilience emerges not merely from household-level improvisation but from the interaction between local strategies and enabling governance and policy frameworks. The contribution of this study lies in empirically demonstrating how an established adaptive capacity framework can be applied to illuminate both the enabling and constraining factors of adaptation at the local level. By systematically analyzing the six dimensions, the study enriches existing frameworks in three ways: (1) it highlights the interplay between structural vulnerabilities and locally driven responses; (2) it shows how adaptive behaviors reflect both the presence and absence of enabling conditions; and (3) it underscores the role of social capital and informal mechanisms as critical, yet often overlooked, determinants of resilience. These insights contribute to advancing adaptation governance debates by bridging theoretical models with the lived realities of farmers and livestock keepers during a global crisis. Conclusion The COVID-19 pandemic exposed significant vulnerabilities in the agricultural sector of southern Iran, particularly among smallholder farmers and livestock keepers. The crisis disrupted production, marketing, labor, and access to critical services, while institutional responses remained fragmented, delayed, or inaccessible. In the absence of sufficient state support, producers relied on individual initiative and informal networks to cope with the shock. These adaptive behaviors, ranging from converting products and finding alternative markets to rotating grazing patterns and automating tasks, reflect both resilience and the limitations of operating in a system lacking structural preparedness. A key insight from this study is that resilience in agriculture during crises cannot be improvised at the moment of impact. It must be built proactively through a foundation of inclusive policies, decentralized governance, and adaptive infrastructure. Policy makers should recognize that natural disasters and pandemics are not exceptional events but increasingly frequent realities. Ensuring sustainable food security in such conditions requires embedding crisis-readiness into routine agricultural planning. Future interventions must focus on strengthening local service delivery, guaranteeing market access during restrictions, improving rural digital infrastructure, and designing flexible support mechanisms, such as mobile veterinary units, emergency insurance, and adaptive credit systems, that can be rapidly deployed. Most importantly, local knowledge and adaptive practices identified during the pandemic should not be overlooked; they offer grounded strategies that, if supported appropriately, can shape a more resilient agricultural future. The experience of COVID-19 is a warning, but also a blueprint. Building resilience means recognizing farmers and herders not just as beneficiaries of aid, but as key actors in crisis management. Their lived responses offer a roadmap for designing agricultural systems that can withstand, and recover from, future shocks. Limitations - Due to the quarantine and travel restrictions, it wasn't easy to interview the respondents - Entering the space of some operations, such as industrial livestock farms, due to the establishment of health laws, it was difficult to interview the operators of these units. - Poor literature of research in the field of COVID-19 on agricultural and livestock operators Declarations Funding The authors received no specific funding for this research. Author Contribution D.R., S.R, and M.S.wrote the main manuscript text. P.L reviewed and polished the main manuscript text. A.SM. Collected data and conducted interviews. All authors reviewed the manuscript. Data Availability The datasets generated and/or analysed during the current study consist of written transcripts of semi-structured interviews. Due to ethical considerations and the need to protect participant confidentiality and privacy, these data are not publicly available. 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Deciphering the impact of COVID-19 pandemic on food security, agriculture, and livelihoods: A review of the evidence from developing countries. Curr. Res. Environ. Sustain. 2 , 100014 (2020). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8515225","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":625557975,"identity":"86bd8611-d240-4298-9cd1-f7ff31fef3f2","order_by":0,"name":"Sadegh Rahmani","email":"","orcid":"","institution":"Agricultural Sciences and Natural Resources University of Khuzestan","correspondingAuthor":false,"prefix":"","firstName":"Sadegh","middleName":"","lastName":"Rahmani","suffix":""},{"id":625557976,"identity":"6fab7472-ecbc-49d2-8040-4fcb427b5dc7","order_by":1,"name":"Davoud Rouzaneh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYDCCAzCGBDOIKSFDiha2BBDJQ4oWHgMQRVgL3wHeh495/tjl8Uv3fH51o8aCh4H98NEN+LRIHmA3NubhSS6WnHN2m3XOMaDDeNLSbuDTYnCAjU2aR4I5ccON3G3GOWxALRI8ZkRoMahP3H8j55lxzj+itSQcTtwgkcP8OLeNCC2Sh9mYDeccOJ4440aaGXNunwQPGyG/8B1vY3zw5k91Yv+M5Mefc77VyfGzHz6GVwsDM4LJJgEm8SpH1/2BFNWjYBSMglEwcgAAQCNChxPriSYAAAAASUVORK5CYII=","orcid":"","institution":"Agricultural Sciences and Natural Resources University of Khuzestan","correspondingAuthor":true,"prefix":"","firstName":"Davoud","middleName":"","lastName":"Rouzaneh","suffix":""},{"id":625557977,"identity":"b79812e2-a15b-49cc-acf8-d28b10e4a213","order_by":2,"name":"Ameneh Savari Mombeni","email":"","orcid":"","institution":"Agricultural Sciences and Natural Resources University of Khuzestan","correspondingAuthor":false,"prefix":"","firstName":"Ameneh","middleName":"Savari","lastName":"Mombeni","suffix":""},{"id":625557978,"identity":"55cc128c-1017-4106-a2c1-2c55b00afab8","order_by":3,"name":"Pouria Liravi","email":"","orcid":"","institution":"University of Derby","correspondingAuthor":false,"prefix":"","firstName":"Pouria","middleName":"","lastName":"Liravi","suffix":""}],"badges":[],"createdAt":"2026-01-04 19:53:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8515225/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8515225/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107374495,"identity":"8d4ac656-ed44-4094-ac1e-cbf51ef7d7d0","added_by":"auto","created_at":"2026-04-20 23:55:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":460857,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual framework of adaptation capacity)Based on Chapagain et al. (2025)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8515225/v1/28c9e291fe4229240708d3dc.png"},{"id":107489042,"identity":"ffeb37c6-b2a9-466e-b404-b2f18e724bf7","added_by":"auto","created_at":"2026-04-22 02:46:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":560685,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area — Khuzestan Province in southwest Iran. With its arid climate, agricultural importance, and strategic position, Khuzestan provides a suitable context for examining farmers’ adaptive behaviors during crises like COVID-19.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8515225/v1/71bcf072c727e37a13095d36.png"},{"id":107487191,"identity":"849ee7ae-1646-4bf4-82ff-084830bf64a1","added_by":"auto","created_at":"2026-04-22 02:39:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":117725,"visible":true,"origin":"","legend":"\u003cp\u003eAdaptive behaviors of farmers and pastoralists in response to the COVID-19 shock, mapped across six dimensions of the adaptive Capacity Framework. These behaviors fall into three main categories— economic, technical-operational, and institutional-social—highlighting how both reactive responses and proactive adaptations were shaped by differences in access to resources, services, and governance.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8515225/v1/abd221a00e09d899946ee7ec.png"},{"id":107961748,"identity":"4e5c948f-b7e3-4015-bd2a-96b6da8dd56a","added_by":"auto","created_at":"2026-04-28 04:40:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1587689,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8515225/v1/957a723d-7086-4471-ba27-74dbc0055c17.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"From Crisis to Capacity: What COVID-19 Teaches about Resilience in Iran’s Farming Systems","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn today\u0026rsquo;s interconnected world, sustainable agricultural systems are vital for food production and security. They also play a critical role in public health and community resilience against climatic, economic, and social shocks. From a systems thinking perspective, agriculture is part of an interconnected network whose performance influences the security and health sectors. Disruptions in this sector during crises can trigger failures across the entire system, undermining crisis management policies, even if they control the crisis\u0026rsquo;s epicenter (Akpabio et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Fanzo, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Clark et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, food systems in many parts of the world, particularly in developing countries, lack the capacity to achieve sustainability and resilience goals. Challenges such as rapid population growth, internal conflicts, natural disasters, and climate change pose serious threats to these systems. Consequently, these disruptions have hindered the core pillars of food security\u0026mdash;availability, access, utilization, stability, agency, and sustainability\u0026mdash;highlighting the urgent need for transformative changes in agricultural and food systems (Clark et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Karimi et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Akpabio et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the global shocks that have severely impacted agricultural systems in recent years are the COVID-19 pandemic and the war in Ukraine, both of which caused economic recessions, disrupted food supply chains, and exacerbated inequality, food insecurity, and social instability (Swinnen \u0026amp; Vos, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kubatko et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This study focuses on local-level adaptive capacity, analyzing how smallholder farmers and livestock keepers in Khuzestan Province responded to the COVID-19 pandemic under severe institutional and economic constraints. A challenge that was particularly severe in developing countries facing chronic climatic, institutional, and economic constraints, disrupting production, processing, trade, food stocks, and purchasing power (Workie et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In this context, smallholder farmers and pastoralists, who depend on local resources and lack adequate institutional support, were highly vulnerable. Their responses, including shifting production patterns, relying on family labor, and using indigenous tools, reflect a concept known in development literature as \u0026ldquo;adaptive capacity,\u0026rdquo; which is essential for enhancing the resilience of agricultural systems against multifaceted crises (Kubatko et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdaptive capacity, a key factor in agricultural system resilience, refers to the set of resources, knowledge, and processes that enable a system or community to adapt to changes while minimizing negative consequences (Folke et al., 2005). This capacity was evident in the active responses of farmers and local communities to the COVID-19 pandemic, which disrupted supply chains, markets, and labor mobility, necessitating flexible, locally based mechanisms (Meuwissen et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Adaptive capacity was demonstrated through actions such as extensive use of family labor, adoption of digital infrastructures, adjustments in cropping patterns, development of local or online sales, and strengthened social and institutional networks for product distribution (Schreiber et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Khan, 2022). These initiatives highlight communities\u0026rsquo; ability to adapt creatively to crises, utilize limited resources, and overcome institutional barriers\u0026mdash;core elements of this concept in academic literature (van Gameren and Zaccai, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, the realization and sustainability of such capacity depend on institutional structures, social capital, resource access, and supportive policies, which remain challenging in many developing countries (Williams et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lindner et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Despite its critical role in addressing crises like COVID-19, local-level data on adaptive capacity remain limited. While its application in climate change research has grown, its role in health crises and other shocks is underexplored. Nevertheless, it is increasingly central to policymaking for food security, resilience, and sustainable development (Cinner et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Asfaw et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile the critical role of adaptive capacity in managing crises like the COVID-19 pandemic is widely acknowledged, research on specific local-level strategies and the contextual factors that enable resilience in agrarian communities remains limited, especially in regions facing institutional constraints. This study addresses this research gap by focusing on Khuzestan Province, Iran, and providing an in-depth qualitative analysis. The primary contribution of this paper is to offer a comparative analysis of the adaptive strategies of both smallholder farmers and pastoralists, revealing key differences in their responses. Furthermore, the research highlights the vital role of social capital and informal networks in compensating for institutional shortcomings, thereby enriching our understanding of local resilience dynamics. Ultimately, this study offers concrete policy lessons for designing anticipatory policies, strengthening adaptive infrastructure, and reconfiguring governance to help rural systems better withstand and recover from future shocks.\u003c/p\u003e\n\u003ch3\u003eConceptual framework\u003c/h3\u003e\n\u003cp\u003eAdaptive capacity, often overlooked, is integral to human systems\u0026rsquo; resilience, enabling responses to natural and societal changes (Hirschfeld et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chepkoech et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Biesbroek \u0026amp; Wals, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It shapes actors\u0026rsquo; abilities to plan and execute adaptation while overcoming socio-political constraints (Biesbroek \u0026amp; Wals, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Adaptive capacity is crucial for designing and implementing measures to adapt to risks and shocks (Chepkoech et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Dapilah et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Effective adaptation and risk mitigation require developing the adaptive capacity of communities and households (Matewos, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOriginating in biology, adaptive capacity refers to an organism\u0026rsquo;s ability to survive environmental changes (de Wildt-Liesveld et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This concept later extended to other fields, notably the social sciences, where anthropologist Julian Steward introduced cultural ecology, defined as \u0026ldquo;the study of processes by which societies adapt to their environments\u0026rdquo; (Plummer and Armitage, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Since then, its role in managing vulnerability and fostering social and environmental resilience has led to systematic applications in social-ecological and human-social systems, including studies on climate change (Mahfoud et al., 2021), water management (Bergsma et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), women\u0026rsquo;s roles in agricultural adaptation (Witinok-Huber and Radil, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), flood exposure (Thanvisitthpon et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and resilience to environmental change (Brown and Westaway, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdaptive capacity has been defined variably in the literature (Jones et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The IPCC Third (2001) and Fourth (2007) Assessment Reports describe it as \u0026ldquo;the ability of systems, institutions, humans, and other organisms to adapt to potential harms, seize opportunities, and respond to consequences\u0026rdquo; (Matewos, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bhowmik et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Adger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) emphasize its role in enabling systems to respond to change through modifications in behavior, resources, and technology, particularly in agriculture. Similarly, Witinok-Huber and Radil (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) define it as the ability of farmers and agricultural communities to develop strategies using existing resources and knowledge to manage social and environmental stresses while sustaining livelihoods. adaptive capacity, the focus of this study, is a latent trait enabling individuals to anticipate, respond to, and recover from changes while minimizing their consequences (Cinner et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, it is unevenly distributed across regions and communities within a country (Mahfoud et al., 2021).\u003c/p\u003e \u003cp\u003eAccording to the Sixth Assessment Report of the IPCC, climate resilience is conceptualized as the \u0026ldquo;result of capacities,\u0026rdquo; encompassing absorptive, adaptive, and transformative capacities. Accordingly, adaptive capacity is regarded as one of the central components of resilience, and its strengthening directly enhances resilience. In the AR6 conceptual framework, vulnerability is defined as the propensity to be adversely affected, which is linked to sensitivity and the lack of adaptive capacity; thus, higher adaptive capacity reduces vulnerability and consequently increases resilience. This logic is emphasized in the conceptual chapters as well as in the discussion on Climate Resilient Development (CRD), where enabling conditions such as governance, financial resources, knowledge, and technology are highlighted as direct means of strengthening adaptive capacity and, in turn, resilience (IPCC, 2022).\u003c/p\u003e \u003cp\u003eTo support policymakers and development planners in enhancing community adaptive capacity, it is essential to analyze its influencing factors, which are embedded in societal systems and vary across time and place (Witinok-Huber and Radil, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Enhancing adaptive capacity is critical for reducing societal vulnerability to global environmental changes and building resilience, enabling communities to address a wide range of external threats (Engle, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Quinlan et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Witinok-Huber and Radil, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Freduah et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Cinner et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Studies indicate that adaptive capacity is a prerequisite for designing and implementing effective adaptation strategies (Adger et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In line with the IPCC's framework, agricultural systems\u0026rsquo; adaptive capacity and resilience depend on post-disaster measures, recovery efforts, and adaptation to COVID-19 impacts (Štreimikienė et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Policymakers face the complex task of building adaptive capacity to enhance agricultural productivity, as farmers\u0026rsquo; challenges vary by spatial and temporal factors (Witinok-Huber and Radil, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough vulnerability determinants have been widely studied, those of adaptive capacity have received less attention, likely due to their context-specific nature (Engle, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Warrick et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Because adaptive capacity varies regionally, a framework is needed to assess it and develop structural and non-structural measures to address natural disasters (Freduah et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hirschfeld et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To address this need, frameworks for assessing adaptive capacity have been proposed (Berke et al., 2015; Gupta et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). These frameworks should include components that reflect the system\u0026rsquo;s internal dynamics and its ability to adapt to new conditions (Dixon et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, no universal framework exists, as components depend on local systems and contexts, and selected determinants often fail to fully capture community conditions (Warrick et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This limitation points to the need for tailored approaches to evaluating adaptive capacity at the local level. Frameworks typically emphasize social factors like technology, infrastructure, institutions, and knowledge, but their relative importance varies by context and time (Freduah et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Two approaches to measuring adaptive capacity exist: inductive, data-driven methods, which rely on expert judgment but are criticized for oversimplification and limited spatial validity, and deductive, theory-guided methods, which map cause-and-effect relationships to identify leverage points (Bhowmik et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Matewos, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdaptive capacity varies across regions, requiring context-specific evaluation of temporal and spatial factors (Engle, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This study adopts a deductive qualitative approach, applying an existing adaptive capacity framework to interpret factors influencing resilience. Using six predefined dimensions, resources, information, governance, policies, infrastructure, and perceptions, we analyze local-level data to reveal how structural and non-structural determinants shaped farmers\u0026rsquo; and livestock keepers\u0026rsquo; adaptive responses during the COVID-19 pandemic(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eKnowledge and Information\u003c/b\u003e \u003c/p\u003e \u003cp\u003eInformation is a key component of adaptive capacity (Freduah et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mahfoud et al., 2021). Knowledge, a critical aspect of information, drives public concern about risks and motivates preventive behaviors (Reser et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Awareness, reflecting this knowledge, is a prerequisite for adaptive behaviors and adjusting to new situations (Sundblad et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Grunblatt, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mahfoud et al., 2021). Access to information empowers communities by raising awareness of specific group needs (Ospina and Heeks, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). For example, Stanturf et al. (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) highlight the role of information access in guiding government and donor investments to reduce social vulnerability to epidemics, such as Ebola, and strengthen adaptive capacity. Similarly, Tam et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that individuals with greater knowledge and awareness were more likely to adopt protective behaviors during the COVID-19 pandemic.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResources Access\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAccess to resources is a critical driver of farmers\u0026rsquo; adaptive capacity in responding to change (Witinok-Huber \u0026amp; Radil, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The ability of individuals and communities to cope with change depends heavily on access to and control over diverse livelihood assets (Jones et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Resource constraints pose significant challenges for smallholder farmers in adapting to disruptions (Fanadzo et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Rozaki (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) emphasizes that access to basic and food resources was essential during and after the COVID-19 pandemic to ensure food security and adaptive stability in rural agricultural communities. Lal (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) identifies supply chain disruptions, physical and economic barriers, and limited labor access as key reasons for resource constraints during the pandemic. Among these resources, infrastructure plays a pivotal role in enabling adaptive capacity, particularly during crises like the COVID-19 pandemic.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGovernance\u003c/h2\u003e \u003cp\u003eGovernance is a critical component of adaptive capacity, shaping individuals\u0026rsquo; and communities\u0026rsquo; ability to adapt through effective decision-making and resource management (Vincent, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Engle, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Lockwood et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Brooks et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) identify governance as the primary determinant of adaptive capacity, while Engle (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) emphasizes the influence of management and active institutions (Kruse, 2015). Despite its importance, empirical research on governance\u0026rsquo;s role in adaptation remains limited (Medema et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Governance refers to formal and informal institutional arrangements that regulate resource use in society (Rodriguez, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Effective governance and management approaches facilitate adaptations, thereby enhancing or diminishing adaptive capacity (Clarvis and Engle, 2015). Actors at various governance levels develop and implement adaptation policies, strengthening adaptive capacity (Plummer, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Participatory approaches further support sustainable management of natural, financial, and human resources during adaptation (Mahfoud et al., 2021). For example, Dutta and Fischer (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) argue that local governance was crucial during the COVID-19 pandemic for aligning policy-making with local realities to coordinate responses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePolicies\u003c/h3\u003e\n\u003cp\u003ePolicies refer to policy-making that shapes the effective use of resources like infrastructure, playing a vital role in building adaptive capacity for agricultural communities. Stakeholder participation in formulating policies and strategies is crucial for enhancing adaptive capacity and mitigating losses (Ceddia et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Policies, programs, and projects that support adaptation efforts enable communities to manage risks and adapt effectively (Thanvisitthpon et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Iglesias and Grout (year) identify effective policy-making as essential for enhancing the adaptive capacity of agricultural communities against environmental risks. Adger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) note that policy-making guides critical components of adaptation, including technology, infrastructure, and knowledge. Tran et al. (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) highlight that rural and low-income communities faced greater challenges during the COVID-19 pandemic due to inequitable support policies.\u003c/p\u003e\n\u003ch3\u003eInfrastructure\u003c/h3\u003e\n\u003cp\u003eInfrastructure, as a key resource, includes physical assets that help individuals meet basic needs and enhance productivity (Fanadzo et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Tangible assets, particularly infrastructure, significantly influence adaptive capacity, often outweighing psychological factors (Chetri et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Mortreux and Barnett (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) view infrastructure as physical capital in adaptive capacity. Countries with weak infrastructure are highly vulnerable due to limited adaptive capacity (Biesbroek and Wals, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). For example, a study of the Ebola outbreak in Liberia highlighted how poor infrastructure reduced community resilience and adaptive capacity (source needed). Similarly, the Canadian National Advisory Committee (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) noted that robust public health infrastructure is critical for managing epidemics like SARS (NAC, 2003). Tran et al. (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found that robust infrastructure supported local adaptive capacity during the COVID-19 pandemic.\u003c/p\u003e\n\u003ch3\u003ePerception\u003c/h3\u003e\n\u003cp\u003ePerception, shaped by policies and information, is a critical component of adaptive capacity (Quiroga et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Farmers\u0026rsquo; adaptive behavior is influenced by their perceptions of risk factors, particularly at the local level (Quiroga et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Witinok-Huber \u0026amp; Radil, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Perceptions often rely on intuitive, subconscious processing of information rather than logic or probability (Grunblatt and Alessa, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Factors such as awareness and information shape these perceptions, contributing to adaptive capacity (Sudarmadi et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Sherly et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tam et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Providing knowledge to stakeholders enhances awareness and understanding of changing conditions, clarifying implications for diverse interests (Clarvis and Engle, 2015). For example, during the SARS pandemic, the Canadian National Advisory Committee (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) emphasized factors that shaped public risk perception (NAC, 2003). Similarly, Tam et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) underscored the role of risk perception in driving adaptive behaviors during COVID-19 outbreaks.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis study employed a deductive qualitative design to examine how Iranian farmers\u0026rsquo; adaptive behaviors aligned with the adaptive Capacity Framework during the COVID-19 pandemic. The findings aim to provide a conceptual foundation for future research on shocks and disruptions in agricultural societies.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis study employed a theory-driven qualitative design with a deductive orientation, in which the adaptive capacity framework served as a predefined analytical model. The framework comprised six components: Resources, Information, Governance, Policy-Making, Infrastructure, and Perception. Using this deductive approach, the interview data were systematically coded and interpreted in relation to these six components, allowing us to assess farmers\u0026rsquo; and livestock keepers\u0026rsquo; adaptive capacity during the COVID-19 pandemic. This design ensured analytical consistency while also capturing contextual insights from rural communities in Khuzestan, Iran, a region characterized by complex socio-economic and environmental challenges.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Area\u003c/h3\u003e\n\u003cp\u003eSouthwest Iran's Khuzestan province served as the study's location (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Map of Study Area). With a total area of roughly 62,800 km\u003csup\u003e2\u003c/sup\u003e, Khuzestan Province is one of the primary agricultural centers of the nation. With major rivers like the Karun, Dez, Karkheh, Jarrahi, and Zohreh, which collectively supply almost one-third of Iran's surface water resources, this province serves as the foundation for the nation's irrigated agriculture (Ardebili and Khademalrasoul, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Chaharmahali et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). About 10% of Iran's harvested croplands (1.22\u0026nbsp;million hectares) and 18% of its total crop production (16.7\u0026nbsp;million tons) come from Khuzestan, which is also the only producer of sugarcane in Iran (Savari et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The province also contributes significantly to the production of rice, dates, wheat, and maize (Moradi-Majd et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe climate in Khuzestan is mainly arid to semi-arid with less than 250 mm of precipitation per year and average annual temperatures of around 30 degrees Celsius, above the national average (Nejad et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The main climate challenges are high evapotranspiration, recurrent droughts, and frequent heat waves (Salari et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite its water-rich rivers, Khuzestan is increasingly vulnerable to water scarcity due to water transfers between basins, inefficient irrigation systems, and soil salinity (Mao et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These pressures have led to frequent farmer protests, reflecting the precarious situation of agricultural livelihoods and national food security (Salari et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe farming systems in Khuzestan are mainly smallholder and pastoral, with rice farming in the northern districts exceeding 3,000 hectares per year, making the province the third-largest rice-producing province in Iran (Moradi-Majd et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Khuzestan has also historically been a major producer of wheat and continues to rank among the top producers of this strategic crop, along with maize and date production, which are important to rural livelihoods (Dehghanpir et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These systems are particularly vulnerable to multiple stressors, including drought, floods, salinity, dust storms, and social crises.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKhuzestan was one of the most hard-hit provinces during the COVID-19 pandemic, as high rural and agricultural population density, reliance on local labor markets, and limited access to health services made farmers and pastoralists particularly vulnerable to the impacts of COVID-19 on livelihoods, which were compounded by market closures, rising input costs, and mobility restrictions, along with the existing water and climate stresses (Savari et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This is an example of the paradox of Iran's agricultural governance, where policies of national self-sufficiency have encouraged the production of water-intensive crops such as sugarcane in this arid region, but adaptive infrastructure and crisis management have been weak (Madani et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eParticipant Sampling\u003c/h3\u003e\n\u003cp\u003eIn the difficult socioeconomic environment of Khuzestan, the study focused on 57 participants, including 38 crop farmers and 19 livestock producers. Purposive sampling was used to choose people who had firsthand knowledge of how COVID-19 affected livestock and farming operations. Direct experience was defined in this study as (i) directly overseeing farming or livestock production during the pandemic; (ii) experiencing disruptions in labor, markets, input supply, extension, and veterinary services; and/or (iii) putting adaptive strategies into practice, such as changing cropping patterns, herd management, or depending on unofficial networks for support.\u003c/p\u003e \u003cp\u003eUsing this definition, the sampling process was designed to capture those who had first-hand experience with the impact of COVID-19 on their livelihoods, which was the case for purposively selected farmers and livestock keepers. This approach aligns with the goals of qualitative research to capture multiple perspectives and those that are based on experiences (Biernacki \u0026amp; Waldorf, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; Mishra et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eData were collected from spring to summer 2021, during the fourth and fifth waves of COVID-19 in Iran, when the pandemic continued to significantly impact agricultural activities in Khuzestan, using multiple methods of data collection to capture the adaptive capacity of the purposively selected participants: direct observation, semi-structured interviews, field notes, and evidence recording (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Direct observations were made based on repeated field visits over several weeks, allowing the researchers to observe how farmers and livestock keepers adapted to pandemic-related disruptions. Semi-structured interviews with open-ended questions provided rich insights into farmers' perceptions, emotions, and adaptive strategies (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Interview Questions). Field notes and evidence recording complemented these methods by documenting contextual details and tangible observations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eUsing deductive content analysis, which is appropriate for theory-guided research, data from observations, field notes, interviews, and evidence recordings were examined (Elo and Kyng\u0026auml;s, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Rouzaneh and Savari, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Although the main source for coding and interpretation was interview transcripts, additional data sources, including field notes, direct observations, and evidence recordings, were methodically included to support and contextualize the interview results.\u003c/p\u003e \u003cp\u003eUsing the adaptive Capacity Framework as the conceptual framework, the study team created a structured coding scheme for interview transcripts and related materials, including meaning units that were coded into categories aligned with the six framework components (Resources, Information, Governance, Policy-Making, Infrastructure, and Perception), with the goal of aligning data with the framework, capturing both anticipated and emergent patterns, and using NVivo software to manage the data, systematically code, retrieve themes across participants, visualize the data, and compare patterns between crop and livestock farmers, thus increasing analytic rigor and transparency.\u003c/p\u003e \u003cp\u003eThis structured yet flexible approach ensured that each component\u0026rsquo;s influence on farmers\u0026rsquo; adaptive strategies during the COVID-19 pandemic was analyzed in a conceptually grounded and contextually relevant manner, while the use of multiple data sources enhanced the validity of the findings.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eSemi-Structured Interview Guide about adaptation capacity and adaptation Behavior\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecomponents\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eList of Questions\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccess to resources\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you personally face any changes in food availability and food prices since the outbreak of COVID-19?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation and Knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHow have prices for your products changed between the outbreak of COVID-19 and today?\u003c/p\u003e \u003cp\u003eThinking about social distancing and communication constraints, how do you get information relevant to your farm activities (including input purchases, consulting, and market information, etc.) since the outbreak of COVID-19? (e.g., face-to-face personal network, social media, internet, mobile phone messages, TV, newspaper)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceptions effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrom your perspective, who benefits and who loses from the COVID-19 outbreak? Please explain.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolicies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecifically for government support, what public policies and government subsidies could be created or improved to support farmers in handling the pandemic?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhich actors, rules, and regulations impact your decision\u0026ndash;making in times of COVID-19?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eServices and Infrastructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhat services and support would you wish to have in place to facilitate adaptation to COVID-19? And how should they be implemented?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEthics statement\u003c/h2\u003e \u003cp\u003eAll methods were carried out in accordance with relevant guidelines and regulations. The study protocol was reviewed and approved by the Institutional Review Board (IRB) of the Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran. All interviewees were informed about data protection and study objectives, and oral informed consent was obtained from all participants prior to data collection. All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn this study, using the adaptive capacity model, the adaptive behaviors of two groups of agricultural operators (farmers and pastoralists) in the face of the shock caused by the COVID-19 pandemic were analyzed and compared (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Data obtained from 57 qualitative interviews were categorized and analyzed in six main components of the model: access to resources, information and knowledge, policymaking, governance, infrastructure, and understanding of impacts.\u003c/p\u003e \u003cp\u003e \u003cb\u003e1. Knowledge and Information\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFarmers\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFarmers\u0026rsquo; awareness of the economic consequences of the COVID-19 pandemic strongly influenced their adaptive behaviors. They observed sharp declines in the selling prices of certain crops due to mobility restrictions, reduced consumer demand, and increased transportation costs. This awareness not only informed immediate reactions but also triggered deliberate strategic decisions to minimize losses and secure income.\u003c/p\u003e \u003cp\u003eFor example, several farmers transformed low-value raw materials into higher-value products or modified cropping patterns to capture better market opportunities. This pattern indicates that economic knowledge acted as a driver for adaptive strategies, particularly in terms of value addition, diversification, and market-oriented adjustments. The choice to innovate within production chains also reflects farmers\u0026rsquo; reasoning that long-term income stability requires both resourcefulness and responsiveness to market signals.\u003c/p\u003e \u003cp\u003e \u003cem\u003e\"We kept calling other farmers and asking, 'How are you managing your fields these days?' Little by little, we learned new tricks to keep the work going even with all the restrictions.\"\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eLivestock farmers\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAmong livestock keepers, economic knowledge similarly shaped adaptive behaviors, but the strategies differed due to the nature of livestock production. Awareness of falling prices and reduced sales opportunities led some to temporarily suspend operations, while others reallocated labor from hired workers to family members or sold part of their herd to mitigate losses.\u003c/p\u003e \u003cp\u003eThese responses reveal a multidimensional adaptation process. Shifting to family labor represents a social adjustment, reducing herd size is an economic decision, and altering daily production routines demonstrates technical adjustment. Compared to crop farmers, livestock keepers prioritized minimizing immediate losses over pursuing innovation, illustrating how context-specific constraints influence adaptive strategies.\u003c/p\u003e \u003cp\u003e \u003cem\u003e\"Because of falling prices and fewer buyers, we had to rely more on family members for feeding and care, and in some cases, we sold a few animals to make ends meet.\"\u003c/em\u003e \u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eComparative Insight\u003c/h2\u003e \u003cp\u003eBoth groups adjusted behaviors based on economic knowledge, but the pathways differed: farmers leveraged knowledge to innovate and explore new opportunities, whereas livestock keepers focused on downscaling and reallocating existing resources. This contrast highlights how the type of production, available resources, and risk perception collectively shape the adaptive capacity of rural actors. Across both groups, access to timely and relevant economic information was a key enabler of strategic decision-making and short-term adaptation during the pandemic.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2. Resources Access\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eFarmers\u003c/h2\u003e \u003cp\u003eDuring the COVID-19 pandemic, farmers faced substantial constraints on productive assets and essential resources, which directly shaped adaptive behaviors. Limited financial reserves, agricultural equipment, and institutional support forced farmers to rely heavily on family labor and small-scale, low-input production strategies. The absence of savings, insurance, or external safety nets heightened vulnerability and required careful prioritization of resource allocation.\u003c/p\u003e \u003cp\u003eFarmers made strategic trade-offs between maintaining staple crops versus high-value crops, or between irrigation and conserving inputs for future seasons. These decisions reflect adaptive planning: rather than halting production, farmers optimized available resources, experimented with low-input or value-added strategies, and adjusted market-oriented practices to reduce losses and maintain income security.\u003c/p\u003e \u003cp\u003e \u003cem\u003e\"Since the beginning of this virus outbreak, access to food has become more difficult because, on the one hand, it became difficult to go out, people entered the market very carefully and followed health protocols for shopping, and on the other hand, the costs of commuting by taxi for the purchase had doubled. We were also facing an increase in the price of food because we had to buy when we went out for shopping, and the shopkeepers had hidden some goods and doubled the price of their...\"\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eLivestock Keepers\u003c/h2\u003e \u003cp\u003eFor livestock keepers, resource constraints were closely linked to feed availability, veterinary services, and access to live animal markets. The pandemic caused acute feed shortages, price inflation, and service interruptions, exposing production systems to immediate shocks. Without effective insurance or emergency support, livestock keepers had to implement rapid and multifaceted adaptive strategies.\u003c/p\u003e \u003cp\u003eThese strategies included reallocating labor from hired workers to family members, selling part of the herd to cover operational costs, and adjusting feeding and herd management routines to conserve scarce resources. Social and economic dimensions were intertwined: using family labor strengthened household cohesion while reducing dependence on external inputs, and downsizing herds minimized financial exposure to fluctuating markets.\u003c/p\u003e \u003cp\u003e\"\u003cem\u003eAll our assets are animals. In this situation, when prices fall and the price of animal feed rises, we have nothing to rely on. They are not buying our milk and dairy products due to quarantine restrictions and fear of disease transmission, and we don't know what to do with our daily production\u003c/em\u003e.\"\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eComparative Insight\u003c/h2\u003e \u003cp\u003eBoth farmers and livestock keepers experienced heightened vulnerability due to limited access to productive assets and essential household resources. However, farmers primarily confronted broader financial and market constraints, adapting through labor reallocation and low-input innovation, while livestock keepers faced acute disruptions in feed, veterinary services, and market access, leading to rapid adjustments in herd management and labor allocation.\u003c/p\u003e \u003cp\u003eIn both cases, access to resources functioned as a background stressor, framing the conditions under which adaptive behaviors emerged. The differential responses underscore how resource constraints interact with production type, household structure, and market dependencies to influence the nature, timing, and complexity of adaptive strategies.\u003c/p\u003e \u003cp\u003eThese findings highlight that while limited resources constrain options, they also actively shape the strategic pathways that farmers and livestock keepers adopt under crisis conditions.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3. Governance\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eFarmers\u003c/h2\u003e \u003cp\u003eGovernance, encompassing formal and informal institutions, regulations, policies, and actors that shape decision-making, played a pivotal role in determining farmers\u0026rsquo; adaptive responses during the COVID-19 pandemic. Formal governance structures included national crisis management bodies such as the National Corona Headquarters, the Ministry of Health, and other government agencies responsible for implementing public health measures. Informal governance influences emerged from local leaders, cooperatives, and community networks, shaping farmers\u0026rsquo; practical options in the field.\u003c/p\u003e \u003cp\u003eThe most impactful governance interventions were top-down regulations including curfews, market closures, and strict health protocols. While aimed at public safety, these measures disrupted agricultural operations by restricting market access, delaying input deliveries, and constraining labor availability. Farmers responded by strategically adjusting production and marketing behaviors: some developed alternative marketing channels, engaged in value addition through processing, or redistributed labor within the household to maintain farm productivity.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eUnfortunately, local authorities are not doing anything useful during these closures and restrictions. The governor and district administrations must find a solution for local businesses..\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThese responses reflect a combination of reactive adaptation\u0026mdash;responding to immediate regulatory shocks\u0026mdash;and proactive adaptation, such as experimenting with new product chains or market-oriented solutions. The data reveal that farmers\u0026rsquo; adaptive strategies were strongly shaped by the interplay between governance limitations and local problem-solving capacities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLivestock farmers\u003c/h2\u003e \u003cp\u003eLivestock producers experienced governance influences both through formal institutions\u0026mdash;Veterinary Departments, Agricultural Departments, and Ministries of Health\u0026mdash;and informal community actors such as family members and local influencers. Governance mechanisms affected multiple behavioral dimensions, including market participation, labor allocation (e.g., shifting from hired to family labor), herd management, and temporary withdrawal from livestock activities.\u003c/p\u003e \u003cp\u003eCritical disruptions, such as veterinary clinic closures due to guild shutdowns or delayed institutional support, led to tangible negative outcomes, including increased livestock mortality and reduced herd productivity. Livestock keepers implemented adaptive strategies such as labor reallocation, herd downsizing, sharing veterinary knowledge within informal networks, and temporary suspension of certain production activities to cope with the governance-induced constraints.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eDue to the closure of guilds during the coronavirus restrictions, we have faced the closure of veterinary offices; hence, we have had animal deaths due to the lack of access to veterinary services during the epidemic\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThese behaviors highlight the multidimensional impact of governance: regulatory gaps or rigid top-down measures directly affected operational capacity, while informal networks mitigated some consequences, demonstrating the interaction between formal and informal governance structures in shaping adaptation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eComparative Insight\u003c/h2\u003e \u003cp\u003eBoth farmers and livestock keepers were highly affected by governance-related constraints, but the nature of the impacts differed. Crop farmers primarily navigated market and input disruptions, fostering innovation in marketing and value addition. Livestock farmers confronted more acute service and health-related gaps, which forced them toward labor reduction, herd downsizing, or partial exit strategies.\u003c/p\u003e \u003cp\u003eOverall, the findings underscore that governance failures\u0026mdash;characterized by delayed, non-sector-specific, or top-down interventions\u0026mdash;significantly limited the resilience of small-scale agricultural producers.\u003c/p\u003e \u003cp\u003eAdaptive behaviors emerged not only as responses to environmental and economic stressors but were also mediated by the structural and functional effectiveness of governance institutions.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4. Policies\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eFarmers\u003c/h2\u003e \u003cp\u003eThe Policies component examines the role of formal public policies, government support mechanisms, and subsidy systems in shaping adaptive responses during the COVID-19 pandemic. The analysis revealed a substantial lack of targeted policy support for the agricultural sector, despite its pivotal role in national food security. Farmers consistently reported gaps in structured aid programs, demonstrating a policy vacuum that left them vulnerable during crisis conditions.\u003c/p\u003e \u003cp\u003eOfficial assessments corroborate these shortcomings. For example, a report by the Iranian Parliament Research Center (IPRC) highlighted that while the government considered measures such as expanding agricultural insurance, providing direct subsidies, stimulating domestic consumption, and implementing food reserve policies, these initiatives were either delayed or insufficiently implemented (Iranian Parliament Research Center, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Consequently, farmers faced a disconnect between announced measures and practical realities, requiring them to independently adopt technical and economic strategies to mitigate losses.\u003c/p\u003e \u003cp\u003eFrom interviews, farmers articulated two main domains of priority policy support:\u003c/p\u003e \u003cp\u003eTechnical support: guaranteed purchase of agricultural products, subsidized inputs, access to agricultural insurance, and provision of veterinary and plant health services.\u003c/p\u003e \u003cp\u003eFinancial and economic support: concessional loans, grants, extension of credit repayments, and market price regulation.\u003c/p\u003e \u003cp\u003eAdditionally, social protection measures\u0026mdash;such as health coverage, social security, and supplementary insurance schemes tailored to occupational risks\u0026mdash;were emphasized as critical.\u003c/p\u003e \u003cp\u003e\"\u003cem\u003eI propose that the government should first extend all facilities in the agricultural sector for at least one year, and provide agricultural insurance free of charge or with a discount. Also, the government should directly buy products from farmers... and control the prices so they don\u0026rsquo;t increase for no reason\u003c/em\u003e.\"\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eLivestock farmers\u003c/h2\u003e \u003cp\u003eLivestock producers reported similar gaps in policy support, but with a distinct focus reflecting their sector-specific challenges. Pastoralists faced feed shortages, market instability, and interruptions in veterinary services, yet no comprehensive policy mechanism addressed these vulnerabilities.\u003c/p\u003e \u003cp\u003eLivestock farmers\u0026rsquo; priorities included:\u003c/p\u003e \u003cp\u003eEconomic and financial support: deferrals on debt repayment, direct subsidies, and regulation of feed prices.\u003c/p\u003e \u003cp\u003eTechnical and veterinary support: affordable access to feed and medicines, regular veterinary visits, and effective disease control programs.\u003c/p\u003e \u003cp\u003eMarket interventions: government-facilitated purchasing systems for livestock products to stabilize prices and ensure market access.\u003c/p\u003e \u003cp\u003e\"The government can give us time to repay the loans... even though the price of meat has become more expensive, our livestock is not bought and is sold at a very low price. The country\u0026rsquo;s livestock affairs support company can buy heavy livestock from us and release it to the market at the right time.\"\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eComparative Insight\u003c/h2\u003e \u003cp\u003eBoth farmers and livestock keepers experienced a pronounced policy gap during the pandemic, reflecting structural weaknesses in agricultural governance. Crop farmers were primarily concerned with input access, price regulation, and income security, while livestock producers emphasized service delivery, veterinary support, and market guarantees. The absence of proactive, context-sensitive policies significantly constrained adaptive capacity in both groups.\u003c/p\u003e \u003cp\u003eThese findings underscore that adaptive responses were not merely technical or behavioral; they were deeply mediated by the availability, timing, and effectiveness of policy interventions. Differences in sector-specific vulnerabilities shaped divergent priorities, revealing how nuanced policy design is essential for supporting resilient agricultural systems.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5. Infrastructure\u003c/b\u003e \u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eFarmers\u003c/h2\u003e \u003cp\u003eThis component reflects the availability and adequacy of economic, agricultural, and health-related services and infrastructure during the COVID-19 crisis. Farmers faced significant challenges due to the limited availability and quality of essential services, particularly in rural areas. The absence of adequate financial services, market infrastructure, and healthcare access forced many to rely on personal resources and informal networks to maintain production and livelihoods.\u003c/p\u003e \u003cp\u003eThe study identified three priority areas of infrastructure needs:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eEconomic\u003c/b\u003e: Access to financial credit and direct government purchases of produce.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eAgricultural\u003c/b\u003e: Continued provision of inputs and extension services.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eHealth\u003c/b\u003e: Access to preventive health supplies and rural medical support.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eGovernment-imposed restrictions such as market closures, office shutdowns, and traffic bans disrupted supply chains and access to services. As a result, many farmers called for non-face-to-face administrative services, distribution of hygiene supplies, and targeted financial support to reduce economic pressure.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eIn my opinion, in this situation, the government should provide hygiene items such as masks and alcohol through rural health centers, and provide financial assistance to the disadvantaged and weak... so as to avoid unnecessary travel to the city and at the same time, the work does not fall behind\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eLivestock farmers\u003c/h2\u003e \u003cp\u003eFor livestock producers, the weaknesses in infrastructure similarly spanned three domains:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eEconomic\u003c/b\u003e: Lack of stable access to inputs and credit.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eAgricultural\u003c/b\u003e: Shortages of feed, veterinary services, and reliable distribution channels.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eHealth\u003c/b\u003e: Insufficient health facilities and supplies in rural areas.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThese deficiencies forced livestock keepers to adopt adaptive mechanisms such as reducing herd size, minimizing external labor, or even withdrawing from production. The need for coordinated delivery of essential inputs, accessible credit schemes, and local veterinary services emerged as critical to sustaining their operations.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eThe government should provide health items to the villagers through health centers, provide financial assistance to the disadvantaged and vulnerable, make going to and from the offices non-face-to-face by phone and online to avoid unnecessary travel to the city\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eComparative Insight\u003c/h2\u003e \u003cp\u003eBoth groups experienced structural service gaps that undermined adaptive responses. Farmers emphasized access to markets and credit, while livestock keepers were more affected by supply-chain breakdowns and health service deficits. Across both, the lack of decentralized, accessible, and responsive infrastructure significantly limited their resilience during the pandemic.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis of Adaptive Behaviors\u003c/h2\u003e \u003cp\u003eThe six components, Information and Knowledge, Perceptions of Effects, Policies, Governance, Services and Infrastructure, collectively shaped the adaptive behaviors of farmers and livestock keepers during the COVID-19 shock. The observed adaptive responses can be classified into three major domains:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e1. Economic Adaptive Behaviors\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFarmers\u003c/b\u003e: Processing raw products (e.g., horticultural goods), seeking alternative markets, and reducing costs by cutting inputs or labor.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eLivestock Keepers\u003c/b\u003e: Selling part or all of livestock herds, reducing operational expenses, and substituting hired labor with family labor.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e2. Technical and Operational Adaptations\u003c/h3\u003e\n\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFarmers\u003c/b\u003e: Modifying production cycles, changing crop patterns, storing products to wait for better prices.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eLivestock Keepers\u003c/b\u003e: Shifting grazing times, rotating pastures more intensively, and changing livestock diets.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e3. Institutional and Social Strategies\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFarmers\u003c/b\u003e: Demanding government intervention (e.g., subsidies, direct purchase), avoiding travel to urban centers, using informal networks.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eLivestock Keepers\u003c/b\u003e: Engaging with local governance structures, calling for decentralized veterinary services, relying on social capital.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e6. Perceptions\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eFarmers\u003c/h2\u003e \u003cp\u003eFarmers\u0026rsquo; perceptions of the COVID-19 pandemic shaped not only their understanding of immediate disruptions but also their anticipatory reasoning about potential future impacts. Key perceived disruptions included labor shortages coupled with rising wages, sharp declines in crop prices, income reductions, restricted access to markets, higher transportation costs, postharvest losses, and breakdowns in cooperative support networks.\u003c/p\u003e \u003cp\u003eThese perceptions triggered adaptive strategies that were both reactive and proactive. For example, farmers transformed raw crops into value-added products to secure income, explored alternative sales channels such as local cooperatives or online platforms, and reorganized work schedules to optimize limited labor. The decisions were informed by an integrated understanding of market dynamics, labor availability, and institutional responsiveness. This demonstrates that farmers\u0026rsquo; adaptive behaviors were guided by a multi-dimensional awareness, which combined immediate problem-solving with anticipation of systemic disruptions.\u003c/p\u003e \u003cp\u003e\"\u003cem\u003eThe outbreak of COVID-19 has led to the imposition of restrictions, and this has increased the cost of our agricultural activities. Therefore, this problem has had a negative impact on farmers' income and has put farmers' livelihoods in danger.\"\u003c/em\u003e\u003c/p\u003e \u003cdiv id=\"Sec33\" class=\"Section3\"\u003e \u003ch2\u003eLivestock farmers\u003c/h2\u003e \u003cp\u003eLivestock keepers\u0026rsquo; perceptions extended deeply into operational, economic, and ecological dimensions. Participants reported critical challenges such as closure of livestock markets, rising feed prices, mortality risks from disease, and limited access to veterinary and animal health services. These pressures created both short-term shocks and long-term uncertainties, which forced livestock farmers to reconsider herd size, grazing practices, and labor allocation.\u003c/p\u003e \u003cp\u003eAdaptive responses were multidimensional: reallocating tasks from hired labor to family members, implementing small-scale automation for feeding and milking, processing livestock products to extend shelf life, and adjusting grazing rotations to balance nutrition and feed cost constraints. Notably, some interventions carried ecological trade-offs: for example, extending pasture grazing times to offset feed shortages risked long-term pasture degradation, highlighting the tension between immediate economic survival and sustainable resource management.\u003c/p\u003e \u003cp\u003e\"\u003cem\u003eDue to the increase in feed prices during the corona epidemic, I have had to rotate the sheep for 2 more hours in the pastures to compensate for nutrition, which has weakened the capacity of the pastures\u003c/em\u003e.\"\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e \u003ch2\u003eComparative Insight\u003c/h2\u003e \u003cp\u003eWhile both groups perceived multi-layered pandemic impacts, the nature and focus of their adaptations differed substantially. Farmers prioritized product handling, market innovation, and value addition as a response to market disruptions, whereas livestock keepers focused on herd management, labor reallocation, and operational sustainability under resource constraints. Across both groups, perception acted as a central driver: it not only informed immediate behavioral choices but also shaped strategic anticipations for managing risk under uncertainty. These findings underscore the critical role of perceived systemic pressures in guiding adaptive behaviors in agricultural and pastoral systems during crises.\u003c/p\u003e \u003cp\u003e\"The analysis highlights how the six dimensions of adaptive capacity\u0026mdash;knowledge and information, access to resources, governance, policies, infrastructure, and perceptions\u0026mdash;collectively shaped farmers\u0026rsquo; and livestock keepers\u0026rsquo; responses to the COVID-19 pandemic. Rather than focusing on the specific adaptive actions, the findings emphasize the underlying conditions, constraints, and enabling factors that influenced the emergence of adaptive strategies. In this way, the study underscores that the observed behaviors are manifestations of broader adaptive capacities, demonstrating how different vulnerabilities, institutional access, and production systems guided decision-making and strategy development under crisis conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\"\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study set out to analyze how smallholder farmers and livestock keepers in southern Iran adapted to the systemic disruptions caused by the COVID-19 pandemic, using a six-dimensional adaptive capacity framework. By applying this framework, rather than developing a new one, the study provides empirical insights into how adaptive capacity is enacted under crisis conditions and how resilience is shaped at the local scale.\u003c/p\u003e \u003cp\u003eThe findings demonstrate that adaptive capacity is not a static attribute but a dynamic process shaped by both structural constraints and lived experiences. Farmers and livestock keepers drew on local knowledge, informal networks, and experimental practices when formal institutions and governance structures failed to provide timely support. These adaptive behaviors\u0026mdash;such as diversifying products, reallocating labor, modifying grazing practices, and exploring alternative markets\u0026mdash;represent concrete manifestations of adaptive capacity. At the same time, they reveal the limits of resilience when adaptive actions are improvised under conditions of weak infrastructure and policy support, often leading to short-term coping at the expense of long-term sustainability.\u003c/p\u003e \u003cp\u003eThe distinction between adaptive capacity and adaptive behaviors is central to interpreting the results. While adaptive capacity refers to the enabling conditions captured through six dimensions (resources, information and knowledge, governance, policies, infrastructure, and perceptions), adaptive behaviors are the observable responses that emerge when those capacities are activated under stress. This study shows how weaknesses in systemic dimensions\u0026mdash;such as inadequate rural infrastructure, centralized governance, and fragmented policies\u0026mdash;restricted the scope of adaptive behaviors and sometimes generated maladaptive outcomes. Conversely, where information, social capital, and local organization were relatively strong, adaptive responses were more effective and resilient.\u003c/p\u003e \u003cp\u003eIn relation to resilience, our results suggest that local resilience cannot be achieved through individual coping alone but requires institutional and structural reinforcement. COVID-19 exposed the fragility of agricultural livelihoods in Khuzestan: short-term adaptive actions helped households survive, but without systemic support they risk undermining future adaptive capacity. Thus, resilience emerges not merely from household-level improvisation but from the interaction between local strategies and enabling governance and policy frameworks.\u003c/p\u003e \u003cp\u003eThe contribution of this study lies in empirically demonstrating how an established adaptive capacity framework can be applied to illuminate both the enabling and constraining factors of adaptation at the local level. By systematically analyzing the six dimensions, the study enriches existing frameworks in three ways: (1) it highlights the interplay between structural vulnerabilities and locally driven responses; (2) it shows how adaptive behaviors reflect both the presence and absence of enabling conditions; and (3) it underscores the role of social capital and informal mechanisms as critical, yet often overlooked, determinants of resilience. These insights contribute to advancing adaptation governance debates by bridging theoretical models with the lived realities of farmers and livestock keepers during a global crisis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe COVID-19 pandemic exposed significant vulnerabilities in the agricultural sector of southern Iran, particularly among smallholder farmers and livestock keepers. The crisis disrupted production, marketing, labor, and access to critical services, while institutional responses remained fragmented, delayed, or inaccessible. In the absence of sufficient state support, producers relied on individual initiative and informal networks to cope with the shock. These adaptive behaviors, ranging from converting products and finding alternative markets to rotating grazing patterns and automating tasks, reflect both resilience and the limitations of operating in a system lacking structural preparedness.\u003c/p\u003e \u003cp\u003eA key insight from this study is that resilience in agriculture during crises cannot be improvised at the moment of impact. It must be built proactively through a foundation of inclusive policies, decentralized governance, and adaptive infrastructure. Policy makers should recognize that natural disasters and pandemics are not exceptional events but increasingly frequent realities. Ensuring sustainable food security in such conditions requires embedding crisis-readiness into routine agricultural planning.\u003c/p\u003e \u003cp\u003eFuture interventions must focus on strengthening local service delivery, guaranteeing market access during restrictions, improving rural digital infrastructure, and designing flexible support mechanisms, such as mobile veterinary units, emergency insurance, and adaptive credit systems, that can be rapidly deployed. Most importantly, local knowledge and adaptive practices identified during the pandemic should not be overlooked; they offer grounded strategies that, if supported appropriately, can shape a more resilient agricultural future.\u003c/p\u003e \u003cp\u003eThe experience of COVID-19 is a warning, but also a blueprint. Building resilience means recognizing farmers and herders not just as beneficiaries of aid, but as key actors in crisis management. Their lived responses offer a roadmap for designing agricultural systems that can withstand, and recover from, future shocks.\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e- Due to the quarantine and travel restrictions, it wasn\u0026apos;t easy to interview the respondents\u003c/p\u003e\n\u003cp\u003e- Entering the space of some operations, such as industrial livestock farms, due to the establishment of health laws, it was difficult to interview the operators of these units.\u003c/p\u003e\n\u003cp\u003e- Poor literature of research in the field of COVID-19 on agricultural and livestock operators\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors received no specific funding for this research.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eD.R., S.R, and M.S.wrote the main manuscript text. P.L reviewed and polished the main manuscript text. A.SM. Collected data and conducted interviews. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the current study consist of written transcripts of semi-structured interviews. Due to ethical considerations and the need to protect participant confidentiality and privacy, these data are not publicly available. An anonymised version of the interview transcripts may be made available from the corresponding author upon reasonable request, subject to approval by the relevant ethics committee and compliance with informed consent agreements.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdger, W. N. et al. Assessment of adaptation practices, options, constraints and capacity. In: (eds Parry, M. L. C. O. F., Palutikoff, J. P., Van Der Linden, P. J. \u0026amp; Hanson, C. E.) 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Sustain.\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e, 100014 (2020).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Adaptive Capacity, Smallholder Farmers, COVID-19 Pandemic, Adaptation Strategies, Agricultural Resilience, Future Shocks","lastPublishedDoi":"10.21203/rs.3.rs-8515225/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8515225/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe COVID-19 pandemic exposed the structural fragility of agricultural systems in southern Iran by disrupting production, marketing, access to inputs, and essential services. This study aimed to analyze and compare the adaptive capacity and adaptive strategies of smallholder farmers and livestock keepers in Khuzestan Province in response to this widespread shock. Using a qualitative approach and a six-dimensional adaptive capacity framework (including resources, information and knowledge, policies, governance, infrastructure, and perception), data were collected through 57 semi-structured interviews and analyzed using deductive content analysis. The findings revealed that in the absence of effective institutional support, farmers and livestock keepers adopted divergent strategies. Farmers focused on value chain restructuring, market diversification, and product transformation, while livestock keepers engaged in herd management adjustments, cost reduction, and increased reliance on local resources. Both groups drew heavily on social capital and informal networks to compensate for institutional gaps. The key contribution of this study lies in providing a comparative analysis of these two groups and highlighting the critical role of social capital in local resilience. We conclude that locally driven responses, despite structural constraints, offer valuable lessons for designing anticipatory policies, strengthening adaptive infrastructure, and reconfiguring governance to enhance agricultural resilience. These insights are crucial for preparing rural systems to better withstand and recover from future shocks.\u003c/p\u003e","manuscriptTitle":"From Crisis to Capacity: What COVID-19 Teaches about Resilience in Iran’s Farming Systems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-20 23:55:48","doi":"10.21203/rs.3.rs-8515225/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7b54ea09-320e-4c83-b543-24a6ddb36a7e","owner":[],"postedDate":"April 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66584663,"name":"Social science/Development studies"},{"id":66584664,"name":"Earth and environmental sciences/Environmental social sciences"}],"tags":[],"updatedAt":"2026-04-28T04:39:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-20 23:55:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8515225","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8515225","identity":"rs-8515225","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}