Introduction

There is a broad consensus among scientists, the public, and policymakers that human activities are driving global climate warming, posing an increasing risk for farming worldwide1,2,3. Globally, agriculture contributes 18–29% to the global emissions of greenhouse gases whilst farmers are also major victims of climate change4,5. Typical effects of climate change include droughts, floods, and heat waves affecting the output and income of farmers in many regions worldwide and requiring adjustments to practices, such as adjusted water management, improved cultivars, and land use diversification. Mitigation measures for agriculture involve the reduction of emissions of the GHGs: carbon dioxide, nitrous oxide, and methane and increasing soil carbon sequestration2. However, there are several barriers to successful implementation of adaptation and mitigation measures, including a lack of knowledge, consciousness, perceptions, and motivation of farmers3,6,7,8 as well as lack of investment and institutional capacity to support change9. Some of the implementation barriers are systemic since farmers need the support of both governments and agrifood businesses.

Awareness and understanding of climate change have increased since the 1980s when it first entered public consciousness10,11. Steg12 found that most Europeans believe that climate change is real and caused by humans, but that this does not translate to climate action. Both the IPCC Sixth Assessment Report2 and the EU Climate Adaptation Strategy13 acknowledge the challenges and lack of implementation at the farm level. Generally, farmers14 as well as people employed in the fossil fuel sector15 appear to be less open to change and probably more distrustful of policy and science than others in society16,17. The alignment of climate-skeptical populist parties to the farmers’ interests may fuel political distrust and skepticism among farmers (e.g., van der Ploeg18): “If you don’t trust politicians, why would you trust their claims about climate change and their policies to mitigate emissions?”. Others10,19 argue that farmers generally may be more politically distrustful and more climate skeptical than the general public. However, when farmers are more aware of climate change and the associated risks for their farm output, they may be more willing to adapt their practices3,20. Perhaps surprisingly, both the IPCC and the European Commission hardly mention the importance of understanding how to change farmers’ attitudes as an enabler for climate action. So far, farmers’ skepticism regarding climate change has not been compared to people with other occupations3,21,22,23, or studies were mainly restricted to one specific country or region24,25.

Agriculture and climate change in Europe

On average, only ~4% of the working population in Europe is farmer, whilst 38% of the total land area of the EU is used for agricultural production26. The relative share of GHG emissions from the European agricultural sector including by land use and land use change (LULUC) is 12%. This is less than the global share of 22%, because other economic sectors contribute more, and contributions from LULUC in Europe are relatively small4. Increased drought is already the major cause of loss of agricultural production, and this is likely to persist and worsen27. The current cost of drought in Europe is estimated at €9 billion28. Climate risks, damages, and the need for adaptive measures are generally higher in southern than northern European countries29,30. Without increased availability of irrigation and improved water management in a broad sense, crop losses in 2100 could amount to 80% in some southern European countries28.

It is not only the occupation of farmers compared to other working people in society (also called non-farmers in this contribution) that matters for their skepticism, but also the country—the macro-level context—they live in. Generally, higher GDP relates to pro-environmental attitudes and reduced climate change skepticism31,32: environmental protection is more affordable for richer countries, leading to generally greater support of environmental policies33,34 and less skepticism. In contrast, other scholars35,36 suggest opposite associations with GDP; they found that whilst rich countries on average experience fewer ecological disturbances37, the high costs of transforming the economy to a more environmental-friendly economy make people more skeptical about introducing expensive environmental measures, and about climate change in general. Likewise, in less affluent countries that experience more severe ecological disturbances, people are generally more willing to accept expensive climate policies and are less skeptical about climate change34. When agriculture is of greater importance in terms of area, economy or employment within a country, it can be expected that the societal appreciation of agriculture in a country is higher resulting in smaller differences in skepticism between farmers and non-farmers. We chose to use the agricultural area as a macro-level indicator as it is a more “tangible” proxy for importance to the general public than agricultural share in national GDP or employment. A third macro-level factor is trust in technical innovation, measured by the Global Innovation Index (GII). Higher GII scores, indicating more innovative economies, are associated with greater trust that innovation will solve climate change issues and potentially less skepticism about climate change among farmers and non-farmers. A fourth macro-level factor is the natural circumstances that farmers deal with when working on their land, which distinguishes them from most non-farmers. This includes the effects of the weather and its variability38, but also the location in relation to mountains, rivers or streams, and closeness to the sea (salination). Structural change of weather patterns by climate change affects the biophysical parameters underlying farm practices, either representing a threat to agriculture or an opportunity, and both demanding adaptations. In Northwest Europe, increasing temperatures and longer growing seasons can increase crop production and reduce production costs. This contrast between the North and South could have implications for farmers’ climate change perceptions.

We compare farmers to the working population in general. Europe provides a promising case in view of the abundant availability of survey data (European Social Survey and EU Barometer over a time span of 12 years) with ample variation in economic and socio-cultural development of agricultural practices, natural conditions, and climate change. To explain farmers’ skepticism in Europe, survey data were combined with socio-economic country information and biophysical information about climate change and adaptation, and controlled for micro-level factors such as age, gender, and education level, which have been shown to be relevant in shaping environmental attitudes39,40. The analysis moves beyond the focus on a single or small number of countries and only individual or contextual factors, by studying whether a farmer in one context has different beliefs about climate change than in another context, as compared to the rest of the working population in Europe. We focus on skepticism as an attitude, because it will be difficult to convince (non-)farmers to make sacrifices in work and lifestyle and support climate mitigation and adaptation if they do not believe the climate is changing or will have a real impact on their work and lives19. Lastly, the analysis responds to pleas that climate policies require a socio-economic transition41, combining insights from social sciences with natural sciences42.

Results

The Eurobarometer survey (6 waves, 2011–2021, 28 countries, N = 89867 of which 1.53% farmers) was used to analyze climate impact skepticism of farmers compared to the rest of the working population (non-farmers) and the European Social Survey (ESS, 2 rounds: 2016 and 2020, 25 countries, N = 75419 of which 2.37% farmers) for attribution skepticism (see Supplementary Table 1). Skepticism was determined by classifying the lack of belief that climate change is a serious problem (impact skepticism) and the belief that climate change mainly is a human-induced process (attribution skepticism). Most respondents believe in the reality of climate change impacts and human attribution. However, the share of farmers that is skeptical is somewhat higher than for non-farmers, 10.5% versus 8.1% regarding impact and 11.6% versus 7.2% regarding human attribution (Fig. 1, Class 4 and 5).

Fig. 1: Climate change skepticism of European farmers versus non-farmers.
figure 1

a regarding climate change impacts (data Eurobarometer for 2011–2021), b regarding human attribution (data European Social Survey for 2016–2022). The scale of impact skepticism runs from 1 to 10, with ‘1’ meaning it is “an extremely serious problem” and ‘10’ meaning it is “not at all a serious problem”, but aggregated to five classes. The scale of attribution skepticism runs from ‘1’ “Entirely by human activity” to ‘5’ “Entirely by natural processes”.

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These differences for the total European sample appear small. We observe a gradient for both impact and attribution skepticism increasing from the South to the North (Fig. 2), which may suggest an association with the geographical trends for climate change and GDP.

Fig. 2: Geographical distribution of climate change skepticism of farmers and non-farmers in Europe.
figure 2

Data climate change impact skepticism for 2011–2021, data human attribution skepticism for 2016–2022. The scale of impact skepticism runs from 1 to 10, with ‘1’ meaning it is “an extremely serious problem” and ‘10’ meaning it is “not at all a serious problem”. The scale of attribution skepticism runs from ‘1’ “Entirely by human activity” to ‘5’ “Entirely by natural processes”.

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Cross-national differences in impact and attribution skepticism

For farmers, the variation of impact skepticism in countries, relative to the mean of the total sample of European farmers, is larger than skepticism about attribution (Fig. 3). Farmers in Mediterranean countries, led by Greece, are least skeptical (Fig. 3: class “overall believing”), likely because they suffer most from climate change. The overall picture is that of a diverse European farmers community with sometimes counterintuitive attitudes about the human responsibility for climate change and the extent of its impacts. For example, the position of farmers in comparable neighboring countries can be very different, for example, between Slovakia and Hungary, the Netherlands and Belgium, or Latvia and Estonia.

Fig. 3: Correlation between impact and attribution skepticism of farmers in European countries.
figure 3

Y-axis: skepticism regarding climate change impacts (data 2011–2021). X-axis: skepticism regarding human attribution (data for 2016–2022). Labels are tentative characterizations of the quadrants. The average position of all European farmers is represented by the X-Y coordinate (1,1). Filled data points indicate outlying countries with a statistically significant difference.

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Skepticism of farmers versus non-farmers

Overall, in Europe, the skepticism score of farmers for negative impacts of climate change (M = 3.73) is about 5% higher than for non-farmers (M = 3.44), which is also the case for the impact skepticism score for human attribution (M = 2.66 for farmers as compared to M = 2.51 for non-farmers. See Supplementary Table 2 for details). However, the difference in skepticism varies considerably between countries (Fig. 4).

Fig. 4: Difference between climate change skepticism of farmers and non-farmers in European countries.
figure 4

a Average score difference for impact skepticism. b difference for attribution skepticism.

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Differences in impact skepticism between farmers and non-farmers are significant (p < 0.05) for 11 countries (Fig. 4b). In Austria and Poland, the farmers are significantly less skeptical about the negative impact of climate change than non-farmers (Supplementary Table 3). The difference in attribution skepticism between farmers and non-farmers is statistically significant (p < 0.05) for 11 countries (Fig. 4a). Greece is exceptional in that farmers are significantly less skeptical about the human attribution than non-farmers (Supplementary Table 3).

The correlation between the difference in climate attitudes between farmers and non-farmers per country provides insight into the dissensus in Europe (Fig. 5). Most countries can be characterized as internally divided, with farmers more skeptical than non-farmers (Fig. 5, upper right quadrant “overall disharmony”). The position of outlying countries follows the climate attitudes of farmers (Fig. 3).

Fig. 5: Correlation between difference of skepticism between farmers and non-farmers in European countries.
figure 5

Y-axis: difference of skepticism regarding climate change impacts (data 2011–2021). X-axis: difference of skepticism regarding human attribution (data 2016–2022). Labels are tentative characterizations of quadrants. A country close to X-Y coordinate (0,0) indicates that climate skepticism amongst farmers and non-farmers is similar. Filled data points indicate outlying countries.

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Causes of variation in skepticism

To analyze country-level differences, the national GDP, GII, agricultural land share, and climate risk were added to the multilevel model. GDP and land share were taken from World Bank data and Eurostat, respectively. We developed an indicator of agricultural climate risk per country, based on Trnka et al.29, which compared well to observations of perceived climate change impacts by agricultural experts in Zhao et al.30. The climate risk indicator was derived from two agroclimatic indicators: change in length of the growing season and number of days with drought stress for crops, both being available for twelve pedoclimatic zones in Europe. The climate risk indicator runs from positive (climate risks) to negative (climate benefits) (See Supplementary Table 6 and Supplementary Data 1 for details). The country-level indicators matter for the explanation of skepticism, shown by the Intra Class Coefficient of the empty multilevel model (not reported), which shows that 6.1% of the variance in attribution skepticism and 4.2% of the impact skepticism is associated with country differences.

The direct effects of the country-level variables show that people in countries with a higher share of agricultural land and a lower climate risk for agriculture are more skeptical about the impact of climate change. GDP and GII show no significant relation with impact skepticism (Fig. 6 and Supplementary Table 4). People in countries with a lower GDP per capita, a higher share of agricultural land, a lower score on GII, and a lower climate change risk for agriculture are more skeptical about human attribution (Fig. 6 and Supplementary Table 5). Sensitivity analysis showed that all findings remain robust (see Supplementary Tables 4 and 5), taking into account underrepresentation of farmers (see Supplementary Table 7).

Fig. 6: Determinants of climate change skepticism for an average farmer in Europe.
figure 6

a Model predicted effect on attribution skepticism (range 1–5), b: effect on impact skepticism (range 1–10). The four included determinants are indexed GDP per capita, agricultural share of land (%), risk of climate change for agriculture and Global Innovation Index (GII). The model uses individual control variables and multilevel structure with random intercept and random coefficient for farmers.

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Finally, we analyzed the extent to which the effect on climate skepticism of being a farmer differs between countries. The positive relationship between being a farmer and being skeptical about climate change is stronger in countries with a higher GDP and with a higher GII (Fig. 7). So, country contexts do matter, as impact skepticism of farmers is higher in countries with higher GDP than in lower GDP countries, compared to the rest of the working population, while on average across Europe it does not (Fig. 6). The other cross-level interactions were non-significant.

Fig. 7: Country-level determinants of climate change impact skepticism for farmers and non-farmers in Europe.
figure 7

a Predicted effect of GDP per capita on impact skepticism using a model including cross-level interactions (GDP centered with a mean value of 0 by subtracting the mean from each value). b Predicted effect of Global Innovation Index (GII).

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Discussion

The importance of understanding farmers’ attitudes towards the contribution to climate mitigation and adaptation in Europe was highlighted by the European Parliament elections in June 2024. Election results showed a strong growth of populist and right-wing parties (from 235 seats in 2019 to 272 seats (38% of total) in 2024) that plead for relaxation or even abolition of targets and ambitions in the EU Green Deal. It could well be the case that the opinions of right-wing parties towards climate change are more in the interest of farmers than non-farmers. Previous studies on climate change opinions focus on a variety of indicators, ranging from awareness, skepticism, and belief, to concern about climate change3,43, but have as yet not compared farmers with the other working population.

We quantified skepticism of farmers and non-farmers in Europe and distinguished between climate impact and human attribution19,44,45. We show that farmers in general are significantly more skeptical than non-farmers, with a large diversity between countries. Impact and attribution skepticism in Europe increases from the South to the North, irrespective of being a farmer or not (Fig. 2). Differences between farmers and non-farmers in impact skepticism most strongly relate to GDP and level of innovation (Figs. 5 and 6). In countries with a higher GDP or with a higher level of innovation, the differences between the skepticism of farmers and non-farmers are larger, both because farmers are more skeptical than their peers in lower GDP countries and because non-farmers are less skeptical in general. As the survey response did not distinguish between attribution to agriculture and other economic sectors, it could be that the proportion of farmers being skeptical about the role of agriculture is larger than the proportion that is skeptical about human attribution in general. Moreover, answers to attitude questions in a survey might reflect social desirability, although there is no reason to assume that this is more the case for farmers than non-farmers. Recent research even shows that farmers are not influenced to any great extent by the social desirability bias46.

An increase in impact skepticism of farmers in higher GDP countries might be counterintuitive, as well as its difference from skepticism of non-farmers. Apparently, in these countries, the education and media coverae of the climate issue are better, decreasing the impact of skepticism in general. However, farmers in high-GDP countries face increasing pressure in view of costs to comply with environmental regulations47, and they perceive this agenda to affect their economic viability, which may adversely affect their trust in the reporting of the media and in their contribution to climate change. This increasing pressure on farmers has been an important factor for the farm protests in the Netherlands, Belgium, France, and Germany and a recent political landslide in the Netherlands. This is confirmed by the result that in countries with a higher level of innovation (GII), the difference between farmers and non-farmers is larger in terms of impact skepticism. However, it should also be stressed that some of the countries with high GDP are also currently less severely affected by climate change.

We conclude that in spite of small samples of farmers in some countries and the volatility of survey responses over time, the differences between the climate skepticism of farmers versus non-farmers and between European regions are overall robust. This is also true for the relation of skepticism with GDP, agricultural area, climate risks, and innovation capacity, but our analysis does not capture the effects of specific EU and national agricultural and environmental policies for farmers. Results for countries with small samples of farmers are generally not significant.

The EU environmental policies traditionally involve command-and-control approaches through directives and laws, but with large national autonomy regarding implementation48. Information and communication about these policies is foremost a national responsibility, but public extension services have been cut or privatized49. This erosion of public extension services can be related to the observation that only in one-third of European countries, climate-affected crop farmers had a good understanding of the consequences of climate change50. Although beliefs about climate change do not persistently translate into actions12,39,51, understanding and reducing climate skepticism among farmers is important for more effective mitigation and adaptation. The voting majority of non-farmers believes in climate change impacts (Fig. 1) and until now supports the current EU goals for climate mitigation. Farmers share this belief, but least in the Northwest Europe (Fig. 2). Whilst farmers in the dry parts of Europe are more willing to act, the current rate of climate change may have reached the limits of the adaptation for farmers and innovation capacity, and the future of their business is at stake.

However, support for climate change action appears to be under more pressure since the 2024 EU elections. Farmers’ attribution skepticism may hamper specific mitigation measures for GHG from the agricultural sector. We recommend increasing public communication to the farmer community to decrease attribution skepticism. Although only 12% of farmers deny human-caused climate change (Fig. 1), their role in farm protests is probably more substantial (“loud minority”). The design of national communication campaigns or contextual justifications in outreach programs, educational initiatives, or farmer-led innovation hubs should therefore specifically address attribution skepticism. Public communications on climate change impacts may yield high levels of support from citizens, even among those who are skeptical about the causes of climate change52. Furthermore, receiving the message on the climate change effects at the local level is one of the unique predictors of the engagement of citizens with climate change53. Another challenge is to reduce impact skepticism, which is largest in the north-western European countries where climate risks for farming are lowest. Moreover, because in the Netherlands, Denmark, and other countries with a high-tech and intensive agriculture, the emission of GHGs per unit of, especially, livestock products is lowest in Europe54, the farmers’ conviction is that intensive livestock production should remain where it is. A survey on farmers in the Netherlands indicated that communication campaigns had small effects on willingness to mitigate the most important GHGs, methane and nitrous oxide, likely because of the absence of financial savings, which farmers regard as more likely for reduction of CO2 by energy saving measures55. In the southern and dry regions of the EU, farmers already experience increasing climate risks. In these regions, impact skepticism is unlikely to hinder short-term adaptive solutions (e.g., other cultivars, irrigation, tillage), but may pose barriers for more systemic, long-term preventive measures (e.g., soil conservation and water management, and changing land use and crop rotation).

For effective EU climate policies in agriculture (and perhaps environmental policies in general), a more intensive, differentiated, and customized participation and communication process is needed, involving all political levels (from local to EU-level56). Such a change needs to consider that farmers are typically more conservative in their value orientation and resistant to change than the general population, as shown in a cross-national study in seven European countries14. The values of stability, continuity and predictability might explain their skepticism towards climate policy measures that request a radical shift in the status quo of farming and the farmers’ lifestyle. Farmers identify themselves as production-oriented risk managers, rather than conservationists and sustainable countryside managers57. This implies that such a process focusing on agriculture could also become sluggish. Part of the farmers’ skepticism may relate to a perceived lack of (financial) co-responsibility of agrifood businesses and government. Finally, the adoption of additional climate measures for farmers is not easy, as in general farms, are small enterprises without employees, faced with a suite of EU-wide and national environmental, sometimes complex, regulations58, while their economic margins are small. One approach to lower the financial barriers is revision of the subsidies to farmers as part of the EU Common Agricultural Policy, which amounts to €387 billion for 2021–2027 and still rewards land ownership and is less effective for providing climate mitigation, adaptation, and other public goods59. However, a substantial acceleration of climate mitigation and adaptation goes beyond the power of the EU Commission and demands collective and coordinated climate action from farmers, agrifood businesses, consumers, and governments.

Methods

Our study used two datasets, the European Social Survey (ESS) Round 8 and Round 10 and measures attribution skepticism (i.e., skepticism about the human causes of climate change, 2016–2017 and 2020–2022), and the Special Eurobarometer surveys on climate change (Supplementary Table 1), collected every two years over the period 2011–2021, measuring impact skepticism across distinct samples. Both the ESS and the Eurobarometer are long-standing, widely recognized social science surveys with comparatively low biases, such as those related to representation and response rates. Country-level data were gathered from various sources and compiled into separate datasets. Data processing was conducted using Stata and Excel, and all steps were thoroughly documented. The commented code is available upon request (Lea Kröner; l.kroner@uu.nl).

The ESS datasets were obtained from the openly accessible Datafile Builder (https://ess.sikt.no/en/data-builder/), which offers harmonized data waves. The Eurobarometer datasets were downloaded from the GESIS Leibniz Institute for the Social Sciences open-access data catalog (https://search.gesis.org/) and appended across six waves. Each of the country-level datasets was merged with the corresponding survey datasets using a many-to-one (m:1) merge command, with countryname as the key variable. This variable has identical coding across both the survey datasets and the country-level datasets, ensuring consistency during merging.

Individual level data ESS—attribution skepticism

The eighth and tenth rounds of the ESS were conducted through face-to-face interviews between 2016 and 2017 and 2020 and 2022, respectively. These waves were chosen because they feature the key rotating module on climate and energy45. Generally, the ESS questionnaires aim to measure public attitudes, beliefs, and behaviors. We included Austria, Belgium, Bulgaria, Croatia, Czech Republic, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, the Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom in our analysis. This resulted after listwise deletion of missing values on the variables of interest in 75,419 observations (1789 Farmers) across 25 countries, each with a minimum representative sample size of 1500 respondents (or 800 if the population is below 2 million).

Attribution skepticism45, the dependent variable in this study, was measured with the question: “Do you think that climate change is caused by natural processes, human activity, or both?”. The response options ranged from 1 “Entirely by natural processes” to 5 “Entirely by human activity”. These were reverse-coded to represent skepticism. The independent variable, whether someone is a farmer or not, was based on the occupation variable. We coded those who belong to the category “Skilled Agricultural, Forestry & Fishery” as farmers and the people belonging to the other categories as non-farmers. Other categories include Armed Forces, Managers, Professionals, Technicians and associate professionals, Services and Sales Workers, Skilled agricultural, Forestry & Fishery, Craft and related trades Workers, Plant and Machine Operators, and Assemblers, Elementary Occupations, and Not applicable.

The control variables included gender with 1 “male” and 0 “female”, age, trust in politicians with 0 “No trust at all” until 10 “Complete trust”, and educational level (scale 1–7). These variables were included due to their established role as determinants of climate change perceptions and their differences between farmers and non-farmers. The questionnaires are available on the ESS website at: https://www.europeansocialsurvey.org/methodology/ess-methodology/source-questionnaire.

Individual level data Eurobarometer special issues—impact skepticism

The Eurobarometer has been regularly surveying the public on behalf of the European Commission and other EU entities since 1973. The Eurobarometer questionnaires focus on topics related to the EU and perspectives on contemporary political and social issues. Face-to-face interviews are performed in the spring and fall and are always based on new samples (“repeated cross-section” design). Except for small countries like Luxembourg and Malta, the standard sample size (in terms of completed interviews) in the standard Eurobarometer surveys is 1000 respondents per country. Additionally, the Eurobarometer has special issue waves. This study considered answers from 6 special issue waves on climate change that took place between 2011 and 2021. After appending the waves, merging the contextual data, and listwise deletion of missing values on the variables of interest, 89,867 observations (1378 farmers) within 28 countries remained. These countries are Austria, Belgium, Bulgaria, Croatia, Cyprus, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Great Britain, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, and Sweden.

The dependent variable impact skepticism was measured with the reverse-coded question “how serious a problem do you think climate change is at this moment?” Please use a scale from 1 to 10, with ‘1’ meaning it is “not at all a serious problem” and ‘10’ meaning it is “an extremely serious problem”. Moreover, we included a time variable to control for contextual differences between the two waves.

To operationalize the independent variable of whether the respondent is a farmer, the following question was used: “What is your current occupation?”, with 18 response options. These options are Responsible for ordinary shopping, etc./Student/Unemployed, temporarily not working/Retired, unable to work/Farmer/Fisherman/Professional (lawyer, etc.)/Owner of a shop, craftsmen, etc./Business proprietors, etc./Employed professional (employed doctor, …)/General management, etc./Middle management, etc./Employed position, at desk/Employed position, traveling/Employed position, service job/Supervisor/Skilled manual worker/Unskilled manual worker, etc. Furthermore, on the individual level, we controlled for gender, age, and education of the respondents. Moreover, we included a time variable to control for a trend toward less skepticism, where we recoded the waves to a variable ranging from 1 to 6, which were treated as continuous (2011 = 1) (2013 = 2) (2015 = 3) (2017 = 4) (2019 = 5) (2021 = 6). Whilst political orientation is commonly recognized as a determinant of climate change perceptions, we did not include it in the main analyses of both our studies due to a high number of missing values on these variables. However, when we conducted the analyses on a subsample where missing values were handled through listwise deletion and political orientation, the results remained stable. For more details on the questionnaires, see the GESIS Leibniz Institute for the Social Sciences open-access data catalog at https://search.gesis.org/.

Contextual country-level data

We included three independent variables at the country-level and their interactions with being a farmer in the analysis. To measure the economic well-being of the country, we used the average annual indexed GDP per capita in purchasing power parities (PPPs). It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. The volume index of GDP per capita in purchasing power standards (PPS) is expressed in relation to the European Union average set to equal 100. If the index of a country is higher than 100, this country’s level of GDP per head is higher than the EU average and vice versa. Basic figures are expressed in PPS, i.e., a common currency that eliminates the differences in price levels between countries, allowing meaningful volume comparisons of GDP between countries. Please note that the index, calculated from PPS figures and expressed with respect to EU27_2020 = 100, is intended for cross-country comparisons rather than for temporal comparisons. Moreover, the General Innovation Index (GII) per country between 2014 and 2021 is used based on Eurostat data (https://ec.europa.eu/eurostat/databrowser/view/tec00114/default/table?lang=en). To measure what area of the country is occupied by agriculture, we used the average annual agricultural land share per country between 2014 and 2020 based on data from the World Bank (https://data.worldbank.org/indicator/AG.LND.AGRI.ZS?end=2018&start=2014). Agricultural land refers to the share of land area that is arable, under permanent crops, or under permanent pastures. Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded. Land under permanent crops is land cultivated with crops that occupy the land for long periods and need not be replanted after each harvest, such as cocoa, coffee, and rubber. This category includes land under flowering shrubs, fruit trees, nut trees, and vines, but excludes land under trees grown for wood or timber. Permanent pasture is land used for five or more years for forage, including natural and cultivated crops. Land area is a country’s total area, excluding area under inland water bodies, national claims to the continental shelf, and exclusive economic zones. In most cases, the definition of inland water bodies includes major rivers and lakes. As a measure of the climate risk for agriculture of a country, we defined an index combining the change in the length of the growing season and of number of dry days. Originally, the score runs from positive (climate benefits) to negative (climate costs), but we reverse-coded it, so that countries with a higher risk have a higher value on the scale (see Supplementary Table 6).

Models and statistical techniques

The data were analyzed using multilevel statistical methods. The rationale is that the surveyed individuals in both studies are nested in countries, and relationships between variables on different levels (individual and country) are to be investigated. Multilevel models are designed to adequately include the dependencies of individuals nested in the same country60. We included cross-level interaction terms of the country-level factors (i.e., indexed GDP/capita, GII, agricultural share of land (%) and climatic risk index for agriculture) with the independent variable “farmer” on the individual level, to investigate whether potential differences in the effect of being a farmer across countries can be explained by differences in the macro factors across countries. In the Supplementary Tables 4 (Eurobarometer) and 5 (ESS), these form Models 1 to 5. Models 6 to 9 in both tables report the robustness analyses. Models 6a and 6b replace agricultural employment with the share of agricultural land used in the main analyses (Models 5a and 5b). The results do not change. Models 7a and 7b include political orientation in the Eurobarometer and replace political trust with political orientation in the ESS. The results are robust. To assess the representation of farmers, we compared the percentage of farmers in our samples to the share of agricultural employment per country (Supplementary Table 7). For many countries, the survey representation aligns closely with the actual share of agricultural employment. In addition, to address potential bias, we re-ran the analyses excluding countries where farmers were notably underrepresented, marked in red in the table. The results do not change, as shown in Models 8a and 8b. Finally, in Models 9a and 9b, we have run additional regression analyses where we have deleted the 20% countries with the lowest share of farmers. Again, the results are robust.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.