Abstract
Individuals and communities socially construct risk, and societies with greater risk perception may be more apt to mobilize or adapt to emergent threats like climate change. Increasing climate change awareness is often considered necessary in the first stages of the adaptation process to manage its impacts and reduce overall vulnerability. Since agriculture is affected by climate change in several ways, farmers can provide first-hand observations of climate change impacts and adaptation options. This paper aims to identify the current research trends and set the future research agenda on climate change awareness, perceived impacts, and adaptive capacity from farmers’ experiences and behavior. We analyzed a portfolio of 435 articles collected from WoS and Scopus databases between 2010 and 2020 using bibliometrics. From the original portfolio, we select 108 articles for a more comprehensive and systematic review. Publication trends and content analysis have been employed to identify influential work, delineate the mental structure of farmers’ beliefs and concerns, and identify main research gaps. The comprehensive analysis reported (1) farmers’ socio-demographic characteristics influencing farmers’ perceptions; (2) awareness and changing climate evidence due to human activity; (3) the main perceived effects (rising temperatures, changing rainfall patterns, and extreme events); (4) the most relevant adaptation measures (crop changing and soil/water conservation techniques); and (5) factors and barriers limiting adaptation (lack of information, credit, and expertness). The review outlines the main gaps and their drivers to help future researchers, managers, and decision-makers to prioritize their actions according to farmers’ concerns and their adaptive capacity to reduce farming vulnerability.
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Introduction
Its scale, complexity, and controversy have made climate change one of the most globally debated risk representation objects (Li et al. 2017). Climate risk is directly linked to vulnerability because climate change impacts might result from the interaction of climate-related hazards with vulnerabilities of societies and systems exposed (Selvaraju 2012). Individuals and communities socially construct risk perception, and societies with greater risk perception may be more apt to mobilize or adapt to newly emerging threats (Smith and Mayer 2018; Soubry et al. 2020). One of the unique characteristics of climate change is that it is often seen as a distant psychological threat (Sterman and Sweeney 2007), whose effects and risks are spatially and temporally differentiated (Woods et al. 2017). In other words, its effects are assumed to impact individuals and communities that are geographically, temporally, and even generationally removed from themselves (Azadi et al. 2019a). Yet, events perceived to be “closer” to an individual tend to be more salient and have a more decisive proximate influence on individual decisions (Spence et al. 2012), thus increasing the perceived risk of climate-related extreme events (Azadi et al. 2019b; Bo and Wolff 2020).
Climate change is both a physical and social phenomenon (Hulme 2009), and individuals are not “blank slates” receiving information about climate change (Wolf and Moser 2011). Personal experience and local knowledge, together with social learning exchange, may help to reduce agricultural systems’ vulnerability. Along with different approaches, de Boer et al. (2016), Eitzinger et al. (2018), and more recently, Tiet et al. (2022) point out that individuals manage to trade off the information they receive about the consequences of climate change with their previous beliefs and local know-how about changes in weather patterns and past climate-related events in their area, thus generating adaptive behaviors able to integrate both types of knowledge. Furthermore, a recent study by Rust et al. (2022) confirmed how delving into farmers’ experiences could increase trust in others’ recommendations, indicating that social learning through similar peers — such as other farmers or water managers — is important for farmers to be persuaded to act.
Many have argued that deepening personal experience could be the first step for reducing individual and community psychological distance from climate change while promoting behavioral change (Phadke et al. 2015; Asplund 2016; Geiger et al. 2017; Wi 2019). Accordingly, social and behavioral sciences have discussed associative processing methods and the nature, extent, significance, and influence of the personal experience of climate change over the past decade to understand how it affects adaptive capacity, that is, the ability to moderate impacts or to cope with the consequences of climate change (Myers et al. 2013; Reser et al. 2014; van der Linden 2014; Broomell et al. 2015; Marlon et al. 2018). Among others, Reser and Bradley (2020) highlighted four main themes conditioning psychological distance: (1) the extent and underpinnings of public acceptance or “belief” regarding anthropogenic climate change; (2) the effectiveness of communication regarding climate change and the level of public engagement; (3) the nature of environmental risk awareness, perception, and response in the context of climate change; and (4) the unfolding and increasingly dramatic local and global biophysical environmental changes, events, and conditions attributed to climate change.
Increasing awareness is often considered necessary in the first stages of the adaptation process to manage climate change impacts and reduce overall vulnerability, because the degree of awareness tends to reflect the level of exposure to climate risks of a community (Ado et al. 2019). Consequently, being aware requires recognizing that climate change is a problem and understanding the risks and impacts that need to be dealt with (Lieske et al. 2014). On the other hand, risk perception is how individuals receive information or stimuli from their environment, transform it into psychological awareness, and (re)act accordingly. In other words, it refers to a mental construct, an individual’s assessment of the probability of a particular event and its consequences, or a subjective estimation of the nature of a threat and its severity (Azadi et al. 2019a). Although counterintuitive, some authors concluded that higher awareness of climate change might relate to lower risk perception due to risk normalization (Luis et al. 2018). Consequently, individuals could develop psychological risk minimization strategies to curtail perceived threats and psychologically adapt to the situations. Therefore, timely and accurate risk perception is an essential determinant of intentions and for the choice of adaptation methods (Deressa et al. 2011). In the case of farmers, poor risk perception may lead to maladaptation (i.e., fatalism, denial, and wishful thinking) and increase their vulnerability to climate change, while accurate risk perception may positively influence the farm level’s adaptation process (Le Dang et al. 2014).
Recency effects and occurrence of extreme meteorological events, such as an exceptionally rainy winter or a very dry summer, or sudden changes in daily temperature, can determine both risk awareness and perception (Ng’ombe et al. 2020). An individual’s level of concern about climate change can also vary by problem scale; problems often seem more urgent when perceived as local (Maas et al. 2020). For example, Schlüter et al. (2017) highlighted that in various behavioral models, individuals’ awareness and perception are input factors for climate change adaptation, while the behavior is the output. Otherwise, “belief” in climate change risks was heightened by the awareness of more observable climate change-related phenomena (e.g., extreme weather events or droughts) but it was not a direct cause of adaptation behavior (Li et al. 2021). Likewise, socio-economic and demographic variables such as gender, age, education, and income affect climate change awareness and its risks (Azocar et al. 2021; Mallappa and Shivamurthy 2021). Likewise, group norms and ideology, aligned with political party affiliation, have been shown to influence an individual’s belief in climate change (Dietz 2020).
Farmers develop their activity dealing with the complexity of interrelated nature and human systems characterized by biophysical conditions and socioeconomic transformations (Abid et al. 2016a, b). Consequently, farmers are in a favorable position to offer first-hand observations, while providing a deeper understanding of climate change manifestation, relevance, effects, and narratives (de Matos et al. 2020; Talanow et al. 2021). However, as some authors suggested, “seeing is not believing” for farmers, and even after being impacted by climatic extremes, many continue to be resistant to face climate change (Houser et al. 2019). Anyway, the nature and severity of some perceived impacts of climate change (e.g., increasing temperatures, heat stress, droughts, rainfall decrease, and changes in seasonality, pests, and diseases) reinforce the identification of climate change “hotspots,” in which agricultural activity could be heavily affected (Shukla et al. 2016). According to de Sherbinin (2014), the “hottest hotspots” are those in northern latitudes (concerning the Equator), which are predicted to experience significant temperature changes. The two most prominent hotspots are the Mediterranean, which will see declines in mean precipitation and has been confirmed as a “climate change hotspot for highly interconnected climate risks” (IPCC 2022), and North-Eastern Europe, which will suffer increases in winter precipitation and strong regional warming relative to the global mean. Likewise, Central America, southern Africa, and South Asia are predicted to increase precipitation variability. Agricultural vulnerability will increase in these regions where water availability is currently problematic (Pausas and Millan 2019; Tuel and Eltahir 2020). For example, in the Mediterranean region or the Southern European coast, the relative profitability of agriculture can be significantly reduced, and the loss of agricultural land and farmland value can vary from 60 to 80% by 2100 (EEA 2019).
Accurate bottom-up knowledge on the level of farmers’ climate change awareness and perception enables policy-makers and managers to understand and re-think climate change policies at the local level, which is essential to address agricultural risks in climate change hotspots (Simane et al. 2016; Asare-Nuamah and Botchway 2019). Farmers’ attitudes considering both perceived impacts and adaptation strategies have been only relatively explored through case study analyses (Etana et al. 2020; Tesfahun and Chawla 2020; Ahmed et al. 2021; Nalau and Verrall 2021). With this paper, we aim to comprehensively review the last decade’s literature on farmers’ behavior particularly focusing on which driving factors are building the scientific debate on farmers’ personal experience and local knowledge. We focus on two main research questions:
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RQ1: What is the current publication trend at the global scale on climate change awareness, perceived risk, and adaptive capacity from farmers’ experiences (e.g., authors’ profile, sources, affiliated countries and institutions, methods, keywords, and themes)? (Bibliometric analysis, BA)
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RQ2: How do farmers’ attitudes and perspectives determine their perception regarding climate change awareness, impacts, and adaptation measures and barriers? (Systematic literature review, SLR)
The remainder of this paper is structured as follows. The “Material and methods” section focuses on methodological aspects, where the use of BA and SLR is explained, and the process of their implementation is described. The results of the BA are provided in the “Bibliometrics” section, focusing on core subject areas, journals and authors’ profiles and co-citations, the temporal evolution of the research and co-occurrences, and ways in which risk, awareness, and perception are being clustered to address farmers’ behavior on climate change. The “Literature review of farmers’ behavior” section synthesizes findings from the SLR by presenting a detailed analysis of six main topics: (a) socio-demographic farmers’ profile, (b) awareness, (c) perceived impacts, (d) adaptation measures, (e) factors affecting adaptation, and (e) adaptation barriers and constraints. Opportunities and limitations to advance current research on perceived risks and adaptive capacity are finally discussed in the “Discussion and further research” section, including final remarks and implications for future research.
Material and methods
We combined BA and SLR to provide deeper state-of-the-art knowledge of farmers’ attitudes regarding climate change, considering awareness, perceived risks, and actions to increase adaptation. BA contributes a descriptive and statistical evaluation of scientific publications output for tracking progress and tracing knowledge of a research field (Opejin et al. 2020; Mao et al. 2021). The SLR is more robust than the traditional narrative review owing to its thorough, replicable, and transparent procedures, able to identify, assess, and interpret the available records on a particular theme with a broader motive to understand recent progress, find out the scientific gaps, and delineate the future directions (Crane et al. 2017; Mengist et al. 2020; Shaffril et al. 2021). Both tools can simplify the dynamic and complex linkages between different documents and associated information and entail visualization of the knowledge structure using data reduction techniques (Moral-Munoz et al. 2019).
Data collection
Web of Science and Scopus databases served for this study. The first one is the most authoritative citation database and has been widely applied for bibliometric analysis, while Scopus provides coverage of social sciences and farmers’ behavior-related publications (Das and Goswami 2021). The search was conducted in May 2021 and data from the period 2010–2020 were analyzed. The last decade was confirmed as the hottest decade since record-keeping began 140 years ago, according to the world’s temperature data and historical observations collected by the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA).
The review process followed a screening and inclusion criteria protocol in which results were filtered by language (English), type of publication (article or review), and core collection (no subject area restriction). The setting of the conceptual boundaries was based on the terms “climate change” + “risk,” “impact,” “perception,” “adaptation,” and their derivations, combined with terms describing their application in a rural environment (e.g., “farmer,” “irrigation”). We used a combination of a triple query protocol (Table 1).
The combination of each query returned 5784 and 1579 results in the Scopus and WoS databases, respectively. We applied a manual filtering process based on delete duplication (after normalizing the document’s titles and first author’s last name to ensure consistency between databases) and title screening. Consequently, 1438 results were ignored, and 4104 results were excluded after title screening for different reasons: the method was partially or totally out of the social scope of the study (e.g., life cycle assessment, modeling, cost–benefit analysis, ecosystem-based approach, indicators meaning); the topic was not significantly related to the field (e.g., projections on climate change impacts, perception from agriculture students and advisors, prospective scenarios and regional policy design, and climate change variability vs meteorological records); and the context expanded beyond agricultural areas (agroforestry, aquaculture). We consider the remaining 1821 results for abstract screening (512), of which 435 were used for the BA after a second screening process (Online Resource 1). Finally, 108 papers from full-text screening were used for the SLR, selecting those using a survey to collect farmers’ attitudes, as this tool can synthesize farmers’ perceptions and compare their behavior through a specific questions’ typology (Wheeler et al. 2021). Figure 1 presents the snapshot of the data collection and analysis method adopted in this study.
Data analysis
The selected literature was analyzed by considering both quantitative (univariate statistics) and qualitative (thematic analysis) methods. For the BA, data has been analyzed by combining two main procedures: performance analysis and science mapping. According to Rosato et al. (2021), performance analysis provides data about the volume and impact of research using a wide range of indicators and techniques (e.g., word frequency, citation, and counting publications by a unit of analysis). Science mapping, meanwhile, provides first- and second-generation relational indicators to create a spatial representation of how different elements relate to one another (e.g., co-citation, bibliographic coupling, and co-occurrence of keywords). We extracted different elements for each publication, including keywords, author information, institutional affiliation, journals, and citations, which allowed us to determine the academic performance and key issues in the field of farmers’ behavior on climate change.
We used the bibliometrix R-package (including the biblioshiny app) and OriginPro 2022 statistical software in combination with the VOSviewer software (version 1.6.17) (Aria and Cuccurullo 2017). The last one is a Java programming language used to create, visualize, and explore maps based on network data and taking a distance-based approach to visualizing a network of clusters in which nodes represent different elements duly organized according to their orders of magnitude (from higher to lower values) (Van Eck and Waltman 2020). For the SLR, a thematic analysis has been conducted with the aim of complementing BA results and minimizing bias. After carefully reading and categorizing the selected corpus of references, core themes and top-level concepts discussed in the literature have been analyzed by case study contributions (Pizzi et al. 2020). Finally, a causal-loop diagram (CLD) provides a straightforward graphical representation of the most relevant issues and interactions across the triple-loop dimensions (awareness, perceived impacts, and adaptation measures and barriers) obtained from the thematic analysis. This heuristic tool supports meaningful hypotheses for data gathering and theory building (Coletta et al. 2021), and can be used as a diagnostic mechanism that helps to identify potential gaps in current farmers’ experiences and behaviors.
Bibliometrics
This section presents the BA results in detail. First, we analyze the trends of publications considering the most influential authors and references (“Authors” section). Then, we present the results of sources co-citation analysis and category co-occurrence analysis to explore the discipline distribution and the most influential documents (“Sources and documents” section). The results of keyword plus analysis and burst detection are demonstrated in the “Keywords” section, while the “Themes” section reveals the main themes on which farmers’ behavior on climate change is focused on.
Authors
Our collection comprises 435 documents (422 research articles and 13 review articles) that account for 1428 authors from 65 countries, with a co-author’s ratio per document of 3.8 and a collaboration index of 3.44, with a high level of co-authorship (only 28 single-authored documents). Figure 2 synthesizes the authors’ plot results. The analysis reveals that the annual production of articles on climate change perception and adaptation from farmers’ behavior has not been constant over the period considered: recent years have seen rapid growth of this field, with 370 of the total articles published between 2015 and 2020 (i.e., 62 per year, on average, compared to 12 per year between 2010 and 2014).
The frequency of publication by authors is calculated through Lotka’s Law, concluding that 1256 authors (88%) have written just one document. The authors with the highest number of papers are Sha Fahad and Jianling Wang (Jiaotong University, China) (Huong et al. 2017; Fahad and Wang 2018; Fahad et al. 2018, 2020), Jinxia Wang (Peking University) (Wang et al. 2010, 2019; Hou et al. 2015; Zhang et al. 2017), Muhammad Abid (University of Islamabad, Pakistan) (Abid et al. 2015, 2016a, 2016b, 2019; Khan et al. 2020a, b), Samuel A. Donkoh (University for Development Studies, Ghana) (Kusakari et al. 2014; Azumah et al. 2017; Adzawla et al. 2019b, 2020; Tetteh et al. 2020), and Uttam Khanal and colleagues (Queensland University, Australia) (Khanal et al. 2018a, 2018b, 2019a, 2019b).
The main topics include climate change impacts on food production, crop vulnerability, crop choice, and determinants of adaptation to extreme weather events, especially from case studies in Pakistan, Nepal, and China. The majority of the top 10 most relevant authors concentrated their activity in the last 3 years, and just four published during the first half of the decade. Likewise, of 669 institutions, the five most relevant authors’ affiliations are from the universities of Addis Ababa, Putra Malaysia, Iowa State, Vermont, and Michigan State, while the USA and China lead corresponding authors’ countries.
The co-authorship and co-occurrence of leading authors considering fractional counting have been calculated according to three units of analysis: authors, affiliations, and countries. The authors’ analysis highlighted 38 co-authorships, duly organized in 14 clusters, with at least three articles published in common. Of them, the strongest collaboration is the cluster led by J. Gordon Arbuckle Jr. and colleagues and focused on farmers’ beliefs and perceived risks in the USA, including concepts such as techno-optimism or science-truth to deal with climate change-related issues (Arbuckle et al. 2013a, 2013b, 2015; Roesch-McNally et al. 2017; Gardezi and Arbuckle 2019, 2020). Regarding the affiliation analysis, only three co-authored papers were published by three authors from the same affiliation, while 47 papers from 29 clusters were published by two authors from the same institution. Thus, the field is characterized by a high degree of heterogeneity regarding co-authorship affiliation corpus, which in turn is related to the inclusion of authors’ affiliations not primarily focused on climate change studies, such as the top 3 affiliations by co-authored contributions: College of Resources, Science and Technology (Beijing Normal University), the Department of Sociology (Iowa State University), and the Institute of Agricultural and Resource Economics (University of Agriculture, Faisalabad, Pakistan). The difference in affiliations is also exemplified when considering co-authors’ countries: authors’ affiliations in co-authored publications sum a total of 90 countries, being 36 countries suitably organized in six clusters, where the one lead by the USA is the most relevant in terms of geographical interdependence in the last 5 years, while a secondary cluster co-led by China and Australia concentrate most authors’ citations received in 2018.
Sources and documents
The 435 documents have been published in 174 different sources. Of them, the top 10 journals were considered core sources according to Bradford’s Law, which describes how the articles on a particular subject are scattered throughout the mass of periodicals. These journals cover various topics, such as sustainable development, natural resources management, or geographical issues, but only four can be considered climate change journals. Furthermore, eight of the top 10 sources published more than ten articles, making up almost one-third of the library (32.6% of documents) (Table 2). Likewise, source dynamics highlighted 2015–2016 as the period in which core sources growth was faster, considering cumulate occurrences between sources (e.g., Sustainability was the journal that had grown more exponentially since 2015, when it added its first occurrence, while GeoJournal added their first occurrence in 2018 to increase its significance for nine times in 2020). Moreover, three journals (Climate and Development, Climatic Change, and Land Use Policy) indexed as top quartile journals (Q1) in different WoS categories (development studies, meteorology and atmospheric sciences, and environmental studies) accumulated between one-third and half of their occurrences in 2020 only (Fig. 3).
Besides the number of published documents, we considered additional indicators, related to citations, to eventually identify further sources that appear to be relevant for the scientific community. We distinguished between local and global citations: local citations refer to citations that a reference received from articles included in the collection; in contrast, global citations refer to the total citations that an article from the collection has received from articles not included in the collection, that is, all over the world. Our results (see Table 3) highlight that four out of the ten most cited documents were published on journals (The Journal of Agricultural Science, Journal of Environmental Management, Earth System Dynamics, and Global Environmental Change) not included in the top 10 sources (Fig. 3), with Global Environmental Change ranking first in terms of total global citations, with more than half of them (473 of 875 citations, 54.1%). The average of total citations per article was 18.6, but higher levels were identified between 2011 and 2013, when 44 articles were published. Regarding local citations, five countries (USA, Germany, China, UK, and Australia) lead the ranking by accumulating more than half (54.8%) of the total local citations.
The local and global citations ratio is 8.62, considering that the 435 documents accumulated 1051 local citations and 8109 global citations. Most documents (239 documents, 54.9%) were not cited at the local level but at the global level (just 45 documents, 10.3%, were not cited globally). Furthermore, the top 10 most cited documents were published between 2011 and 2015 in multifocal journals where environmental and climate change topics are dominant (Table 3). The first two ranked articles are those with the higher number of local and global citations, while the contributions by Esham and Garforth (2013) and Manandhar et al. (2011) score the maximum and minimum values of the ratio, respectively. Otherwise, the local citation ranking can be considered when analyzing the internal consistency of the library regarding mutual recognition between the most-cited contributions.
Keywords
After clustering synonymous keywords across the selected literature, the list of “keywords + ” function, which encompasses not only the keywords of the selected articles but also the keywords of the documents that these articles cite, was automatically generated by a computer algorithm. The analysis identified 981 most used author’s keywords and 1471 keywords + . Thus, a total of 5327 occurrences have been established, 22.5% (1207 occurrences) of them between the top 10 most used keywords + , identifying a triple focus on the challenging climate scenarios (climate change, climate effects), the farmers’ roles and perspectives (agricultural worker, smallholder, agriculture, farmers’ attitude, perception), and their capacity to respond to climate change impacts (adaptive management, adaptation, and strategic approach) (Fig. 4). Similar results were obtained at the title and abstract level, although some new keywords appeared, such as farmers’ knowledge or food security. Furthermore, evolution over time reveals that researchers initially tried to relate farmers’ behavior on climate change to keywords like mitigation and local adaptation, while, subsequently, they moved on to awareness, impacts, and resilience, mainly focused on adapted behavior, environmental impact assessment, and policy-making strategies to address risk perception, and vulnerability. Likewise, although not ranked first, the time scale highlighted the relevance of some methodological tools applied in the research, such as questionnaire survey (Morton et al. 2017; Brussow et al. 2019), interviews (Montgomery et al. 2017; Iniguez-Gallardo et al. 2020), climatological analysis (Tunde and Ajadi 2018; Nkuba et al. 2020), risk assessment (Mubaya et al. 2012; Abdul-Razak and Kruse 2017), cost–benefit analysis (Mitter et al. 2019; Singh 2020), and socio-economic indicators (Tesfahunegn et al. 2016; Quiroga et al. 2020).
Themes
We applied a clustering algorithm on the keyword plus co-occurrence network analysis to delineate the conceptual structure of the farmers’ behavior on climate change and define what science talks about and which are the main trends. Callon’s centrality index measures a network’s interaction or external cohesion degree, while Callon’s density index measures the internal strength or cohesion of the network. According to both indexes, research themes can be mapped as “motor-themes” if topics are well developed and are essential for structuring a research field; “basic themes” for those transversal topics with high expectancy in short-term development; “niche themes” for those issues of marginal importance with a lack of external feedbacks; and “emerging or declining themes” for those themes both weakly developed and peripheral for the advance of the research topic. Figure 5 shows the time span of combined Callon’s centrality and density indexes in two-time slices, 2010–2015 and 2016–2020. According to the obtained results, the number of clusters reduced over time: from ten clusters before 2015 to six since 2016, partially due to a concentration process in which some motor themes have been merged and evolved. Interestingly, the “adaptation” cluster remains the main motor theme for the whole period. In contrast, the “climate change” cluster ranks first during the whole period considering Callon’s density index, although tripling the number of occurrences since 2016, reinforcing his dominance as a basic theme. Regarding centrality, some restructuring has occurred among motor and basic themes. For example, “food security” and “crop production” were ranked as core issues (emerging themes) before 2015 but have been progressively included as examples of “intercropping” issues or as part of the basic theme “crops” (like “vulnerability” and “drought” issues). Likewise, “agriculture” was considered a niche theme and “agricultural management” a motor theme before 2015, but they have been progressively included in the “agriculture” cluster. “Empirical analysis” (based on case studies research) appeared as the only niche theme since 2016, highlighting a highly developed but partially isolated research interest.
Conversely, some top 10 most used keywords + (e.g., “perception,” “farmers’ attitude”) are missed as core themes but highly included as clusters’ sub-themes. Tables 4 and 5 synthesize the main characteristics of thematic analysis for each period (2010–2015 and 2016–2020). Three main conclusions can be highlighted: (1) clusters on “climate change,” “adaptation,” and “agriculture” remain in the three main clusters considering keywords + occurrence across both periods; (2) “perception” is considered one of the principal sub-themes in half of the 2010–2015 themes and one-third of the 2016–2020 themes; and (3) “climate change” is the most geographically distributed theme in both periods, although spatial coverage increased during 2016–2020, especially in Asia, Africa, and the Americas.
Literature review of farmers’ behavior
Socio-demographic characteristics
Most studies include a farmers’ profile with basic information regarding age, gender, education, farming experience, farm size, and association membership (Online Resource 2). Although age is put out of the analysis in some studies due to its multi-collinearity effect with farming experience (e.g., Abrha and Simhadri 2015), about 70% of the studies include this issue to deepen farmers’ socio-demographic profile. The dominant age range is differing: the mean age in studies carried out in Niger (e.g., Ado et al. 2019, 2020) or Vietnam (e.g., Nong et al. 2020) is under 40 years old, while in the Philippines (e.g., Lasco et al. 2016) or Zimbabwe (e.g., Mutandwa et al. 2019) is under 50 years, and the oldest farmers are surveyed in the USA (e.g., Liu et al. 2014) and China (e.g., Zhang et al. 2020). Likewise, some studies apply an “age barrier” on farmers (e.g., 50 years old) as a parameter to delve into the driving factors determining climate change perception (e.g., Idrissou et al. 2020).
Gender and farm size are considered in about half of the studies. Regarding gender, studies are men-focused, being only five studies in which the female gender exceeds 50% (e.g., Liu et al. 2014; Li et al. 2017; Ferdushi et al. 2019; Assan et al. 2020; Chhogyel et al. 2020), and just one specifically addressed to behavior analysis of female farmers (Lawson et al. 2020). Extremes in most common farm size are noted: from less than half a hectare in India (e.g., Esham and Garforth 2013; Aryal et al. 2020; Funk et al. 2020; Islam et al. 2020; Singh 2020; Sujakhu et al. 2020) to 5–10 ha in African countries (e.g., Ochieng et al. 2017; Akinbile et al. 2018; Idrissou et al. 2020), but about 25 ha in Cambodia (e.g., Thangrak et al. 2020) or 70 ha in Hungary (e.g., Li et al. 2017).
Education is included in more than two-thirds of the studies, providing two types of information: years of formal education or degrees achieved. Illiterate and primary education are the dominant categories in half of the studies, mainly located in African countries, such as Benin (e.g., Idrissou et al. 2020), Ghana (e.g., Assan et al. 2020), and Burkina Faso (e.g., Alvar-Beltran et al. 2020), but also in Asian countries, such as Pakistan (e.g., Bacha et al. 2018) or China (e.g., Quan et al. 2019). Otherwise, high school is the highest educational range in 11 studies, although in only three of them the representativeness is higher than 50%: China (e.g., Jin et al. 2015, 2016), the USA (e.g., Arbuckle et al. 2013b), and Hungary (e.g., Li et al. 2017). The farming experience is considered in about 40% of the studies. Surveyed farmers have more than 10 years of farming experience, with only two exceptions: the study by Chepkoech et al. (2020) in Kenya and Elum et al. (2017) in South Africa.
Awareness
Farmer views regarding the leading causes of climate change (e.g., human versus non-human induced) are more divergent than climate change occurrence. Only one in five papers asks about climate change awareness, and from that, 70% reported how farmers agree with statements like “the climate is changing” or “the climate change is occurring” (e.g., Niles et al. 2013; Ndamani and Watanabe 2017; Asrat and Simane 2018; Ferdushi et al. 2019; Biswas et al. 2020). However, only half of the sample delves into statements explaining the causes of climatic change (Online Resource 3). As a common trend, farmers tend to consider that climate is mainly changing because of human activity (e.g., Fadina and Barjolle 2018; Agesa et al. 2019; Roesch-McNally et al. 2017, 2020). For example, in a recent study among farmers in Pakistan, Fahad et al. (2020) revealed that the majority of farmers (73%) have noticed and are aware of the human role in climatic variations, while similar research conducted in South Africa by Elum et al. (2017) increases this evidence until 95% of the farmers. Moreover, few studies reflect how farmers consider climate change a result of human activity and natural changes (e.g., Mase et al. 2015; Abera and Tesema 2019; Amir et al. 2020a). On the contrary, farmers can also consider that climate change is not occurring due to a lack of physical evidence (Abid et al. 2016b). Although most papers reinforce a dominant farmers’ profile, some papers exemplify the diversity when characterizing farmers. For example, in the study by Arbuckle et al. (2013a) in the Midwestern United States, one-third of the respondents believed that climate change is caused by natural changes in the environment together with human activities, while another one-third of the farmers mainly focused on natural changes and the last third reports a lack of sufficient evidence to know if climate change is occurring and its causes.
Perceived impacts
Farmers’ perceptions of long-term or short-term changes in climate are a crucial pre-indicator in the climate change adaptation process. Studies reported 13 significant climate change impacts considering their physical and agricultural nature (detailed in Online Resource 4). Among them, farmers mainly perceive three impacts conditioning farming activity: (1) rising and extreme temperatures, (2) changing rainfall patterns and unpredictable and erratic trends, and (3) increasing drought and dry spells. Most studies report an increasing trend in temperature and variability (e.g., Asfaw et al. 2019), especially over the last 15–20 years (e.g., Fosu-Mensah et al. 2012; Esham and Garforth 2013; Akhtar et al. 2019), while including a slight increase in temperature for both summer and winter seasons (e.g., Abbas et al. 2019). Likewise, other studies focus on identifying unpredictive temperature-related events (e.g., Bagagnan et al. 2019) that seem larger and more robust than those historically experienced (e.g., Niles et al. 2013). Furthermore, a reduction in the number of cold days and an increase in the number of hot days have been reported in a few studies (Tambo and Abdoulaye 2013).
Regarding changes in rainfall patterns, farmers perceive a strong decrease in rainfall over the last decade (e.g., Comoe and Siegrist 2015; Brussow et al. 2019) but also changes in frequency and length of rainy days and seasons (e.g., Tesfahun and Chawla 2020). Some studies discuss potential discrepancies between farmers’ perceptions and meteorological observations of temperature and precipitation. For example, the study by Ochieng et al. (2017) in Kenya identifies a mismatch between farmers’ beliefs and evidence of climate data: farmers perceive a decline in rainfall, despite no evidence in the climate data. According to the authors, this could be due to increasing temperature since high temperature often leads to higher evapotranspiration and greater water demand. However, other studies identify a match between farmers’ perceptions and historical meteorological trends, especially regarding temperature increase and irregular precipitation patterns (e.g., Elum et al. 2017; Bacha et al. 2018).
The third most perceived risk (drought and dry spells) is directly related to the previous two (temperature and rainfall patterns) because the combination of persistent high temperatures and low rainfall periods is the main driver for drought risk, as reported in the study by Popoola et al. (2018) in South Africa. Similarly, Soglo and Nonvide (2019) determine from their experience in Benin that drought tends to occur every year during the crop production season due to decreasing rainfall patterns. Moreover, since agricultural yields are highly dependent on temperature and precipitation patterns, most farmers often blame an unfavorably changing climate for their decreasing yields and crop failures (e.g., Brussow et al. 2019), especially for maize, bean, and coffee farmers (e.g., Harvey et al. 2018). Additionally, most farmers detail an increase in pest and disease outbreaks (e.g., Fosu-Mensah et al. 2012; Shi et al. 2019) and soil-related problems, including soil infertility, soil salinity, and soil erosion (e.g., Abid et al. 2016b; Alotaibi et al. 2020; Aryal et al. 2020), leading to a reduction in the amount of organic matter and loss of rooting depth (e.g., Khan et al. 2020b) and increasing land degradation (e.g., Callo-Concha 2018; Kumasi et al. 2019).
Adaptation measures
Studies report 11 main climate change adaptation measures (Table 6 and further details in Online Resource 5), of which (1) changing cropping patterns, (2) introducing new crop varieties, and (3) promoting soil and water conservation techniques are the most applied. About half of the studies report examples of changing cropping patterns, including intercropping (e.g., Lawson et al. 2020), planting of short-term crops (e.g., Diallo et al. 2020), changing planting dates (e.g., Abid et al. 2016b), crop rotation (e.g., Fadina and Barjolle 2018), and crop combination (e.g., Ado et al. 2020). Likewise, studies highlight the introduction of new crop varieties more adapted to water scarcity (drought-tolerant crops) or new pests resulting from changing weather conditions (insect-tolerant crops) (Azumah et al. 2017). In their study in Bangladesh, authors such as Ferdushi et al. (2019) pointed out how crop diversification can be a compelling adaptation option to stabilize crop revenue and farm income. Frequently, crop diversification is accompanied by other measures such as planting shade trees to reduce soil moisture loss, as reported in the study by Esham and Garforth (2013) in Sri Lanka. Another complementary measure is extending cropping to the dry season to promote high-yielding hybrid crops and even long-duration crops, as reported by Tambo and Abdoulaye (2013) in Nigeria.
In some studies, such as Asfaw et al. (2019) in Ethiopia, the proportion of farmers who adapted to climate change is substantially less than those who perceive the incidence of a changing climate. However, although some studies report minor adaptation intention (e.g., one-third of the farmers in the study by Fahad et al. 2020 in Pakistan), in most studies, farmers had taken at least one adaptation strategy, even farmers developed various adaptation methods simultaneously (e.g., Funk et al. 2020), including the intensification of agricultural production by using more inputs, especially fertilizers, planting fruit and fodder tree, improving soil and water conservation practices, and using crop residues as livestock feed (e.g., Belay et al. 2017). For instance, farmers may change cropping patterns and crop varieties, which may require an increase/decrease in supplementary irrigation (e.g., Deressa et al. 2011). Farmers may also decide to change their occupation (switch to off-farm income) to earn additional income based on their livelihood (e.g., Marie et al. 2020) or to insure their crop in the event of crop failure through crop insurance (e.g., Fadairo et al. 2020; Singh 2020; Thinda et al. 2020).
Moreover, some studies distinguish adaptation measures considering their reactive or preventive nature. For example, the study carried out in Nepal by Budhathoki et al. (2020) reports the reactive nature of farmers during heatwaves, when they mainly apply better water management practices, alter fertilizer and pesticide use, and change crop types and planting dates, but as soon as the risk is overcome, they return to traditional practices. Similarly, some actions related to changing cropping practices or varieties are implemented by farm households in the short term but cannot be maintained in successive crop campaigns. For example, to cope with droughts in South Africa, as reported by Myeni and Moeletsi (2020) or in Ethiopia, as reported by Belay et al. (2017), or in response to more crop pest attacks on old varieties or to extreme maximum temperatures which are negatively affecting the growth of most productive varieties, as reported by Abid et al. (2016b) in Pakistan. Some adaptation options are applied given their long-term benefits to reduce risks, such as soil and water conservation techniques to avoid flooding risk by constructing small-scale irrigation dams (e.g., Gebru et al. 2020), adaptation to dry season farming by water stored for vegetable farmers (e.g., Sadiq et al. 2019), as well as improve soil moisture and organic matter retention in line with agroecological practices (e.g., Harvey et al. 2018).
Factors conditioning adaptation
Socio-demographic characteristics and land tenure are the main factors affecting farmers’ motivation to adapt (Online Resource 6). Regarding farmers’ profiles, most studies report age as statistically significant when considering climate change awareness and perceived risks. In this line, the study of Abbas et al. (2019) in Pakistan determines how older farmers are the ones who perceive climate risks and impacts more clearly, while the study of Alotaibi et al. (2020) in Saudi Arabia confirms how older farmers are also those with higher levels of beliefs regarding climate change occurrence. Likewise, Comoe and Siegrist (2015), in their study in Cote d’Ivoire, conclude that an increase in age significantly influences the adoption of new crop varieties with a short growing cycle, while young farmers more frequently adopt the crop association and intercropping techniques. Similarly, in their Ethiopian study, Belay et al. (2017) highlight that age increase is positively related to the decision to intensify agricultural inputs (e.g., fertilizers and pesticides use) but not highly related to the probability of the household adapting to climate change by tree planting.
Educational level significantly and positively influences the likelihood of the adoption of some adaptation strategies. For example, farmers with higher education are modifying crop varieties or changing the land area under cultivation (e.g., Esfandiari et al. 2020). Belay et al. (2017), in their study of Ethiopian farmers, identify how a unit increase in the number of years of education could increase by 2–3% of the likelihood of adopting crop diversification, change in planting date, and integrating crop with livestock production. An explanation would be that educated farmers are expected to be more inclined to adopt new technologies based on their awareness of the available climate change adaptation measures (e.g., Bagagnan et al. 2019).
Vulnerability to climate change tends to be gender-biased (e.g., Jin et al. 2015; Brussow et al. 2019), but some studies provide mixed findings asking whether adaptation strategies differ by gender. While some studies find no direct effect of gender (Lasco et al. 2016), others conclude that men and women choose different adaptation strategies (e.g., Soglo and Nonvide 2019; Aryal et al. 2020). For instance, Zhang et al. (2020) report that male farmers are more likely than female farmers to adopt a rotational grazing strategy. Authors suggest that this can be explained because men are more likely than women to access information about climate change and weather forecasts, increasing their adaptive capacity. Likewise, some studies identify how gender-related differences can be motivated by other socio-economic variables such as education (e.g., Afriyie-Kraft et al. 2020). The study by Hirpha et al. (2020) confirms that the likelihood of adapting to climate change in Ethiopia is higher for male-headed households than for female-headed households, mainly because of cultural and social norms.
Farm size mainly determines the decision to combine multiple strategies to cope with climate change. According to Fadina and Barjolle (2018), in their study in Benin, the larger the farm, the more farmers opt to combine several adaptation strategies: agroforestry and perennial plantation, crop-livestock diversification, or new crop varieties. Likewise, the study by Asrat and Simane (2018) in Ethiopia found that when the farm size increases by one hectare, the probability of adaptation by combining different cropping options increases by about 1% in the wet lowland and by about 15% in the dry lowland. Other studies focused on how farm size influences the type of adaptation. For example, Myeni and Moeletsi (2020) work in South Africa suggests that larger farms are less likely to adopt technical expertise adaptation in favor of traditional adaptation. The authors argue that this could probably be due to the labor-intensiveness and resource-intensiveness of the strategies. Thus, large farms require significant financial investments in labor and inputs, which can be financially unattainable.
The majority of regression tests also reveal that the household head’s farming experience significantly and positively influence farmers’ awareness of climate change. The study by Thangrak et al. (2020) in Cambodia concludes that farmers with more farming experience are likely to be more aware and to have a better understanding of climate change and farm-related decision-making. This fits well with the study by Ado et al. (2019) in Niger, in which an increase in farming experience by 1 year increases the likelihood of awareness by one unit. Similarly, more farming experience increases recommended agricultural practices and improves crop varieties (e.g., Aydogdu and Yenigun 2016; Kawadia and Tuwari 2017; Sadiq et al. 2019). In line with the study by Zhang et al. (2020), this implies that the higher the farming experience, the more the farmer will be aware of climate change and willing to adjust farming methods by acting on crops.
The land tenure system is vital to adaptation as landowners adopt new technologies more quickly than tenants. According to Roco et al. (2015), Chilean farmers with land tenure security exhibit a sharper awareness of environmental problems. Along the same line, in their study in Vietnam, Huong et al. (2017) report that farmer land tenure status is positively associated with most adaptation measures (e.g., water harvesting and infrastructures). According to the authors, farmers with long-term use rights of suitable land are more likely to adapt their farming to perceived climate change, reducing the probability of no adaptation to almost zero (Khan et al. 2020b).
Lastly, some studies confirm that union farm membership contributes to affront climate change impacts in a shared way, ensuring trust and confidence among the farmers (e.g., Aryal et al. 2020). Likewise, being part of a formal agricultural cooperative or association provides updated climate change information, improved agricultural inputs, and access to different farm equipment, which are crucial for increasing adaptation to climate change (e.g., Burnham 2017; Gebru et al. 2020). However, most studies are aware of the negative contribution of being member of a union farm. For example, Al-Amin et al. (2019) argue that farmers could receive misleading or contradictory climate change information or even ignore the existence of climate services to improve decision-making, while the study by Adzawla et al. (2019a, b) in Ghana determined that union farm membership did not substantially improve the farmers’ recovery capacity and resilience from climate shock.
Adaptation barriers and constraints
About one in four papers ask about which obstacles limit farmers’ ability to apply for adaptation measures. Farmers identify ten main barriers that hindered their adaptive capacity (Table 7 and Online Resource 7 for further details). The three major ones are (1) the lack of information on adaptation strategies and weather forecasting (confirmed by nearly two-thirds of the sample), (2) the lack of credit facilities and financial support to promote adaptation (according to half of the sample), and (3) the absence or poor irrigation expertness (reported by 40% of the sample). Interestingly, these three obstacles are combined in some papers (Ochieng et al. 2017; Zizinga et al. 2017; Ali et al. 2020; Marie et al. 2020). Authors such as Ochieng et al. (2017) and Esham and Garforth et al. (2020) identify a limited ability of farmers to access the necessary knowledge and technologies to adapt to the extreme effects aggravated by climate change. The explanation seems related to poor skills in improving farmers’ practices and access to weather forecasts and climate change-related information. Sujakhu et al. (2020) consider that farmers require different climate information during each stage of the farming process to appropriately adapt to climate change and its related hazards, while the study by Fahad and Wang (2018) in Pakistan opts to combine different information sources (e.g., the media, technicians) and personal experience. However, farmers, and more specifically smallholders, sometimes fail to adapt, even when provided with adequate information, because they are resource-constrained and are conditioned by a lack of credit facilities or financial support (e.g., Alemayehu and Bewket 2017; Zizinga et al. 2017). According to Sujakhu et al. (2020) or Zhang et al. (2020), with more financial resources, farmers are better able to use the available information to improve their management practices and make productive investments (e.g., they can purchase new crop varieties and irrigation technologies that are necessary for adjusting to climate changes or diversifying their livelihood and income sources).
The absence or the inadequacy of irrigation expertness are reported in studies carried out in Pakistan (e.g., Amir et al. 2020a) and Iran (e.g., Esfandiari et al. 2020), suggesting that the lack of mechanisms to better control both water allocation and water efficiency constrain farmers’ adaptive capacity, especially in some cropping systems (e.g., wheat and rice). The cost of current water conservation techniques is also mentioned, which is not always affordable for most farmers (e.g., Bagagnan et al. 2019). In most cases, this is associated with the inability of farmers to use both surface and groundwater due to limited technological and financial capacity (e.g., Ali et al. 2020). Moreover, some authors consider low literacy rates and lack of education as secondary barriers to adaptation (e.g., Belay et al. 2017; Bagagnan et al. 2019). Likewise, some barriers are different considering the gender dimension. For example, the study by Assan et al. (2020) on Ghanaian farmers highlights how women worry more about the lack of information and financial support than men, while men identify poor irrigation expertness as the main barrier to adaptation.
Discussion and further research
Climate change tends to be addressed by accurate statistics and modeling but it is generally perceived abstractly, differing from other hazards because it occurs gradually, over an extensive period, being difficult to directly discern changes as they occur (Weber 2016). Furthermore, climate change observations are spaced in time, and individual and collective memory of past events can be faulty or uncertain (Song et al. 2021), distinguishing between knowing facts (semantic) versus reliving events or experiences (episodic) (Plate 2017). Considering climate change as both a physical and social phenomenon, farmers’ knowledge and local experience is becoming more relevant to ensure reliable attitude change and increased adaptation. A better understanding of farmers’ behaviors is indeed fundamental to promoting accurate actions as it allows (i) focusing on the specific behaviors to be changed, (ii) examining the driving factors motivating those behaviors, (iii) defining and applying different interventions, and (iv) systematically evaluating the effects of these interventions on the resulting farmers’ behaviors.
Our study attempted to systematically examine the literature on farmers’ behavior by combining a triple-loop approach on risk awareness, perception, and adaptation. The review elicited how the research on climate change awareness, perceived impacts, and adaptation measures and barriers is fast-growing and illustrates an inherently multifocal research topic. A comprehensive BA pointed out research collaboration (e.g., high level of co-authorship) from a transdisciplinary perspective beyond climate change issues (e.g., sustainable development, natural resources management, urban–rural land use). Works included in the cluster led by J. Gordon Arbuckle Jr. and colleagues (e.g., Arbuckle et al. 2013a, 2013b, 2015), who pointed out farmers’ beliefs and perceived risks in the USA, exemplified this issue. Likewise, rapid growth in the publication ratio (85% of articles produced in the last 5 years) and an increasing number of global citations demonstrated main consolidated research areas related to climate change impacts (e.g., reduce on food production, crop vulnerability) and adaptation measures (e.g., crop choice), while new concepts (e.g., techno-optimism, science-truth) appeared to deal with extreme weather events (e.g., Gardezi and Arbuckle 2019, 2020) by prioritizing climate-smart agriculture (Gardezi et al. 2022). Thematic analysis and clustering confirmed a dichotomy in the research interest generated by the triple-loop dimensions: while “adaptation” was considered as a motor theme, structuring the research field, “perception” and “awareness” were partially considered as sub-themes, that is, being included in the basic theme “climate change” but without enough attention to be a niche or emerging theme. A recent review by Ricart et al. (2022) confirmed the low occurrence rate between climate change perception and awareness research in benefit of adaptation research. Moreover, previous research demonstrated how farmers’ awareness combined with an accurate perception is imperative to scale farmers’ ability to mitigate the effects on farming activities and as a preliminary step to increase adaptive capacity (Akano et al. 2022; Sen et al. 2021).
The SLR analysis delved into main themes isolated during the BA by highlighting farmers’ local experience from main topics, driving factors, motivations, and barriers when facing climate change. The first interesting point was the ability of multiple sociodemographic characteristics to influence farmers’ behavior regarding climate change: age, gender, education, farming experience, and farm size have been identified as key issues in understanding farmers’ adaptive capacity. Furthermore, it was possible to identify a dominant farmer’s profile from the analysis of the empirical research: a man of 40–50 years old, illiterate or with primary education, counting more than 10 years of farming experience, and working with a farm size between 5 and 10 ha. This profile confirms that most farmers have been farming in the area for quite a long time and therefore they could witness changes in temperatures and rainfall patterns (Mbwambo et al. 2021). Likewise, results show how oldest, highest educated, and most experienced farmers are the most aware of climate change occurrence, those who perceive more impacts, and who are more confident with adaptation measures to deal with climate change, while gender and farm size influence the way of adaptation but not the degree of agreement with climate change occurrence, perceived impacts, and need for adaptation.
The review upholds key interactions between farmers’ characteristics and behaviors regarding climate change awareness, perceived impacts, and adaptation measures and barriers (Fig. 6). Field observations support how farmers are primarily aware of climate change, which is considered the most challenging issue with direct effects on crop productivity, while they recognize human activities’ responsibility (including agricultural activity) in global warming. Some studies moved one step further and suggest that awareness, combined with local knowledge, are the main prerequisites for (smallholder) farmers to perceive climate change impacts and adopt adaptation strategies (e.g., Myeni and Moeletsi 2020; Roesch-McNally et al. 2020). Interestingly, and in line with recent studies by Reddy et al. (2022) and Sohail et al. (2022), the systematic review confirms that farmers’ awareness of climate change occurrence and severity is more robust than that of the causing factors of climate change. The review also identifies a common pattern to describe the main perceived impacts compared to those historically experienced, in which local knowledge was used in conjunction with scientific knowledge systems from meteorological data analysis (e.g., Ayanlade et al. 2017; Alvar-Beltran et al. 2020). Most of the reported case studies analyze both physical and agricultural impacts of climate change, although with greater detail on the first. Farmers noticed physical impacts such as rising extreme temperatures, changing rainfall patterns and erratic trends, and increased droughts frequency and/or intensity, whereas perceived agricultural impacts are limited to reducing crop production, increasing pests and diseases, and conditioning soil fertility combined with land degradation. Furthermore, some studies reported both types of impacts to delve into a causal relationship among them (e.g., Roco et al. 2015; Elum et al. 2017; Abbas et al. 2019; Ado et al. 2020).
Farmers promote adaptation measures capable of reinforcing crop production (e.g., changing cropping patterns, introducing new crop varieties) and improving natural resources management (e.g., promoting soil and water conservation techniques). However, as confirmed by a recent study (Paudel et al. 2022), some adaptation options are resource-intensive (e.g., fertilizers and agrochemicals use, water harvesting and infrastructures, supplementary irrigation), being inaccessible for smallholder farmers with limited capital or no access to financial support, which has been observed in most African and Asian case studies in which lack of credit facilities was the main barrier to adaptation (e.g., Bacha et al. 2018; Marie et al. 2020). To face this limitation, some authors (Abebe et al. 2022) advocate strengthening the comprehensive knowledge of the states of farmers’ adaptation by considering current and planned farm adaptation practices. Furthermore, and considering the nature of the reviewed studies in which farmers’ vulnerability is at the core of the research, attention should be put on the best cost-effective actions to ensure an effective rural and climate policy action to respond to evolving climate risk. In this line, authors such as Aleksandrova and Costella (2021) and Rana et al. (2022) advise reinforcing the social protection agenda to tackle the issues of poverty, inequality, and vulnerability, which should be integrated into comprehensive climate risk management practices.
The content analysis also reported that most explanatory factors for farmers’ awareness, perceived risks, and adaptive capacity are common among geographically distant case studies. The triple-loop dimensions are not geographically sensitive, meaning global climate change effects are perceived as locally relevant. This could be used to homogenize social learning from a local scale while checking common and replicable assessments to improve farmers’ adaptive capacity (Schlosberg and Collins 2014). However, the sample is not geographically representative. Although high-income countries perceived climate change impacts more clearly than ever before (Callaghan et al. 2021), a low representation of Global North-based literature has been identified, with a ratio of 1 to 9 in favor of Global South studies. Most studies focused on African and Asian countries (96 of 108 articles), both regions in the top 10 most affected areas by climate change according to the Global Climate Risk Index in 2020. This ratio enhances a recent literature review by Soubry et al. (2020) in which the proportion was 1 to 6. According to the mentioned authors, Global North studies tend to emphasize farmers’ characterization rather than how they perceive or react to climate change. Likewise, and concomitantly, the fact that farmers in the Global South have generally suffered first and more strongly (including forced migration) from climate impacts due to their consideration of climate change hotspots might bias the research interest towards the former region (Piguet 2022).
Another outcome of the review is the cross-sectional nature of the analyses (e.g., one-off surveys, interviews, or focus groups at a point in time). Although some sampled studies combine multi-stage techniques (e.g., Adzawla et al.2019a; Aryal et al. 2020) and different data collection tools (e.g., Asayehegn et al. 2017; Ado et al. 2020), in general, it remains unexplored how farmers’ awareness, perception and adaptation evolve. That is, farmers’ beliefs can differ some years later (e.g., due to the occurrence of new extreme events or after consolidating the use of climate services) and eventually guide different attitudes and motivate alternative behaviors (Sierra-Barón et al. 2021). Consequently, there is a need to shift research efforts from the point in time to over-time studies by using a panel approach (repeated surveys to the same farmers or similar profiles as representative) that could provide better information to close the farmers’ feedback loop. A recent study by Wheeler et al. (2021) employed panel data (following the same farmer over 5 years) to examine climate change perceptions’ influence on-farm adaptation. Results show that farmers who initially thought climate change imposed a risk had a higher propensity to apply more prudent farm practices, which subsequently decreased their climate risk perceptions after 5 years (and vice versa). Authors such as Dakurah (2021) suggest analyzing climatic data beyond inter-seasonal climatic events to include intra-seasonal climatic episodes as the latter are more critical to farmers: within every season, farmers are worried about when rain will start, how long will the season last, or if dry spells will occur. Likewise, it could be helpful to introduce past experiences in extreme events as examples of inter-seasonal climatic episodes to reduce farmers’ psychological distance to climate change and increase attitude change (Datta and Behera 2022).
We are aware of some limitations of our study, especially concerning data collection. Although an extensive sample has been used to carry out the BA and the SLR, the selection criteria were limited to scientific articles, excluding additional scientific documents (books, chapter books, reports, academic studies, etc.). Consequently, some publications providing empirical and local knowledge to reinforce foundational theories on farmers’ behavior regarding climate change have not been considered. Likewise, the sample was limited to English-speaking sources, which leaves out relevant contributions in other languages widely used to collect data at the local scale. Furthermore, the review targeted the survey results while complementary information from semi-structured interviews or focus groups remained in the background.
Considering the main results obtained from the BA and the SLR, and to face the limitations of the review, we suggest future research could explore three main questions: (1) Which socio-demographic characteristics are conditioning farmers’ climate change perceived impacts and how can they be analyzed in depth? (e.g., How characteristics can be synthesized in surveys to compare farmers’ profiles? Could other data collection tools such as semi-structured interviews or focus groups complement surveys’ feedback?); (2) How farmers’ awareness, perceived impacts, and adaptive capacity have evolved and how stable they are (e.g., Does longitudinal research ensure more robust farmers’ attitudes? Which drivers can destabilize farmers’ perception?); and (3) Is farmers’ behavior associated with the (in)existence of mitigation and adaptation strategies at regional and local scales? These three-fold questions could also facilitate the application of the Theory of Planned Behavior as the combination of the “antecedent or information” approach (i.e., internal drivers explaining farmers’ attitudes) with the “consequence or structural” approach (i.e., contextual factors encouraging farmers’ attitude change) (Masud et al. 2016). Consequently, a transdisciplinary investigation can further explore how farmers interact with climate change. For example, social sciences (e.g., Sociology, Psychology, and Geography) could identify the main social aspects influencing farmers’ behavior. In contrast, natural sciences (e.g., Agronomy, Earth Science, Geology, and Engineering) could produce more accurate climate change scenarios and projections in which risks and impacts will be easily identifiable by farmers.
Data Availability
The dataset reviewed during the current study are available in the reference list and characterized in the supplementary sources.
References
Abbas Q, Han J, Adeel A, Ullah R (2019) Dairy production under climatic risks: perception, perceived impacts and adaptations in Punjab, Pakistan. Int J Environ Res Public Health 16:4036. https://doi.org/10.3390/ijerph16204036
Abdul-Razak M, Kruse S (2017) The adaptive capacity of smallholder farmers to climate change in Northern Region of Ghana. Climate Risk Manage 17:104–122. https://doi.org/10.1016/j.crm.2017.06.001
Abebe F, Zuo A, Wheeler SA, Bjornlund H, Chilundo M, et al. (2022) The influences on farmers’ planned and actual farm adaptation decisions: evidence from small-scale irrigation schemes in South-Eastern Africa. Ecol Econ 202:107594. https://doi.org/10.1016/j.ecolecon.2022.107594
Abera N, Tesema D (2019) Perceptions and practices of climate change adaptation and mitigation strategies among farmers in the Konta Special District Ethiopia. Environ Socio-Econ Stud 7(4):1–16. https://doi.org/10.2478/environ-2019-0019
Abid M, Scheffran J, Schneider UA, Ashfaq M (2015) Farmers’ perception of and adaptation strategies to climate change and their determinants: the case of Punjab province, Pakistan. Earth Syst Dynam 6:225–243. https://doi.org/10.5194/esd-6-225-2015
Abid M, Schneider UA, Scheffran J (2016) Adaptation to climate change and its impacts on food productivity and crop income: perspectives of farmers in rural Pakistan. J Rural Stud 47(Part A):254–266. https://doi.org/10.1016/j.rurstud.2016.08.005
Abid M, Schilling J, Scheffran J, Zulfiqar F (2016b) Climate change vulnerability, adaptation and risk perceptions at farm level in Punjab, Pakistan. Sci Total Environ 547:447–460. https://doi.org/10.1016/j.scitotenv.2015.11.125
Abid M, Scheffran J, Schneider UA, Elahi E (2019) Farmer perceptions of climate change, observed trends and adaptation of agriculture in Pakistan. Environ Manage 63:110–123. https://doi.org/10.1007/s00267-018-1113-7
Abrha MG, Simhadri S (2015) Local climate trends and farmers’ perceptions in Southern Tigray Northern Ethiopia. Am J Environ Sci 11(4):262–277. https://doi.org/10.3844/ajessp.2015.262-277
Ado AM, Leshan J, Savadogo P, Bo L, Shah AA (2019) Farmers’ awareness and perception of climate change impacts: case study of Aguie district in Niger. Environ Dev Sustain 21:2963–2977. https://doi.org/10.1007/s10668-018-0173-4
Ado AM, Savadogo P, Pervez AKMK, Mudimu GT (2020) Farmers’ perceptions and adaptation strategies to climate risks and their determinants: insights from a farming community of Aguie district in Niger. GeoJournal 85:1075–1095. https://doi.org/10.1007/s10708-019-10011-7
Adzawla W, Kudadze S, Mohammed AR, Ibrahim II (2019) Climate perceptions, farmers’ willingness-to-insure farms and resilience to climate change in Northern region. Ghana. Environ Dev 32:100466. https://doi.org/10.1016/j.envdev.2019.100466
Adzawla W, Azumah SB, Anani PY, Donkoh SA (2019) Gender perspectives of climate change adaptation in two selected districts of Ghana. Heliyon 5(11):e02854. https://doi.org/10.1016/j.heliyon.2019.e02854
Adzawla W, Azumah SB, Anani PY, Donkoh SA (2020) Analysis of farm households’ perceived climate change impacts, vulnerability and resilience in Ghana. Scientific African 8:e00397. https://doi.org/10.1016/j.sciaf.2020.e00397
Afriyie-Kraft L, Zabel A, Damnyag L (2020) Adaptation strategies of Ghanaian cocoa farmers under a changing climate. Forest Policy Econ 113:102115. https://doi.org/10.1016/j.forpol.2020.102115
Agesa BL, Onyango CM, Kathumo VM, Onwonga RM, Karuku GN (2019) Climate change effects on crop production in Yatta sub-county: farmer perceptions and adaptation strategies. Afr J Food Agric Nutr Dev 19(1):14010–14042. https://doi.org/10.18697/ajfand.84.BLFB1017
Ahmed Z, Guha GS, Shew AM, Alam GMM (2021) Climate change risk perceptions and agricultural adaptation strategies in vulnerables riverine char islands of Bangladesh. Land Use Policy 103:105295. https://doi.org/10.1016/j.landusepol.2021.105295
Akano O, Modirwa S, Oluwasemire K, Oladele O (2022) Awareness and perception of climate change by smallholder farmers in two agroecological zones of Oyo state Southwest Nigeria. GeoJournal, Latest Articles. https://doi.org/10.1007/s10708-022-10590-y
Akhtar R, Afroz R, Masud MM, Rahman M, Khalid H, et al. (2018) Farmers’ perceptions, awareness, attitudes and adaptation behaviour towards climate change. J Asia Pac Econ 23(2):246–262. https://doi.org/10.1080/13547860.2018.1442149
Akhtar R, Masud MM, Afroz R (2019) Perception of climate change and the adaptation strategies and capacities of the rice farmers in Kedah Malaysia. Environ Urban Asia 10(1):99–115. https://doi.org/10.1177/0975425318822338
Akinbile LA, Aminu OO, Kolade RI (2018) Perceived effect of climate change on forest dependent livelihoods in Oyo State. Nigeria J Agr Extension 22(2):169–179. https://doi.org/10.4314/jae.v22i2.15
Al-Amin A, Akhter T, Islam A, Jahan H, Hossain MJ et al (2019) An intra-household analysis of farmers’ perceptions of and adaptation to climate change impacts: empirical evidence from drought prone zones of Bangladesh. Clim Change 156:545–565. https://doi.org/10.1007/s10584-019-02511-9
Alam MdM, Siwar C, Molla RI, Talib B, Toriman ME (2012) Paddy farmers’ adaptation practices to climatic vulnerabilities in Malaysia. Mitig Adapt Strateg Glob Change 17:415–423. https://doi.org/10.1007/s11027-011-9333-7
Alemayehu A, Bewket W (2017) Smallholder farmers’ coping and adaptation strategies to climate change and variability in the central highlands of Ethiopia. Local Environ 22(7):825–839. https://doi.org/10.1080/13549839.2017.1290058
Ali MF, Ashfaq M, Hassan S, Ullah R (2020) Assessing indigenous knowledge through farmers’ perception and adaptation to climate change in Pakistan. Pol J Environ Stud 29(1):525–532. https://doi.org/10.15224/pjoes/85194
Alotaibi BA, Kassem HS, Nayak RK, Muddassir M (2020) Farmers’ beliefs and concerns about climate change: an assessment from Southern Saudi Arabia. Agriculture 10:253. https://doi.org/10.3390/agriculture10070253
Alvar-Beltran J, Dao A, Marta AD, Heureux A, Sanou J, et al. (2020) Farmers’ perceptions of climate change and agricultural adaptation in Burkina Faso. Atmosphere 11:827. https://doi.org/10.3390/atmos11080827
Amamou H, Sassi MB, Aouadi H, Khemiri H, Mahouachi M, et al. (2018) Climate change-related risks and adaptation strategies as perceived in dairy cattle farming systems in Tunisia. Climate Risk Manage 20:38–49. https://doi.org/10.1016/j.crm.2018.03.004
Amir S, Saqib Z, Khan MI, Ali A, Khan MA, et al. (2020a) Determinants of farmers’ adaptation to climate change in rain-fed agriculture in Pakistan. Arab J Geosci 13:1025. https://doi.org/10.1007/s12517-020-06019-w
Amir S, Saqib Z, Khan MI, Khan MA, Bokhari SA, et al. (2020b) Farmers’ perceptions and adaptation practices to climate change in rainfed area: a case study from district Chakwal Pakistan. Pak J Agri Sci 57(2):465–475. https://doi.org/10.21162/PAKJAS/19.9030
Arbuckle JG, Morton LW, Hobbs J (2013a) Farmer beliefs and concerns about climate change and attitudes toward adaptation and mitigation: evidence from Iowa. Clim Change 118:551–563. https://doi.org/10.1007/s10584-013-0700-0
Arbuckle JG, Prokopy LS, Haigh T, Hobbs J, Knoot T et al (2013b) Climate change beliefs, concerns, and attitudes toward adaptation and mitigation among farmers in the Midwestern United States. Clim Change 117:943–950. https://doi.org/10.1007/s10584-013-0707-6
Arbuckle JG, Morton LW, Hobbs J (2015) Understanding farmer perspectives on climate change adaptation and mitigation: the roles of trust in sources of climate information, climate change beliefs, and perceived risk. Environ Behav 47(2):205–234. https://doi.org/10.1177/0013916513503832
Aria M, Cuccurullo C (2017) Bibliometrix: an R-tool for comprehensive science mapping analysis. J Informetr 11(4):959–975. https://doi.org/10.1016/j.joi.2017.08.007
Aryal JP, Sapkota TB, Rahut DB, Krupnik TJ, Shahrin S, et al. (2020) Major climate risks and adaptation strategies of smallholder farmers in Coastal Bangladesh. Environ Manage 66:105–120. https://doi.org/10.1007/s00267-020-01291-8
Asare-Nuamah P, Botchway E (2019) Comparing smallholder farmers’ climate change perception with climate data: the case of Adansi North District of Ghana. Heliyon 5(12):e03065. https://doi.org/10.1016/j.heliyon.2019.e03065
Asayehegn K, Temple L, Sanchez B, Iglesias A (2017) Perception of climate change and farm level adaptation choices in central Kenya. Cah Agric 26:25003. https://doi.org/10.1051/cagri/2017007
Asfaw A, Simane B, Bantider A, Hassen A (2019) Determinants in the adoption of climate change adaptation strategies: evidence from rainfed-dependent smallholder farmers in north-central Ethiopia (Woleka sub-basin). Environ Dev Sustain 21:2535–2565. https://doi.org/10.1007/s10668-018-0150-y
Asplund T (2016) Natural versus anthropogenic climate change: Swedish farmers’ joint construction of climate perceptions. Public Underst Sci 25(5):560–575. https://doi.org/10.1177/0963662514559655
Asrat P, Simane B (2018) Farmers’ perception of climate change and adaptation strategies in the Dabus watershed North-West Ethiopia. Ecological Processes 7:7. https://doi.org/10.1186/s13717-018-0118-8
Assan E, Suvedi M, Olabisi LS, Bansah KJ (2020) Climate change perceptions and challenges to adaptation among smallholder farmers in semi-arid Ghana: a gender analysis. J Arid Environ 182:104247. https://doi.org/10.1016/j.jaridenv.2020.104247
Ayanlade A, Radeny M, Morton JF (2017) Comparing smallholder farmers’ perception of climate change with meteorological data: a case study from southwestern Nigeria. Weather Clim Extremes 15:24–33. https://doi.org/10.1016/j.wace.2016.12.001
Aydogdu MH, Yenigun K (2016) Farmers’ risk perceptions towards climate change: a case of the GAP-Sanhurfa region Turkey. Sustainability 8:806. https://doi.org/10.3390/su8080806
Azadi Y, Yazdanpanah M, Mahmoudi H (2019a) Understanding smallholder farmers’ adaptation behaviors through climate change beliefs, risk perception, trust, and psychological distance: evidence from wheat growers in Iran. J Environ Manage 250:109456. https://doi.org/10.1016/j.jenvman.2019.109456
Azadi Y, Yazdanpanah M, Forouzani M, Mahmoudi H (2019b) Farmers’ adaptation choices to climate change: a case study of wheat growers in Western Iran. J Water Clim Change 10(1):102–116. https://doi.org/10.2166/wcc.2018.242
Azocar G, Billi M, Calvo R, Huneeus N, Lagos M, et al. (2021) Climate change perception, vulnerability, and readiness: inter-country variability and emerging patterns in Latin America. J Environ Stud Sci 11:23–36. https://doi.org/10.1007/s13412-020-00639-0
Azumah SA, Donkoh SA, Ansah IGK (2017) Contract farming and the adoption of climate change croping and adaptation strategies in the northern region of Ghana. Environ Dev Sustain 19:2275–2295. https://doi.org/10.1007/s10668-016-9854-z
Bacha MS, Nafees M, Adnan S (2018) Farmers’ perceptions about climate change vulnerabilities and their adaptation measures in District Swat. Sarhad J Agric 34(2):311–326. https://doi.org/10.17582/journal.sja/2018/34.2.311.326
Bagagnan AR, Ouedraogo I, Fonta WM (2019) Perceived climate variability and farm level adaptation in the central river region of the Gambia. Atmosphere 10:423. https://doi.org/10.3390/atmos10070423
Bakhsh K, Kamran MA (2019) Adaptation to climate change in rain-fed farming system in Punjab Pakistan. Int J Commons 13(2):833–847. https://doi.org/10.5334/ijc.887
Belay A, Recha JW, Woldeamanuel T, Morton JF (2017) Smallholder farmers’ adaptation to climate change and determinants of their adaptation decisions in the Central Rift Valley of Ethiopia. Agric Food Secur 6:24. https://doi.org/10.1186/s40066-017-0100-1
Biswas S, Chaterjee S, Roy DC (2020) Understanding of farmers’ perception of climate change and adaptation strategies: a case study in Jhargram distriact of West Bengal India. J Appl Natur Sci 12(2):207–212. https://doi.org/10.31018/jans.vi.2241
Bo S, Wolff K (2020) I can see clearly now: episodic future thinking and imaginability in perceptions of climate-related risk events. Front Psychol 11:218. https://doi.org/10.3389/fpsyg.2020.00218
Broomell SB, Budescu DV, Por H-H (2015) Personal experience with climate change predicts intentions to act. Global Environ Chang 32:67–73. https://doi.org/10.1016/j.gloenvcha.2015.03.001
Brussow K, Gornott C, Fabe A, Grote U (2019) The link between smallholders’ perception of climatic changes and adaptation in Tanzania. Clim Change 157:545–563. https://doi.org/10.1007/s10584-019-02581-9
Bryan E, Ringler C, Okoba B, Roncoli C, Silvestri S, et al. (2013) Adapting agriculture to climate change in Kenya: household strategies and determinants. J Environ Manage 114:26–35. https://doi.org/10.1016/j.jenvman.2012.10.036
Budhathoki NK, Paton D, Lassa JA, Zander KK (2020) Assessing farmers’ preparedness to cope with the impacts of multiple climate change-related hazards in the Terai lowlands of Nepal. Int J Disast Risk Re 49:101656. https://doi.org/10.1016/j.ijdrr.2020.101656
Burnham M, Ma Z (2017) Climate change adaptation: factors influencing Chinese smallholder farmers’ perceived self-efficacy and adaptation intent. Reg Environ Change 17:171–186. https://doi.org/10.1007/s10113-016-0975-6
Callaghan M, Schleussner CF, Nath S, Lejeune Q, Knutson TR et al (2021) Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies. Nat Clim Chang 11:966–972. https://doi.org/10.1038/s41558-021-01168-6
Callo-Concha D (2018) Farmer perceptions and climate change adaptation in the West Africa Sudan Savannah: reality check in Dassari, Benin, and Dano Burkina Faso. Climate 6:44. https://doi.org/10.3390/cli6020044
Chepkoech W, Mungai NW, Stober S, Lotze-Campen H (2020) Understanding adaptive capacity of smallholder African indigenous vegetable farmers to climate change in Kenya. Climate Risk Manage 27:100204. https://doi.org/10.1016/j.crm.2019.100204
Chhogyel N, Kumar L, Bajgai Y, Hasan MdK (2020) Perceptions of farmers on climate change and its impacts on agriculture across various altitudinal zones of Bhutan Himalayas. Int J Environ Sci Te 17:3607–3620. https://doi.org/10.1007/s13762-020-02662-8
Coletta VR, Pagano A, Pluchinotta I, Fratino U, Scrieciu A, et al. (2021) Causal Loop Diagrams for supporting Nature Based Solutions participatory design and performance assessment. J Environ Manage 280:111668. https://doi.org/10.1016/j.jenvman.2020.111668
Comoe H, Siegrist M (2015) Relevant drivers of farmers’ decision behavior regarding their adaptation to climate change: a case study of two regions in Cote d’Ivoire. Mitig Adapt Strateg Glob Change 20:179–199. https://doi.org/10.1007/s11027-013-9486-7
Crane TA, Delaney A, Tamás PA, Chesterman S, Ericksen P (2017) A systematic review of local vulnerability to climate change in developing country agriculture. Wiley Interdiscip Rev Clim Chang 8(4):e464. https://doi.org/10.1002/wcc.464
Dakurah G (2021) How do farmers’ perceptions of climate variability and change match or and mismatch climatic data? Evidence from North-West Ghana Geojournal 86(5):2387–2406. https://doi.org/10.1007/s10708-020-10194-4
Das S, Goswami K (2021) Progress in agricultural vulnerability and risk research in India: a systematic review. Reg Environ Change 21:24. https://doi.org/10.1007/s10113-021-01749-3
Datta P, Behera B (2022) Factors influencing the feasibility, effectiveness, and sustainability of farmers’ adaptation strategies to climate change in the Indian Eastern Himalayan Foothills. Environ Manage 70:911–925. https://doi.org/10.1007/s00267-022-01724-6
de Boer J, Botzen W, Terpstra T (2016) Flood risk and climate change in the Rotterdam area, the Netherlands: enhancing citizen’s climate risk perceptions and prevention responses despite skepticism. Reg Environ Change 16:1613–1622. https://doi.org/10.1007/s10113-015-0900-4
de Matos Carlos S, da Cunha DA, Pires MV, do Couto-Santos FR (2020) Understanding farmers’ perceptions and adaptation to climate change: the case of Rio das Contas basin, Brazil. GeoJournal 85:805–821. https://doi.org/10.1007/s10708-019-09993-1
de Sherbinin A (2014) Climate change hotspots mapping: what have we learned? Clim Change 123:23–37. https://doi.org/10.1007/s10584-013-0900-7
Deressa TT, Hassan RM, Ringler C (2011) Perception of and adaptation to climate change by farmers in the Nile basin of Ethiopia. J Agric Sci 149(1):23–31. https://doi.org/10.1017/S0021859610000687
Diallo A, Donkor E, Owusu V (2020) Climate change adaptation strategies, productivity and sustainable food security in southern Mali. Clim Change 159:309–327. https://doi.org/10.1007/s10584-020-02684-8
Dietz T (2020) Political events and public views on climate change. Clim Change 161:1–8. https://doi.org/10.1007/s10584-020-02791-6
EEA (2019) Climate change adaptation in the agriculture sector in Europe, EEA Report No 4/2019, European Environment Agency. https://doi.org/10.2800/537176
Eitzinger A, Binder C, Meyer M (2018) Risk perception and decision-making: do farmers consider risks from climate change? Clim Change 151(3–4):507–524. https://doi.org/10.1007/s10584-018-2320-1
Elum ZA, Modise DM, Marr A (2017) Farmer’s perception of climate change and responsive strategies in three selected provinces of South Africa. Climate Risk Manage 16:246–257. https://doi.org/10.1016/j.crm.2016.11.001
Esfandiari M, Khalilabad HRM, Boshrabadi HM, Mehrjerdi MRZ (2020) Factors influencing the use of adaptation strategies to climate change in paddy lands of Kamfiruz. Iran. Land Use Policy 95:104628. https://doi.org/10.1016/j.landusepol.2020.104628
Esham M, Garforth C (2013) Agricultural adaptation to climate change: insights from a farming community in Sri Lanka. Mitig Adapt Strat Gl 18:535–549. https://doi.org/10.1007/s11027-012-9374-6
Etana D, van Wesenbeeck CFA, de Cock-Buning T (2020) Socio-cultural aspects of farmers’ perception of the risk of climate change and variability in Central Ethiopia. Clim Dev 13(2):139–151. https://doi.org/10.1080/17565529.2020.1737796
Fadairo O, Williams PA, Nalwanga FS (2020) Perceived livelihood impacts and adaptation of vegetable farmers to climate variability and change in selected sites from Ghana, Uganda and Nigeria. Environ Dev Sustain 22:6831–6849. https://doi.org/10.1007/s10668-019-00514-1
Fadina AMR, Barjolle D (2018) Farmers’ adaptation strategies to climate change and their implications in the Zou Department of South Benin. Environments 5:15. https://doi.org/10.3390/environments5010015
Fahad S, Wang J (2018) Farmers’ risk perception, vulnerability, and adaptation to climate change in rural Pakistan. Land Use Policy 79:301–309. https://doi.org/10.1016/j.landusepol.2018.08.018
Fahad S, Wang J, Khan AA, Ullah A, Ali U et al (2018) Evaluation of farmers’ attitude and perception toward production risk: lessons from Khyber Pakhtunkhwa Province Pakistan. Hum Ecol Risk Assess 24(6):1710–1722. https://doi.org/10.1080/10807039.2018.1460799
Fahad S, Inayat T, Wang J, Dong L, Hu G, et al. (2020) Farmers’ awareness level and their perceptions of climate change: a case of Khyber Pakhtunkhwa Province Pakistan. Land Use Policy 96:104669. https://doi.org/10.1177/j.landusepol.2020.104669
Ferdushi KF, Ismail MT, Kamil AA (2019) Perceptions, knowledge and adaptation about climate change: a study on farmers of Haor areas after a flash flood in Bangladesh. Climate 7:85. https://doi.org/10.3390/cli7070085
Fosu-Mensah BY, Vlek PLG, MacCarthy DS (2012) Farmers’ perception and adaptation to climate change: a case study of Sekyedumase district in Ghana. Environ Dev Sustain 14:495–505. https://doi.org/10.1007/s10668-012-9339-7
Funk C, Sathyan AR, Winker P, Breuer L (2020) Changing climate – changing livelihood: smallholder’s perceptions and adaptation strategies. J Environ Manage 259:109702. https://doi.org/10.1016/j.jenvman.2019.109702
Gardezi M, Arbuckle JG (2019) The influence of objective and perceived adaptive capacity on Midwestern farmers’ use of cover crops. Weather Clim Soc 11(3):665–679. https://doi.org/10.1175/WCAS-D-18-0086.1
Gardezi M, Arbuckle JG (2020) Techno-optimism and farmers’ attitudes toward climate change adaptation. Environ Behav 52(1):82–105. https://doi.org/10.1177/0013916518793482
Gardezi M, Michael S, Stock R, Vij S, Ogunyiola A, et al. (2022) Prioritizing climate-smart agriculture: an organizational and temporal review. WIREs Clim Change 13(2):e755. https://doi.org/10.1002/wcc.755
Gebru GW, Ichoku HE, Phil-Eze PO (2020) Determinants of smallholder farmers’ adoption of adaptation strategies to climate change in Eastern Tigray National Regional State of Ethiopia. Heliyon 6:e04356. https://doi.org/10.1016/j.heliyon.2020.e04356
Geiger N, Swim JK, Fraser J (2017) Creating a climate for change: interventions, efficacy and public discussion about climate change. J Environ Psychol 51:104–116. https://doi.org/10.1016/j.jenvp.2017.03.010
Harvey CA, Saborio-Rodriguez M, Martinez-Rodriguez MR, Viguera B, Chain-Guadarrama A, et al. (2018) Climate change impacts and adaptation among smallholder farmers in Central America. Agric & Food Secur 7:57. https://doi.org/10.1186/s40066-018-0209-x
Hasibuan AM, Gregg D, Stringer R (2020) Accounting for diverse risk attitudes in measures of risk perceptions: a case study of climate change risk for small-scale citrus farmers in Indonesia. Land Use Policy 95:104252. https://doi.org/10.1016/j.landusepol.2019.104252
Hirpha HH, Mpandeli S, Bantider A (2020) Determinants of adaptation strategies to climate change among the smallholder farmers in Adama District Ethiopia. Int J Clim Chang Str 12(4):463–476. https://doi.org/10.1108/IJCCSM-01-2019-0002
Hisali E, Birungi P, Buyinza F (2011) Adaptation to climate change in Uganda: evidence from micro level data. Global Environ Chang 21(4):1245–1261. https://doi.org/10.1016/j.gloenvcha.2011.07.005
Hou L, Huang J, Wang J (2015) Farmers’ perceptions of climate change in China: the influence of social networks and farm assets. Clim Res 63:191–201. https://doi.org/10.3354/cr01295
Houser M, Gunderson R, Stuart D (2019) Farmers’ perception of climate change in context: toward a political economy of relevance. Sociol Ruralis 59(4):789–809. https://doi.org/10.1111/soru.12268
Hulme M (2009) Why we disagree about climate change: understanding controversy, inaction and opportunity. Cambridge University Press, London
Huong NTL, Bo YS, Fahad S (2017) Farmers’ perception, awareness and adaptation to climate change: evidence from northwest Vietnam. Int J Clim Chang Str 9(4):555–576. https://doi.org/10.1108/IJCCSM-02-2017-0032
Idrissou YI, Assani AS, Baco MN, Yabi AJ, Traoré IA (2020) Adaptation strategies of cattle farmers in the dry and sub-humid tropical zones of Benin in the context of climate change. Heliyon 6:e04373. https://doi.org/10.1016/j.heliyon.2020.e04373
Iniguez-Gallardo V, Bride I, Tzanapoulos J (2020) Between concepts and experiences: understandings of climate change in southern Ecuador. Public Underst Sci 29(7):745–756. https://doi.org/10.1177/0963662520936088
Iqpal MA, Abbas A, Naqvi SAA, Rizwan M, Samie A, et al. (2020) Drivers of farm households’ perceived risk sources and factors affecting uptake of mitigation strategies in Punjab Pakistan: implications for sustainable agriculture. Sustainability 12:9895. https://doi.org/10.3390/su12239895
Islam MsM, Jannat A, Dhar AR, Ahamed T (2020) Factors determining conversion of agricultural land use in Bangladesh: farmers’ perceptions and perspectives of climate change. GeoJournal 85:343–362. https://doi.org/10.1007/s10708-018-09966-w
IPCC (2022) Climate change 2022: impacts, adaptation, and vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. In: Pörtner H-O, Roberts DC, Tignor M, Poloczanska ES, Mintenbeck K, Alegría A, Craig M, Langsdorf S, Löschke S, Möller V, Okem A, Rama B (eds.). Cambridge University Press. Cambridge University Press, Cambridge, UK and New York, NY, USA, p 3056. https://doi.org/10.1017/9781009325844
Jin J, Wang X, Gao Y (2015) Gender differences in farmer’ responses to climate change adaptation in Yongqiao district, China. Sci Total Environ 538:942–948. https://doi.org/10.1016/j.scitotenv.2015.07.027
Jin J, Wang W, Wang X (2016) Adapting agriculture to the drought hazard in rural China: household strategies and determinants. Nat Hazards 82:1609–1619. https://doi.org/10.1007/s11069-016-2260-x
Kawadia G, Tuwari E (2017) Farmers’ perception of climate change in Madhya Pradesh. Area Dev Pol 2(2):192–207. https://doi.org/10.1080/23792949.2017.1309985
Khan NA, Gao Q, Iqbal MA, Abid M (2020a) Modeling food growers’ perceptions and behavior towards environmental changes and its induced risks: evidence from Pakistan. Environ Sci Pollut R 27:20292–20308. https://doi.org/10.1007/s11356-020-08341-y
Khan I, Lei H, Shah IA, Ali I, Khan I, et al. (2020) Farm households’ risk perception, attitude and adaptation strategies in dealing with climate change: promise and perils from rural Pakistan. Land Use Policy 91:104395. https://doi.org/10.1016/j.landusepol.2019.104395
Khanal U, Wilson C, Lee B, Hoang V-N (2018a) Smallholder farmers’ participation in climate change adaptation programmes: understanding preferences in Nepal Clim. Policy 18(7):916–927. https://doi.org/10.1080/14693062.2017.1389688
Khanal U, Wilson C, Hoang V-N, Lee B (2018b) Farmers’ adaptation to climate change, its determinants and impacts on rice yield in Nepal. Ecol Econ 144:139–147. https://doi.org/10.1016/j.ecolecon.2017.08.006
Khanal U, Wilson C, Hoang V-N, Lee B (2019a) Autonomous adaptations to climate change and rice productivity: a case study of the Tanahun district Nepal. Clim Dev 11(7):555–563. https://doi.org/10.1080/17565529.2018.1469965
Khanal U, Wilson C, Hoang V-N, Lee B (2019b) Impact of community-based organizations on climate change adaptation in agriculture: empirical evidence from Nepal. Environ Dev Sustain 21:621–635. https://doi.org/10.1007/s10668-017-0050-6
Kumasi TC, Antwi-Agyei P, Obiri-Danso K (2019) Small-holder farmers’ climate change adaptation practices in the Upper East region of Ghana. Environ Dev Sustain 21:745–762. https://doi.org/10.1007/s10668-017-0062-2
Kusakari Y, Asubonteng KO, Jasaw GS, Dayour F, Dzivenu T et al (2014) Farmer-perceived effects of climate change on livelihoods in Wa Dest Dsitrict, Upper West Region of Ghana. J Disaster Res 9(4):516–528. https://doi.org/10.20965/jdr.2014.p0516
Lasco RD, Espaldon MLO, Habito CMD (2016) Smallholder farmers’ perceptions of climate change and the roles of trees and agroforestry in climate risk adaptation: evidence from Bohol, Philippines. Agroforest Syst 90:521–540. https://doi.org/10.1007/s10457-015-9874-y
Lawson ET, Alare RS, Salifu ARZ, Thompson-Hall M (2020) Dealing with climate change in semi-arid Ghana: understanding intersectional perceptions and adaptation strategies of women farmers. GeoJournal 85:439–452. https://doi.org/10.1007/s10708-019-09974-4
Le Dang H, Li E, Nuberg I, Bruwer J (2014) Understanding farmers’ adaptation intention to climate change: a structural equation modelling study in the Mekong delta Vietnam. Environ Sci Policy 41:11–22. https://doi.org/10.1016/j.envsci.2014.04.002
Li S, Juhasz-Horvath L, Harrison PA, Pinter L, Rounsevell MDA (2017) Relating farmer’s perceptions of climate change risk to adaptation behaviour in Hungary. J Environ Manage 185:21–30. https://doi.org/10.1016/j.jenvman.2016.10.051
Li W, Ruiz-Menjivar J, Zhang L, Zhang J (2021) Climate change perceptions and the adoption of low carbon-agricultural technologies: evidence from rice production systems in the Yangtze River Basin. Sci Total Environ 759:143554. https://doi.org/10.1016/j.scitotenv.2020.143554
Lieske DJ, Wade T, Ann L (2014) Climate change awareness and strategies for communicating the risk of coastal flooding: a Canadian Maritime case example. Estuar Coast Shelf S 140:83–94. https://doi.org/10.1016/j.ecss.2013.04.017
Liu Z, Smith WJ Jr, Safi AS (2014) Rancher and farmer perceptions of climate change in Nevada, USA. Clim Change 122:313–327. https://doi.org/10.1007/s10584-013-0979-x
Luis S, Vauclair C-M, Lima ML (2018) Raising awareness of climate change causes? Cross-national evidence for the normalization of societal risk perception of climate change. Environ Sci Policy 80:74–81. https://doi.org/10.1016/j.envsci.2017.11.015
Maas A, Wardropper C, Roesch-McNally G, Abatzoglou J (2020) A (mis)alignment of farmer experience and perceptions of climate change in the U.S. inland Pacific Northwest. Clim Change 162:1011–1029. https://doi.org/10.1007/s10584-020-02713-6
Macholdt J, Honermeier B (2016) Variety choice in crop production for climate change adaptation: farmer evidence from Germany. Outlook Agric 45(2):117–123. https://doi.org/10.1177/0030727016650770
Mallappa VKH, Shivamurthy M (2021) Factor influencing fishery-based farmers’ perception and their response to climate-induced crisis management. Environ Dev Sustain 23:11766–11791. https://doi.org/10.1007/s10668-020-01141-x
Manandhar S, Vogt DS, Perret SR, Kazama F (2011) Adapting cropping systems to climate change in Nepal: a cross-regional study of farmers’ perception and practices. Reg Environ Change 11:335–348. https://doi.org/10.1007/s10113-010-0137-1
Mao G, Hu H, Liu X, Crittenden J, Huang N (2021) A bibliometric analysis of industrial wastewater treatments from 1998 to 2019. Environ Pollut 275:115785. https://doi.org/10.1016/j.envpol.2020.115785
Marie M, Yirga F, Haile M, Tquabo F (2020) Farmers’ choices and factors affecting adoption of climate change adaptation strategies: evidence from northwestern Ethiopia. Heliyon 6:e03867. https://doi.org/10.1016/j.heliyon.2020.e03867
Marlon JR, van der Linden S, Howe P, Leiserowitz A, Woo SHL, et al. (2018) Detecting local environmental change: the role of experience in shaping risk judgments about global warming. J Risk Res 22:936–950. https://doi.org/10.1080/13669877.2018.1430051
Mase AS, Gramig BM, Prokopy LS (2015) Climate change beliefs, risk perceptions, and adaptation behaviour among Midwestern U.S. crop farmers. Clim Risk Manag 15:8–17. https://doi.org/10.1016/j.crm.2016.11.004
Masud MM, Al-Amin AQ, Junsheng H, Ahmed F, Yahaya SR, et al. (2016) Climate change issue and theory of planned behaviour: relationship by empirical evidence. J Clean Prod 113:613–623. https://doi.org/10.1016/j.clepro.2015.11.080
Mengist W, Soromessa T, Legese G (2020) Method for conducting systematic literature review and meta-analysis for environmental science research. MethodsX 7:100777. https://doi.org/10.1016/j.mex.2019.100777
Mitter H, Larcher M, Schonhart M, Stottinger M, Schmid E (2019) Exploring farmers’ climate change perceptions and adaptation intentions: empirical evidence from Austria. Environ Manage 63:804–821. https://doi.org/10.1007/s00267-019-01158-7
Montgomery SC, Martin RJ, Guppy C, Wright GC, Tighe MK (2017) Farmer knowledge and perception of production constraints in Northwest Cambodia. J Rural Stud 56:12–20. https://doi.org/10.1016/j.rurstud.2017.09.003
Moral-Munoz JA, López-Herrera AG, Herrera-Viedma E, Cobo MJ (2019) Science mapping analysis software tools: a review. In: Glanzel W, Moed HF, Schmoch U, Thelwall M (eds) Springer handbook of science and technology indicators. Springer, Cham. https://doi.org/10.1007/978-3-030-02511-3_7
Morton LW, Roesch-McNally G, Wilke AK (2017) Upper Midwest farmer perceptions: too much uncertainty about impacts of climate change to justify changing current agricultural practices. J Soil Water Conserv 72(3):215–225. https://doi.org/10.2489/jswc.72.3.215
Mubaya CP, Njuki J, Mutsvangwa EP, Mugabe FT, Nanja D (2012) Climate variability and change or multiple stressors? Farmer perceptions regarding threats to livelihoods in Zimbabwe and Zambia. J Environ Manage 102:9–17. https://doi.org/10.1016/j.jenvman.2012.02.005
Mutandwa E, Hanyani-Mlambo B, Manzvera J (2019) Exploring the link between climate change perceptions and adaptation strategies among smallholder farmers in Chimanimani district of Zimbabwe. Int J Soc Econ 46(7):850–860. https://doi.org/10.1108/IJSE-12-2018-0654
Mbwambo SG, Mourice SK, Tarimo AJP (2021) Climate change perceptions by smallholder coffee farmers in the Northern and Southern Highlands of Tanzania. Climate 9(6):90. https://doi.org/10.3390/cli9060090
Myeni L, Moeletsi ME (2020) Factors determining the adoption of strategies used by smallholder farmers to cope with climate variability in the Eastern Free State South Africa. Agriculture 10:410. https://doi.org/10.3390/agriculture10090410
Myers TA, Maibach EW, Roser-Renouf C, Akerlof K, Leiserowitz AA (2013) The relationship between personal experience and belief in the reality of global warming. Nat Clim Change 3(4):343–347. https://doi.org/10.1038/nclimate1754
Ndamani F, Watanabe T (2017) Determinants of farmers’ climate risk perceptions in agriculture – a rural Ghana perspective. Water 9:210. https://doi.org/10.3390/w9030210
Ng’ombe JN, Tembo MC, Masasi B (2020) “Are they aware, and why?” Bayesian analysis of predictors of smallholder farmers’ awareness of climate change and its risks to agriculture. Agronomy 10:376. https://doi.org/10.3390/agronomy10030376
Niles MT, Lubell M, Haden VR (2013) Perceptions and responses to climate policy risks among California farmers. Global Environ Chang 23:1752–1760. https://doi.org/10.1016/j.gloenvcha.2013.08.005
Nkuba MR, Chanda R, Mmopelwa G, Kato E, Mangheni MN, et al. (2020) Influence of indigenous knowledge and scientific climate forecasts on arable farmers’ climate adaptation methods in the Rwenzori region, Western Uganda. Environ Manage 65:500–516. https://doi.org/10.1007/s00267-020-01264-x
Nong HTT, Gan C, Hu B (2020) Climate change vulnerability and adaptation in Vietnam from a gender perspective: a case study of Northern province of Vietnam. Int J Soc Econ 47(8):953–972. https://doi.org/10.1108/IJSE-09-2019-0534
Ochieng J, Kirimi L, Makau J (2017) Adapting to climate variability and change in rural Kenya: farmer perceptions, strategies and climate trends. Nat Resour Forum 41:195–208. https://doi.org/10.1111/1477-8947.12111
Opejin AK, Aggarwal RM, White DD, Jones JL, Maciejewski R, et al. (2020) A bibliometric analysis of food-energy-water nexus literature. Sustainability 12:1112. https://doi.org/10.3390/su12031112
Orduño-Torres MA, Kallas Z, Herrera SIO (2020) Farmers’ environmental perceptions and preferences regarding climate change adaptation and mitigation actions; towards a sustainable agricultural system in Mexico. Land Use Policy 99:105031. https://doi.org/10.1016/j.landusepol.2020.105031
Pausas JG, Millan MM (2019) Greening and browning in a climate change hotspot: the Mediterranean Basin. Bioscience 69(2):143–151. https://doi.org/10.1093/biosci/biy157
Paudel D, Tiwari KR, Raut N, Bajracharya RM, Bhattarai S, et al. (2022) What affects farmers in choosing better agroforestry practice as strategy of climate change adaptation? An experience from the mid-hills of Nepal. Heliyon 8:e09695. https://doi.org/10.1016/j.heliyon.2022.e09695
Paudel B, Zhang Y, Yan J, Rai R, Li L, et al. (2020) Farmers’ understanding of climate change in Nepal Himalayas: important determinants and implications for developing adaptation strategies. Clim Change 158(3):485–502. https://doi.org/10.1007/s10584-019-02607-2
Phadke R, Manning C, Burlager S (2015) Making it personal: diversity and deliberation in climate adaptation planning. Clim Risk Manage 9:62–76. https://doi.org/10.1016/j.crm.2015.06.005
Piguet E (2022) Linking climate change, environmental degradation, and migration: an update after 10 years. WIREs Clim Change 13(1):e746. https://doi.org/10.1002/wcc.746
Pizzi S, Caputo A, Corvino A, Venturelli A (2020) Management research and the UN sustainable development goals (SDGs): a bibliometric investigation and systematic review. J Clean Prod 276:124033. https://doi.org/10.1016/j.jclepro.2020.124033
Plate L (2017) Climate change and the metamorphosis of memory: a response to Stef Craps. Parallax 23(4):493–497. https://doi.org/10.1080/13534645.2017.1374519
Popoola OO, Monde N, Yusuf SFG (2018) Perceptions of climate change impacts and adaptation measures used by crop smallholder farmers in Amathole district municipality, Eastern Cape province, South Africa. GeoJournal 83:1205–1221. https://doi.org/10.1007/s10708-017-9829-0
Quan S, Li Y, Song J, Zhang T, Wang M (2019) Adaptation to climate change and its impacts on wheat yield: perspectives of farmers in Henan of China. Sustainability 11:1928. https://doi.org/10.3390/su11071928
Quiroga A, Suarez C, Solis JD, Martinez-Juarez P (2020) Framing vulnerability and coffee farmers’ behaviour in the context of climate change adaptation in Nicaragua. World Dev 126:104733. https://doi.org/10.1016/j.worlddev.2019.104733
Reddy KV, Paramesh V, Arunachalam V, Das B, Ramasundaram R, Pramanik M, …, Mattar MA (2022) Farmers’ perception and efficacy of adaptation decisions to climate change. Agron 12:1023. https://doi.org/10.3390/agronomy12051023
Reser JP, Bradley GL, Ellul C (2014) Encountering climate change: ‘seeing’ is more than ‘believing.’ Wires Clim Change 5:521–537. https://doi.org/10.1002/wcc.286
Reser JP, Bradley GL (2020) The nature, significance, and influence of perceived personal experience of climate change. WIREs Clim Change 11(5):e668. https://doi.org/10.1002/wcc.668
Ricart S, Castelletti A, Gandolfi C (2022) On farmers’ perceptions of climate change and its nexus with climate data and adaptive capacity A comprehensive review. Environ Res Lett 17:083002. https://doi.org/10.1088/1748-9326/ac810f
Roco L, Engler A, Bravo-Ureta B-E, Jara-Rojas R (2015) Farmers’ perception of climate change in Mediterranean Chile. Reg Environ Change 15:867–879. https://doi.org/10.1007/s10113-014-0669-x
Roesch-McNally GE, Arbuckle JG, Tyndall JC (2017) What could farmers do? Adaptation intentions under a corn belt climate change scenario. Agr Hum Values 34:333–346. https://doi.org/10.1007/s10460-016-9719-y
Roesch-McNally G, Garrett A, Fery M (2020) Assessing perceptions of climate risk and adaptation among small farmers in Oregon’s Willamette Valley. Renew Agr Food Syst 35:626–630. https://doi.org/10.1017/s1742170519000267
Rondhi M, Khasan AF, Mori Y, Kondo T (2019) Assessing the role of the perceived impact of climate change on national adaptation policy: the case of rice farming in Indonesia. Land 8:81. https://doi.org/10.3390/land8050081
Rust NA, Stankovics P, Jarvis RM, Morris-Trainor Z, de Vries JR, et al. (2022) Have farmers had enough of experts? Environ Manage 69:31–44. https://doi.org/10.1007/s00267-021-01546-y
Sadiq MA, Kuwornu JKM, Al-Hassan RM, Alhassan SI (2019) Assessing maize farmers’ adaptation strategies to climate change and variability in Ghana. Agriculture 9:90. https://doi.org/10.3390/agriculture9050090
Schlosberg D, Collins LB (2014) From environmental to climate justice: climate change and the discourse of environmental justice. Wires Clim Change 5(3):359–374. https://doi.org/10.1002/wcc.275
Schlüter M, Baeza A, Dressler G, Frank K, Groeneveld J (2017) A framework for mapping and comparing behavioural theories in models of social-ecological systems. Ecol Econ 131:21–35. https://doi.org/10.1016/j.ecolecon.2016.08.008
Selvaraju R (2012) Climate risk assessment and management in agriculture. In: Meybeck A, Lankoski J, Redfern S, Azzu N, Gitz V (eds) Building resilience for adaptation to climate change in the agriculture sector. Food and Agriculture Organization, Rome, pp 71–90
Sen LTH, Bond J, Phuong LTH, Winkel A, Tran UC, et al. (2021) The importance of climate change awareness for the adaptive capacity of ethnic minority farmers in the mountainous areas of Thua Thien Hue province. Local Environ 26(2):239–251. https://doi.org/10.1080/13549839.2021.1886064
Shaffril HAM, Samah AA, Samsuddin SF (2021) Guidelines for developing a systematic literature review for studies related to climate change adaptation. Environ Sci Pollut Res 28:22265–22277. https://doi.org/10.1007/s11356-021-13178-0
Shi X, Sun L, Chen X, Wang L (2019) Farmers’ perceived efficacy of adaptive behaviors to climate change in the Loess Plateau. China. Sci Total Environ 697:134217. https://doi.org/10.1016/j.scitotenv.2019.134217
Shukla R, Sachdeva K, Joshi PK (2016) Inherent vulnerability of agricultural communities in Himalaya: a village-level hotspot analysis in the Uttarakhand state of India. Appl Geogr 74:182–198. https://doi.org/10.1016/j.apgeog.2016-07-013
Sierra-Barón W, Navarro O, Naranjo D, Sierra E, González C (2021) Beliefs about climate change and their relationship with environmental beliefs and sustainable behavior: a view from rural communities. Sustainability 13:5326. https://doi.org/10.3390/su13095326
Simane B, Zaitchik BF, Foltz JD (2016) Agro-ecosystem specific climate vulnerability analysis: application of the livelihood vulnerability index to a tropical highland region. Mitig Adapt Strat Gl 21:39–65. https://doi.org/10.1007/s11027-014-9568-1
Simelton E, Quinn CH, Batisani N, Dougill AJ, Dyer JC (2013) Is rainfall really changing? Farmers’ perceptions, meteorological data, and policy implications. Clim Dev 5(2):123–138. https://doi.org/10.1080/17565529.2012.751893
Singh S (2020) Farmers’ perception of climate change and adaptation decisions: a micro-level evidence from Bundelkhand Region. India. Ecol Indic 116:106475. https://doi.org/10.1016/j.ecoling.2020.106475
Smith EK, Mayer A (2018) A social trap for the climate? Collective action, trust and climate change risk perception in 35 countries. Global Environ Chang 49:140–153. https://doi.org/10.1016/j.gloenvcha.2018.02.014
Soglo YY, Nonvide GMA (2019) Climate change perceptions and responsive strategies in Benin: the case of maize farmers. Clim Change 155:245–256. https://doi.org/10.1007/s10584-019-02452-3
Sohail MT, Elkaeed EB, Irfan M, Acevedo-Duque A, Mustafa S (2022) Determining farmers’ awareness about climate change mitigation and wastewater irrigation: a pathway toward green and sustainable development. Front Environ Sci 10:900193. https://doi.org/10.3389/fenvs.2022.900193
Song S, Wang S, Fu B, Dong Y, Liu Y, et al. (2021) Improving representation of collective memory in socio-hydrological models and new insights into flood risk management. J Flood Risk Manag 14:e12679. https://doi.org/10.1111/jfr3.12679
Soubry B, Sherren K, Thornton TF (2020) Are we taking farmers seriously? A review of the literature on farmer perceptions and climate change, 2007–2018. J Rural Stud 74:210–222. https://doi.org/10.1016/j.jrurstud.2019.09.005
Spence A, Poortinga W, Pidgeo NF (2012) The psychological distance of climate change. Risk Anal 32:957–972. https://doi.org/10.1111/j.1539-6924.2011.01695.x
Sterman JD, Sweeney LB (2007) Understanding public complacency about climate change: adults’ mental models of climate change violate conservation of matter. Clim Change 80:213–238. https://doi.org/10.1007/s10584-006-9107-5
Sujakhu NM, Ranjitkar S, Yang H, Su Y, Xu J, et al. (2020) Quantifying farmers’ climate change adaptation strategies and the strategy determinants in Southwest China. Int J Clim Chang Str 12(4):511–532. https://doi.org/10.1108/IJCCSM-12-2019-0073
Sulewski P, Kloczko-Gajewska A (2014) Farmers’ risk perception, risk aversion and strategies to cope with production risk: an empirical study from Poland. Stud Agric Econ 116:140–147. https://doi.org/10.7896/j.1414
Talanow K, Topp EN, Loos J, Martin-Lopez B (2021) Farmers’ perceptions of climate change and adaptation strategies in South Africa’s Western Cape. J Rural Stud 81:203–219. https://doi.org/10.1016/j.jrurstud.2020.10.026
Tambo JA, Abdoulaye T (2013) Smallholder farmers’ perceptions of and adaptation to climate change in the Nigerian savanna. Reg Environ Change 13:375–388. https://doi.org/10.1007/s10113-012-0351-0
Tesfahun AA, Chawla AS (2020) Risk perceptions and adaptation strategies of smallholder farmers to climate change and variability in North Shoa Zone Ethiopia. Manag Env Qual Int J 31(1):254–272. https://doi.org/10.1108/MEQ-04-2019-0076
Tesfahunegn GB, Mekonen K, Tekle A (2016) Farmers’ perception on causes, indicators and determinants of climate change in northern Ethiopia: implication for developing adaptation strategies. Appl Geogr 73:1–12. https://doi.org/10.1016/j.apgeog.2016.05-009
Tetteh BKD, Ansah IGK, Donkoh SA, Appiah-Twumasi M, Avornyo FK (2020) Perceptions of weather variability and climate change on goat producers’ choice of coping and adaptation strategies: evidence from climate-smart and non-climate-smart villages in the Jirapa and Lawra districts. Clim Dev 12(7):614–625. https://doi.org/10.1080/17565529.2019.1664975
Thangrak V, Somboonsuke B, Sdoodee S, Darnsawasdi R, Voe P (2020) The smallholder farmers’ perceptions of climate variability impact on rice production and the case of adaptation strategies in Banteay Meanchey, (BMC). Cambodia Int J Agric Tech 16(2):505–516
Thinda KT, Ogundeji AA, Belle JA, Ojo TO (2020) Understanding the adoption of climate change adaptation strategies among smallholder farmers: evidence from land reform beneficiaries in South Africa. Land Use Policy 99:104858. https://doi.org/10.1016/j.landusepol.2020.104858
Tiet T, To-The N, Nguyen-Anh T (2022) Farmers’ behaviors and attitudes toward climate change adaptation: evidence from Vietnamese smallholder farmers. Environ Dev Sustain 24:14235–14260. https://doi.org/10.1007/s10668-021-02030-7
Tuel A, Eltahir EAB (2020) Why is the Mediterranean a climate change hotspot? J Clim 33(14):5829–5843. https://doi.org/10.1175/JCLI-D-19.0910.1
Tunde AM, Ajadi BS (2018) Indigenous understanding of climate change, impacts and coping strategies in a rural setting of Kwara State, Nigeria. Geogr Environ Sustain 11(4):85–99. https://doi.org/10.24057/2071-9388-2018-11-4-85-99
Van der Linden S (2014) On the relationship between personal experience, affect and risk perception: the case of climate change. Eur J Soc Psychol 44:430–440. https://doi.org/10.1002/ejsp.2008
Van Eck N, Waltman L (2020) VOSviewer manual for VOSviewer version 1.6.16. Leiden University, Leiden. Available here: https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.16.pdf
Wang J, Mendelsohn R, Dinar A, Huang J (2010) How Chinese farmers change crop choice to adapt to climate change. Clim Chang Econ 1(3):167–185. https://doi.org/10.1142/S2010007810000145
Wang J, Yang Y, Huang J, Adhikari B (2019) Adaptive irrigation measures in response to extreme weather events: empirical evidence from the North China plain. Reg Environ Change 19:1009–1022. https://doi.org/10.1007/s10113-018-1442-3
Wang T, Yan J, Cheng X, Yu Y (2020) Irrigation influencing farmers’ perception of temperature and precipitation: a comparative study of two regions of the Tibetan Plateau. Sustainability 12:8164. https://doi.org/10.3390/su12198164
Weber EU (2016) What shapes perceptions of climate change? New research since 2010. Wires Clim Change 7(1):125–134. https://doi.org/10.1002/wcc.377
Wheeler SA, Nauges C, Zuo A (2021) How stable are Australian farmers’ climate change risk perceptions? New evidence of the feedback loop between risk perceptions and behaviour. Global Environ Chang 68:102274. https://doi.org/10.1016/j.gloenvcha.2021.102274
Wi A (2019) Citizen participation as a key enabler for successful public education policies in climate change mitigation in Singapore. Int Res Geo Environ Edu 28(1):53–69. https://doi.org/10.1080/10382046.2018.1430789
Wolf J, Moser SC (2011) Individual understandings, perceptions, and engagement with climate change: insights from in-depth studies across the world. Wires Clim Change 2(4):547–569. https://doi.org/10.1002/wcc.120
Woods BA, Nielsen HO, Pedersen AB, Kristofersson D (2017) Farmers’ perception of climate change and their likely responses in Danish agriculture. Land Use Policy 65:109–120. https://doi.org/10.1016/j.landusepol.2017.04.007
Zhang T, Wang J, Teng Y (2017) Adaptive effectiveness of irrigated area expansion in mitigating the impacts of climate change on crop yields in Northern China. Sustainability 9(5):851. https://doi.org/10.3390/su9050851
Zhang C, Jin J, Kuang F, Ning J, Wan X, et al. (2020) Farmers’ perceptions of climate change and adaptation behavior in Wushen Banner, China. Environ Sci Pollut R 27:26484–26494. https://doi.org/10.1007/s11356-020-09048-w
Zizinga A, Kangalawe RYM, Ainslie A, Tenywa MM, Majaliwa J, et al. (2017) Analysis of farmer’s choices for climate change adaptation practices in South-Western Uganda, 1980–2009. Climate 5:89. https://doi.org/10.3390/cli5040089
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Open access funding provided by Politecnico di Milano within the CRUI-CARE Agreement. This work was supported by the European Union’s Horizon 2020 research and innovation program Marie Sklodowska-Curie Individual Fellowship (Grant agreement 832464).
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Ricart, S., Gandolfi, C. & Castelletti, A. Climate change awareness, perceived impacts, and adaptation from farmers’ experience and behavior: a triple-loop review. Reg Environ Change 23, 82 (2023). https://doi.org/10.1007/s10113-023-02078-3
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DOI: https://doi.org/10.1007/s10113-023-02078-3