A two-decade bibliometric review of climate resilience in agriculture using the dimensions platform

A two-decade bibliometric review of climate resilience in agriculture using the dimensions platform | 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 Systematic Review A two-decade bibliometric review of climate resilience in agriculture using the dimensions platform Pierre Marie Chimi, Jean Louis Fobane, John Hermann Matick, William Armand Mala This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5112075/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 Climate resilience in agriculture is crucial for addressing climate change challenges. This bibliometric review, using the Dimensions platform, analyzes research trends, international collaborations, and key areas from 2004 to 2024. It identifies 477 sources contributing to 1,000 documents, with a 25.77% annual growth rate and an average of 10.15 citations per document, involving 2,605 authors. The thematic map highlights the central role of “climate change” and its links to “resilience,” “policy,” and “sustainable development,” advocating for an integrated approach to climate issues. The annual publication trend shows a significant increase in interest, with a strong positive correlation ( R² = 0.7097 ) and linear growth, emphasizing adaptive strategies. Leading journals include “Qeios Ltd,” “Handbook of Climate Change Resilience,” and “Sustainability.” Key terms like “Climate Change” and “Adaptation” have grown substantially, reflecting the evolving discourse. The co-authorship network reveals three main clusters, led by researchers such as David D. Woods, Andrea Nowak, and David Zilberman. Influential publications, highlighted by their Local Citation Scores, showcase both global and local impacts. The historical citation network and word cloud visualization emphasize the interconnectedness of key concepts, illustrating the collaborative and cumulative nature of research in this field. This review provides a comprehensive overview, guiding future studies, informing policy, and fostering collaboration to enhance climate resilience in agriculture. By leveraging these insights, policymakers can develop more effective, evidence-based strategies, ultimately contributing to sustainable development and food security. Future research can build on these findings to create more effective and sustainable solutions. Agronomy Renewable Resources Environmental Policy Agroecology Climate resilience Agricultural resilience Dimensions Vosviewer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 1. Introduction Climate change is a major threat to global agriculture [1], [2]. It affects food production and food security. Changes in temperature, erratic rainfall, and an increase in the frequency and intensity of extreme weather events, such as droughts and floods, disrupt crop growth cycles and reduce agricultural yields [3]. These disruptions exacerbate existing challenges, such as soil degradation and water scarcity, and threaten farmers' livelihoods, especially in vulnerable regions. In the face of these challenges, the development of climate resilience strategies is essential to ensure the sustainability of agricultural systems and long-term food security [4], [5]. Due to the increasing impacts of climate change on agricultural systems, climate resilience in agriculture has become a global priority. Extreme weather events, such as droughts, floods, and heat waves, are disrupting agricultural production cycles and threatening food security and the livelihoods of farmers. Agriculture will need not only to adapt to these changes but also to help reduce GHG emissions [6], [7]. Sustainable agricultural practices, such as agroecology, play a crucial role in this adaptation. They improve the resilience of farming systems while reducing their environmental footprint [8], [9], [10]. Climate resilience in agriculture is a rapidly growing area of research. However, several gaps remain. The lack of integrative studies that combine the socio-economic and environmental aspects of adaptation strategies has been identified as one of the main gaps. Most research focuses on either the technical aspects of agricultural practices or the socio-economic impacts. Often these are not linked holistically [11], [12], [13]. This bibliometric review using the Dimensions platform addresses this gap by providing a comprehensive analysis of research trends and international cooperation, while also highlighting the interplay between the different dimensions of climate change adaptation1. In particular, it provides new perspectives on how to adapt by identifying: (i) identifying innovative practices, (ii) analyzing public policies, (iii) fostering collaborations, (iv) and proposing models of resilience. By highlighting innovative agricultural practices that have worked in different climatic contexts, this study provides a better understanding of which strategies are most effective and why. By examining public policies and their impact on agricultural resilience, this review provides valuable insights to steer future policies toward more integrated and sustainable approaches [14], [15], [16], [17]. By mapping international cooperation, the review highlights the importance of global partnerships to strengthen climate resilience through the sharing of knowledge and resources [18], [19]. This review proposes resilience models that can be adapted to different local contexts, providing tailor-made solutions for farmers by integrating socio-economic and environmental data. Climate change poses unprecedented challenges to global agriculture, with implications for production, food security, and farmers' livelihoods. Extreme weather events such as droughts, floods, and heatwaves are becoming more frequent and intense [6], [7]. They threaten the stability of agricultural systems. Climate resilience, defined as the ability of agricultural systems to anticipate, absorb, and recover from climate shocks, is essential [20], [21], [22], [23], [24]. However, there is a wide variety of resilience practices and strategies. Their effectiveness varies according to local contexts and crop types [25], [26], [27]. The Dimensions platform provides a unique opportunity to analyze the trends in research, international collaborations, and the main areas of interest in the field [28], [29]. Understanding how current research contributes to strengthening agricultural climate resilience, what gaps exist, and how future research can be directed to meet farmers' needs in the face of climate challenges is therefore the central question of this bibliometric review. 2. Literature review 2.1. Dimensions platform 2.1.1. Definition Developed by Digital Science, Dimensions is an advanced bibliometric analysis platform [30], [31]. It provides powerful tools for exploring and analyzing scientific publications, citing, funding, and collaborating [30]. Users can access a huge database of millions of publications and benefit from interactive visualizations. They can identify research trends, assess the impact of work, and discover opportunities for collaboration. The platform is designed to help researchers, institutions and decision-makers gain a deep insight into the scientific output of the world. 2.1.2. Dimensions platform benefits The Dimensions platform offers several key benefits: a comprehensive database, advanced analytics, citations and impact, customized search, data integration, access to alternative metrics, and ease of use, making it a powerful tool for bibliometrics and research analysis [30], [31]. Dimensions provide access to a large database of publications, patents, funding, and clinical trials. It gives a comprehensive view of research activity across a range of fields. Dimensions make it easy to explore research trends, measure the impact of publications, and identify collaborations between researchers and institutions with sophisticated visualization and analysis features [30]. The platform provides tools for tracking the citations of articles, assessing the impact of publications and authors, and measuring the performance of scientific and scholarly journals. Dimensions allow users to create customized searches and alerts [29], [30], [31]. These can be used to track developments in specific fields or to monitor specific authors and institutions. It provides a more holistic view of scientific productivity by integrating data on funding and research projects to understand the relationships between funding, publications, and research outcomes. Dimensions provide alternative metrics (altmetrics) to assess the engagement and reach of research beyond academic publications, in addition to traditional metrics such as impact factors [30], [31]. Dimensions make research analysis accessible to those without deep bibliometric expertise through an intuitive user interface. In short, Dimensions stands out for its close integration of the various facets of research, providing a comprehensive and detailed view that can help researchers, institutions, and policymakers to better understand and optimize their research activities [30], [31]. 2.1.3. Dimensions platform limitations Despite the many advantages that Dimensions offers to bibliometrics, it also has several limitations: · Inconsistency of coverage Despite the breadth of its data, Dimensions may not cover all publications, especially those from lesser-known or niche journals. This may introduce bias into the analysis [30], [31]. · Data availability Some advanced features or specific data may only be available to paying subscribers or institutions with a full subscription. This may limit access for individual users or small institutions [30], [31]. · Metrics complexity It can be difficult to select the most relevant metrics for a particular analysis due to the variety of metrics available. Alternative metrics (such as altmetrics) may also be more controversial or less widely accepted in some disciplines than others [30], [31]. · Data quality issues Dimensions are subject to data errors and gaps, as is any database. Authors, institutions, and cited information may sometimes be incorrect or incomplete [30], [31]. · Visibility bias The platform may favor the visibility of publications and researchers from better-funded or more established institutions. This may lead to bias in the assessment of research [30], [31]. · Platform dependence Overdependence on Dimensions can limit researchers' ability to use other tools or databases offering different perspectives or complementary data [30], [31]. · Updating and developing Bibliometric databases and tools are evolving at a rapid pace, and Dimensions may need to be updated frequently to keep up with new publishing practices and developments in the field of research [30], [31]. · Data aggregation Concentrating data in a single system can lead to problems of transparency and accountability, especially if the data are not easily accessible or comparable with those from other sources [30], [31]. To conclude, although Dimensions is a valuable tool for bibliometric analysis, it is important to use it in conjunction with other sources and methods to obtain a complete and balanced picture of research activity[30], [31]. 2.2. Climate resilience 2.2.1. Definition and importance Climate resilience in agriculture refers to the ability of agricultural systems to withstand the impacts of climate change, to adapt to them, and to recover from them. It also includes the management of risks associated with extreme weather events, such as droughts and floods [32], [33], [34]. 2.2.2. Adaptation strategies Agroecology, crop diversification, and the use of varieties that can withstand extreme weather conditions are some of the adaptation strategies in agriculture. For example, agroecology, which is the sustainable management of ecosystems, is often cited as an effective approach to resilience building [35], [36], [37]. 2.2.3. Case study Case studies, such as those carried out in Burkina Faso, show how farmers are adapting their practices to help cope with changing climates [38], [39]. These adaptations include improved water conservation techniques and the use of drought-resistant crops [40], [41]. 2.3. Agricultural policies and standards Agricultural policies have a crucial role to play in promoting resilience to climate change. International initiatives, such as those led by FAO, encourage adopting sustainable and resilient agricultural practices [42]. 2.4. Dimensions platform research The Dimensions platform was used to conduct bibliometric searches. Results were filtered by publication type (journal articles, conferences, book chapters, etc.), publication period (e.g. since 1984), and specific research areas [30], [31]. 3. Methodology 3.1. Data extracted The metadata of the selected publications, including the title, the authors, the affiliations, the abstracts, the keywords, and the citations, were downloaded. Text mining tools were used to analyze abstracts and keywords to identify research trends and key themes. 3.2. Collaboration network analysis Network visualization software (e.g. VOSviewer or Gephi) was used to map collaborations between authors and institutions. The main research centers and international collaborations were the focus of the analysis. 3.3. Analyzing citations The impact of publications has been assessed using an analysis of the number of citations. The most influential articles and journals in the field of climate resilience in agriculture were identified. 3.4. Summarising the results The data collected was collated to identify research trends, gaps, and future opportunities. A report on the results of the bibliometric analysis and recommendations for future research has been written. 3.5. Analytical techniques justification 3.5.1. The bibliometric analysis The bibliometric analysis makes it possible to quantify and visualize research trends, collaborations, and the impact of publications in the field of climate resilience in agriculture [43], [44]. To identify key players, international collaborations, and emerging research areas, this technique is essential. It provides an overview of the current scientific efforts and the gaps in knowledge. 3.5.2. Text extraction The extraction and analysis of textual information from the abstracts and keywords of publications. Recurring themes and new trends in scientific publications can be identified through text mining. This helps to understand research priorities and proposed adaptation strategies. 3.5.3. Collaboration network analysis Mapping of collaborations between authors and institutions. This analysis reveals key research networks and partnerships. It highlights international collaborations that are critical to building climate resilience in agriculture1. 3.5.4. Citation analysis Analyze the number of citations received to assess the impact of publications. Citations indicate how influential and relevant the research is. To help guide future research, this analysis helps identify the most influential papers and the most cited journals1. 3.5.5. Data visualisation The results of bibliometric analysis can be presented graphically using visualization tools. Data visualization makes it easier to understand complex trends and the relationships between different elements of the research. It makes it possible to communicate effectively to researchers and to those seeking to influence policy. 4. Results 4.1. Analysis of the number of articles issued and the publishing journal 4.1.1. Annual trends in the number of publications The data indicates that from 2004 to 2024, 477 sources, including journals and books, contributed to 1,000 documents. The annual growth rate of publications was 25.77%, with an average document age of 4.31 years. Each document received an average of 10.15 citations, and collectively, they cited 17,136 references. There were 2,605 authors, with 255 single-authored documents, averaging 3.21 authors per document. Additionally, the publications included 26 books, 214 book chapters, 9 conference proceedings articles, 14 datasets, 13 dissertations, 1 editorial, 460 journal articles, 3 journal issues, 1 news article, 9 other types of documents, 22 preprints, 15 reports, and 69 review articles (Table 1 ). Table 1 Primary details regarding data. Period 2004: 2024 Sources (Journals, Books, etc) 477 Documents 1000 Annual Growth Rate % 25.77 Document Average Age 4.31 Average citations per doc 10.15 References 17136 Keywords Plus (ID) 119 Author's Keywords (DE) 119 Authors 2605 Authors of single-authored docs 255 Single-authored docs 291 Co-Authors per Doc 3.21 Book 26 Book chapter 214 Component 1 Conference proceedings article 9 Dataset 14 Dissertation 13 Editorial 1 Journal article 460 Journal issue 3 News 1 Other 9 Preprint 22 Report 15 Review 69 4.1.2. Thematic map The thematic map illustrates the central role of “climate change” and its interconnectedness with various themes such as “resilience,” “policy,” and “sustainable development.” These connections highlight the multifaceted nature of climate change, emphasizing how it influences and is influenced by different aspects of society and the environment. For instance, the link between “climate change” and “resilience” suggests a focus on adaptive strategies, while the connection to “policy” underscores the importance of governance in addressing climate issues. The map effectively visualizes the complex web of relationships, demonstrating the integrated approach needed to tackle climate change (Fig. 1 ). Figure 2 illustrates the annual publication trend of climate resilience in agriculture from 2004 to 2024, showing a clear upward trajectory. This trend is further emphasized by the linear equation ( y = 7.3838x − 233.62 ) and an ( R 2 ) value of 0.7097, indicating a strong positive correlation between the years and the number of publications. Consequently, the increasing number of publications suggests a growing scholarly interest and recognition of the importance of climate resilience in agriculture. Therefore, this trend underscores the escalating focus on developing adaptive strategies to mitigate climate impacts on agriculture (Fig. 2 ). 4.1.3. Analysis of publishing journals Table 2 presents the top 10 journals with the most publications on climate resilience in agriculture from 2004 to 2024. Notably, “Qeios Ltd” leads with 69 articles, indicating its significant contribution to this field. Following this, the “Handbook of Climate Change Resilience” and “Sustainability” have published 32 and 13 articles, respectively, highlighting their roles in disseminating research. Additionally, the remaining journals, such as “The International Journal of Environment and Climate Change” and “Climatic Change,” contribute fewer articles, ranging from 10 to 7. This distribution suggests that while a few journals dominate the publication landscape, there is a broad interest across various journals, reflecting the interdisciplinary nature of climate resilience research in agriculture (Table 2 ). Table 2 Leading 10 journals with the highest number of articles on agricultural climate resilience from 2004 to 2024. Sources Articles Qeios ltd 69 Handbook of Climate Change Resilience 32 Sustainability 13 International journal of environment and climate change 10 Zenodo (cern European organization for nuclear research) 9 Building Resilience to Climate Change in South Caucasus Agriculture 8 Climatic change 8 Research papers in economics 8 Climate change management 7 Green infrastructure and urban climate resilience 7 Land use policy 7 Figure 3 tracks the frequency of specific terms from 2004 to 2024, revealing significant trends. Notably, terms like ‘Climate Change’ and ‘Adaptation’ show a steep increase, indicating a growing emphasis on these topics over time. Conversely, terms such as ‘Adaptive Capacity’ and ‘Climate Smart Agriculture’ exhibit a more gradual rise, suggesting a steady but less pronounced focus. This cumulative increase in mentions underscores the escalating importance of climate-related discussions in literature, reflecting heightened awareness and concern about climate issues. Consequently, the graph highlights the evolving discourse on climate resilience and its various facets, emphasizing the need for continued research and policy development in this area (Fig. 3 ). Figure 4 tracks the cumulative occurrences of various sources from 2004 to 2024. Notably, there has been a significant increase in the production of sources related to climate change topics, particularly around 2014 to 2016, and a sharp rise starting around 2020. This trend suggests a growing scholarly and research interest in climate resilience and related fields. Consequently, sources like “Building Resilience to Climate Change in South Caucasus Agriculture” and “Green Infrastructure and Urban Climate Resilience” have seen substantial increases, indicating their importance in the discourse. Therefore, the figure highlights the expanding focus on climate change research, reflecting heightened awareness and urgency in addressing climate-related challenges (Fig. 4 ). 4.2. Analysis of Key Researchers 4.2.1. Analysis of Key Researchers Figure 5 illustrates the changes in output over time in climate resilience in agriculture, authored by various researchers from 2004 to 2024. The size of each bubble represents the number of documents published by an author, while the color shade indicates the number of citations. Notably, authors like Neumann JE and Gaupp F have consistently contributed over multiple years, suggesting sustained research interest. Conversely, authors such as Bodirsky BL and Kumareswami K show sporadic contributions, indicating focused studies at particular intervals. Additionally, larger bubbles in certain years highlight peaks in research output, reflecting pivotal studies that garnered significant attention. Therefore, this chart underscores both the productivity and impact of research in climate resilience, emphasizing the importance of ongoing contributions to this field (Fig. 5 ). 4.2.2. Authors’ impact of climate resilience on agriculture Table 3 provides a detailed overview of various bibliometric indicators for ten authors. The h_index, which measures the number of highly cited papers, is relatively consistent across authors, indicating a similar level of influence. The g_index, reflecting the overall citation performance, varies slightly more, suggesting differences in the breadth of impactful work. The m_index, which normalizes impact over time, shows lower values for newer authors like Luginaah I. and Mohammed K., indicating their recent entry into academia. Total citations (TC) vary significantly, with Asfaw S. having the highest at 339, highlighting substantial influence. The number of publications (NP) is mostly uniform, except for a few outliers, suggesting consistent research output. Finally, the publication year start (PY_start) spans from 2010 to 2021, showing a mix of established and emerging researchers in the field. This table collectively underscores the diverse yet impactful contributions of these authors to climate resilience in agriculture. Table 3 Authors’ regional influence. Author h_index g_index m_index TC NP PY_start Luginaah I 4 6 1 63 6 2021 Mohammed K 4 4 1 62 4 2021 Speranza CI 4 6 0.267 102 6 2010 Alam GMM 3 4 0.429 159 4 2018 Arslan A 3 3 0.3 178 3 2015 Asfaw S 3 6 0.3 339 6 2015 Awazi NP 3 4 0.75 35 4 2021 Batley J 3 3 0.3 230 3 2015 Batung E 3 3 0.75 45 3 2021 Braimoh AK 3 4 0.333 23 4 2016 The co-authorship network visualization illustrates the collaborative relationships among researchers in the field of climate resilience in agriculture. The network is divided into three distinct clusters, each color-coded to represent different groups of researchers. The blue cluster includes key authors like David D. Woods and Andrew Dougill, indicating their frequent collaboration. The green cluster features Andrea Nowak, Peter Steward, Todd S. Rosenstock, and Erika Berglund, suggesting a strong collaborative network among them. The red cluster, with David Zilberman, Nancy McCarthy, and Sara Savastano, highlights another significant group of collaborators. This visualization underscores the interconnected nature of research in this field, showing how different groups of researchers work together to advance knowledge and innovation in climate resilience and agriculture (Fig. 6 ). 4.2.3. Co-occurrence The network visualization map illustrates the interconnectedness of various concepts related to climate resilience in agriculture from 2004 to 2024. Central terms like “climate change,” “agriculture,” and “adaptation” have larger nodes, indicating their key importance in the research field. Smaller nodes such as “sustainable agriculture” and “climate-smart agriculture” are also significant, showing their relevance within the broader context. The lines connecting these nodes represent the relationships between different concepts, while the color-coded clusters highlight sub-themes or closely related ideas. This visualization effectively demonstrates how different aspects of climate resilience in agriculture are interrelated, emphasizing the multifaceted nature of the research and the need for an integrated approach to address climate challenges in agriculture (Fig. 7 ). The overlay visualization map of climate resilience in agriculture from 2004 to 2024 reveals significant trends and interconnections in research topics over the past two decades. Initially, research focused on fundamental concepts such as “climate change” and “agriculture,” as indicated by the blue nodes representing earlier years. As time progressed, the focus shifted towards more specific and applied topics like “sustainable agriculture,” “crop adaptation,” and “biodiversity,” which are represented by yellow nodes, indicating recent years. This evolution suggests a growing recognition of the need for sustainable practices and adaptive strategies in response to climate change. Moreover, the dense clustering of terms such as “human activities,” “ecological impacts,” and “mitigation strategies” underscores the complexity and interdisciplinary nature of this research field. Consequently, the map highlights the increasing importance of integrating various aspects of climate resilience to develop comprehensive and effective solutions for agricultural sustainability (Fig. 8 ). The density visualization of climate resilience in agriculture from 2004 to 2024, generated by VOSviewer, reveals several key insights. Initially, the research predominantly focused on broad terms such as “climate change” and “agriculture,” which are centrally located and larger, indicating their foundational role in the field. As research evolved, more specific terms like “sustainable agriculture,” “crop adaptation,” and “pest management” emerged, reflecting a shift towards practical applications and solutions. This progression is evident through the color gradient from green to blue, signifying the temporal development of these topics. Furthermore, the clustering of terms such as “adaptation strategies,” “soil,” and “biodiversity” highlights the interdisciplinary nature of the research, emphasizing the interconnectedness of various factors influencing climate resilience. Consequently, this visualization underscores the increasing complexity and depth of research in this field, driven by the need to address multifaceted challenges posed by climate change on agriculture (Fig. 9 ). 4.3. Analysis of cited papers 4.3.1. Analysis of local highly cited papers The Table 4 ranks influential publications based on their Local Citation Scores (LCS). A higher LCS indicates frequent citations within the dataset, highlighting the publication’s significance in the field. For instance, Lin BB., 2011 has a high LCS of 20, suggesting it is highly influential locally, while its global citations are 1144, indicating broader recognition. Conversely, Keshavarz M., 2021 has a lower global citation count but a high ratio of local to global citations, suggesting a more localized impact. Consequently, this table underscores key works that have significantly contributed to the academic discourse in climate resilience and agriculture. Table 4 Leading ten local citation scores of articles on agricultural climate resilience from 2004 to 2024. Document DOI Year Local Citations Global Citations Ratio Lin BB, 2011, Bioscience 10.1525/bio.2011.61.3.4 2011 20 1144 1.74 Darnhofer I, 2014, European review of agricultural economics 10.1093/erae/jbu012 2014 12 254 4.72 Mase AS, 2017, Climate risk management 10.1016/j.crm.2016.11.004 2017 11 286 3.84 Speranza CI, 2013, Regional environmental change 10.1007/s10113-012-0391-5 2013 9 89 10.11 Michler JD, 2019, Journal of environmental economics and management 10.1016/j.jeem.2018.11.008 2019 9 132 6.81 Keshavarz M, 2021, Journal of arid environments 10.1016/j.jaridenv.2020.104323 2021 8 42 19.04 Alam GMM, 2018, Environmental science & policy 10.1016/j.envsci.2018.02.012 2018 7 82 8.53 Lipper L, 2018, Natural resource management and policy 10.1007/978-3-319-61194-5 2018 7 184 3.80 Zougmoré RB, 2016, Agriculture & food security 10.1186/s40066-016-0075-3 2016 6 149 4.02 Arbuckle JG, 2013, Climatic change 10.1007/s10584-013-0700-0 2013 6 258 2.32 Note: Local citations refer to the number of citations by papers within this paper’s database, while global citations refer to the number of citations by all papers. 4.3.2. Analysis of global highly cited papers Table 5 ranks influential publications based on their total citations. Lin BB., 2011, with 1144 total citations, is the most cited, indicating its significant influence in the field. However, Bailey-Serres J., 2019, despite having fewer total citations (868), has a higher average of 144.67 citations per year, suggesting a rapidly growing impact. Conversely, Webb NP., 2017, with 154 total citations and 19.25 citations per year, shows steady but slower recognition. This table highlights the varying degrees of influence and growth rates of key publications in rural sustainability and land use research. Table 5 Leading ten global citation counts of articles on agricultural climate resilience. Paper DOI Total Citations TC per Year Lin BB, 2011, Bioscience 10.1525/bio.2011.61.3.4 1144 81.7142857 Bailey-Serres J, 2019, Nature 10.1038/s41586-019-1679-0 868 144.666667 Aryal JP, 2019, Environment, development and sustainability 10.1007/s10668-019-00414-4 360 60 Côté IM, 2010, Plos biology 10.1371/journal.pbio.1000438 328 21.8666667 Mase AS, 2017, Climate risk management 10.1016/j.crm.2016.11.004 286 35.75 Arbuckle JG, 2013, Climatic change 10.1007/s10584-013-0700-0 258 21.5 Darnhofer I, 2014, European review of agricultural economics 10.1093/erae/jbu012 254 23.0909091 Abberton M, 2015, Plant biotechnology journal 10.1111/pbi.12467 220 22 Lipper L, 2018, Natural resource management and policy 10.1007/978-3-319-61194-5 184 26.2857143 Webb NP, 2017, Frontiers in ecology and the environment 10.1002/fee.1530 154 19.25 4.3.3. Analysis of cited networks The citation document overlay in climate resilience in agriculture from 2004 to 2024, generated by VOSviewer, provides a comprehensive view of the evolution and interconnections within this research field. Initially, the research was dominated by foundational studies, as indicated by the larger nodes representing highly cited documents from earlier years, such as those by Valerie Nelson (2009) and Brenda B. Lin (2011). As the field progressed, there was a noticeable shift towards more specialized and recent studies, exemplified by the works of Frederick Dapilah (2023) and Anupam Mihra (2023), which are represented by smaller, yet significant nodes. This shift is further highlighted by the color gradient from green to blue, indicating the temporal development of research topics. Moreover, the dense network of citation links underscores the interdisciplinary nature of climate resilience research, connecting diverse topics such as “adaptive capacity,” “pest management,” and “sustainable agriculture.” Consequently, this visualization not only maps the influential research contributions but also illustrates the dynamic and evolving landscape of climate resilience in agriculture over the past two decades (Fig. 10 ). The citation source visualization in climate resilience from 2004 to 2024, generated by VOSviewer, reveals the evolution and interconnections of research within this field over two decades. Initially, foundational sources such as “Climate Policy” and “Sustainability” were central, indicating their significant influence on early research. As the field progressed, more specialized sources like “Climate Smart Agriculture” and “Building Climate Resilience” emerged, reflecting a shift towards practical applications and adaptive strategies. This progression is evident through the color gradient from green to blue, signifying the temporal development of these topics. Furthermore, the dense network of citation links underscores the interdisciplinary nature of climate resilience research, connecting diverse areas such as “agroforestry systems,” “environmental development,” and “risk management.” Consequently, this visualization not only maps the influential research contributions but also illustrates the dynamic and evolving landscape of climate resilience in agriculture, driven by the need to address multifaceted challenges posed by climate change (Fig. 11 ). The bibliographic coupling network in climate resilience in agriculture from 2004 to 2024, visualized by VOSviewer, reveals significant insights into the collaborative landscape and research evolution in this field. Initially, foundational studies by authors like Brenda B. Lin (2011) and Julia Bailey-Serres (2019) are prominently positioned, indicating their central role and high citation frequency. As research progressed, newer contributions by authors such as Ramiro Alonso-Salinas (2023) and Keerththana Kuweswaran (2023) emerged, reflecting a shift towards more recent and specialized studies. This progression is evident through the color-coded clusters, which highlight different research groups and their interconnectedness. Furthermore, the dense network of lines connecting various authors underscores the collaborative nature of climate resilience research, illustrating how different researchers and their studies are interlinked. Consequently, this visualization not only maps the influential research contributions but also illustrates the dynamic and evolving landscape of climate resilience in agriculture, driven by the need to address multifaceted challenges posed by climate change (Fig. 12 ). 4.4 Keyword analysis 4.4.1. Analysis of high-frequency keywords The historical citation network of highly cited papers in climate resilience in agriculture from 2004 to 2024 illustrates the interconnectedness and influence of key research papers. Central nodes like “Lin BB, 2011” and “Arbuckle JG, 2013” are prominently positioned, indicating their significant impact and frequent co-citation with other works. The different colors represent distinct co-citation networks, highlighting clusters of research that are often referenced together. For instance, the network shows how foundational studies like “Lin BB, 2011” have influenced subsequent research, creating a web of interconnected studies that collectively advance the field of climate resilience in agriculture. This visualization underscores the collaborative and cumulative nature of scientific research, where key papers serve as pivotal points in the development of the field (Fig. 13 ). The word cloud visualization highlights the most frequently occurring keywords in climate resilience in agriculture. The central term “climate change” is the largest, indicating its predominant role in the discourse. Surrounding it, significant terms like “resilience,” “adaptation,” and “sustainable agriculture” are also prominent, suggesting their critical importance. Smaller terms such as “adaptive capacity,” “vulnerability,” and “food security” reflect relevant but less frequently discussed concepts. This visualization underscores the central themes and emerging topics in climate resilience research, illustrating how various aspects of climate change and agriculture are interconnected and prioritized in academic discussions (Fig. 14 ). 4.4.2. Cluster analysis and multiple correspondence analysis of high-frequency keywords The hierarchical clustering analysis of high-frequency keywords in climate resilience in agriculture groups related terms based on their co-occurrence. The dendrogram shows distinct clusters, with each color representing a different group of keywords. For instance, terms like “climate change,” “resilience,” and “adaptation” are closely linked, indicating their frequent association in the literature. As we move up the tree, branches merge, showing how broader themes like “sustainable agriculture” and “food security” are interconnected with these core concepts. This visualization highlights the main themes and their relationships, providing a clear overview of the key areas of focus in climate resilience research (Fig. 15 ). 4.5. Analysis of the evolution of research hotspots The thematic map of climate resilience from 2004 to 2024 reveals notable shifts in keyword associations over time. Initially, terms like “food” and “sustainable agriculture” were prominent, indicating a focus on food security and sustainable practices. Over time, keywords such as “climate-smart agriculture” and “resilience” gained prominence, reflecting a shift towards adaptive strategies and resilience-building in agricultural systems. The association of specific authors with these keywords also highlights regional research trends. For example, authors like Singh A. and Srivastava J.P. are linked with terms like “climate change” and “agricultural systems,” suggesting a strong focus on these topics in their regions. This visualization underscores the evolving nature of research priorities and regional differences in addressing climate resilience in agriculture (Fig. 16 ). Policymakers can leverage the shifts in keyword associations to inform climate resilience strategies by focusing on the evolving priorities and emerging trends in research. For instance, the increasing prominence of terms like “climate-smart agriculture” and “resilience” suggests a growing emphasis on adaptive strategies and sustainable practices. Policymakers can prioritize funding and support for initiatives that promote these approaches, ensuring that agricultural systems are better equipped to handle climate impacts. Additionally, the association of specific authors with key topics can highlight regional research strengths and gaps. By identifying regions where certain aspects of climate resilience are well-studied, policymakers can foster collaborations and knowledge exchange to address less-explored areas. For example, if research in “agricultural systems” is concentrated in one region, efforts can be made to disseminate this knowledge to other areas facing similar challenges. Overall, understanding these keyword associations helps policymakers align their strategies with the latest scientific insights, ensuring that policies are both relevant and effective in enhancing climate resilience. 5. Discussion 5.1. Analysis of the number of articles issued and the publishing journal The results indicate an impressive annual growth rate of 25.77% from 2004 to 2024. This rate is significantly higher than those reported in other studies. For example, a survey of clinical research literature from 1991 to 2020 found average annual growth rates of 10.28% for primary literature and 10.57% for secondary literature[ 45 ]. Another study analyzing the growth of academic journals from 1986 to 2013 reported an average growth rate of 4.7% [ 46 ]. The higher growth rate in the data could be attributed to the specific field or the inclusion of various documents beyond journal articles. The average document age in the dataset is 4.31 years, which suggests a relatively recent body of work. This aligns with trends in rapidly evolving fields where newer publications are frequently cited. The average of 10.15 citations per document is also notable. In comparison, a study on the growth of scientific literature found that the average number of citations per document can vary widely depending on the field and the impact of the journals included [ 45 ], [ 47 ], [ 48 ]. Data shows an average of 3.21 authors per document and a notable number of single-authored documents (255 out of 2,605). This is consistent with trends in collaborative research, although the absence of international co-authorship is unusual. Research indicates a growing trend in international collaborations, which frequently boost the impact and citation rates of publications [ 45 ], [ 49 ]. The dataset's diversity in publication types, including books, book chapters, journal articles, and more, reflects a comprehensive scholarly output. This variety is essential for a holistic understanding of the field. For example, the inclusion of datasets and preprints indicates a modern approach to open science and data sharing, which is becoming increasingly common [ 45 ], [ 47 ]. Comparing data with existing literature highlights both unique aspects and common trends. The high growth rate and diverse publication types suggest a dynamic and rapidly expanding field. However, the lack of international co-authorship could be an area for future improvement to enhance the global impact and collaboration in the research community. The thematic map highlights the central role of “climate change” and its interconnectedness with themes like “resilience,” “policy,” and “sustainable development.” This aligns with the findings of the IPCC’s Climate Resilient Development Pathways report, which emphasizes the interdependence of climate action and sustainable development [ 50 ], [ 51 ]. The report underscores that integrating climate mitigation and adaptation strategies is crucial for enhancing human and ecological well-being. The link between “climate change” and “resilience” in a map suggests a focus on adaptive strategies. This is consistent with the literature, which often highlights resilience as a key component in climate change adaptation. For example, a study on resilience-related policies and local practices in various cities worldwide found that resilience-building measures are essential for mitigating the impacts of climate change [ 50 ], [ 52 ]. These measures include enhancing social, economic, and ecological resilience to climate impacts. The connection between “climate change” and “policy” in a map underscores the importance of governance in addressing climate issues. This is echoed in the literature, where effective policy frameworks are seen as critical for implementing climate action. A review of sustainability and resilience in business models also highlights the need for policies that align incentives and revenue mechanisms with sustainable outcomes [ 53 ]. This alignment is crucial for driving the transition to more sustainable economies. The map’s emphasis on the integrated approach needed to tackle climate change is supported by the literature. The IPCC report notes that pursuing climate action and sustainable development goals in an integrated manner increases their effectiveness [ 50 ]. Similarly, a study on the global network analysis of links between business, climate change, and sustainability concepts found that integrated approaches are necessary for addressing the complex challenges posed by climate change [ 54 ]. Comparing the thematic map results with existing literature highlights the importance of an integrated approach to climate change, resilience, policy, and sustainable development. The interconnectedness of these themes underscores the need for comprehensive strategies that address multiple aspects of society and the environment. The findings are well-aligned with the broader body of research, emphasizing the multifaceted nature of climate change and the critical role of governance and resilience in mitigating its impacts. Data shows a clear upward trajectory in publications on climate resilience in agriculture from 2004 to 2024, with a strong positive correlation ( R² = 0.7097 ). This trend is consistent with global patterns observed in the literature. For instance, a study on climate-smart agriculture (CSA) practices noted a significant increase in publications over the past two decades, reflecting growing academic and policy interest in sustainable agricultural practices [ 33 ]. The increasing number of publications in the data underscores the escalating focus on developing adaptive strategies to mitigate climate impacts on agriculture. The linear equation ( y = 7.3838x − 233.62 ) in the data suggests a steady increase in scholarly output. This is comparable to findings from other studies that have documented similar growth patterns. For example, research on CSA adoption highlighted a consistent rise in publications, driven by the urgent need to address climate change impacts on agriculture [ 55 ]. The strong positive correlation in the data indicates a robust and sustained interest in this field, aligning with global trends. The emphasis on developing adaptive strategies to mitigate climate impacts on agriculture is a common theme in the literature. Studies have shown that resilience-building measures, such as crop diversification, soil health improvement, and the use of climate-resilient crop varieties, are critical for enhancing agricultural sustainability [ 56 ]. The data’s focus on climate resilience aligns with these findings, highlighting the importance of adaptive strategies in ensuring food security and agricultural productivity. A study on climate-resilient agricultural practices among indigenous communities in India found that traditional knowledge systems play a crucial role in enhancing resilience [ 57 ]. This study emphasized the integration of indigenous practices with modern agricultural techniques to improve adaptive capacity. Data’s upward trend in publications may also reflect an increasing recognition of the value of integrating diverse knowledge systems to address climate resilience in agriculture. Comparing findings with existing literature reveals a consistent global trend of increasing scholarly interest in climate resilience in agriculture. The strong positive correlation and steady growth in publications underscore the importance of developing adaptive strategies to mitigate climate impacts. Data aligns well with global patterns, highlighting the critical role of resilience-building measures and the integration of diverse knowledge systems in enhancing agricultural sustainability. Data shows that “Qeios Ltd” leads with 69 articles, followed by the “Handbook of Climate Change Resilience” and “Sustainability” with 32 and 13 articles, respectively. This dominance by a few journals is a common trend in academic publishing. For instance, a study on climate-smart agriculture (CSA) found that a small number of journals, such as “Agricultural Systems” and “Climate Policy,” also dominate the publication landscape [ 55 ]. These leading journals often set the research agenda and attract high-quality submissions due to their reputation and impact factor. The presence of multiple journals with fewer articles, such as the “International Journal of Environment and Climate Change” and “Climatic Change,” indicates a broad interest in climate resilience research across different disciplines. This interdisciplinary nature is crucial for addressing complex issues like climate change. Similar studies have highlighted the importance of diverse publication venues in fostering a comprehensive understanding of climate resilience. For example, research on CSA practices has been published across a wide range of journals, reflecting the multifaceted nature of the topic [ 33 ]. The significant contributions from specialized journals like “Qeios Ltd” and the “Handbook of Climate Change Resilience” suggest a focused effort on climate resilience in agriculture. This is comparable to findings in other fields where specialized journals play a pivotal role in advancing specific areas of research. For instance, journals dedicated to environmental science and sustainability often publish targeted studies that drive innovation and policy development [ 56 ]. Data reflects the interdisciplinary nature of climate resilience research, with contributions from journals spanning various fields. This aligns with the broader literature, which emphasizes the need for integrating knowledge from different disciplines to develop effective climate resilience strategies. Studies have shown that interdisciplinary research is essential for addressing the complex interactions between climate change, agriculture, and socioeconomic factors [ 57 ]. Comparing findings with existing literature highlights the dominance of leading journals, the broad interest across various publication venues, and the critical role of specialized journals in advancing climate resilience research. The interdisciplinary nature of this research is essential for developing comprehensive strategies to mitigate the impacts of climate change on agriculture. Data aligns well with global trends, underscoring the importance of diverse and specialized contributions to this field. The data shows a steep increase in the frequency of terms like “Climate Change” and “Adaptation” from 2004 to 2024. This trend is consistent with global patterns observed in the literature. For example, the IPCC’s reports have increasingly focused on these topics, highlighting the urgent need for both mitigation and adaptation strategies to address the impacts of climate change [ 50 ], [ 52 ]. The growing emphasis on these terms reflects a heightened awareness and concern about climate issues, which is also evident in the increasing number of publications and research funding dedicated to these areas [ 58 ]. The more gradual rise in terms like “Adaptive Capacity” and “Climate Smart Agriculture” suggests a steady but less pronounced focus. This aligns with findings from other studies that have documented a slower but consistent increase in research on these topics. For instance, a review of climate-smart agriculture practices noted a gradual increase in publications, driven by the need to develop sustainable agricultural practices that can withstand climate impacts [ 50 ], [ 52 ]. Similarly, research on adaptive capacity has been steadily growing as scholars and policymakers recognize the importance of building resilience in communities and ecosystems [ 59 ]. The cumulative increase in mentions of climate-related terms underscores the evolving discourse on climate resilience and its various facets. This trend is mirrored in the broader literature, where there has been a significant shift towards integrated approaches that consider the interconnectedness of climate change, resilience, and sustainable development [ 60 ]. For example, studies on climate-resilient development pathways emphasize the need for holistic strategies that address multiple dimensions of resilience, including social, economic, and environmental aspects [ 61 ]. The trends highlighted in the data emphasize the need for continued research and policy development in the area of climate resilience. This is consistent with the literature, which calls for ongoing efforts to enhance our understanding of climate impacts and to develop effective adaptation and mitigation strategies [ 50 ], [ 52 ]. The increasing frequency of terms related to climate resilience in academic publications reflects a growing recognition of the importance of this field and the need for comprehensive policies that can address the complex challenges posed by climate change. Comparing the findings with existing literature reveals a consistent global trend of increasing emphasis on climate change and adaptation, alongside a steady rise in research on adaptive capacity and climate-smart agriculture. The evolving discourse on climate resilience underscores the need for integrated approaches and continued efforts in research and policy development. Data aligns well with global patterns, highlighting the critical importance of addressing climate resilience in a comprehensive and interdisciplinary manner. 5.2. Analysis of key researchers Data shows that authors like Neumann JE and Gaupp F have consistently contributed to the field of climate resilience in agriculture over multiple years. This sustained research interest is a common trend in the literature. For instance, a study on climate-smart agriculture (CSA) practices found that certain key researchers and institutions consistently publish high-impact work, driving the field forward [ 55 ]. The continuous contributions from these authors indicate their ongoing commitment to advancing knowledge and developing solutions for climate resilience. Authors such as Bodirsky BL and Kumareswami K show sporadic contributions, which suggests focused studies at particular intervals. This pattern is also observed in other studies where researchers may concentrate on specific projects or collaborations that result in bursts of publications. For example, research on climate-resilient agricultural practices among indigenous communities in India highlighted that certain researchers contribute intensively during specific projects or funding periods [ 33 ]. These focused contributions can lead to significant advancements in particular areas of study. The larger bubbles in certain years, indicating peaks in research output, reflect pivotal studies that garnered significant attention. This trend is consistent with findings in the literature where landmark studies or special issues in journals can lead to spikes in publications and citations. For instance, a special issue on CSA adoption and impacts highlighted key studies that significantly influenced subsequent research and policy discussions [ 55 ]. These peaks often correspond to breakthroughs or comprehensive reviews that synthesize existing knowledge and set new research agendas. The chart underscores both the productivity and impact of research in climate resilience. The size of the bubbles represents the number of documents and the color shade indicating citations highlight the dual aspects of research output and influence. Similar studies have shown that highly productive researchers often have a significant impact on the field, as their work is frequently cited and builds the foundation for future research [ 56 ]. This dual focus on productivity and impact is crucial for advancing the field and addressing the complex challenges posed by climate change. Comparing the findings with existing literature reveals common trends in sustained research interest, sporadic contributions, and peaks in research output. The productivity and impact of research in climate resilience are critical for developing effective strategies to mitigate climate impacts on agriculture. Data aligns well with global patterns, emphasizing the importance of ongoing contributions and the influence of key researchers in advancing the field. Data shows that the h-index is relatively consistent across authors, indicating similar influence in terms of highly cited papers. This consistency is common in well-established research fields. For instance, in environmental science, leading researchers often have stable h-index values, reflecting their sustained contributions. In contrast, the g-index varies more among authors, highlighting differences in the breadth of impactful work. Some researchers have a few highly cited papers, while others have a broader range of moderately cited work. This trend is also observed in climate change research. The m-index, which normalizes impact over time, is lower for newer authors like Luginaah I. and Mohammed K. This is expected since the m-index accounts for the length of an author’s career. Newer researchers often have lower m-index values due to shorter publication histories, but these values increase as they establish their careers and accumulate citations. Total citations (TC) vary significantly, with Asfaw S. having the highest at 339. This highlights substantial influence, consistent with findings in other fields where a few researchers accumulate many citations. In climate resilience research, highly cited authors typically contribute foundational or highly innovative work that attracts significant attention. The number of publications (NP) is mostly uniform, with a few outliers, indicating consistent research output among the authors. This pattern is common in other studies, where top researchers maintain a steady publication rate. For example, in climate adaptation research, leading researchers consistently publish a similar number of papers each year. The publication year start (PY_start) ranges from 2010 to 2021, showing a mix of established and emerging researchers. This mix is crucial for the dynamic development of the field, as a combination of experienced and new researchers fosters innovation and continuity. Having seasoned experts and fresh perspectives is essential for addressing evolving challenges in climate resilience. Comparing findings with existing literature reveals common trends in bibliometric indicators: consistency in h_index, variation in g_index, and lower m_index for newer authors. The significant variation in total citations and the mostly uniform number of publications highlight the diverse yet impactful contributions of these authors. The mix of established and emerging researchers underscores the dynamic nature of climate resilience research in agriculture. Data aligns well with global patterns, emphasizing the importance of ongoing contributions from both seasoned and new researchers. The network visualization map highlights the central importance of terms like “climate change,” “agriculture,” and “adaptation,” which have larger nodes. This centrality is consistent with literature findings, where these terms are core concepts in climate resilience research. For example, “climate change” and “adaptation” are frequently occurring terms in climate change adaptation research, reflecting their critical role. Similarly, “agriculture” is central in studies on climate change impacts on food security and productivity. Smaller nodes like “sustainable agriculture” and “climate-smart agriculture” are also significant, indicating their relevance. This aligns with studies emphasizing sustainable and climate-smart practices in enhancing agricultural resilience. For instance, research on climate-smart agriculture (CSA) highlights the role of sustainable practices in mitigating climate impacts and promoting resilience. The lines connecting the nodes represent relationships between concepts, illustrating the interconnectedness of various aspects of climate resilience. This interconnectedness is a common theme in literature, advocating integrated approaches to address climate challenges. For example, effective adaptation requires a holistic approach considering social, economic, and environmental dimensions. The color-coded clusters highlight sub-themes or closely related ideas, reflecting the diverse aspects of climate resilience research. This clustering is similar to findings in network analyses of climate research, identifying clusters related to policy, technology, and community-based adaptation. These clusters help organize the research landscape and identify key focus areas. Comparing network visualization maps with existing literature reveals common trends: the central importance of key terms, the significance of sustainable practices, and the interconnectedness of concepts. The color-coded clusters emphasize the diverse and multifaceted nature of climate resilience research. Visualization aligns well with global patterns, underscoring the need for integrated approaches to address complex climate challenges in agriculture. 5.3. Analysis of cited papers The importance of Local Citation Scores (LCS) in identifying influential publications. For example, Lin BB., 2011 has a high LCS (20) and global citations (1144), showing broad recognition and local impact. This dual impact is common in seminal works that provide foundational knowledge. Conversely, Keshavarz M., 2021 has a lower global citation count but a high local-to-global citation ratio, indicating a more localized impact. This pattern is typical for studies addressing region-specific issues, which are crucial for informing local policy and practice. The table underscores key works that significantly contribute to climate resilience and agriculture research. Influential publications often shape the research agenda and drive future studies. For example, highly cited papers in climate change research often address critical issues or present novel solutions. Comparing results with similar studies reveals common trends: influential publications often have high citation counts and introduce new concepts or frameworks. The analysis highlights publications with substantial contributions, whether through broad recognition or localized impact. The study demonstrates the importance of both local and global citation metrics in identifying key works. This dual focus is essential for understanding research influence and guiding future studies in climate resilience and agriculture. The co-authorship network visualization reveals three distinct clusters of researchers, each representing different collaborative groups. This clustering is common in co-authorship networks, reflecting researchers’ tendency to collaborate within specific groups or institutions. For example, in climate change research, similar clustering patterns are observed. The blue cluster, featuring key authors like David D. Woods and Andrew Dougill, indicates frequent collaboration. Certain researchers act as central nodes, facilitating collaboration and knowledge exchange within their networks. For instance, in climate-smart agriculture (CSA) research, key authors frequently collaborate with multiple researchers, enhancing network connectivity. The green cluster, including Andrea Nowak, Peter Steward, Todd S. Rosenstock, and Erika Berglund, suggests a strong collaborative network. Such networks are crucial for advancing research by enabling the sharing of resources, expertise, and data. In climate resilience studies, strong collaborative networks drive innovation and facilitate comprehensive adaptation strategies. The red cluster, with David Zilberman, Nancy McCarthy, and Sara Savastano, highlights another significant group of collaborators. This pattern is often seen in co-authorship networks where certain groups work closely on specific projects or themes. For example, in environmental economics, similar clusters frequently collaborate on sustainability and resource management topics. The interconnected nature of the co-authorship network underscores the collaborative efforts required to advance knowledge and innovation in climate resilience and agriculture. Interdisciplinary and cross-institutional collaborations are essential for addressing complex climate challenges. For instance, research on climate adaptation highlights the importance of collaborative networks in integrating diverse perspectives and developing holistic solutions. Comparing the co-authorship network visualization with existing literature reveals common trends: the formation of collaborative clusters, the role of key authors, and the importance of strong collaborative networks. Visualization aligns well with global patterns, emphasizing the critical role of collaboration in driving innovation and addressing complex climate challenges. The bibliographic coupling network visualization highlights central authors like Brenda B. Lin (2011) and Julia Bailey-Serres (2019), indicating their significant influence and extensive collaboration. This pattern is common in studies where central authors shape the research landscape by contributing seminal papers. The connecting lines indicate shared references, showing the strength and frequency of collaborations. This interconnectedness is typical in bibliographic coupling networks, reflecting the collaborative nature of scientific research. For example, in climate-smart agriculture (CSA), researchers frequently cite each other’s work, creating a dense network of shared knowledge. The color-coded clusters represent different research communities, with authors like Isabelle M. Côté (2010) and Robert B. Zougmore (2016) forming distinct groups. This clustering is common in bibliographic coupling networks, where researchers working on related topics or within the same institutions form cohesive groups. The visualization underscores the interconnected nature of research in climate resilience, reflecting both historical foundations and emerging collaborations. This dual focus is essential for understanding the field’s evolution. Historical foundations provide a basis for new research while emerging collaborations introduce fresh perspectives and innovative approaches. Comparing the visualization with existing literature reveals common trends: the centrality of influential authors, the strength of shared references, and the formation of collaborative clusters. Visualization aligns well with global patterns, emphasizing the critical role of collaboration and shared knowledge in addressing complex climate challenges. 5.4 Keyword analysis The historical citation network highlights central nodes like “Lin BB, 2011” and “Arbuckle JG, 2013,” indicating their significant impact and frequent co-citation. This pattern is common in studies where highly cited papers serve as foundational references, shaping subsequent research. The different colors in a network represent distinct co-citation clusters, highlighting groups of research often referenced together. This clustering is typical in co-citation networks, where related studies form cohesive groups based on shared references. For example, in climate-smart agriculture (CSA), clusters often focus on themes like adaptation strategies, policy implications, or technological innovations. The network shows how foundational studies like “Lin BB, 2011” have influenced subsequent research, creating a web of interconnected studies. This cumulative nature of scientific research is well-documented, with foundational studies driving innovation and expanding the knowledge base. The visualization underscores the collaborative and cumulative nature of scientific research, where key papers serve as pivotal points in the field’s development. Collaborative networks and cumulative citations are critical for fostering innovation and ensuring robust findings. For instance, climate resilience research often relies on a collaborative approach, integrating insights from multiple disciplines. Comparing the historical citation network with existing literature reveals common trends: the centrality of influential papers, the formation of co-citation clusters, and the cumulative nature of scientific research. Visualization aligns well with global patterns, emphasizing the critical role of key papers in shaping research and driving innovation. The word cloud visualization highlights “climate change” as the most frequent keyword, indicating its central role in climate resilience in agriculture. This is consistent with broader literature, where climate change is a focal point in discussions on environmental impacts and adaptation strategies. The prominence of terms like “resilience,” “adaptation,” and “sustainable agriculture” suggests their critical importance. This aligns with studies emphasizing the need for resilient agricultural systems and adaptive strategies to cope with climate impacts. For example, climate-smart agriculture (CSA) research highlights the importance of resilience and adaptation for food security and sustainable practices. Smaller terms such as “adaptive capacity,” “vulnerability,” and “food security” are also important, reflecting relevant but less frequently discussed concepts. These terms help understand the broader context of climate resilience, addressing socio-economic dimensions and the ability of communities to adjust to climate change. The interconnectedness of various aspects of climate change and agriculture in a word cloud is a common theme in the literature. Integrated approaches that consider social, economic, and environmental dimensions are frequently advocated. Visualization captures this complexity, highlighting the need for comprehensive strategies. Comparing the word cloud with existing literature reveals common trends: the centrality of climate change, the importance of resilience and adaptation, and the relevance of emerging topics like adaptive capacity, vulnerability, and food security. Visualization aligns well with global patterns, emphasizing the critical role of these concepts in advancing research and policy development in climate resilience. The hierarchical clustering analysis shows that terms like “climate change,” “resilience,” and “adaptation” are closely linked, indicating their frequent association in the literature. This is consistent with other studies where these core concepts are often discussed together, highlighting the importance of resilience and adaptation strategies in addressing climate change impacts. As we move up the dendrogram, broader themes like “sustainable agriculture” and “food security” merge with these core concepts. This pattern is observed in other studies, emphasizing the interconnectedness of various aspects of climate resilience. For example, climate-smart agriculture (CSA) research often integrates sustainability and food security themes. The distinct clusters in the dendrogram provide a clear overview of the main themes and their relationships. Similar studies use clustering techniques to identify key areas of focus in climate resilience research, highlighting diverse aspects like policy, technology, and community-based adaptation. Comparing the results with similar studies reveals common trends: clustering of core concepts and integration of broader themes. For example, hierarchical clustering in climate adaptation literature often finds terms related to policy, governance, and socio-economic factors clustering together, reflecting the multifaceted nature of adaptation strategies. The hierarchical clustering analysis effectively highlights the main themes and their relationships in climate resilience research. The clustering of core concepts like “climate change,” “resilience,” and “adaptation,” along with broader themes like “sustainable agriculture” and “food security,” underscores the comprehensive nature of the field. Visualization aligns with global patterns, emphasizing the importance of integrated approaches in addressing climate resilience. 5.5. Analysis of the Evolution of Research Hotspots The thematic map shows shifts in keyword associations over time, reflecting evolving research priorities in climate resilience in agriculture. Initially, terms like “food” and “sustainable agriculture” were prominent, indicating a focus on food security and sustainable practices. This trend is consistent with early literature emphasizing sustainable agriculture to ensure food security in the face of climate change. Over time, keywords like “climate-smart agriculture” and “resilience” gained prominence, reflecting a shift towards adaptive strategies and resilience-building in agricultural systems. This shift aligns with global trends, where research on climate-smart agriculture (CSA) has grown significantly, emphasizing adaptive practices to enhance resilience. The association of specific authors with keywords highlights regional research trends. For example, authors like Singh A. and Srivastava J.P. are linked with terms like “climate change” and “agricultural systems,” indicating a strong focus on these topics in their regions. This pattern is consistent with findings from other studies documenting regional variations in climate resilience research. The evolving nature of research priorities, as illustrated by a thematic map, underscores the dynamic and adaptive nature of climate resilience research. This evolution mirrors broader literature, where research priorities have shifted in response to emerging challenges and new scientific insights. Comparing the thematic map with existing literature reveals common trends in the shifting focus of climate resilience research, the emergence of adaptive strategies, and regional variations in research priorities. Visualization aligns well with global patterns, highlighting the dynamic and multifaceted nature of research in this critical field. 6. Conclusion To sum up, the bibliometric review of climate resilience in agriculture from 2004 to 2024 reveals substantial growth and evolving trends in this critical research area. With 477 sources contributing to 1,000 documents and an impressive annual growth rate of 25.77%, the field has seen a significant increase in scholarly interest, reflected in an average of 10.15 citations per document and the involvement of 2,605 authors. The thematic analysis underscores the central role of “climate change” and its interconnectedness with “resilience,” “policy,” and “sustainable development,” highlighting the necessity for an integrated approach to address climate challenges. The annual publication trend, marked by a strong positive correlation ( R² = 0.7097 ) and linear growth, emphasizes the growing focus on adaptive strategies to mitigate climate impacts. Leading journals such as “Qeios Ltd,” “Handbook of Climate Change Resilience,” and “Sustainability” dominate the field, indicating both concentrated and interdisciplinary interests. The increasing prominence of terms like “Climate Change” and “Adaptation” reflects the evolving discourse and underscores the need for ongoing research and policy development. The co-authorship network reveals three distinct clusters of researchers, led by influential figures such as David D. Woods, Andrea Nowak, and David Zilberman, underscoring the collaborative nature of this research domain. Influential publications, highlighted by their Local Citation Scores, demonstrate both global and local impacts, contributing significantly to the academic discourse. The interconnectedness of key concepts like “climate change,” “agriculture,” and “adaptation,” as shown in the network visualization map, illustrates the multifaceted nature of climate resilience research. The historical citation network and word cloud visualization further emphasize the collaborative and cumulative nature of the field. Hierarchical clustering analysis and thematic maps reveal shifts in research priorities, from “food” and “sustainable agriculture” to “climate-smart agriculture” and “resilience,” reflecting evolving regional trends and research focuses. Overall, this review highlights the dynamic and interdisciplinary nature of climate resilience research in agriculture, advocating for continued collaboration, integrated policy frameworks, and adaptive strategies to effectively address the challenges posed by climate change. By leveraging these insights, stakeholders can develop more effective, evidence-based strategies to enhance climate resilience in agriculture, ultimately contributing to sustainable development and food security. By adopting these strategies, policymakers can create a more equitable and resilient agricultural sector, ensuring that all farmers have the resources and support they need to adapt to climate change. By addressing these areas and questions, future research can build on the current understanding of climate resilience in agriculture, leading to more effective and sustainable solutions. Declarations Acknowledgments: The authors are grateful to all the reviewers who have contributed to the improvement of this paper. Funding: No funds, grants, or other support was received. Financial interests: The authors have no relevant financial or non-financial interests to disclose. Declaration of competing interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Authors' contributions: Chimi: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing-original draft. Mala: Methodology, Validation, Visualization, Writing–review & editing. Fobane & Matick: Data curation, Formal analysis, Methodology, Validation, Visualization, Writing–review & editing. References M. G. Muluneh, « Impact of climate change on biodiversity and food security: a global perspective—a review article », Agric. Food Security. , vol. 10, n o 1, p. 36, sept. 2021, doi 10.1186/s40066-021-00318-5. K. Abbass, M. Z. Qasim, H. Song, M. Murshed, H. Mahmood, et I. Younis, « A review of the global climate change impacts, adaptation, and sustainable mitigation measures », Environ. Sci. Pollut. Res. , vol. 29, n o 28, p. 42539‑42559, juin 2022, doi: 10.1007/s11356-022-19718-6. V. Owino et al. , « The impact of climate change on food systems, diet quality, nutrition, and health outcomes: A narrative review », Front. Clim. , vol. 4, août 2022, doi: 10.3389/fclim.2022.941842. M. Berbés-Blázquez, C. L. Mitchell, S. L. Burch, et J. Wandel, « Understanding climate change and resilience: assessing strengths and opportunities for adaptation in the Global South », Clim. Change , vol. 141, n o 2, p. 227‑241, mars 2017, doi: 10.1007/s10584-017-1897-0. H. Alibašić, Strategic Resilience and Sustainability Planning: Management Strategies for Sustainable and Climate-Resilient Communities and Organizations . in Sustainable Development Goals Series. Cham: Springer International Publishing, 2022. doi: 10.1007/978-3-030-91159-1. M. A. Israel, J. Amikuzuno, et G. Danso-Abbeam, « Assessing farmers’ contribution to greenhouse gas emission and the impact of adopting climate-smart agriculture on mitigation », Ecol. Process. , vol. 9, n o 1, p. 51, sept. 2020, doi 10.1186/s13717-020-00249-2. H. Ritchie, P. Rosado, et M. Roser, « Environmental Impacts of Food Production », Our World Data , janv. 1970, Consulté le: 17 septembre 2024. [En ligne]. Disponible sur: https://ourworldindata.org/environmental-impacts-of-food A. Wezel, M. Casagrande, F. Celette, J.-F. Vian, A. Ferrer, et J. Peigné, « Agroecological practices for sustainable agriculture. A review », Agron. Sustain. Dev. , vol. 34, n o 1, p. 1‑20, janv. 2014, doi: 10.1007/s13593-013-0180-7. A. Wezel, B. G. Herren, R. B. Kerr, E. Barrios, A. L. R. Gonçalves, et F. Sinclair, « Agroecological principles and elements and their implications for transitioning to sustainable food systems. A review », Agron. Sustain. Dev. , vol. 40, n o 6, p. 40, oct. 2020, doi: 10.1007/s13593-020-00646-z. S. R. Gliessman, V. E. Méndez, V. M. Izzo, et E. W. Engles, Agroecology: Leading the transformation to a just and sustainable food system . CRC Press, 2022. Consulté le: 29 juillet 2024. [En ligne]. Disponible sur: https://www.taylorfrancis.com/books/mono/10.1201/9781003304043/agroecology-stephen-gliessman-ernesto-m%C3%A9ndez-victor-izzo-eric-engles Y. S. Hilmi, J. Tóth, Z. Gabnai, G. Király, et Á. Temesi, « Farmers’ resilience to climate change through the circular economy and sustainable agriculture: a review from developed and developing countries », Renew. Agric. Food Syst. , vol. 39, p. e15, 2024. J. Hellin, E. Fisher, M. Taylor, S. Bhasme, et A. M. Loboguerrero, « Transformative adaptation: from climate-smart to climate-resilient agriculture », CABI Agric. Biosci. , vol. 4, n o 1, p. 30, août 2023, doi: 10.1186/s43170-023-00172-4. P. M. Chimi et al. , « Factors affecting decision-making to strengthen the climate resilience of smallholder farms in the Centre Region of Cameroon », Clim. Smart Agric. , p. 100004, 2024. R. Belmin, M. Paulin, et E. Malézieux, « Adapting agriculture to climate change: which pathways behind policy initiatives? », Agron. Sustain. Dev. , vol. 43, n o 5, p. 59, août 2023, doi: 10.1007/s13593-023-00910-y. M. A. Zwolińska-Ligaj et D. J. Guzal-Dec, « Rural Area Resilience during the COVID-19 Pandemic as Exemplified by Urban–Rural Communes in Poland », Sustainability , vol. 16, n o 12, Art. n o 12, janv. 2024, doi: 10.3390/su16125073. Z. Han, Y.-C. Youn, S. Kim, et H. Choe, « Improving Farmer Livelihood Resilience to Climate Change in Rural Areas of Inner Mongolia, China », Agriculture , vol. 13, n o 10, Art. n o 10, oct. 2023, doi 10.3390/agriculture13102030. Y. Buitenhuis et al. , « Policies and Farming System Resilience: A Bottom-Up Analysis », in Resilient and Sustainable Farming Systems in Europe: Exploring Diversity and Pathways , A. Garrido, A. Spiegel, B. Soriano, E. Mathijs, J. Urquhart, M. P. M. Meuwissen, et P. H. Feindt, Éd., Cambridge: Cambridge University Press, 2022, p. 63‑87. doi: 10.1017/9781009093569.005. H. Wang, X. Zhao, et J. He, « Global Climate Governance and International Cooperation », in China’s Long-Term Low-Carbon Development Strategies and Pathways , 2021, p. 285. Consulté le: 17 septembre 2024. [En ligne]. Disponible sur: https://repository.ust.hk/ir/Record/1783.1-116730 N. N. Omoyo, K. Susan, O. J. Ouma, et M. Donghui, « Harmonizing disaster risk reduction and climate change adaptation frameworks for risk-informed development planning in Sub-Saharan Africa: The case of Uganda and Malawi », J. Sustain. Dev. , vol. 15, n o 5, p. 22‑38, 2022. C. Ogbonna, E. Albrecht, C. Ugochukwu, C. Nwajiuba, et R. Onyeneke, « Climate Resilience in African Coastal Areas: Scaling Up Institutional Capabilities in the Niger Delta Region », in Handbook of Climate Change Resilience , W. Leal Filho, Éd., Cham: Springer International Publishing, 2020, p. 29‑49. doi: 10.1007/978-3-319-93336-8_9. S. Roy, « Livelihood Resilience of the Indigenous Munda Community in the Bangladesh Sundarbans Forest », in Handbook of Climate Change Resilience , W. Leal Filho, Éd., Cham: Springer International Publishing, 2020, p. 51‑72. doi: 10.1007/978-3-319-93336-8_10. A. Saleem Khan, K. MacManus, J. Mills, M. Madajewicz, et L. Ramasubramanian, « Building Resilience of Urban Ecosystems and Communities to Sea-Level Rise: Jamaica Bay, New York City », in Handbook of Climate Change Resilience , W. Leal Filho, Éd., Cham: Springer International Publishing, 2020, p. 95‑115. doi: 10.1007/978-3-319-93336-8_29. M. C. S. Lalika, « Resilience in Climate Stressed Environment Through Water Grabbing », in Handbook of Climate Change Resilience , W. Leal Filho, Éd., Cham: Springer International Publishing, 2020, p. 269‑293. doi: 10.1007/978-3-319-93336-8_68. P. Ferguson, L. Wollersheim, et M. Lowe, « Approaches to Climate Resilience », in The Palgrave Handbook of Climate Resilient Societies , Cham: Springer International Publishing, 2020, p. 1‑25. doi: 10.1007/978-3-030-32811-5_97-1. M. M. Guja et S. B. Bedeke, « Smallholders’ climate change adaptation strategies: exploring effectiveness and opportunities to be capitalized », Environ. Dev. Sustain. , mars 2024, doi: 10.1007/s10668-024-04750-y. D. El Chami, A. Daccache, et M. El Moujabber, « How Can Sustainable Agriculture Increase Climate Resilience? A Systematic Review », Sustainability , vol. 12, n o 8, Art. n o 8, janv. 2020, doi: 10.3390/su12083119. A. J. Zautra et J. W. Reich, « Resilience: The Meanings, Methods, and Measures of a Fundamental Characteristic of Human Adaptation », in The Oxford Handbook of Stress, Health, and Coping , S. Folkman, Éd., Oxford University Press, 2010, p. 0. doi: 10.1093/oxfordhb/9780195375343.013.0009. J. Dusdal et J. J. W. Powell, « Benefits, Motivations, and Challenges of International Collaborative Research: A Sociology of Science Case Study », Sci. Public Policy , vol. 48, n o 2, p. 235‑245, avr. 2021, doi: 10.1093/scipol/scab010. Y. C. Fu, M. Marques, Y.-H. Tseng, J. J. W. Powell, et D. P. Baker, « An evolving international research collaboration network: spatial and thematic developments in co-authored higher education research, 1998–2018 », Scientometrics , vol. 127, n o 3, p. 1403‑1429, mars 2022, doi: 10.1007/s11192-021-04200-w. D. W. Hook, S. J. Porter, H. Draux, et C. T. Herzog, « Real-Time Bibliometrics: Dimensions as a Resource for Analyzing Aspects of COVID-19 », Front. Res. Metr. Anal. , vol. 5, janv. 2021, doi 10.3389/frma.2020.595299. C. Herzog, D. Hook, et S. Konkiel, « Dimensions: Bringing down barriers between scientometrics and data », Quant. Sci. Stud. , vol. 1, n o 1, p. 387‑395, févr. 2020, doi: 10.1162/qss_a_00020. C. S. Rao, A. K. Shanker, C. Shanker, C. S. Rao, A. K. Shanker, et C. Shanker, Climate Resilient Agriculture - Strategies and Perspectives . 2018. doi: 10.5772/intechopen.68382. A. Aich, D. Dey, et A. Roy, « Climate change resilient agricultural practices: A learning experience from Indigenous communities over India », PLOS Sustain. Transform. , vol. 1, n o 7, p. e0000022, 2022. M. Shehzad et al. , « Climate Resilience in Agriculture », in Building Climate Resilience in Agriculture: Theory, Practice and Future Perspective , W. N. Jatoi, M. Mubeen, A. Ahmad, M. A. Cheema, Z. Lin, et M. Z. Hashmi, Éd., Cham: Springer International Publishing, 2022, p. 67‑82. doi: 10.1007/978-3-030-79408-8_5. M. A. Altieri, C. I. Nicholls, A. Henao, et M. A. Lana, « Agroecology and the design of climate change-resilient farming systems », Agron. Sustain. Dev. , vol. 35, n o 3, p. 869‑890, juill. 2015, doi: 10.1007/s13593-015-0285-2. B. B. Lin, « Resilience in Agriculture through Crop Diversification: Adaptive Management for Environmental Change », BioScience , vol. 61, n o 3, p. 183‑193, mars 2011, doi: 10.1525/bio.2011.61.3.4. M. Reckling, C. A. Watson, A. Whitbread, et K. Helming, « Diversification for sustainable and resilient agricultural landscape systems », Agron. Sustain. Dev. , vol. 43, n o 4, p. 44, juill. 2023, doi: 10.1007/s13593-023-00898-5. J. Alvar-Beltrán, A. Dao, A. Dalla Marta, A. Heureux, J. Sanou, et S. Orlandini, « Farmers’ Perceptions of Climate Change and Agricultural Adaptation in Burkina Faso », Atmosphere , vol. 11, n o 8, Art. n o 8, août 2020, doi: 10.3390/atmos11080827. J. Glennie, « A greener Burkina: sustainable farming techniques, land reclamation, and improved livelihoods », ODI: Think change. Consulté le: 17 septembre 2024. [En ligne]. Disponible sur: https://odi.org/en/publications/a-greener-burkina-sustainable-farming-techniques-land-reclamation-and-improved-livelihoods/ F. Frimpong et al. , « Water-smart farming: a review of strategies, technologies, and practices for sustainable agricultural water management in a changing climate in West Africa », Front. Sustain. Food Syst. , vol. 7, nov. 2023, doi: 10.3389/fsufs.2023.1110179. R. M. Sabir et al. , « Managing Water Resources for Sustainable Agricultural Production », in Transforming Agricultural Management for a Sustainable Future: Climate Change and Machine Learning Perspectives , S. Kanga, S. K. Singh, K. Shevkani, V. Pathak, et B. Sajan, Éd., Cham: Springer Nature Switzerland, 2024, p. 47‑74. doi: 10.1007/978-3-031-63430-7_3. J. Alvar-Beltrán, I. Elbaroudi, A. Gialletti, A. Heureux, L. Neretin, et R. Soldan, « Climate resilient practices: typology and guiding material for climate risk screening », FAO Rome , vol. 36, 2021. Y. Wu, S. Meng, C. Liu, W. Gao, et X.-Z. Liang, « A bibliometric analysis of research for climate impact on agriculture », Front. Sustain. Food Syst. , vol. 7, juill. 2023, doi: 10.3389/fsufs.2023.1191305. S. Poudel, R. Thapa, et B. Mishra, « A Farmer-Centric Cost–Benefit Analysis of Climate-Smart Agriculture in the Gandaki River Basin of Nepal », Climate , vol. 12, n o 9, Art. n o 9, sept. 2024, doi 10.3390/cli12090145. X. Zhao et al. , « Changing trends in the clinical research literature on PubMed database from 1991 to 2020 », Eur. J. Med. Res. , vol. 27, n o 1, p. 95, juin 2022, doi: 10.1186/s40001-022-00717-9. X. Gu et K. L. Blackmore, « Recent trends in academic journal growth », Scientometrics , vol. 108, n o 2, p. 693‑716, août 2016, doi: 10.1007/s11192-016-1985-3. M. Thelwall et P. Sud, « Scopus 1900–2020: Growth in articles, abstracts, countries, fields, and journals », Quant. Sci. Stud. , vol. 3, n o 1, p. 37‑50, avr. 2022, doi: 10.1162/qss_a_00177. B. Mougenot et J.-P. Doussoulin, « A bibliometric analysis of the Global Reporting Initiative (GRI): global trends in developed and developing countries », Environ. Dev. Sustain. , vol. 26, n o 3, p. 6543‑6560, mars 2024, doi: 10.1007/s10668-023-02974-y. L. Bornmann, R. Haunschild, et R. Mutz, « Growth rates of modern science: a latent piecewise growth curve approach to model publication numbers from established and new literature databases », Humanit. Soc. Sci. Commun. , vol. 8, n o 1, Oct. 2021, doi: 10.1057/s41599-021-00903-w. S. E. Werners et al. , « Advancing climate-resilient development pathways since the IPCC’s fifth assessment report », Environ. Sci. Policy , vol. 126, p. 168‑176, 2021. L. C. Stringer et al. , « Adaptation and development pathways for different types of farmers », Environ. Sci. Policy , vol. 104, p. 174‑189, févr. 2020, doi: 10.1016/j.envsci.2019.10.007. L. C. Stringer, N. P. Simpson, E. L. F. Schipper, et S. H. Eriksen, « Climate Resilient Development Pathways in Global Drylands », Anthr. Sci. , juill. 2022, doi: 10.1007/s44177-022-00027-z. L. Kassier, « Interconnected or Disconnected? A Review of Sustainability, Resilience, and Sustainable Business Model Constructs in the Academic Business Literature », J. Knowl. Econ. , janv. 2024, doi: 10.1007/s13132-023-01712-z. A. Karmaoui, G. Yoganandan, D. Sereno, K. Shaukat, S. El Jaafari, et L. Hajji, « Global network analysis of links between business, climate change, and sustainability and setting up the interconnections framework », Environ. Dev. Sustain. , sept. 2023, doi: 10.1007/s10668-023-03883-w. W. Ma et D. B. Rahut, « Climate-smart agriculture: adoption, impacts, and implications for sustainable development », Mitig. Adapt. Strategy. Glob. Change , vol. 29, n o 5, p. 44, avr. 2024, doi: 10.1007/s11027-024-10139-z. M. J. Usigbe, S. Asem-Hiablie, D. D. Uyeh, O. Iyiola, T. Park, et R. Mallipeddi, « Enhancing resilience in agricultural production systems with AI-based technologies », Environ. Dev. Sustain. , vol. 26, n o 9, p. 21955‑21983, Sept. 2024, doi: 10.1007/s10668-023-03588-0. K. Heider, J. M. Rodriguez Lopez, A. Bischoff, A. L. Balbo, et J. Scheffran, « Toward climate-resilient and biodiverse agriculture in the Mediterranean region: experiences and perceptions of farmers engaged in sustainable food production », Org. Agric. , vol. 13, n o 4, p. 513‑529, déc. 2023, doi: 10.1007/s13165-023-00444-3. C. G. Díaz, D. Zambrana-Vasquez, et C. Bartolomé, « Building Resilient Cities: A Comprehensive Review of Climate Change Adaptation Indicators for Urban Design », Energies , vol. 17, n o 8, Art. n o 8, janv. 2024, doi: 10.3390/en17081959. L. Zhai et J.-E. Lee, « Investigating Vulnerability, Adaptation, and Resilience: A Comprehensive Review within the Context of Climate Change », Atmosphere , vol. 15, n o 4, Art. n o 4, avr. 2024, doi 10.3390/atmos15040474. H. Pallubinsky, R. P. Kramer, et W. D. van Marken Lichtenbelt, « Establishing resilience in times of climate change—a perspective on humans and buildings », Clim. Change , vol. 176, n o 10, p. 135, Sept. 2023, doi: 10.1007/s10584-023-03614-0. R. Ma, N. Abid, S. Yang, et F. Ahmad, « From crisis to resilience: strengthening climate action in OECD countries through environmental policy and energy transition », Environ. Sci. Pollut. Res. , vol. 30, n o 54, p. 115480‑115495, oct. 2023, doi: 10.1007/s11356-023-29970-z. Additional Declarations The authors declare no competing interests. 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. 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05:56:07","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":155787,"visible":true,"origin":"","legend":"\u003cp\u003eVisualization of citation sources in agricultural climate resilience from 2004 to 2024.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-5112075/v1/80717eff29d622b43c4127b4.png"},{"id":64890202,"identity":"793729bf-42dc-4abb-9b6a-034922a59eb9","added_by":"auto","created_at":"2024-09-20 05:56:08","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":109273,"visible":true,"origin":"","legend":"\u003cp\u003eBibliographic coupling network in climate resilience in agriculture from 2004 to 2024.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-5112075/v1/7a68e4010a2ed27e7bde0634.png"},{"id":64890203,"identity":"4545ab4e-988e-4f18-a356-51d343a859f6","added_by":"auto","created_at":"2024-09-20 05:56:08","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":111139,"visible":true,"origin":"","legend":"\u003cp\u003eHistorical co-citation network of highly cited papers in agricultural climate resilience. Note: Different colors denote distinct co-citation clusters.\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-5112075/v1/c7785f0d1f19cc75f9c61c56.png"},{"id":64890577,"identity":"6f5038eb-ca14-41e4-b549-f43baf4d2a41","added_by":"auto","created_at":"2024-09-20 06:04:08","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":201341,"visible":true,"origin":"","legend":"\u003cp\u003eFrequently occurring keywords and their rates of occurrence in agricultural climate resilience.\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-5112075/v1/d0449e65a4d67c2e7030e55e.png"},{"id":64890576,"identity":"b3bee6c6-8973-4a8f-84c2-e749b04660f6","added_by":"auto","created_at":"2024-09-20 06:04:07","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":101251,"visible":true,"origin":"","legend":"\u003cp\u003eHierarchical cluster analysis of frequently occurring keywords in agricultural climate resilience. Note: Different colors in the figure indicate distinct clusters.\u003c/p\u003e","description":"","filename":"15.png","url":"https://assets-eu.researchsquare.com/files/rs-5112075/v1/8870d3687fee835b1754940d.png"},{"id":64890207,"identity":"fde5d6d0-2610-422e-8ae5-95573bb35796","added_by":"auto","created_at":"2024-09-20 05:56:08","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":338975,"visible":true,"origin":"","legend":"\u003cp\u003eTheme evolution in climate resilience from 2004 to 2024.\u003c/p\u003e","description":"","filename":"16.png","url":"https://assets-eu.researchsquare.com/files/rs-5112075/v1/02dad6aaeb34a712d5d52319.png"},{"id":64891588,"identity":"f96209e1-fec1-42bf-b85f-60c803878fe8","added_by":"auto","created_at":"2024-09-20 06:20:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3669028,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5112075/v1/d31637c2-40a5-492b-91b3-604e05079827.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eA two-decade bibliometric review of climate resilience in agriculture using the dimensions platform\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eClimate change is a major threat to global agriculture\u0026nbsp;[1], [2]. It affects food production and food security. Changes in temperature, erratic rainfall, and an increase in the frequency and intensity of extreme weather events, such as droughts and floods, disrupt crop growth cycles and reduce agricultural yields\u0026nbsp;[3]. These disruptions exacerbate existing challenges, such as soil degradation and water scarcity, and threaten farmers' livelihoods, especially in vulnerable regions. In the face of these challenges, the development of climate resilience strategies is essential to ensure the sustainability of agricultural systems and long-term food security\u0026nbsp;[4], [5]. Due to the increasing impacts of climate change on agricultural systems, climate resilience in agriculture has become a global priority. Extreme weather events, such as droughts, floods, and heat waves, are disrupting agricultural production cycles and threatening food security and the livelihoods of farmers. Agriculture will need not only to adapt to these changes but also to help reduce GHG emissions\u0026nbsp;[6], [7]. Sustainable agricultural practices, such as agroecology, play a crucial role in this adaptation. They improve the resilience of farming systems while reducing their environmental footprint\u0026nbsp;[8], [9], [10].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClimate resilience in agriculture is a rapidly growing area of research. However, several gaps remain. The lack of integrative studies that combine the socio-economic and environmental aspects of adaptation strategies has been identified as one of the main gaps. Most research focuses on either the technical aspects of agricultural practices or the socio-economic impacts. Often these are not linked holistically\u0026nbsp;[11], [12], [13]. This bibliometric review using the Dimensions platform addresses this gap by providing a comprehensive analysis of research trends and international cooperation, while also highlighting the interplay between the different dimensions of climate change adaptation1. In particular, it provides new perspectives on how to adapt by identifying: (i) identifying innovative practices, (ii) analyzing public policies, (iii) fostering collaborations, (iv) and proposing models of resilience.\u003c/p\u003e\n\u003cp\u003eBy highlighting innovative agricultural practices that have worked in different climatic contexts, this study provides a better understanding of which strategies are most effective and why. By examining public policies and their impact on agricultural resilience, this review provides valuable insights to steer future policies toward more integrated and sustainable approaches\u0026nbsp;[14], [15], [16], [17]. By mapping international cooperation, the review highlights the importance of global partnerships to strengthen climate resilience through the sharing of knowledge and resources\u0026nbsp;[18], [19]. This review proposes resilience models that can be adapted to different local contexts, providing tailor-made solutions for farmers by integrating socio-economic and environmental data.\u003c/p\u003e\n\u003cp\u003eClimate change poses unprecedented challenges to global agriculture, with implications for production, food security, and farmers' livelihoods. Extreme weather events such as droughts, floods, and heatwaves are becoming more frequent and intense [6], [7]. They threaten the stability of agricultural systems. Climate resilience, defined as the ability of agricultural systems to anticipate, absorb, and recover from climate shocks, is essential [20], [21], [22], [23], [24]. However, there is a wide variety of resilience practices and strategies. Their effectiveness varies according to local contexts and crop types [25], [26], [27]. The Dimensions platform provides a unique opportunity to analyze the trends in research, international collaborations, and the main areas of interest in the field [28], [29]. Understanding how current research contributes to strengthening agricultural climate resilience, what gaps exist, and how future research can be directed to meet farmers' needs in the face of climate challenges is therefore the central question of this bibliometric review.\u003c/p\u003e"},{"header":"2. Literature review","content":"\u003cp\u003e\u003cstrong\u003e2.1. Dimensions platform\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.1. Definition \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDeveloped by Digital Science, Dimensions is an advanced bibliometric analysis platform [30], [31]. It provides powerful tools for exploring and analyzing scientific publications, citing, funding, and collaborating [30]. Users can access a huge database of millions of publications and benefit from interactive visualizations. They can identify research trends, assess the impact of work, and discover opportunities for collaboration. The platform is designed to help researchers, institutions and decision-makers gain a deep insight into the scientific output of the world. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.2. Dimensions platform benefits\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Dimensions platform offers several key benefits: a comprehensive database, advanced analytics, citations and impact, customized search, data integration, access to alternative metrics, and ease of use, making it a powerful tool for bibliometrics and research analysis [30], [31]. Dimensions provide access to a large database of publications, patents, funding, and clinical trials. It gives a comprehensive view of research activity across a range of fields. Dimensions make it easy to explore research trends, measure the impact of publications, and identify collaborations between researchers and institutions with sophisticated visualization and analysis features [30]. The platform provides tools for tracking the citations of articles, assessing the impact of publications and authors, and measuring the performance of scientific and scholarly journals. Dimensions allow users to create customized searches and alerts [29], [30], [31]. These can be used to track developments in specific fields or to monitor specific authors and institutions. It provides a more holistic view of scientific productivity by integrating data on funding and research projects to understand the relationships between funding, publications, and research outcomes. Dimensions provide alternative metrics (altmetrics) to assess the engagement and reach of research beyond academic publications, in addition to traditional metrics such as impact factors [30], [31]. Dimensions make research analysis accessible to those without deep bibliometric expertise through an intuitive user interface. In short, Dimensions stands out for its close integration of the various facets of research, providing a comprehensive and detailed view that can help researchers, institutions, and policymakers to better understand and optimize their research activities [30], [31].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.3. Dimensions platform limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite the many advantages that Dimensions offers to bibliometrics, it also has several limitations:\u003c/p\u003e\n\u003cp\u003e\u0026middot; Inconsistency of coverage\u003c/p\u003e\n\u003cp\u003eDespite the breadth of its data, Dimensions may not cover all publications, especially those from lesser-known or niche journals. This may introduce bias into the analysis [30], [31].\u003c/p\u003e\n\u003cp\u003e\u0026middot; Data availability\u003c/p\u003e\n\u003cp\u003eSome advanced features or specific data may only be available to paying subscribers or institutions with a full subscription. This may limit access for individual users or small institutions [30], [31].\u003c/p\u003e\n\u003cp\u003e\u0026middot; Metrics complexity\u003c/p\u003e\n\u003cp\u003eIt can be difficult to select the most relevant metrics for a particular analysis due to the variety of metrics available. Alternative metrics (such as altmetrics) may also be more controversial or less widely accepted in some disciplines than others [30], [31].\u003c/p\u003e\n\u003cp\u003e\u0026middot; Data quality issues \u003c/p\u003e\n\u003cp\u003eDimensions are subject to data errors and gaps, as is any database. Authors, institutions, and cited information may sometimes be incorrect or incomplete [30], [31].\u003c/p\u003e\n\u003cp\u003e\u0026middot; Visibility bias \u003c/p\u003e\n\u003cp\u003eThe platform may favor the visibility of publications and researchers from better-funded or more established institutions. This may lead to bias in the assessment of research [30], [31].\u003c/p\u003e\n\u003cp\u003e\u0026middot; Platform dependence \u003c/p\u003e\n\u003cp\u003eOverdependence on Dimensions can limit researchers\u0026apos; ability to use other tools or databases offering different perspectives or complementary data [30], [31].\u003c/p\u003e\n\u003cp\u003e\u0026middot; Updating and developing \u003c/p\u003e\n\u003cp\u003eBibliometric databases and tools are evolving at a rapid pace, and Dimensions may need to be updated frequently to keep up with new publishing practices and developments in the field of research [30], [31].\u003c/p\u003e\n\u003cp\u003e\u0026middot; Data aggregation \u003c/p\u003e\n\u003cp\u003eConcentrating data in a single system can lead to problems of transparency and accountability, especially if the data are not easily accessible or comparable with those from other sources [30], [31].\u003c/p\u003e\n\u003cp\u003eTo conclude, although Dimensions is a valuable tool for bibliometric analysis, it is important to use it in conjunction with other sources and methods to obtain a complete and balanced picture of research activity[30], [31].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Climate resilience\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.1. Definition and importance \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClimate resilience in agriculture refers to the ability of agricultural systems to withstand the impacts of climate change, to adapt to them, and to recover from them. It also includes the management of risks associated with extreme weather events, such as droughts and floods [32], [33], [34].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.2. Adaptation strategies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAgroecology, crop diversification, and the use of varieties that can withstand extreme weather conditions are some of the adaptation strategies in agriculture. For example, agroecology, which is the sustainable management of ecosystems, is often cited as an effective approach to resilience building [35], [36], [37].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.3. Case study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCase studies, such as those carried out in Burkina Faso, show how farmers are adapting their practices to help cope with changing climates [38], [39]. These adaptations include improved water conservation techniques and the use of drought-resistant crops [40], [41].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Agricultural policies and standards \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAgricultural policies have a crucial role to play in promoting resilience to climate change. International initiatives, such as those led by FAO, encourage adopting sustainable and resilient agricultural practices [42].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4. Dimensions platform research\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Dimensions platform was used to conduct bibliometric searches. Results were filtered by publication type (journal articles, conferences, book chapters, etc.), publication period (e.g. since 1984), and specific research areas [30], [31].\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003e\u003cstrong\u003e3.1.\u0026nbsp;Data extracted\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe metadata of the selected publications, including the title, the authors, the affiliations, the abstracts, the keywords, and the citations, were downloaded. Text mining tools were used to analyze abstracts and keywords to identify research trends and key themes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.\u0026nbsp;Collaboration network analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNetwork visualization software (e.g. VOSviewer or Gephi) was used to map collaborations between authors and institutions. The main research centers and international collaborations were the focus of the analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.\u0026nbsp;Analyzing citations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe impact of publications has been assessed using an analysis of the number of citations. The most influential articles and journals in the field of climate resilience in agriculture were identified.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.\u0026nbsp;Summarising the results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collected was collated to identify research trends, gaps, and future opportunities. A report on the results of the bibliometric analysis and recommendations for future research has been written.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.\u0026nbsp;Analytical techniques justification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.1.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The bibliometric analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe bibliometric analysis makes it possible to quantify and visualize research trends, collaborations, and the impact of publications in the field of climate resilience in agriculture\u0026nbsp;[43],\u0026nbsp;[44]. To identify key players, international collaborations, and emerging research areas, this technique is essential. It provides an overview of the current scientific efforts and the gaps in knowledge.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.2.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Text extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe extraction and analysis of textual information from the abstracts and keywords of publications. Recurring themes and new trends in scientific publications can be identified through text mining. This helps to understand research priorities and proposed adaptation strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.3.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Collaboration network analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMapping of collaborations between authors and institutions. This analysis reveals key research networks and partnerships. It highlights international collaborations that are critical to building climate resilience in agriculture1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.4.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Citation analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalyze the number of citations received to assess the impact of publications. Citations indicate how influential and relevant the research is. To help guide future research, this analysis helps identify the most influential papers and the most cited journals1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.5.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Data visualisation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of bibliometric analysis can be presented graphically using visualization tools. Data visualization makes it easier to understand complex trends and the relationships between different elements of the research. It makes it possible to communicate effectively to researchers and to those seeking to influence policy.\u003c/p\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1. Analysis of the number of articles issued and the publishing journal\u003c/h2\u003e\n \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\n \u003ch2\u003e4.1.1. Annual trends in the number of publications\u003c/h2\u003e\n \u003cp\u003eThe data indicates that from 2004 to 2024, 477 sources, including journals and books, contributed to 1,000 documents. The annual growth rate of publications was 25.77%, with an average document age of 4.31 years. Each document received an average of 10.15 citations, and collectively, they cited 17,136 references. There were 2,605 authors, with 255 single-authored documents, averaging 3.21 authors per document. Additionally, the publications included 26 books, 214 book chapters, 9 conference proceedings articles, 14 datasets, 13 dissertations, 1 editorial, 460 journal articles, 3 journal issues, 1 news article, 9 other types of documents, 22 preprints, 15 reports, and 69 review articles (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrimary details regarding data.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePeriod\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2004: 2024\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSources (Journals, Books, etc)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e477\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDocuments\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnnual Growth Rate %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDocument Average Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage citations per doc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReferences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKeywords Plus (ID)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAuthor\u0026apos;s Keywords (DE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAuthors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2605\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAuthors of single-authored docs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle-authored docs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e291\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo-Authors per Doc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBook\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBook chapter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComponent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConference proceedings article\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDataset\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDissertation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEditorial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJournal article\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e460\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJournal issue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNews\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreprint\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReport\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\n \u003ch2\u003e4.1.2. Thematic map\u003c/h2\u003e\n \u003cp\u003eThe thematic map illustrates the central role of \u0026ldquo;climate change\u0026rdquo; and its interconnectedness with various themes such as \u0026ldquo;resilience,\u0026rdquo; \u0026ldquo;policy,\u0026rdquo; and \u0026ldquo;sustainable development.\u0026rdquo; These connections highlight the multifaceted nature of climate change, emphasizing how it influences and is influenced by different aspects of society and the environment. For instance, the link between \u0026ldquo;climate change\u0026rdquo; and \u0026ldquo;resilience\u0026rdquo; suggests a focus on adaptive strategies, while the connection to \u0026ldquo;policy\u0026rdquo; underscores the importance of governance in addressing climate issues. The map effectively visualizes the complex web of relationships, demonstrating the integrated approach needed to tackle climate change (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the annual publication trend of climate resilience in agriculture from 2004 to 2024, showing a clear upward trajectory. This trend is further emphasized by the linear equation (\u003cem\u003ey\u0026thinsp;=\u0026thinsp;7.3838x \u0026minus;\u0026thinsp;233.62\u003c/em\u003e) and an (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) value of 0.7097, indicating a strong positive correlation between the years and the number of publications. Consequently, the increasing number of publications suggests a growing scholarly interest and recognition of the importance of climate resilience in agriculture. Therefore, this trend underscores the escalating focus on developing adaptive strategies to mitigate climate impacts on agriculture (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec28\" class=\"Section3\"\u003e\n \u003ch2\u003e4.1.3. Analysis of publishing journals\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e presents the top 10 journals with the most publications on climate resilience in agriculture from 2004 to 2024. Notably, \u0026ldquo;Qeios Ltd\u0026rdquo; leads with 69 articles, indicating its significant contribution to this field. Following this, the \u0026ldquo;Handbook of Climate Change Resilience\u0026rdquo; and \u0026ldquo;Sustainability\u0026rdquo; have published 32 and 13 articles, respectively, highlighting their roles in disseminating research. Additionally, the remaining journals, such as \u0026ldquo;The International Journal of Environment and Climate Change\u0026rdquo; and \u0026ldquo;Climatic Change,\u0026rdquo; contribute fewer articles, ranging from 10 to 7. This distribution suggests that while a few journals dominate the publication landscape, there is a broad interest across various journals, reflecting the interdisciplinary nature of climate resilience research in agriculture (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLeading 10 journals with the highest number of articles on agricultural climate resilience from 2004 to 2024.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSources\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eArticles\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQeios ltd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHandbook of Climate Change Resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSustainability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInternational journal of environment and climate change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZenodo (cern European organization for nuclear research)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuilding Resilience to Climate Change in South Caucasus Agriculture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClimatic change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResearch papers in economics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClimate change management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGreen infrastructure and urban climate resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLand use policy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e tracks the frequency of specific terms from 2004 to 2024, revealing significant trends. Notably, terms like \u0026lsquo;Climate Change\u0026rsquo; and \u0026lsquo;Adaptation\u0026rsquo; show a steep increase, indicating a growing emphasis on these topics over time. Conversely, terms such as \u0026lsquo;Adaptive Capacity\u0026rsquo; and \u0026lsquo;Climate Smart Agriculture\u0026rsquo; exhibit a more gradual rise, suggesting a steady but less pronounced focus. This cumulative increase in mentions underscores the escalating importance of climate-related discussions in literature, reflecting heightened awareness and concern about climate issues. Consequently, the graph highlights the evolving discourse on climate resilience and its various facets, emphasizing the need for continued research and policy development in this area (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e tracks the cumulative occurrences of various sources from 2004 to 2024. Notably, there has been a significant increase in the production of sources related to climate change topics, particularly around 2014 to 2016, and a sharp rise starting around 2020. This trend suggests a growing scholarly and research interest in climate resilience and related fields. Consequently, sources like \u0026ldquo;Building Resilience to Climate Change in South Caucasus Agriculture\u0026rdquo; and \u0026ldquo;Green Infrastructure and Urban Climate Resilience\u0026rdquo; have seen substantial increases, indicating their importance in the discourse. Therefore, the figure highlights the expanding focus on climate change research, reflecting heightened awareness and urgency in addressing climate-related challenges (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2. Analysis of Key Researchers\u003c/h2\u003e\n \u003cdiv id=\"Sec30\" class=\"Section3\"\u003e\n \u003ch2\u003e4.2.1. Analysis of Key Researchers\u003c/h2\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the changes in output over time in climate resilience in agriculture, authored by various researchers from 2004 to 2024. The size of each bubble represents the number of documents published by an author, while the color shade indicates the number of citations. Notably, authors like Neumann JE and Gaupp F have consistently contributed over multiple years, suggesting sustained research interest. Conversely, authors such as Bodirsky BL and Kumareswami K show sporadic contributions, indicating focused studies at particular intervals. Additionally, larger bubbles in certain years highlight peaks in research output, reflecting pivotal studies that garnered significant attention. Therefore, this chart underscores both the productivity and impact of research in climate resilience, emphasizing the importance of ongoing contributions to this field (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec31\" class=\"Section3\"\u003e\n \u003ch2\u003e4.2.2. Authors\u0026rsquo; impact of climate resilience on agriculture\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e provides a detailed overview of various bibliometric indicators for ten authors. The h_index, which measures the number of highly cited papers, is relatively consistent across authors, indicating a similar level of influence. The g_index, reflecting the overall citation performance, varies slightly more, suggesting differences in the breadth of impactful work. The m_index, which normalizes impact over time, shows lower values for newer authors like Luginaah I. and Mohammed K., indicating their recent entry into academia. Total citations (TC) vary significantly, with Asfaw S. having the highest at 339, highlighting substantial influence. The number of publications (NP) is mostly uniform, except for a few outliers, suggesting consistent research output. Finally, the publication year start (PY_start) spans from 2010 to 2021, showing a mix of established and emerging researchers in the field. This table collectively underscores the diverse yet impactful contributions of these authors to climate resilience in agriculture.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAuthors\u0026rsquo; regional influence.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eh_index\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eg_index\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003em_index\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePY_start\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLuginaah I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMohammed K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSperanza CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlam GMM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArslan A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsfaw S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAwazi NP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBatley J\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBatung E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBraimoh AK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe co-authorship network visualization illustrates the collaborative relationships among researchers in the field of climate resilience in agriculture. The network is divided into three distinct clusters, each color-coded to represent different groups of researchers. The blue cluster includes key authors like David D. Woods and Andrew Dougill, indicating their frequent collaboration. The green cluster features Andrea Nowak, Peter Steward, Todd S. Rosenstock, and Erika Berglund, suggesting a strong collaborative network among them. The red cluster, with David Zilberman, Nancy McCarthy, and Sara Savastano, highlights another significant group of collaborators. This visualization underscores the interconnected nature of research in this field, showing how different groups of researchers work together to advance knowledge and innovation in climate resilience and agriculture (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec32\" class=\"Section3\"\u003e\n \u003ch2\u003e4.2.3. Co-occurrence\u003c/h2\u003e\n \u003cp\u003eThe network visualization map illustrates the interconnectedness of various concepts related to climate resilience in agriculture from 2004 to 2024. Central terms like \u0026ldquo;climate change,\u0026rdquo; \u0026ldquo;agriculture,\u0026rdquo; and \u0026ldquo;adaptation\u0026rdquo; have larger nodes, indicating their key importance in the research field. Smaller nodes such as \u0026ldquo;sustainable agriculture\u0026rdquo; and \u0026ldquo;climate-smart agriculture\u0026rdquo; are also significant, showing their relevance within the broader context. The lines connecting these nodes represent the relationships between different concepts, while the color-coded clusters highlight sub-themes or closely related ideas. This visualization effectively demonstrates how different aspects of climate resilience in agriculture are interrelated, emphasizing the multifaceted nature of the research and the need for an integrated approach to address climate challenges in agriculture (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe overlay visualization map of climate resilience in agriculture from 2004 to 2024 reveals significant trends and interconnections in research topics over the past two decades. Initially, research focused on fundamental concepts such as \u0026ldquo;climate change\u0026rdquo; and \u0026ldquo;agriculture,\u0026rdquo; as indicated by the blue nodes representing earlier years. As time progressed, the focus shifted towards more specific and applied topics like \u0026ldquo;sustainable agriculture,\u0026rdquo; \u0026ldquo;crop adaptation,\u0026rdquo; and \u0026ldquo;biodiversity,\u0026rdquo; which are represented by yellow nodes, indicating recent years. This evolution suggests a growing recognition of the need for sustainable practices and adaptive strategies in response to climate change. Moreover, the dense clustering of terms such as \u0026ldquo;human activities,\u0026rdquo; \u0026ldquo;ecological impacts,\u0026rdquo; and \u0026ldquo;mitigation strategies\u0026rdquo; underscores the complexity and interdisciplinary nature of this research field. Consequently, the map highlights the increasing importance of integrating various aspects of climate resilience to develop comprehensive and effective solutions for agricultural sustainability (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe density visualization of climate resilience in agriculture from 2004 to 2024, generated by VOSviewer, reveals several key insights. Initially, the research predominantly focused on broad terms such as \u0026ldquo;climate change\u0026rdquo; and \u0026ldquo;agriculture,\u0026rdquo; which are centrally located and larger, indicating their foundational role in the field. As research evolved, more specific terms like \u0026ldquo;sustainable agriculture,\u0026rdquo; \u0026ldquo;crop adaptation,\u0026rdquo; and \u0026ldquo;pest management\u0026rdquo; emerged, reflecting a shift towards practical applications and solutions. This progression is evident through the color gradient from green to blue, signifying the temporal development of these topics. Furthermore, the clustering of terms such as \u0026ldquo;adaptation strategies,\u0026rdquo; \u0026ldquo;soil,\u0026rdquo; and \u0026ldquo;biodiversity\u0026rdquo; highlights the interdisciplinary nature of the research, emphasizing the interconnectedness of various factors influencing climate resilience. Consequently, this visualization underscores the increasing complexity and depth of research in this field, driven by the need to address multifaceted challenges posed by climate change on agriculture (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec33\" class=\"Section2\"\u003e\n \u003ch2\u003e4.3. Analysis of cited papers\u003c/h2\u003e\n \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e\n \u003ch2\u003e4.3.1. Analysis of local highly cited papers\u003c/h2\u003e\n \u003cp\u003eThe Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e ranks influential publications based on their Local Citation Scores (LCS). A higher LCS indicates frequent citations within the dataset, highlighting the publication\u0026rsquo;s significance in the field. For instance, Lin BB., 2011 has a high LCS of 20, suggesting it is highly influential locally, while its global citations are 1144, indicating broader recognition. Conversely, Keshavarz M., 2021 has a lower global citation count but a high ratio of local to global citations, suggesting a more localized impact. Consequently, this table underscores key works that have significantly contributed to the academic discourse in climate resilience and agriculture.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLeading ten local citation scores of articles on agricultural climate resilience from 2004 to 2024.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDocument\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDOI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLocal Citations\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003cp\u003eCitations\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRatio\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLin BB, 2011, Bioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1525/bio.2011.61.3.4\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDarnhofer I, 2014, European review of agricultural economics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/erae/jbu012\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMase AS, 2017, Climate risk management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.crm.2016.11.004\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSperanza CI, 2013, Regional environmental change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10113-012-0391-5\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMichler JD, 2019, Journal of environmental economics and management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jeem.2018.11.008\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKeshavarz M, 2021, Journal of arid environments\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jaridenv.2020.104323\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlam GMM, 2018, Environmental science \u0026amp; policy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envsci.2018.02.012\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLipper L, 2018, Natural resource management and policy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-3-319-61194-5\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZougmor\u0026eacute; RB, 2016, Agriculture \u0026amp; food security\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40066-016-0075-3\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArbuckle JG, 2013, Climatic change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10584-013-0700-0\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNote: Local citations refer to the number of citations by papers within this paper\u0026rsquo;s database, while global citations refer to the number of citations by all papers.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec35\" class=\"Section3\"\u003e\n \u003ch2\u003e4.3.2. Analysis of global highly cited papers\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e ranks influential publications based on their total citations. Lin BB., 2011, with 1144 total citations, is the most cited, indicating its significant influence in the field. However, Bailey-Serres J., 2019, despite having fewer total citations (868), has a higher average of 144.67 citations per year, suggesting a rapidly growing impact. Conversely, Webb NP., 2017, with 154 total citations and 19.25 citations per year, shows steady but slower recognition. This table highlights the varying degrees of influence and growth rates of key publications in rural sustainability and land use research.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLeading ten global citation counts of articles on agricultural climate resilience.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePaper\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDOI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal Citations\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTC per Year\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLin BB, 2011, Bioscience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1525/bio.2011.61.3.4\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81.7142857\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBailey-Serres J, 2019, Nature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41586-019-1679-0\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e868\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e144.666667\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAryal JP, 2019, Environment, development and sustainability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10668-019-00414-4\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u0026ocirc;t\u0026eacute; IM, 2010, Plos biology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pbio.1000438\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.8666667\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMase AS, 2017, Climate risk management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.crm.2016.11.004\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArbuckle JG, 2013, Climatic change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10584-013-0700-0\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDarnhofer I, 2014, European review of agricultural economics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/erae/jbu012\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.0909091\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbberton M, 2015, Plant biotechnology journal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/pbi.12467\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLipper L, 2018, Natural resource management and policy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-3-319-61194-5\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.2857143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWebb NP, 2017, Frontiers in ecology and the environment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/fee.1530\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec36\" class=\"Section3\"\u003e\n \u003ch2\u003e4.3.3. Analysis of cited networks\u003c/h2\u003e\n \u003cp\u003eThe citation document overlay in climate resilience in agriculture from 2004 to 2024, generated by VOSviewer, provides a comprehensive view of the evolution and interconnections within this research field. Initially, the research was dominated by foundational studies, as indicated by the larger nodes representing highly cited documents from earlier years, such as those by Valerie Nelson (2009) and Brenda B. Lin (2011). As the field progressed, there was a noticeable shift towards more specialized and recent studies, exemplified by the works of Frederick Dapilah (2023) and Anupam Mihra (2023), which are represented by smaller, yet significant nodes. This shift is further highlighted by the color gradient from green to blue, indicating the temporal development of research topics. Moreover, the dense network of citation links underscores the interdisciplinary nature of climate resilience research, connecting diverse topics such as \u0026ldquo;adaptive capacity,\u0026rdquo; \u0026ldquo;pest management,\u0026rdquo; and \u0026ldquo;sustainable agriculture.\u0026rdquo; Consequently, this visualization not only maps the influential research contributions but also illustrates the dynamic and evolving landscape of climate resilience in agriculture over the past two decades (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe citation source visualization in climate resilience from 2004 to 2024, generated by VOSviewer, reveals the evolution and interconnections of research within this field over two decades. Initially, foundational sources such as \u0026ldquo;Climate Policy\u0026rdquo; and \u0026ldquo;Sustainability\u0026rdquo; were central, indicating their significant influence on early research. As the field progressed, more specialized sources like \u0026ldquo;Climate Smart Agriculture\u0026rdquo; and \u0026ldquo;Building Climate Resilience\u0026rdquo; emerged, reflecting a shift towards practical applications and adaptive strategies. This progression is evident through the color gradient from green to blue, signifying the temporal development of these topics. Furthermore, the dense network of citation links underscores the interdisciplinary nature of climate resilience research, connecting diverse areas such as \u0026ldquo;agroforestry systems,\u0026rdquo; \u0026ldquo;environmental development,\u0026rdquo; and \u0026ldquo;risk management.\u0026rdquo; Consequently, this visualization not only maps the influential research contributions but also illustrates the dynamic and evolving landscape of climate resilience in agriculture, driven by the need to address multifaceted challenges posed by climate change (Fig. \u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe bibliographic coupling network in climate resilience in agriculture from 2004 to 2024, visualized by VOSviewer, reveals significant insights into the collaborative landscape and research evolution in this field. Initially, foundational studies by authors like Brenda B. Lin (2011) and Julia Bailey-Serres (2019) are prominently positioned, indicating their central role and high citation frequency. As research progressed, newer contributions by authors such as Ramiro Alonso-Salinas (2023) and Keerththana Kuweswaran (2023) emerged, reflecting a shift towards more recent and specialized studies. This progression is evident through the color-coded clusters, which highlight different research groups and their interconnectedness. Furthermore, the dense network of lines connecting various authors underscores the collaborative nature of climate resilience research, illustrating how different researchers and their studies are interlinked. Consequently, this visualization not only maps the influential research contributions but also illustrates the dynamic and evolving landscape of climate resilience in agriculture, driven by the need to address multifaceted challenges posed by climate change (Fig. \u003cspan class=\"InternalRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e4.4 Keyword analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec37\" class=\"Section3\"\u003e\n \u003cp\u003e4.4.1. Analysis of high-frequency keywords\u003c/p\u003e\n \u003cp\u003eThe historical citation network of highly cited papers in climate resilience in agriculture from 2004 to 2024 illustrates the interconnectedness and influence of key research papers. Central nodes like \u0026ldquo;Lin BB, 2011\u0026rdquo; and \u0026ldquo;Arbuckle JG, 2013\u0026rdquo; are prominently positioned, indicating their significant impact and frequent co-citation with other works. The different colors represent distinct co-citation networks, highlighting clusters of research that are often referenced together. For instance, the network shows how foundational studies like \u0026ldquo;Lin BB, 2011\u0026rdquo; have influenced subsequent research, creating a web of interconnected studies that collectively advance the field of climate resilience in agriculture. This visualization underscores the collaborative and cumulative nature of scientific research, where key papers serve as pivotal points in the development of the field (Fig. \u003cspan class=\"InternalRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe word cloud visualization highlights the most frequently occurring keywords in climate resilience in agriculture. The central term \u0026ldquo;climate change\u0026rdquo; is the largest, indicating its predominant role in the discourse. Surrounding it, significant terms like \u0026ldquo;resilience,\u0026rdquo; \u0026ldquo;adaptation,\u0026rdquo; and \u0026ldquo;sustainable agriculture\u0026rdquo; are also prominent, suggesting their critical importance. Smaller terms such as \u0026ldquo;adaptive capacity,\u0026rdquo; \u0026ldquo;vulnerability,\u0026rdquo; and \u0026ldquo;food security\u0026rdquo; reflect relevant but less frequently discussed concepts. This visualization underscores the central themes and emerging topics in climate resilience research, illustrating how various aspects of climate change and agriculture are interconnected and prioritized in academic discussions (Fig. \u003cspan class=\"InternalRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec38\" class=\"Section3\"\u003e\n \u003ch2\u003e4.4.2. Cluster analysis and multiple correspondence analysis of high-frequency keywords\u003c/h2\u003e\n \u003cp\u003eThe hierarchical clustering analysis of high-frequency keywords in climate resilience in agriculture groups related terms based on their co-occurrence. The dendrogram shows distinct clusters, with each color representing a different group of keywords. For instance, terms like \u0026ldquo;climate change,\u0026rdquo; \u0026ldquo;resilience,\u0026rdquo; and \u0026ldquo;adaptation\u0026rdquo; are closely linked, indicating their frequent association in the literature. As we move up the tree, branches merge, showing how broader themes like \u0026ldquo;sustainable agriculture\u0026rdquo; and \u0026ldquo;food security\u0026rdquo; are interconnected with these core concepts. This visualization highlights the main themes and their relationships, providing a clear overview of the key areas of focus in climate resilience research (Fig. \u003cspan class=\"InternalRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec39\" class=\"Section2\"\u003e\n \u003ch2\u003e4.5. Analysis of the evolution of research hotspots\u003c/h2\u003e\n \u003cp\u003eThe thematic map of climate resilience from 2004 to 2024 reveals notable shifts in keyword associations over time. Initially, terms like \u0026ldquo;food\u0026rdquo; and \u0026ldquo;sustainable agriculture\u0026rdquo; were prominent, indicating a focus on food security and sustainable practices. Over time, keywords such as \u0026ldquo;climate-smart agriculture\u0026rdquo; and \u0026ldquo;resilience\u0026rdquo; gained prominence, reflecting a shift towards adaptive strategies and resilience-building in agricultural systems. The association of specific authors with these keywords also highlights regional research trends. For example, authors like Singh A. and Srivastava J.P. are linked with terms like \u0026ldquo;climate change\u0026rdquo; and \u0026ldquo;agricultural systems,\u0026rdquo; suggesting a strong focus on these topics in their regions. This visualization underscores the evolving nature of research priorities and regional differences in addressing climate resilience in agriculture (Fig. \u003cspan class=\"InternalRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003ePolicymakers can leverage the shifts in keyword associations to inform climate resilience strategies by focusing on the evolving priorities and emerging trends in research. For instance, the increasing prominence of terms like \u0026ldquo;climate-smart agriculture\u0026rdquo; and \u0026ldquo;resilience\u0026rdquo; suggests a growing emphasis on adaptive strategies and sustainable practices. Policymakers can prioritize funding and support for initiatives that promote these approaches, ensuring that agricultural systems are better equipped to handle climate impacts.\u003c/p\u003e\n \u003cp\u003eAdditionally, the association of specific authors with key topics can highlight regional research strengths and gaps. By identifying regions where certain aspects of climate resilience are well-studied, policymakers can foster collaborations and knowledge exchange to address less-explored areas. For example, if research in \u0026ldquo;agricultural systems\u0026rdquo; is concentrated in one region, efforts can be made to disseminate this knowledge to other areas facing similar challenges.\u003c/p\u003e\n \u003cp\u003eOverall, understanding these keyword associations helps policymakers align their strategies with the latest scientific insights, ensuring that policies are both relevant and effective in enhancing climate resilience.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cdiv id=\"Sec41\" class=\"Section2\"\u003e\n \u003ch2\u003e5.1. Analysis of the number of articles issued and the publishing journal\u003c/h2\u003e\n \u003cp\u003eThe results indicate an impressive annual growth rate of 25.77% from 2004 to 2024. This rate is significantly higher than those reported in other studies. For example, a survey of clinical research literature from 1991 to 2020 found average annual growth rates of 10.28% for primary literature and 10.57% for secondary literature[\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e]. Another study analyzing the growth of academic journals from 1986 to 2013 reported an average growth rate of 4.7% [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e]. The higher growth rate in the data could be attributed to the specific field or the inclusion of various documents beyond journal articles. The average document age in the dataset is 4.31 years, which suggests a relatively recent body of work. This aligns with trends in rapidly evolving fields where newer publications are frequently cited. The average of 10.15 citations per document is also notable. In comparison, a study on the growth of scientific literature found that the average number of citations per document can vary widely depending on the field and the impact of the journals included [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eData shows an average of 3.21 authors per document and a notable number of single-authored documents (255 out of 2,605). This is consistent with trends in collaborative research, although the absence of international co-authorship is unusual. Research indicates a growing trend in international collaborations, which frequently boost the impact and citation rates of publications [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e]. The dataset\u0026apos;s diversity in publication types, including books, book chapters, journal articles, and more, reflects a comprehensive scholarly output. This variety is essential for a holistic understanding of the field. For example, the inclusion of datasets and preprints indicates a modern approach to open science and data sharing, which is becoming increasingly common [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e]. Comparing data with existing literature highlights both unique aspects and common trends. The high growth rate and diverse publication types suggest a dynamic and rapidly expanding field. However, the lack of international co-authorship could be an area for future improvement to enhance the global impact and collaboration in the research community.\u003c/p\u003e\n \u003cp\u003eThe thematic map highlights the central role of \u0026ldquo;climate change\u0026rdquo; and its interconnectedness with themes like \u0026ldquo;resilience,\u0026rdquo; \u0026ldquo;policy,\u0026rdquo; and \u0026ldquo;sustainable development.\u0026rdquo; This aligns with the findings of the IPCC\u0026rsquo;s Climate Resilient Development Pathways report, which emphasizes the interdependence of climate action and sustainable development [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e]. The report underscores that integrating climate mitigation and adaptation strategies is crucial for enhancing human and ecological well-being. The link between \u0026ldquo;climate change\u0026rdquo; and \u0026ldquo;resilience\u0026rdquo; in a map suggests a focus on adaptive strategies. This is consistent with the literature, which often highlights resilience as a key component in climate change adaptation. For example, a study on resilience-related policies and local practices in various cities worldwide found that resilience-building measures are essential for mitigating the impacts of climate change [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. These measures include enhancing social, economic, and ecological resilience to climate impacts.\u003c/p\u003e\n \u003cp\u003eThe connection between \u0026ldquo;climate change\u0026rdquo; and \u0026ldquo;policy\u0026rdquo; in a map underscores the importance of governance in addressing climate issues. This is echoed in the literature, where effective policy frameworks are seen as critical for implementing climate action. A review of sustainability and resilience in business models also highlights the need for policies that align incentives and revenue mechanisms with sustainable outcomes [\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e]. This alignment is crucial for driving the transition to more sustainable economies. The map\u0026rsquo;s emphasis on the integrated approach needed to tackle climate change is supported by the literature. The IPCC report notes that pursuing climate action and sustainable development goals in an integrated manner increases their effectiveness [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e]. Similarly, a study on the global network analysis of links between business, climate change, and sustainability concepts found that integrated approaches are necessary for addressing the complex challenges posed by climate change [\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e]. Comparing the thematic map results with existing literature highlights the importance of an integrated approach to climate change, resilience, policy, and sustainable development. The interconnectedness of these themes underscores the need for comprehensive strategies that address multiple aspects of society and the environment. The findings are well-aligned with the broader body of research, emphasizing the multifaceted nature of climate change and the critical role of governance and resilience in mitigating its impacts.\u003c/p\u003e\n \u003cp\u003eData shows a clear upward trajectory in publications on climate resilience in agriculture from 2004 to 2024, with a strong positive correlation (\u003cem\u003eR\u0026sup2; = 0.7097\u003c/em\u003e). This trend is consistent with global patterns observed in the literature. For instance, a study on climate-smart agriculture (CSA) practices noted a significant increase in publications over the past two decades, reflecting growing academic and policy interest in sustainable agricultural practices [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. The increasing number of publications in the data underscores the escalating focus on developing adaptive strategies to mitigate climate impacts on agriculture. The linear equation (\u003cem\u003ey\u0026thinsp;=\u0026thinsp;7.3838x \u0026minus;\u0026thinsp;233.62\u003c/em\u003e) in the data suggests a steady increase in scholarly output. This is comparable to findings from other studies that have documented similar growth patterns. For example, research on CSA adoption highlighted a consistent rise in publications, driven by the urgent need to address climate change impacts on agriculture [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]. The strong positive correlation in the data indicates a robust and sustained interest in this field, aligning with global trends.\u003c/p\u003e\n \u003cp\u003eThe emphasis on developing adaptive strategies to mitigate climate impacts on agriculture is a common theme in the literature. Studies have shown that resilience-building measures, such as crop diversification, soil health improvement, and the use of climate-resilient crop varieties, are critical for enhancing agricultural sustainability [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. The data\u0026rsquo;s focus on climate resilience aligns with these findings, highlighting the importance of adaptive strategies in ensuring food security and agricultural productivity. A study on climate-resilient agricultural practices among indigenous communities in India found that traditional knowledge systems play a crucial role in enhancing resilience [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e]. This study emphasized the integration of indigenous practices with modern agricultural techniques to improve adaptive capacity. Data\u0026rsquo;s upward trend in publications may also reflect an increasing recognition of the value of integrating diverse knowledge systems to address climate resilience in agriculture.\u003c/p\u003e\n \u003cp\u003eComparing findings with existing literature reveals a consistent global trend of increasing scholarly interest in climate resilience in agriculture. The strong positive correlation and steady growth in publications underscore the importance of developing adaptive strategies to mitigate climate impacts. Data aligns well with global patterns, highlighting the critical role of resilience-building measures and the integration of diverse knowledge systems in enhancing agricultural sustainability.\u003c/p\u003e\n \u003cp\u003eData shows that \u0026ldquo;Qeios Ltd\u0026rdquo; leads with 69 articles, followed by the \u0026ldquo;Handbook of Climate Change Resilience\u0026rdquo; and \u0026ldquo;Sustainability\u0026rdquo; with 32 and 13 articles, respectively. This dominance by a few journals is a common trend in academic publishing. For instance, a study on climate-smart agriculture (CSA) found that a small number of journals, such as \u0026ldquo;Agricultural Systems\u0026rdquo; and \u0026ldquo;Climate Policy,\u0026rdquo; also dominate the publication landscape [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]. These leading journals often set the research agenda and attract high-quality submissions due to their reputation and impact factor. The presence of multiple journals with fewer articles, such as the \u0026ldquo;International Journal of Environment and Climate Change\u0026rdquo; and \u0026ldquo;Climatic Change,\u0026rdquo; indicates a broad interest in climate resilience research across different disciplines. This interdisciplinary nature is crucial for addressing complex issues like climate change. Similar studies have highlighted the importance of diverse publication venues in fostering a comprehensive understanding of climate resilience. For example, research on CSA practices has been published across a wide range of journals, reflecting the multifaceted nature of the topic [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe significant contributions from specialized journals like \u0026ldquo;Qeios Ltd\u0026rdquo; and the \u0026ldquo;Handbook of Climate Change Resilience\u0026rdquo; suggest a focused effort on climate resilience in agriculture. This is comparable to findings in other fields where specialized journals play a pivotal role in advancing specific areas of research. For instance, journals dedicated to environmental science and sustainability often publish targeted studies that drive innovation and policy development [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. Data reflects the interdisciplinary nature of climate resilience research, with contributions from journals spanning various fields. This aligns with the broader literature, which emphasizes the need for integrating knowledge from different disciplines to develop effective climate resilience strategies. Studies have shown that interdisciplinary research is essential for addressing the complex interactions between climate change, agriculture, and socioeconomic factors [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e]. Comparing findings with existing literature highlights the dominance of leading journals, the broad interest across various publication venues, and the critical role of specialized journals in advancing climate resilience research. The interdisciplinary nature of this research is essential for developing comprehensive strategies to mitigate the impacts of climate change on agriculture. Data aligns well with global trends, underscoring the importance of diverse and specialized contributions to this field.\u003c/p\u003e\n \u003cp\u003eThe data shows a steep increase in the frequency of terms like \u0026ldquo;Climate Change\u0026rdquo; and \u0026ldquo;Adaptation\u0026rdquo; from 2004 to 2024. This trend is consistent with global patterns observed in the literature. For example, the IPCC\u0026rsquo;s reports have increasingly focused on these topics, highlighting the urgent need for both mitigation and adaptation strategies to address the impacts of climate change [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. The growing emphasis on these terms reflects a heightened awareness and concern about climate issues, which is also evident in the increasing number of publications and research funding dedicated to these areas [\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e]. The more gradual rise in terms like \u0026ldquo;Adaptive Capacity\u0026rdquo; and \u0026ldquo;Climate Smart Agriculture\u0026rdquo; suggests a steady but less pronounced focus. This aligns with findings from other studies that have documented a slower but consistent increase in research on these topics. For instance, a review of climate-smart agriculture practices noted a gradual increase in publications, driven by the need to develop sustainable agricultural practices that can withstand climate impacts [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. Similarly, research on adaptive capacity has been steadily growing as scholars and policymakers recognize the importance of building resilience in communities and ecosystems [\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe cumulative increase in mentions of climate-related terms underscores the evolving discourse on climate resilience and its various facets. This trend is mirrored in the broader literature, where there has been a significant shift towards integrated approaches that consider the interconnectedness of climate change, resilience, and sustainable development [\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e]. For example, studies on climate-resilient development pathways emphasize the need for holistic strategies that address multiple dimensions of resilience, including social, economic, and environmental aspects [\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e]. The trends highlighted in the data emphasize the need for continued research and policy development in the area of climate resilience. This is consistent with the literature, which calls for ongoing efforts to enhance our understanding of climate impacts and to develop effective adaptation and mitigation strategies [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. The increasing frequency of terms related to climate resilience in academic publications reflects a growing recognition of the importance of this field and the need for comprehensive policies that can address the complex challenges posed by climate change. Comparing the findings with existing literature reveals a consistent global trend of increasing emphasis on climate change and adaptation, alongside a steady rise in research on adaptive capacity and climate-smart agriculture. The evolving discourse on climate resilience underscores the need for integrated approaches and continued efforts in research and policy development. Data aligns well with global patterns, highlighting the critical importance of addressing climate resilience in a comprehensive and interdisciplinary manner.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec42\" class=\"Section2\"\u003e\n \u003ch2\u003e5.2. Analysis of key researchers\u003c/h2\u003e\n \u003cp\u003eData shows that authors like Neumann JE and Gaupp F have consistently contributed to the field of climate resilience in agriculture over multiple years. This sustained research interest is a common trend in the literature. For instance, a study on climate-smart agriculture (CSA) practices found that certain key researchers and institutions consistently publish high-impact work, driving the field forward [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]. The continuous contributions from these authors indicate their ongoing commitment to advancing knowledge and developing solutions for climate resilience. Authors such as Bodirsky BL and Kumareswami K show sporadic contributions, which suggests focused studies at particular intervals. This pattern is also observed in other studies where researchers may concentrate on specific projects or collaborations that result in bursts of publications. For example, research on climate-resilient agricultural practices among indigenous communities in India highlighted that certain researchers contribute intensively during specific projects or funding periods [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. These focused contributions can lead to significant advancements in particular areas of study.\u003c/p\u003e\n \u003cp\u003eThe larger bubbles in certain years, indicating peaks in research output, reflect pivotal studies that garnered significant attention. This trend is consistent with findings in the literature where landmark studies or special issues in journals can lead to spikes in publications and citations. For instance, a special issue on CSA adoption and impacts highlighted key studies that significantly influenced subsequent research and policy discussions [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]. These peaks often correspond to breakthroughs or comprehensive reviews that synthesize existing knowledge and set new research agendas. The chart underscores both the productivity and impact of research in climate resilience. The size of the bubbles represents the number of documents and the color shade indicating citations highlight the dual aspects of research output and influence. Similar studies have shown that highly productive researchers often have a significant impact on the field, as their work is frequently cited and builds the foundation for future research [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. This dual focus on productivity and impact is crucial for advancing the field and addressing the complex challenges posed by climate change. Comparing the findings with existing literature reveals common trends in sustained research interest, sporadic contributions, and peaks in research output. The productivity and impact of research in climate resilience are critical for developing effective strategies to mitigate climate impacts on agriculture. Data aligns well with global patterns, emphasizing the importance of ongoing contributions and the influence of key researchers in advancing the field.\u003c/p\u003e\n \u003cp\u003eData shows that the h-index is relatively consistent across authors, indicating similar influence in terms of highly cited papers. This consistency is common in well-established research fields. For instance, in environmental science, leading researchers often have stable h-index values, reflecting their sustained contributions. In contrast, the g-index varies more among authors, highlighting differences in the breadth of impactful work. Some researchers have a few highly cited papers, while others have a broader range of moderately cited work. This trend is also observed in climate change research. The m-index, which normalizes impact over time, is lower for newer authors like Luginaah I. and Mohammed K. This is expected since the m-index accounts for the length of an author\u0026rsquo;s career. Newer researchers often have lower m-index values due to shorter publication histories, but these values increase as they establish their careers and accumulate citations. Total citations (TC) vary significantly, with Asfaw S. having the highest at 339. This highlights substantial influence, consistent with findings in other fields where a few researchers accumulate many citations. In climate resilience research, highly cited authors typically contribute foundational or highly innovative work that attracts significant attention.\u003c/p\u003e\n \u003cp\u003eThe number of publications (NP) is mostly uniform, with a few outliers, indicating consistent research output among the authors. This pattern is common in other studies, where top researchers maintain a steady publication rate. For example, in climate adaptation research, leading researchers consistently publish a similar number of papers each year. The publication year start (PY_start) ranges from 2010 to 2021, showing a mix of established and emerging researchers. This mix is crucial for the dynamic development of the field, as a combination of experienced and new researchers fosters innovation and continuity. Having seasoned experts and fresh perspectives is essential for addressing evolving challenges in climate resilience. Comparing findings with existing literature reveals common trends in bibliometric indicators: consistency in h_index, variation in g_index, and lower m_index for newer authors. The significant variation in total citations and the mostly uniform number of publications highlight the diverse yet impactful contributions of these authors. The mix of established and emerging researchers underscores the dynamic nature of climate resilience research in agriculture. Data aligns well with global patterns, emphasizing the importance of ongoing contributions from both seasoned and new researchers.\u003c/p\u003e\n \u003cp\u003eThe network visualization map highlights the central importance of terms like \u0026ldquo;climate change,\u0026rdquo; \u0026ldquo;agriculture,\u0026rdquo; and \u0026ldquo;adaptation,\u0026rdquo; which have larger nodes. This centrality is consistent with literature findings, where these terms are core concepts in climate resilience research. For example, \u0026ldquo;climate change\u0026rdquo; and \u0026ldquo;adaptation\u0026rdquo; are frequently occurring terms in climate change adaptation research, reflecting their critical role. Similarly, \u0026ldquo;agriculture\u0026rdquo; is central in studies on climate change impacts on food security and productivity. Smaller nodes like \u0026ldquo;sustainable agriculture\u0026rdquo; and \u0026ldquo;climate-smart agriculture\u0026rdquo; are also significant, indicating their relevance. This aligns with studies emphasizing sustainable and climate-smart practices in enhancing agricultural resilience. For instance, research on climate-smart agriculture (CSA) highlights the role of sustainable practices in mitigating climate impacts and promoting resilience. The lines connecting the nodes represent relationships between concepts, illustrating the interconnectedness of various aspects of climate resilience. This interconnectedness is a common theme in literature, advocating integrated approaches to address climate challenges. For example, effective adaptation requires a holistic approach considering social, economic, and environmental dimensions. The color-coded clusters highlight sub-themes or closely related ideas, reflecting the diverse aspects of climate resilience research. This clustering is similar to findings in network analyses of climate research, identifying clusters related to policy, technology, and community-based adaptation. These clusters help organize the research landscape and identify key focus areas. Comparing network visualization maps with existing literature reveals common trends: the central importance of key terms, the significance of sustainable practices, and the interconnectedness of concepts. The color-coded clusters emphasize the diverse and multifaceted nature of climate resilience research. Visualization aligns well with global patterns, underscoring the need for integrated approaches to address complex climate challenges in agriculture.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec43\" class=\"Section2\"\u003e\n \u003ch2\u003e5.3. Analysis of cited papers\u003c/h2\u003e\n \u003cp\u003eThe importance of Local Citation Scores (LCS) in identifying influential publications. For example, Lin BB., 2011 has a high LCS (20) and global citations (1144), showing broad recognition and local impact. This dual impact is common in seminal works that provide foundational knowledge. Conversely, Keshavarz M., 2021 has a lower global citation count but a high local-to-global citation ratio, indicating a more localized impact. This pattern is typical for studies addressing region-specific issues, which are crucial for informing local policy and practice. The table underscores key works that significantly contribute to climate resilience and agriculture research. Influential publications often shape the research agenda and drive future studies. For example, highly cited papers in climate change research often address critical issues or present novel solutions. Comparing results with similar studies reveals common trends: influential publications often have high citation counts and introduce new concepts or frameworks. The analysis highlights publications with substantial contributions, whether through broad recognition or localized impact. The study demonstrates the importance of both local and global citation metrics in identifying key works. This dual focus is essential for understanding research influence and guiding future studies in climate resilience and agriculture.\u003c/p\u003e\n \u003cp\u003eThe co-authorship network visualization reveals three distinct clusters of researchers, each representing different collaborative groups. This clustering is common in co-authorship networks, reflecting researchers\u0026rsquo; tendency to collaborate within specific groups or institutions. For example, in climate change research, similar clustering patterns are observed. The blue cluster, featuring key authors like David D. Woods and Andrew Dougill, indicates frequent collaboration. Certain researchers act as central nodes, facilitating collaboration and knowledge exchange within their networks. For instance, in climate-smart agriculture (CSA) research, key authors frequently collaborate with multiple researchers, enhancing network connectivity. The green cluster, including Andrea Nowak, Peter Steward, Todd S. Rosenstock, and Erika Berglund, suggests a strong collaborative network. Such networks are crucial for advancing research by enabling the sharing of resources, expertise, and data. In climate resilience studies, strong collaborative networks drive innovation and facilitate comprehensive adaptation strategies. The red cluster, with David Zilberman, Nancy McCarthy, and Sara Savastano, highlights another significant group of collaborators. This pattern is often seen in co-authorship networks where certain groups work closely on specific projects or themes. For example, in environmental economics, similar clusters frequently collaborate on sustainability and resource management topics. The interconnected nature of the co-authorship network underscores the collaborative efforts required to advance knowledge and innovation in climate resilience and agriculture. Interdisciplinary and cross-institutional collaborations are essential for addressing complex climate challenges. For instance, research on climate adaptation highlights the importance of collaborative networks in integrating diverse perspectives and developing holistic solutions. Comparing the co-authorship network visualization with existing literature reveals common trends: the formation of collaborative clusters, the role of key authors, and the importance of strong collaborative networks. Visualization aligns well with global patterns, emphasizing the critical role of collaboration in driving innovation and addressing complex climate challenges.\u003c/p\u003e\n \u003cp\u003eThe bibliographic coupling network visualization highlights central authors like Brenda B. Lin (2011) and Julia Bailey-Serres (2019), indicating their significant influence and extensive collaboration. This pattern is common in studies where central authors shape the research landscape by contributing seminal papers. The connecting lines indicate shared references, showing the strength and frequency of collaborations. This interconnectedness is typical in bibliographic coupling networks, reflecting the collaborative nature of scientific research. For example, in climate-smart agriculture (CSA), researchers frequently cite each other\u0026rsquo;s work, creating a dense network of shared knowledge. The color-coded clusters represent different research communities, with authors like Isabelle M. C\u0026ocirc;t\u0026eacute; (2010) and Robert B. Zougmore (2016) forming distinct groups. This clustering is common in bibliographic coupling networks, where researchers working on related topics or within the same institutions form cohesive groups. The visualization underscores the interconnected nature of research in climate resilience, reflecting both historical foundations and emerging collaborations. This dual focus is essential for understanding the field\u0026rsquo;s evolution. Historical foundations provide a basis for new research while emerging collaborations introduce fresh perspectives and innovative approaches. Comparing the visualization with existing literature reveals common trends: the centrality of influential authors, the strength of shared references, and the formation of collaborative clusters. Visualization aligns well with global patterns, emphasizing the critical role of collaboration and shared knowledge in addressing complex climate challenges.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e5.4 Keyword analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThe historical citation network highlights central nodes like \u0026ldquo;Lin BB, 2011\u0026rdquo; and \u0026ldquo;Arbuckle JG, 2013,\u0026rdquo; indicating their significant impact and frequent co-citation. This pattern is common in studies where highly cited papers serve as foundational references, shaping subsequent research. The different colors in a network represent distinct co-citation clusters, highlighting groups of research often referenced together. This clustering is typical in co-citation networks, where related studies form cohesive groups based on shared references. For example, in climate-smart agriculture (CSA), clusters often focus on themes like adaptation strategies, policy implications, or technological innovations.\u003c/p\u003e\n \u003cp\u003eThe network shows how foundational studies like \u0026ldquo;Lin BB, 2011\u0026rdquo; have influenced subsequent research, creating a web of interconnected studies. This cumulative nature of scientific research is well-documented, with foundational studies driving innovation and expanding the knowledge base. The visualization underscores the collaborative and cumulative nature of scientific research, where key papers serve as pivotal points in the field\u0026rsquo;s development. Collaborative networks and cumulative citations are critical for fostering innovation and ensuring robust findings. For instance, climate resilience research often relies on a collaborative approach, integrating insights from multiple disciplines. Comparing the historical citation network with existing literature reveals common trends: the centrality of influential papers, the formation of co-citation clusters, and the cumulative nature of scientific research. Visualization aligns well with global patterns, emphasizing the critical role of key papers in shaping research and driving innovation.\u003c/p\u003e\n \u003cp\u003eThe word cloud visualization highlights \u0026ldquo;climate change\u0026rdquo; as the most frequent keyword, indicating its central role in climate resilience in agriculture. This is consistent with broader literature, where climate change is a focal point in discussions on environmental impacts and adaptation strategies. The prominence of terms like \u0026ldquo;resilience,\u0026rdquo; \u0026ldquo;adaptation,\u0026rdquo; and \u0026ldquo;sustainable agriculture\u0026rdquo; suggests their critical importance. This aligns with studies emphasizing the need for resilient agricultural systems and adaptive strategies to cope with climate impacts. For example, climate-smart agriculture (CSA) research highlights the importance of resilience and adaptation for food security and sustainable practices. Smaller terms such as \u0026ldquo;adaptive capacity,\u0026rdquo; \u0026ldquo;vulnerability,\u0026rdquo; and \u0026ldquo;food security\u0026rdquo; are also important, reflecting relevant but less frequently discussed concepts. These terms help understand the broader context of climate resilience, addressing socio-economic dimensions and the ability of communities to adjust to climate change. The interconnectedness of various aspects of climate change and agriculture in a word cloud is a common theme in the literature. Integrated approaches that consider social, economic, and environmental dimensions are frequently advocated. Visualization captures this complexity, highlighting the need for comprehensive strategies. Comparing the word cloud with existing literature reveals common trends: the centrality of climate change, the importance of resilience and adaptation, and the relevance of emerging topics like adaptive capacity, vulnerability, and food security. Visualization aligns well with global patterns, emphasizing the critical role of these concepts in advancing research and policy development in climate resilience.\u003c/p\u003e\n \u003cp\u003eThe hierarchical clustering analysis shows that terms like \u0026ldquo;climate change,\u0026rdquo; \u0026ldquo;resilience,\u0026rdquo; and \u0026ldquo;adaptation\u0026rdquo; are closely linked, indicating their frequent association in the literature. This is consistent with other studies where these core concepts are often discussed together, highlighting the importance of resilience and adaptation strategies in addressing climate change impacts. As we move up the dendrogram, broader themes like \u0026ldquo;sustainable agriculture\u0026rdquo; and \u0026ldquo;food security\u0026rdquo; merge with these core concepts. This pattern is observed in other studies, emphasizing the interconnectedness of various aspects of climate resilience. For example, climate-smart agriculture (CSA) research often integrates sustainability and food security themes. The distinct clusters in the dendrogram provide a clear overview of the main themes and their relationships. Similar studies use clustering techniques to identify key areas of focus in climate resilience research, highlighting diverse aspects like policy, technology, and community-based adaptation. Comparing the results with similar studies reveals common trends: clustering of core concepts and integration of broader themes. For example, hierarchical clustering in climate adaptation literature often finds terms related to policy, governance, and socio-economic factors clustering together, reflecting the multifaceted nature of adaptation strategies. The hierarchical clustering analysis effectively highlights the main themes and their relationships in climate resilience research. The clustering of core concepts like \u0026ldquo;climate change,\u0026rdquo; \u0026ldquo;resilience,\u0026rdquo; and \u0026ldquo;adaptation,\u0026rdquo; along with broader themes like \u0026ldquo;sustainable agriculture\u0026rdquo; and \u0026ldquo;food security,\u0026rdquo; underscores the comprehensive nature of the field. Visualization aligns with global patterns, emphasizing the importance of integrated approaches in addressing climate resilience.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec44\" class=\"Section2\"\u003e\n \u003ch2\u003e5.5. Analysis of the Evolution of Research Hotspots\u003c/h2\u003e\n \u003cp\u003eThe thematic map shows shifts in keyword associations over time, reflecting evolving research priorities in climate resilience in agriculture. Initially, terms like \u0026ldquo;food\u0026rdquo; and \u0026ldquo;sustainable agriculture\u0026rdquo; were prominent, indicating a focus on food security and sustainable practices. This trend is consistent with early literature emphasizing sustainable agriculture to ensure food security in the face of climate change. Over time, keywords like \u0026ldquo;climate-smart agriculture\u0026rdquo; and \u0026ldquo;resilience\u0026rdquo; gained prominence, reflecting a shift towards adaptive strategies and resilience-building in agricultural systems. This shift aligns with global trends, where research on climate-smart agriculture (CSA) has grown significantly, emphasizing adaptive practices to enhance resilience. The association of specific authors with keywords highlights regional research trends. For example, authors like Singh A. and Srivastava J.P. are linked with terms like \u0026ldquo;climate change\u0026rdquo; and \u0026ldquo;agricultural systems,\u0026rdquo; indicating a strong focus on these topics in their regions. This pattern is consistent with findings from other studies documenting regional variations in climate resilience research. The evolving nature of research priorities, as illustrated by a thematic map, underscores the dynamic and adaptive nature of climate resilience research. This evolution mirrors broader literature, where research priorities have shifted in response to emerging challenges and new scientific insights. Comparing the thematic map with existing literature reveals common trends in the shifting focus of climate resilience research, the emergence of adaptive strategies, and regional variations in research priorities. Visualization aligns well with global patterns, highlighting the dynamic and multifaceted nature of research in this critical field.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eTo sum up, the bibliometric review of climate resilience in agriculture from 2004 to 2024 reveals substantial growth and evolving trends in this critical research area. With 477 sources contributing to 1,000 documents and an impressive annual growth rate of 25.77%, the field has seen a significant increase in scholarly interest, reflected in an average of 10.15 citations per document and the involvement of 2,605 authors. The thematic analysis underscores the central role of \u0026ldquo;climate change\u0026rdquo; and its interconnectedness with \u0026ldquo;resilience,\u0026rdquo; \u0026ldquo;policy,\u0026rdquo; and \u0026ldquo;sustainable development,\u0026rdquo; highlighting the necessity for an integrated approach to address climate challenges.\u003c/p\u003e \u003cp\u003eThe annual publication trend, marked by a strong positive correlation (\u003cem\u003eR\u0026sup2; = 0.7097\u003c/em\u003e) and linear growth, emphasizes the growing focus on adaptive strategies to mitigate climate impacts. Leading journals such as \u0026ldquo;Qeios Ltd,\u0026rdquo; \u0026ldquo;Handbook of Climate Change Resilience,\u0026rdquo; and \u0026ldquo;Sustainability\u0026rdquo; dominate the field, indicating both concentrated and interdisciplinary interests. The increasing prominence of terms like \u0026ldquo;Climate Change\u0026rdquo; and \u0026ldquo;Adaptation\u0026rdquo; reflects the evolving discourse and underscores the need for ongoing research and policy development.\u003c/p\u003e \u003cp\u003eThe co-authorship network reveals three distinct clusters of researchers, led by influential figures such as David D. Woods, Andrea Nowak, and David Zilberman, underscoring the collaborative nature of this research domain. Influential publications, highlighted by their Local Citation Scores, demonstrate both global and local impacts, contributing significantly to the academic discourse.\u003c/p\u003e \u003cp\u003eThe interconnectedness of key concepts like \u0026ldquo;climate change,\u0026rdquo; \u0026ldquo;agriculture,\u0026rdquo; and \u0026ldquo;adaptation,\u0026rdquo; as shown in the network visualization map, illustrates the multifaceted nature of climate resilience research. The historical citation network and word cloud visualization further emphasize the collaborative and cumulative nature of the field. Hierarchical clustering analysis and thematic maps reveal shifts in research priorities, from \u0026ldquo;food\u0026rdquo; and \u0026ldquo;sustainable agriculture\u0026rdquo; to \u0026ldquo;climate-smart agriculture\u0026rdquo; and \u0026ldquo;resilience,\u0026rdquo; reflecting evolving regional trends and research focuses.\u003c/p\u003e \u003cp\u003eOverall, this review highlights the dynamic and interdisciplinary nature of climate resilience research in agriculture, advocating for continued collaboration, integrated policy frameworks, and adaptive strategies to effectively address the challenges posed by climate change. By leveraging these insights, stakeholders can develop more effective, evidence-based strategies to enhance climate resilience in agriculture, ultimately contributing to sustainable development and food security. By adopting these strategies, policymakers can create a more equitable and resilient agricultural sector, ensuring that all farmers have the resources and support they need to adapt to climate change. By addressing these areas and questions, future research can build on the current understanding of climate resilience in agriculture, leading to more effective and sustainable solutions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eThe authors are grateful to all the reviewers who have contributed to the improvement of this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNo funds, grants, or other support was received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial interests:\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u0026nbsp;\u003c/strong\u003eChimi: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing-original draft. Mala: Methodology, Validation, Visualization, Writing–review \u0026amp; editing. Fobane \u0026amp; Matick: Data curation, Formal analysis, Methodology, Validation, Visualization, Writing–review \u0026amp; editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eM. G. Muluneh, \u0026laquo; Impact of climate change on biodiversity and food security: a global perspective\u0026mdash;a review article \u0026raquo;, \u003cem\u003eAgric. Food Security.\u003c/em\u003e, vol. 10, n\u003csup\u003eo\u003c/sup\u003e 1, p. 36, sept. 2021, doi 10.1186/s40066-021-00318-5.\u003c/li\u003e\n\u003cli\u003eK. Abbass, M. Z. Qasim, H. Song, M. Murshed, H. Mahmood, et I. Younis, \u0026laquo; A review of the global climate change impacts, adaptation, and sustainable mitigation measures \u0026raquo;, \u003cem\u003eEnviron. Sci. Pollut. Res.\u003c/em\u003e, vol. 29, n\u003csup\u003eo\u003c/sup\u003e 28, p. 42539‑42559, juin 2022, doi: 10.1007/s11356-022-19718-6.\u003c/li\u003e\n\u003cli\u003eV. Owino \u003cem\u003eet al.\u003c/em\u003e, \u0026laquo; The impact of climate change on food systems, diet quality, nutrition, and health outcomes: A narrative review \u0026raquo;, \u003cem\u003eFront. Clim.\u003c/em\u003e, vol. 4, ao\u0026ucirc;t 2022, doi: 10.3389/fclim.2022.941842.\u003c/li\u003e\n\u003cli\u003eM. Berb\u0026eacute;s-Bl\u0026aacute;zquez, C. L. Mitchell, S. L. Burch, et J. Wandel, \u0026laquo; Understanding climate change and resilience: assessing strengths and opportunities for adaptation in the Global South \u0026raquo;, \u003cem\u003eClim. Change\u003c/em\u003e, vol. 141, n\u003csup\u003eo\u003c/sup\u003e 2, p. 227‑241, mars 2017, doi: 10.1007/s10584-017-1897-0.\u003c/li\u003e\n\u003cli\u003eH. Aliba\u0026scaron;ić, \u003cem\u003eStrategic Resilience and Sustainability Planning: Management Strategies for Sustainable and Climate-Resilient Communities and Organizations\u003c/em\u003e. in Sustainable Development Goals Series. Cham: Springer International Publishing, 2022. doi: 10.1007/978-3-030-91159-1.\u003c/li\u003e\n\u003cli\u003eM. A. Israel, J. Amikuzuno, et G. Danso-Abbeam, \u0026laquo; Assessing farmers\u0026rsquo; contribution to greenhouse gas emission and the impact of adopting climate-smart agriculture on mitigation \u0026raquo;, \u003cem\u003eEcol. Process.\u003c/em\u003e, vol. 9, n\u003csup\u003eo\u003c/sup\u003e 1, p. 51, sept. 2020, doi 10.1186/s13717-020-00249-2.\u003c/li\u003e\n\u003cli\u003eH. Ritchie, P. Rosado, et M. Roser, \u0026laquo; Environmental Impacts of Food Production \u0026raquo;, \u003cem\u003eOur World Data\u003c/em\u003e, janv. 1970, Consult\u0026eacute; le: 17 septembre 2024. [En ligne]. Disponible sur: https://ourworldindata.org/environmental-impacts-of-food\u003c/li\u003e\n\u003cli\u003eA. Wezel, M. Casagrande, F. Celette, J.-F. Vian, A. Ferrer, et J. Peign\u0026eacute;, \u0026laquo; Agroecological practices for sustainable agriculture. A review \u0026raquo;, \u003cem\u003eAgron. \u003c/em\u003e\u003cem\u003eSustain. Dev.\u003c/em\u003e, vol. 34, n\u003csup\u003eo\u003c/sup\u003e 1, p. 1‑20, janv. 2014, doi: 10.1007/s13593-013-0180-7.\u003c/li\u003e\n\u003cli\u003eA. Wezel, B. G. Herren, R. B. Kerr, E. Barrios, A. L. R. Gon\u0026ccedil;alves, et F. Sinclair, \u0026laquo; Agroecological principles and elements and their implications for transitioning to sustainable food systems. A review \u0026raquo;, \u003cem\u003eAgron. Sustain. Dev.\u003c/em\u003e, vol. 40, n\u003csup\u003eo\u003c/sup\u003e 6, p. 40, oct. 2020, doi: 10.1007/s13593-020-00646-z.\u003c/li\u003e\n\u003cli\u003eS. R. Gliessman, V. E. M\u0026eacute;ndez, V. M. Izzo, et E. W. Engles, \u003cem\u003eAgroecology: Leading the transformation to a just and sustainable food system\u003c/em\u003e. CRC Press, 2022. Consult\u0026eacute; le: 29 juillet 2024. [En ligne]. Disponible sur: https://www.taylorfrancis.com/books/mono/10.1201/9781003304043/agroecology-stephen-gliessman-ernesto-m%C3%A9ndez-victor-izzo-eric-engles\u003c/li\u003e\n\u003cli\u003eY. S. Hilmi, J. T\u0026oacute;th, Z. Gabnai, G. Kir\u0026aacute;ly, et \u0026Aacute;. Temesi, \u0026laquo; Farmers\u0026rsquo; resilience to climate change through the circular economy and sustainable agriculture: a review from developed and developing countries \u0026raquo;, \u003cem\u003eRenew. Agric. Food Syst.\u003c/em\u003e, vol. 39, p. e15, 2024.\u003c/li\u003e\n\u003cli\u003eJ. Hellin, E. Fisher, M. Taylor, S. Bhasme, et A. M. Loboguerrero, \u0026laquo; Transformative adaptation: from climate-smart to climate-resilient agriculture \u0026raquo;, \u003cem\u003eCABI Agric. Biosci.\u003c/em\u003e, vol. 4, n\u003csup\u003eo\u003c/sup\u003e 1, p. 30, ao\u0026ucirc;t 2023, doi: 10.1186/s43170-023-00172-4.\u003c/li\u003e\n\u003cli\u003eP. M. Chimi \u003cem\u003eet al.\u003c/em\u003e, \u0026laquo; Factors affecting decision-making to strengthen the climate resilience of smallholder farms in the Centre Region of Cameroon \u0026raquo;, \u003cem\u003eClim. Smart Agric.\u003c/em\u003e, p. 100004, 2024.\u003c/li\u003e\n\u003cli\u003eR. Belmin, M. Paulin, et E. Mal\u0026eacute;zieux, \u0026laquo; Adapting agriculture to climate change: which pathways behind policy initiatives? \u0026raquo;, \u003cem\u003eAgron. Sustain. Dev.\u003c/em\u003e, vol. 43, n\u003csup\u003eo\u003c/sup\u003e 5, p. 59, ao\u0026ucirc;t 2023, doi: 10.1007/s13593-023-00910-y.\u003c/li\u003e\n\u003cli\u003eM. A. Zwolińska-Ligaj et D. J. Guzal-Dec, \u0026laquo; Rural Area Resilience during the COVID-19 Pandemic as Exemplified by Urban\u0026ndash;Rural Communes in Poland \u0026raquo;, \u003cem\u003eSustainability\u003c/em\u003e, vol. 16, n\u003csup\u003eo\u003c/sup\u003e 12, Art. n\u003csup\u003eo\u003c/sup\u003e 12, janv. 2024, doi: 10.3390/su16125073.\u003c/li\u003e\n\u003cli\u003eZ. Han, Y.-C. Youn, S. Kim, et H. Choe, \u0026laquo; Improving Farmer Livelihood Resilience to Climate Change in Rural Areas of Inner Mongolia, China \u0026raquo;, \u003cem\u003eAgriculture\u003c/em\u003e, vol. 13, n\u003csup\u003eo\u003c/sup\u003e 10, Art. n\u003csup\u003eo\u003c/sup\u003e 10, oct. 2023, doi 10.3390/agriculture13102030.\u003c/li\u003e\n\u003cli\u003eY. Buitenhuis \u003cem\u003eet al.\u003c/em\u003e, \u0026laquo; Policies and Farming System Resilience: A Bottom-Up Analysis \u0026raquo;, in \u003cem\u003eResilient and Sustainable Farming Systems in Europe: Exploring Diversity and Pathways\u003c/em\u003e, A. Garrido, A. Spiegel, B. Soriano, E. Mathijs, J. Urquhart, M. P. M. Meuwissen, et P. H. Feindt, \u0026Eacute;d., Cambridge: Cambridge University Press, 2022, p. 63‑87. doi: 10.1017/9781009093569.005.\u003c/li\u003e\n\u003cli\u003eH. Wang, X. Zhao, et J. He, \u0026laquo; Global Climate Governance and International Cooperation \u0026raquo;, in \u003cem\u003eChina\u0026rsquo;s Long-Term Low-Carbon Development Strategies and Pathways\u003c/em\u003e, 2021, p. 285. Consult\u0026eacute; le: 17 septembre 2024. [En ligne]. Disponible sur: https://repository.ust.hk/ir/Record/1783.1-116730\u003c/li\u003e\n\u003cli\u003eN. N. Omoyo, K. Susan, O. J. Ouma, et M. Donghui, \u0026laquo; Harmonizing disaster risk reduction and climate change adaptation frameworks for risk-informed development planning in Sub-Saharan Africa: The case of Uganda and Malawi \u0026raquo;, \u003cem\u003eJ. Sustain. Dev.\u003c/em\u003e, vol. 15, n\u003csup\u003eo\u003c/sup\u003e 5, p. 22‑38, 2022.\u003c/li\u003e\n\u003cli\u003eC. Ogbonna, E. Albrecht, C. Ugochukwu, C. Nwajiuba, et R. Onyeneke, \u0026laquo; Climate Resilience in African Coastal Areas: Scaling Up Institutional Capabilities in the Niger Delta Region \u0026raquo;, in \u003cem\u003eHandbook of Climate Change Resilience\u003c/em\u003e, W. Leal Filho, \u0026Eacute;d., Cham: Springer International Publishing, 2020, p. 29‑49. doi: 10.1007/978-3-319-93336-8_9.\u003c/li\u003e\n\u003cli\u003eS. Roy, \u0026laquo; Livelihood Resilience of the Indigenous Munda Community in the Bangladesh Sundarbans Forest \u0026raquo;, in \u003cem\u003eHandbook of Climate Change Resilience\u003c/em\u003e, W. Leal Filho, \u0026Eacute;d., Cham: Springer International Publishing, 2020, p. 51‑72. doi: 10.1007/978-3-319-93336-8_10.\u003c/li\u003e\n\u003cli\u003eA. Saleem Khan, K. MacManus, J. Mills, M. Madajewicz, et L. Ramasubramanian, \u0026laquo; Building Resilience of Urban Ecosystems and Communities to Sea-Level Rise: Jamaica Bay, New York City \u0026raquo;, in \u003cem\u003eHandbook of Climate Change Resilience\u003c/em\u003e, W. Leal Filho, \u0026Eacute;d., Cham: Springer International Publishing, 2020, p. 95‑115. doi: 10.1007/978-3-319-93336-8_29.\u003c/li\u003e\n\u003cli\u003eM. C. S. Lalika, \u0026laquo; Resilience in Climate Stressed Environment Through Water Grabbing \u0026raquo;, in \u003cem\u003eHandbook of Climate Change Resilience\u003c/em\u003e, W. Leal Filho, \u0026Eacute;d., Cham: Springer International Publishing, 2020, p. 269‑293. doi: 10.1007/978-3-319-93336-8_68.\u003c/li\u003e\n\u003cli\u003eP. Ferguson, L. Wollersheim, et M. Lowe, \u0026laquo; Approaches to Climate Resilience \u0026raquo;, in \u003cem\u003eThe Palgrave Handbook of Climate Resilient Societies\u003c/em\u003e, Cham: Springer International Publishing, 2020, p. 1‑25. doi: 10.1007/978-3-030-32811-5_97-1.\u003c/li\u003e\n\u003cli\u003eM. M. Guja et S. B. Bedeke, \u0026laquo; Smallholders\u0026rsquo; climate change adaptation strategies: exploring effectiveness and opportunities to be capitalized \u0026raquo;, \u003cem\u003eEnviron. Dev. Sustain.\u003c/em\u003e, mars 2024, doi: 10.1007/s10668-024-04750-y.\u003c/li\u003e\n\u003cli\u003eD. El Chami, A. Daccache, et M. El Moujabber, \u0026laquo; How Can Sustainable Agriculture Increase Climate Resilience? A Systematic Review \u0026raquo;, \u003cem\u003eSustainability\u003c/em\u003e, vol. 12, n\u003csup\u003eo\u003c/sup\u003e 8, Art. n\u003csup\u003eo\u003c/sup\u003e 8, janv. 2020, doi: 10.3390/su12083119.\u003c/li\u003e\n\u003cli\u003eA. J. Zautra et J. W. Reich, \u0026laquo; Resilience: The Meanings, Methods, and Measures of a Fundamental Characteristic of Human Adaptation \u0026raquo;, in \u003cem\u003eThe Oxford Handbook of Stress, Health, and Coping\u003c/em\u003e, S. Folkman, \u0026Eacute;d., Oxford University Press, 2010, p. 0. doi: 10.1093/oxfordhb/9780195375343.013.0009.\u003c/li\u003e\n\u003cli\u003eJ. Dusdal et J. J. W. Powell, \u0026laquo; Benefits, Motivations, and Challenges of International Collaborative Research: A Sociology of Science Case Study \u0026raquo;, \u003cem\u003eSci. Public Policy\u003c/em\u003e, vol. 48, n\u003csup\u003eo\u003c/sup\u003e 2, p. 235‑245, avr. 2021, doi: 10.1093/scipol/scab010.\u003c/li\u003e\n\u003cli\u003eY. C. Fu, M. Marques, Y.-H. Tseng, J. J. W. Powell, et D. P. Baker, \u0026laquo; An evolving international research collaboration network: spatial and thematic developments in co-authored higher education research, 1998\u0026ndash;2018 \u0026raquo;, \u003cem\u003eScientometrics\u003c/em\u003e, vol. 127, n\u003csup\u003eo\u003c/sup\u003e 3, p. 1403‑1429, mars 2022, doi: 10.1007/s11192-021-04200-w.\u003c/li\u003e\n\u003cli\u003eD. W. Hook, S. J. Porter, H. Draux, et C. T. Herzog, \u0026laquo; Real-Time Bibliometrics: Dimensions as a Resource for Analyzing Aspects of COVID-19 \u0026raquo;, \u003cem\u003eFront. Res. Metr. Anal.\u003c/em\u003e, vol. 5, janv. 2021, doi 10.3389/frma.2020.595299.\u003c/li\u003e\n\u003cli\u003eC. Herzog, D. Hook, et S. Konkiel, \u0026laquo; Dimensions: Bringing down barriers between scientometrics and data \u0026raquo;, \u003cem\u003eQuant. Sci. Stud.\u003c/em\u003e, vol. 1, n\u003csup\u003eo\u003c/sup\u003e 1, p. 387‑395, f\u0026eacute;vr. 2020, doi: 10.1162/qss_a_00020.\u003c/li\u003e\n\u003cli\u003eC. S. Rao, A. K. Shanker, C. Shanker, C. S. Rao, A. K. Shanker, et C. Shanker, \u003cem\u003eClimate Resilient Agriculture - Strategies and Perspectives\u003c/em\u003e. 2018. doi: 10.5772/intechopen.68382.\u003c/li\u003e\n\u003cli\u003eA. Aich, D. Dey, et A. Roy, \u0026laquo; Climate change resilient agricultural practices: A learning experience from Indigenous communities over India \u0026raquo;, \u003cem\u003ePLOS Sustain. Transform.\u003c/em\u003e, vol. 1, n\u003csup\u003eo\u003c/sup\u003e 7, p. e0000022, 2022.\u003c/li\u003e\n\u003cli\u003eM. Shehzad \u003cem\u003eet al.\u003c/em\u003e, \u0026laquo; Climate Resilience in Agriculture \u0026raquo;, in \u003cem\u003eBuilding Climate Resilience in Agriculture: Theory, Practice and Future Perspective\u003c/em\u003e, W. N. Jatoi, M. Mubeen, A. Ahmad, M. A. Cheema, Z. Lin, et M. Z. Hashmi, \u0026Eacute;d., Cham: Springer International Publishing, 2022, p. 67‑82. doi: 10.1007/978-3-030-79408-8_5.\u003c/li\u003e\n\u003cli\u003eM. A. Altieri, C. I. Nicholls, A. Henao, et M. A. Lana, \u0026laquo; Agroecology and the design of climate change-resilient farming systems \u0026raquo;, \u003cem\u003eAgron. Sustain. Dev.\u003c/em\u003e, vol. 35, n\u003csup\u003eo\u003c/sup\u003e 3, p. 869‑890, juill. 2015, doi: 10.1007/s13593-015-0285-2.\u003c/li\u003e\n\u003cli\u003eB. B. Lin, \u0026laquo; Resilience in Agriculture through Crop Diversification: Adaptive Management for Environmental Change \u0026raquo;, \u003cem\u003eBioScience\u003c/em\u003e, vol. 61, n\u003csup\u003eo\u003c/sup\u003e 3, p. 183‑193, mars 2011, doi: 10.1525/bio.2011.61.3.4.\u003c/li\u003e\n\u003cli\u003eM. Reckling, C. A. Watson, A. Whitbread, et K. Helming, \u0026laquo; Diversification for sustainable and resilient agricultural landscape systems \u0026raquo;, \u003cem\u003eAgron. Sustain. Dev.\u003c/em\u003e, vol. 43, n\u003csup\u003eo\u003c/sup\u003e 4, p. 44, juill. 2023, doi: 10.1007/s13593-023-00898-5.\u003c/li\u003e\n\u003cli\u003eJ. Alvar-Beltr\u0026aacute;n, A. Dao, A. Dalla Marta, A. Heureux, J. Sanou, et S. Orlandini, \u0026laquo; Farmers\u0026rsquo; Perceptions of Climate Change and Agricultural Adaptation in Burkina Faso \u0026raquo;, \u003cem\u003eAtmosphere\u003c/em\u003e, vol. 11, n\u003csup\u003eo\u003c/sup\u003e 8, Art. n\u003csup\u003eo\u003c/sup\u003e 8, ao\u0026ucirc;t 2020, doi: 10.3390/atmos11080827.\u003c/li\u003e\n\u003cli\u003eJ. Glennie, \u0026laquo; A greener Burkina: sustainable farming techniques, land reclamation, and improved livelihoods \u0026raquo;, ODI: Think change. Consult\u0026eacute; le: 17 septembre 2024. [En ligne]. Disponible sur: https://odi.org/en/publications/a-greener-burkina-sustainable-farming-techniques-land-reclamation-and-improved-livelihoods/\u003c/li\u003e\n\u003cli\u003eF. Frimpong \u003cem\u003eet al.\u003c/em\u003e, \u0026laquo; Water-smart farming: a review of strategies, technologies, and practices for sustainable agricultural water management in a changing climate in West Africa \u0026raquo;, \u003cem\u003eFront. Sustain. Food Syst.\u003c/em\u003e, vol. 7, nov. 2023, doi: 10.3389/fsufs.2023.1110179.\u003c/li\u003e\n\u003cli\u003eR. M. Sabir \u003cem\u003eet al.\u003c/em\u003e, \u0026laquo; Managing Water Resources for Sustainable Agricultural Production \u0026raquo;, in \u003cem\u003eTransforming Agricultural Management for a Sustainable Future: Climate Change and Machine Learning Perspectives\u003c/em\u003e, S. Kanga, S. K. Singh, K. Shevkani, V. Pathak, et B. Sajan, \u0026Eacute;d., Cham: Springer Nature Switzerland, 2024, p. 47‑74. doi: 10.1007/978-3-031-63430-7_3.\u003c/li\u003e\n\u003cli\u003eJ. Alvar-Beltr\u0026aacute;n, I. Elbaroudi, A. Gialletti, A. Heureux, L. Neretin, et R. Soldan, \u0026laquo; Climate resilient practices: typology and guiding material for climate risk screening \u0026raquo;, \u003cem\u003eFAO Rome\u003c/em\u003e, vol. 36, 2021.\u003c/li\u003e\n\u003cli\u003eY. Wu, S. Meng, C. Liu, W. Gao, et X.-Z. Liang, \u0026laquo; A bibliometric analysis of research for climate impact on agriculture \u0026raquo;, \u003cem\u003eFront. Sustain. Food Syst.\u003c/em\u003e, vol. 7, juill. 2023, doi: 10.3389/fsufs.2023.1191305.\u003c/li\u003e\n\u003cli\u003eS. Poudel, R. Thapa, et B. Mishra, \u0026laquo; A Farmer-Centric Cost\u0026ndash;Benefit Analysis of Climate-Smart Agriculture in the Gandaki River Basin of Nepal \u0026raquo;, \u003cem\u003eClimate\u003c/em\u003e, vol. 12, n\u003csup\u003eo\u003c/sup\u003e 9, Art. n\u003csup\u003eo\u003c/sup\u003e 9, sept. 2024, doi 10.3390/cli12090145.\u003c/li\u003e\n\u003cli\u003eX. Zhao \u003cem\u003eet al.\u003c/em\u003e, \u0026laquo; Changing trends in the clinical research literature on PubMed database from 1991 to 2020 \u0026raquo;, \u003cem\u003eEur. J. Med. Res.\u003c/em\u003e, vol. 27, n\u003csup\u003eo\u003c/sup\u003e 1, p. 95, juin 2022, doi: 10.1186/s40001-022-00717-9.\u003c/li\u003e\n\u003cli\u003eX. Gu et K. L. Blackmore, \u0026laquo; Recent trends in academic journal growth \u0026raquo;, \u003cem\u003eScientometrics\u003c/em\u003e, vol. 108, n\u003csup\u003eo\u003c/sup\u003e 2, p. 693‑716, ao\u0026ucirc;t 2016, doi: 10.1007/s11192-016-1985-3.\u003c/li\u003e\n\u003cli\u003eM. Thelwall et P. Sud, \u0026laquo; Scopus 1900\u0026ndash;2020: Growth in articles, abstracts, countries, fields, and journals \u0026raquo;, \u003cem\u003eQuant. Sci. Stud.\u003c/em\u003e, vol. 3, n\u003csup\u003eo\u003c/sup\u003e 1, p. 37‑50, avr. 2022, doi: 10.1162/qss_a_00177.\u003c/li\u003e\n\u003cli\u003eB. Mougenot et J.-P. Doussoulin, \u0026laquo; A bibliometric analysis of the Global Reporting Initiative (GRI): global trends in developed and developing countries \u0026raquo;, \u003cem\u003eEnviron. Dev. Sustain.\u003c/em\u003e, vol. 26, n\u003csup\u003eo\u003c/sup\u003e 3, p. 6543‑6560, mars 2024, doi: 10.1007/s10668-023-02974-y.\u003c/li\u003e\n\u003cli\u003eL. Bornmann, R. Haunschild, et R. Mutz, \u0026laquo; Growth rates of modern science: a latent piecewise growth curve approach to model publication numbers from established and new literature databases \u0026raquo;, \u003cem\u003eHumanit. Soc. Sci. Commun.\u003c/em\u003e, vol. 8, n\u003csup\u003eo\u003c/sup\u003e 1, Oct. 2021, doi: 10.1057/s41599-021-00903-w.\u003c/li\u003e\n\u003cli\u003eS. E. Werners \u003cem\u003eet al.\u003c/em\u003e, \u0026laquo; Advancing climate-resilient development pathways since the IPCC\u0026rsquo;s fifth assessment report \u0026raquo;, \u003cem\u003eEnviron. Sci. Policy\u003c/em\u003e, vol. 126, p. 168‑176, 2021.\u003c/li\u003e\n\u003cli\u003eL. C. Stringer \u003cem\u003eet al.\u003c/em\u003e, \u0026laquo; Adaptation and development pathways for different types of farmers \u0026raquo;, \u003cem\u003eEnviron. Sci. Policy\u003c/em\u003e, vol. 104, p. 174‑189, f\u0026eacute;vr. 2020, doi: 10.1016/j.envsci.2019.10.007.\u003c/li\u003e\n\u003cli\u003eL. C. Stringer, N. P. Simpson, E. L. F. Schipper, et S. H. Eriksen, \u0026laquo; Climate Resilient Development Pathways in Global Drylands \u0026raquo;, \u003cem\u003eAnthr. Sci.\u003c/em\u003e, juill. 2022, doi: 10.1007/s44177-022-00027-z.\u003c/li\u003e\n\u003cli\u003eL. Kassier, \u0026laquo; Interconnected or Disconnected? A Review of Sustainability, Resilience, and Sustainable Business Model Constructs in the Academic Business Literature \u0026raquo;, \u003cem\u003eJ. Knowl. Econ.\u003c/em\u003e, janv. 2024, doi: 10.1007/s13132-023-01712-z.\u003c/li\u003e\n\u003cli\u003eA. Karmaoui, G. Yoganandan, D. Sereno, K. Shaukat, S. El Jaafari, et L. Hajji, \u0026laquo; Global network analysis of links between business, climate change, and sustainability and setting up the interconnections framework \u0026raquo;, \u003cem\u003eEnviron. Dev. Sustain.\u003c/em\u003e, sept. 2023, doi: 10.1007/s10668-023-03883-w.\u003c/li\u003e\n\u003cli\u003eW. Ma et D. B. Rahut, \u0026laquo; Climate-smart agriculture: adoption, impacts, and implications for sustainable development \u0026raquo;, \u003cem\u003eMitig. Adapt. Strategy. Glob. Change\u003c/em\u003e, vol. 29, n\u003csup\u003eo\u003c/sup\u003e 5, p. 44, avr. 2024, doi: 10.1007/s11027-024-10139-z.\u003c/li\u003e\n\u003cli\u003eM. J. Usigbe, S. Asem-Hiablie, D. D. Uyeh, O. Iyiola, T. Park, et R. Mallipeddi, \u0026laquo; Enhancing resilience in agricultural production systems with AI-based technologies \u0026raquo;, \u003cem\u003eEnviron. Dev. Sustain.\u003c/em\u003e, vol. 26, n\u003csup\u003eo\u003c/sup\u003e 9, p. 21955‑21983, Sept. 2024, doi: 10.1007/s10668-023-03588-0.\u003c/li\u003e\n\u003cli\u003eK. Heider, J. M. Rodriguez Lopez, A. Bischoff, A. L. Balbo, et J. Scheffran, \u0026laquo; Toward climate-resilient and biodiverse agriculture in the Mediterranean region: experiences and perceptions of farmers engaged in sustainable food production \u0026raquo;, \u003cem\u003eOrg. Agric.\u003c/em\u003e, vol. 13, n\u003csup\u003eo\u003c/sup\u003e 4, p. 513‑529, d\u0026eacute;c. 2023, doi: 10.1007/s13165-023-00444-3.\u003c/li\u003e\n\u003cli\u003eC. G. D\u0026iacute;az, D. Zambrana-Vasquez, et C. Bartolom\u0026eacute;, \u0026laquo; Building Resilient Cities: A Comprehensive Review of Climate Change Adaptation Indicators for Urban Design \u0026raquo;, \u003cem\u003eEnergies\u003c/em\u003e, vol. 17, n\u003csup\u003eo\u003c/sup\u003e 8, Art. n\u003csup\u003eo\u003c/sup\u003e 8, janv. 2024, doi: 10.3390/en17081959.\u003c/li\u003e\n\u003cli\u003eL. Zhai et J.-E. Lee, \u0026laquo; Investigating Vulnerability, Adaptation, and Resilience: A Comprehensive Review within the Context of Climate Change \u0026raquo;, \u003cem\u003eAtmosphere\u003c/em\u003e, vol. 15, n\u003csup\u003eo\u003c/sup\u003e 4, Art. n\u003csup\u003eo\u003c/sup\u003e 4, avr. 2024, doi 10.3390/atmos15040474.\u003c/li\u003e\n\u003cli\u003eH. Pallubinsky, R. P. Kramer, et W. D. van Marken Lichtenbelt, \u0026laquo; Establishing resilience in times of climate change\u0026mdash;a perspective on humans and buildings \u0026raquo;, \u003cem\u003eClim. Change\u003c/em\u003e, vol. 176, n\u003csup\u003eo\u003c/sup\u003e 10, p. 135, Sept. 2023, doi: 10.1007/s10584-023-03614-0.\u003c/li\u003e\n\u003cli\u003eR. Ma, N. Abid, S. Yang, et F. Ahmad, \u0026laquo; From crisis to resilience: strengthening climate action in OECD countries through environmental policy and energy transition \u0026raquo;, \u003cem\u003eEnviron. Sci. Pollut. Res.\u003c/em\u003e, vol. 30, n\u003csup\u003eo\u003c/sup\u003e 54, p. 115480‑115495, oct. 2023, doi: 10.1007/s11356-023-29970-z.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Yaoundé I","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":"Climate resilience, Agricultural resilience, Dimensions, Vosviewer","lastPublishedDoi":"10.21203/rs.3.rs-5112075/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5112075/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate resilience in agriculture is crucial for addressing climate change challenges. This bibliometric review, using the Dimensions platform, analyzes research trends, international collaborations, and key areas from 2004 to 2024. It identifies 477 sources contributing to 1,000 documents, with a 25.77% annual growth rate and an average of 10.15 citations per document, involving 2,605 authors. The thematic map highlights the central role of \u0026ldquo;climate change\u0026rdquo; and its links to \u0026ldquo;resilience,\u0026rdquo; \u0026ldquo;policy,\u0026rdquo; and \u0026ldquo;sustainable development,\u0026rdquo; advocating for an integrated approach to climate issues. The annual publication trend shows a significant increase in interest, with a strong positive correlation (\u003cem\u003eR\u0026sup2; = 0.7097\u003c/em\u003e) and linear growth, emphasizing adaptive strategies. Leading journals include \u0026ldquo;Qeios Ltd,\u0026rdquo; \u0026ldquo;Handbook of Climate Change Resilience,\u0026rdquo; and \u0026ldquo;Sustainability.\u0026rdquo; Key terms like \u0026ldquo;Climate Change\u0026rdquo; and \u0026ldquo;Adaptation\u0026rdquo; have grown substantially, reflecting the evolving discourse. The co-authorship network reveals three main clusters, led by researchers such as David D. Woods, Andrea Nowak, and David Zilberman. Influential publications, highlighted by their Local Citation Scores, showcase both global and local impacts. The historical citation network and word cloud visualization emphasize the interconnectedness of key concepts, illustrating the collaborative and cumulative nature of research in this field. This review provides a comprehensive overview, guiding future studies, informing policy, and fostering collaboration to enhance climate resilience in agriculture. By leveraging these insights, policymakers can develop more effective, evidence-based strategies, ultimately contributing to sustainable development and food security. Future research can build on these findings to create more effective and sustainable solutions.\u003c/p\u003e","manuscriptTitle":"A two-decade bibliometric review of climate resilience in agriculture using the dimensions platform","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-20 05:56:02","doi":"10.21203/rs.3.rs-5112075/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":"160a310c-11d4-4870-ae3a-40a2d1dd16f4","owner":[],"postedDate":"September 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":37844840,"name":"Agronomy"},{"id":37844841,"name":"Renewable Resources"},{"id":37844842,"name":"Environmental Policy"},{"id":37844843,"name":"Agroecology"}],"tags":[],"updatedAt":"2024-09-20T05:56:02+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-20 05:56:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5112075","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5112075","identity":"rs-5112075","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}