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Communicating about Climate Change with Farmers

Abstract and Keywords

Communication with farmers about climate change has proven to be difficult, with relatively low acceptance of anthropogenic climate change or the idea that climate change will negatively affect agriculture. Many farmers have been impervious to climate change communications because of the nature of farming, their worldviews, and the controversies about climate change in the media. Segmentation studies from the agriculture and natural resource management literatures provide evidence of homogeneous farmer groups internationally with respect to climate change attitudes and behaviors in a farming context. Understanding these segments—including their values, beliefs, and behaviors—is important for developing tailored and targeted communications approaches. Based on understanding of commonly observed farmer segments, it is possible to tailor communication strategies to better engage with segments of concern, including which message to use, appropriate sources, as well as alternative communication techniques based on participatory approaches and use of the arts. For certain segments, discussion about human-induced climate change should be avoided given that it is contentious and not critical for how farmers should respond to climate change. Theoretical frameworks from psychology and marketing—such as the theory of planned behavior, the attitude-to-behavior process model, the motivation and opportunity and determinants (MODE) model, motivation to avoid harm, and the elaboration likelihood model—can also be used to inform the design of communication strategies for engaging with farmers. However, a careful analysis of farmer segments, their worldviews, their beliefs, and their position in the consumer decision-making process suggests that the recommendations from these theoretical models should not be implemented uniformly across farmer segments. Rather, the various theoretical models provide a number of strategies that need to be selectively applied based on knowledge of the target segment. While use of theory and understanding of segments will help to improve communications with farmers, it is apparent that changing the beliefs of farmers in some segments about the need to respond to climate change will require more than simply increasing the quantity or quality of communications. Engaging farmers in these segments requires a much richer information set and a much greater effort to show farmers how they should be responding to climate variability and change using practical demonstrations and participatory approaches.

Keywords: farmers, climate change communications, target marketing, communication messages, communication channels, trusted sources, alternative communication methods, participatory approaches


Survey results from Australia, New Zealand, Scotland, and the United States since the beginning of the 21st century indicate that a majority of farmers believe that climate change is occurring (Prokopy et al., 2015a). However, there is much lower acceptance among farmers that it is partly human-induced, with only 25–46% of respondents believing there was an anthropogenic element to climate change in the countries surveyed, apart from Australia (59%). In terms of whether climate change is likely to be a threat to agriculture, the surveys indicate that only 22–45% of farmers accept this, with the average across the six surveys conducted by Prokopy and colleagues (2015a) being about 35%. Thus, only about a third of farmers believe they need to be worried about the impacts of climate change.

The low proportion of farmers indicating concern about the impacts of climate change on agriculture has a number of potential consequences. Those farmers who do not believe climate change is occurring may not recognize when environmental thresholds (e.g., increasing drought making land marginal) are being reached (Robertson & Murray-Prior, 2016) and consequently may not adapt in optimal ways (Wheeler et al., 2013). This may eventually affect food security, particularly if the extent of climate change is toward the higher end of forecasts. Lesser acceptance of climate change may also lead to greater hostility toward government programs involving agriculture that seek to mitigate carbon emissions (e.g., soil carbon incentive programs) and reduce their effectiveness. Agriculture is also an important voice in national policy. In many developed countries farming is archetypal in a nation’s psyche (Sherley, Morrison, Duncan, & Parton, 2014). When the majority of farmers are seen to be very concerned about a changing climate, then it is more likely that a national government will take climate policy more seriously. However, when a majority of farmers think that the impacts on agriculture will be negligible and many argue that the greater threat is from the potential government response to a changing climate (Fleming & Vanclay, 2010; Prokopy et al., 2015a), then the influence of farmers on climate policy is more likely to be marginal or even negative. For these reasons it is important to communicate effectively with farmers about climate change. However, engaging with farmers about climate change has proven to be challenging, even in countries such as Australia where impacts are likely to be more severe (Fleming & Vanclay, 2010; Robertson & Murray-Prior, 2016).

The effectiveness of climate change communications with farmers needs to be assessed in terms of the goals of the communication. The goal of this communication will vary depending on the views held by different farmers about climate change and their stage of “change readiness” (Stevens, 2013). Models of the consumer decision-making process and change readiness suggest that people move through different stages of awareness and concern before moving on to behavior change (Roozmand et al., 2011; Semenza et al., 2008; Stevens, 2013). Thus, depending on farmers’ decision stage, climate change communication may seek to address beliefs about the existence of climate change, encourage changed practices to adapt or mitigate the effects of climate change, or focus on the need to be responsive to working with government programs. It should be noted that there is debate in the literature about whether it is critical to convince people of the anthropogenic causes of climate change to bring about behavior change, with some arguing that it is unnecessary and can be unhelpful (Arbuckle et al., 2014).

This article begins with an examination of the theoretical and empirical evidence about how to more effectively communicate with landholders about climate change, focusing on the theories from social psychology and marketing that may provide some guidance. From these theories a set of principles are identified that can be used to underpin communication efforts. Next, studies that have examined why it is difficult to communicate with farmers are reviewed. From these studies, a number of factors related to the nature of farming, discourses or ways of thinking prevalent among farmers, and commentary in the media about climate change that have led many farmers to either be neutral or negative in their responses to climate change communications are discussed. The literature on farmer segments is then explored to better identify the distinct groups within farming communities and their beliefs with respect to climate change and their values. This is important for the design and targeting of communication messages. If messages are tailored according to segment beliefs and values and farmers’ position in the consumer decision process, they are more likely to be effective. Once we have an understanding of the different farmer segments, the focus shifts to identifying different messages and engagement strategies for communicating with farmers about climate change. One factor that is identified as important theoretically in influencing a positive response to communications is trust in the messenger; this is also found to be an issue in the agriculture context, so the evidence about source credibility or trust in the agriculture context is reviewed next. Finally, the literature on alternative and innovative approaches for communication with landholders about climate change is reviewed, including use of the arts and participatory approaches.

Theoretical Perspectives on How to Effectively Communicate with Farmers

Perspectives from social psychology and consumer behavior can provide a useful understanding of how to successfully communicate with landholders regarding climate change. The central problem in climate change is how to change the attitudes and behavior of a target group (farmers, landholders, industry groups, governments, or consumers). A number of theories can be successfully applied in social marketing programs targeted at such groups, including:

  1. 1. Theory of planned behavior

  2. 2. Attitude-to-behavior process model

  3. 3. Motivation and opportunity and determinants (MODE) model

  4. 4. Motivation to avoid harm

  5. 5. Elaboration likelihood model

A brief explanation of each follows.

Theory of Planned Behavior

The theory of planned behavior posits first that behavior comes about not from attitudes themselves but from behavioral intention for behaviors important to individuals, such as land management practices for a farmer. A landholder may plan to engage in sustainable farming practices, but a number of events may prevent him or her from doing so or even cause him or her to consider unsustainable practices due to economic pressures. Second, the theory of planned behavior model posits three distinct groups of attitudes that combine to affect behavioral intention:

  1. 1. Attitudes toward the behavior itself

  2. 2. Attitudes toward what other people think of you doing the behavior

  3. 3. Attitudes toward your own ability to carry out the behavior

Attitude toward the behavior itself comes from beliefs about the consequences of the behavior, moderated by evaluations of how important those consequences are to the individual.


For example, measurement of attitude toward consequences of land clearing might include:

  1. 1. Greater land clearing makes my farm more productive.

  2. 2. Greater land clearing shows my skill as a farmer.

Research shows that there is not a widespread level of belief among farmers that climate change is anthropogenic or human induced (Barnes & Toma, 2012) and that providing more information about climate change will not influence the direction but only the strength with which attitudes are held (Bright & Manfredo, 1997).

Measurement of the importance of consequences might include:

  1. 1. Having a more productive farm is important to me.

  2. 2. My skills as a farmer are important to me.

An example of the importance of the consequences in communication with landholders is shown in research by Buys, Miller, and van Megen (2012), who found in East Gippsland, Australia, that residents who saw climate change as anthropogenic saw the changing climate as evidence of climate change, while those who were more skeptical termed it weather variability.

Attitude toward what other people might think about one’s actions is known as “subjective norms.” Subjective norms are influenced by a person’s beliefs about what other people think or their “normative beliefs” and are also moderated by a person’s motivation to comply with those other people.


For example, normative beliefs about speeding might be measured by:

  1. 1. My friends like to see me clear more land.

  2. 2. My parents like to see me clear more land.

Corresponding measures of motivation to comply might be:

  1. 1. It’s important to go along with my friends.

  2. 2. It’s important to go along with my parents’ wishes.

As will be discussed later in this article, the social norms with respect to climate change advocates and government are relatively negative among many farmers and landholders, and there is a low motivation to comply with what they see as limitations on their farming practices by outside bodies (Prokopy et al., 2015a).

Perceived behavioral control, or attitude toward one’s own ability to carry out the behavior, is given by capacity and autonomy. That is, control is given by perceived capacity or ability to carry out an action, moderated by perceived ability to exercise that control. Autonomy is grounded in the idea of self-efficacy.


For example, capacity can be measured by:

  1. 1. It’s easy to clear additional land.

  2. 2. I can clear land as fast as neighboring farmers can.

A corresponding measure of autonomy might include:

  1. 1. I can decide for myself whether I can clear more land.

  2. 2. Sometimes I find that I can’t help myself but to clear additional land that might be of use some day.

While the other parts of the behavioral intention suggest that influencing farmers’ attitudes toward the behavior is difficult with respect to climate change, there is considerable evidence that landholders and farmers believe that they have capacity and autonomy to improve farming practices related to the consequences of climate change such as water (Kromm & White, 1991; Robertson, Edgar, & Tyson, 2013) and fire management (Toman, Shindler, & Brunson, 2006).

Overall behavioral intention then is given by the sum of all three factors—attitude toward the behavior, subjective norms, and perceived behavioral control:


where W1, W2, and W3 are weights reflecting the relative importance of each of the three factors.

In practice, researchers and policymakers rarely try to measure a complete theory of planned behavior model. Instead, it serves as a useful framework for thinking about the different features that affect a person’s attitudes and the subsequent behaviors elicited by those attitudes.

Attitude-to-Behavior Process Model

Psychologist Russel Fazio (Fazio, 1990) argues that attitudes are drawn from memory about past experiences or other learning events (Fazio & Zanna, 1981). According to Fazio’s process model, an attitude is activated from memory. If the attitude is not activated, then the attitude cannot affect behavior. Farmers with greater experience may act quite differently in a drought situation; for example, they may destock and reduce land-clearing efforts. Research on communication with farmers on climate change also suggests that a change in climate may not indicate that “climate change” is occurring, rather that it is the result of “weather variability” (Buys et al., 2012; Prokopy et al., 2015a; Robertson & Roy, 2014).

In some situations an attitude may not be activated, which means that the landholder will not be able to use it to help make an evaluation. Indeed the cues or triggers that cause memory to bring up particular attitudes may be counter to an otherwise preferred behavior. The activation of an attitude serves to direct our interpretation of the situation. Fazio’s work is particularly important as it shows that attitudes are difficult to shift and we tend to look for information that confirms existing beliefs (or self-fulfilling prophecies; see Darley & Fazio, 1980).

Motivation and Opportunity and Determinants (MODE) Model

The theory of planned behavior and similar models imply a mostly conscious deliberation about behavior as the weighted aggregation of many different attitudes. The attitude to behavior model, on the other hand, implies a more impulsive, emotional link between simple attitudes and behavior. We can probably see some occasions when we have acted impulsively and other occasions when we have acted thoughtfully, carefully weighing the costs and benefits of an action. What makes the difference? Fazio’s MODE (motivation and opportunity and determinants) model attempts to integrate these two different explanations of attitude and behavior.

Thinking about a situation and weighing our attitudes about consequences and how other people may think all require effort. To apply effort we need to be motivated. We also have to be capable of applying such cognitive effort. That is, a landholder needs to be smart enough to recognize and weigh the various issues and want to and have the opportunity to make that effort. Motivation to think about a situation would be a function of being able to recognize the consequences of the decision or behavior. Opportunity to make an effortful evaluation of the situation also is likely to affect the decision-making processes. If there is no time to gather one’s thoughts, then simple heuristic (rule of thumb) evaluations are likely to occur and decisions will be based on one’s initial attitude.

Motivation to Avoid Harm

Motivation to avoid harm is a seen as an important predictor of purchasing environmentally friendly products (Newman, Dhar, & Gorlin, 2016). In essence, motivation to avoid harm occurs when potential actions or events can make the person feel vulnerable or threatened. There is a motivation to avoid such harm when the people feel they have the self-efficacy to engage in behaviors that avoid harm. The reverse is also true, that people are unlikely to change behavior under this model if they see no large risk or threat or that the unfavorable event has a low cost. Likewise, even if threatened, they may not change behavior if they do not have self-efficacy, a belief that they can enact change, and/or are not aware of the behaviors that can be used to avoid harm.

One would expect that with agriculture vulnerable to climate change and being a source of greenhouse gases, landholders would be motivated to act, given the high level of threat (Climate Council, 2014; Hyland, Jones, Parkhill, Barnes, & Williams, 2016; Mycoo, 2015). However, changes due to climate change may not be perceived as threats by landholders, who instead may attribute changes in climate to normal “climate variability” (Barnes & Toma, 2012; Jemison, Hall, Welcomer, & Haskell, 2014; Prokopy et al., 2015a; Robertson & Roy, 2014).

Elaboration Likelihood Model

This model specifies that people process messages that persuade them through a cognitive/central route or a peripheral route. The cognitive/central route involves active reflection. People are more likely to actively reflect on the content of the message when they have personal involvement with the issue (Bright & Manfredo, 1997; Petty et al., 1983) or when their knowledge and/or the complexity of the message allows them to engage with the issue (Bright & Manfredo, 1997). On the other hand, peripheral evaluation is based on “non-content factors such as source attractiveness, perceived expertise, or credibility” (Toman et al., 2006, p. 324). Thus, people are likely to use central route processing, which is generally more effective at changing attitudes, when they are already interested in the issue. When they do not have a pre-existing interest, the trustworthiness or credibility of the source is critical for persuading people. The key implication from this model for communicating with landholders is that a trustworthy source needs to be used wherever possible.

A summary of the implications from each of these five models for how to communicate with farmers is presented in Table 1.

Table 1. Summary of Social Marketing Theories and Implications for Communications with Farmers



Theory of planned behavior

Identify factors preventing landholders from changing behavior and influence those factors.

Influence attitude toward climate change and the consequences of climate change.

Influence normative beliefs and motivations to comply with others who are doing the right thing in terms of behavioral change.

Attitude-to-behavior process model

Provide evidence that climate change is not consistent with existing patterns of weather variability.

Provide definite evidence of change in either means or in variability of temperatures and rainfall patterns.

Motivation and opportunity and determinants (MODE) model

Encourage more thoughtful decision-making about how farmers should adapt to the long-term changes that will result from climate change, and help to mitigate its effects. Clarify the consequences of action and inaction.

Motivation to avoid harm

Provide information demonstrating why climate change is increasing variability of climate as well as changing mean temperatures and rainfall patterns.

Elaboration likelihood model

Use sources for information that are regarded as trustworthy by farmers, for example, extension officers, agribusiness consultants, farmer networks, accountants, bank managers.

Why Farmers Don’t Engage with or Respond Well to Climate Change Communications

The provision of information is often variable in its effect on behavior change. Some reasons for this variability are suggested by the theoretical models just described: social norms, attitudes toward the behavior, farming context, attitudes toward information providers, political beliefs, and concern about potential sources of harm all influence the likelihood of behavior change. Thus, individual and industry factors as well as the social milieu all influence the likely effectiveness of landholder communications about climate change.

Several studies have sought to identify why it can be difficult to engage with and communicate with landholders about climate change. This includes a discourse analysis of 22 apple growers, 29 dairy farmers, and 12 agricultural consultants conducted by Fleming and Vanclay (2010) in Tasmania, Australia; Robertson and Murray-Prior’s (2016) study of 30 West Australian crop-livestock dryland farmers and four farm advisors; and Prokopy et al.’s (2015a) cross-national comparison of farmers’ climate change beliefs and risk perceptions.

From these three studies, several factors emerge that influence farmers’ belief in climate change and consequently their sensitivity to climate change–related communications. The first reason is related to the small relative short-term effect of climate change within a highly variable system. Climate change is slow-moving, and, in the short run, the effects are relatively small and are smaller than the potential impacts of a variable climate (Robertson & Murray-Prior, 2016). For example, Robertson and Murray-Prior (2016) note that a 6% reduction in wheat yield is predicted in Western Australian between 2010 and 2030. As Asseng and Pannell (2013) point out, adaptation to climate change for Australian farmers should be consistent with “normal responses to short-term variations in weather.” For farmers in various countries, the potential negative effects of government regulation in policy response to climate change is greater than the effect of climate change itself, at least in the short run (Fleming & Vanclay, 2010; Prokopy et al., 2015a, Robertson & Murray-Prior, 2016). Consequently, as Prokopy et al. (2015a, p. 499) contend, “by denying climate change many farmers feel that they are safeguarding their business from the potential legislation that could emerge if climate change were to be recognized as a viable threat.” Thus, in the short run the impacts of climate change are seen by some farmers to be small relative to other weather-related impacts and shocks in agriculture (e.g., variability to prices)—of greater concern is the consequences for farming of any government responses.

Second, many farmers are not overly concerned about the long-term consequences of climate change. For many farmers the planning horizon is relatively short, and “managing the here and now of climate . . . variability takes precedence” (Robertson & Murray-Prior, 2016, p. 191). There is also a lot of confidence in the ability of technological change to manage the impacts of climate change. There is a long history of technological innovation and productivity increases, which creates a sense of optimism about the future (Robertson & Murray-Prior, 2016). Climate change is assumed to be gradual, and adaptation and technological progress are thought to enable farmers to respond to it effectively (Fleming & Vanclay, 2010). Consequently, as pointed out by Fleming and Vanclay (2010), some farmers simply do not “hear” the message that they will be affected by climate change.

Third, there are beliefs about nature that lead farmers to be relatively unresponsive to climate change messages or the need to change behaviors. One of the discourses identified by Fleming and Vanclay (2010) is the “discourse of money.” Within this discourse, nature is a resource to be monitored, controlled, and maximized for wealth creation. Farmers should only focus on sustainability to the extent that it enables them to maintain or increase existing levels of productivity and profit. Within this mindset, the gradual changes that are likely to occur through climate change that can be managed through technological innovation and adaptation are immaterial. A second problematic discourse identified by Fleming and Vanclay (2010) is the “discourse of earth.” Under this discourse, the earth has dominion over humans, and humans are seen to be too insignificant to have any real effect on the earth. The idea that climate change could be anthropogenic simply does not resonate with those who subscribe to this view, and communications involving a focus on human-induced climate change will not be well received.

Fourth, the controversy about climate change has led to what Fleming and Vanclay (2010) describe as a “discourse of questioning.” This discourse has a number of elements. The first is that there is uncertain or incomplete information about climate change. While there might be something happening, the information currently available is seen to be “too confusing, complex, distant, tainted or difficult to understand” (Fleming & Vanclay, 2010, p. 15). Second, vested interests are seen as wanting to exaggerate the effects of climate change (Robertson & Murray-Prior, 2016). This is partly because science is dominated by scarce funding, so scientists follow fashions and produce research findings that reinforce the priorities of such fashions. It is also in scientists’ best interests to present a negative view of the effects of climate change. Consequently, the motives and views of climate scientists are not to be trusted, particularly any information seen to controversial or emotional. This suspicion of climate scientists has been encouraged by the controversy occurring on the release of the Intergovernmental Panel on Climate Change reports and the tendency in the media to regularly present the views of climate skeptics (Robertson & Murray-Prior, 2016). As a result, the most easily adopted position for farmers who subscribe to this discourse is fence sitting or total rejection of the evidence (Fleming & Vanclay, 2010).

Underpinning some of these beliefs are broader cultural values, such as political beliefs and worldviews. Cultural values form the context in which people process information, form causal attributions, and perform other cognitions that shape their beliefs about and responses to climate change information, such as risk and scientific consensus (Kahan, Jenkins-Smith, & Braman, 2011; Weber, 2010). In particular, it has been established that people engage in “cultural cognition,” a process of selectively paying attention to and fitting perceptions of new information to existing values (Kahan et al., 2011). This cultural cognition results from people having worldviews that make them less responsive to climate change communications. Studies have investigated these psychological phenomena with particular reference to farmers’ beliefs about climate change and the implications for climate change communication (Arbuckle, Morton, & Hobbs, 2015; Islam, Barnes, & Toma, 2013). There is substantial evidence that political orientation is also related to particular beliefs about climate change in the United States, where a more conservative political position tends to be associated with lower levels of concern about, or disagreement with, the scientific consensus regarding climate change (Shwom et al., 2015), and many farmers are conservative in political orientation. There is also a growing body of research showing similar trends in other westernized countries, though eastern European countries have not shown the same divide (McCright, Dunlap, & Marquart-Pyatt, 2016).

While not all farmers hold these views, these reasons—either individually or in combination—have created or resulted from a worldview for many farmers that is somewhat impervious to climate change communications. These findings have a number of implications for climate change communications, which will be discussed later in this article.

It is also worth noting that, particularly in developing countries, worldviews and beliefs may not always be the primary determinants of climate change inaction. In a survey study of Tanzanian villagers, Below et al. (2012) identified a set of structural variables including the availability of quality education opportunities for both men and women, agricultural extension, and microcredit services as the most promising means of improving climate change adaptation. Chen et al. (2014) found that Chinese farmers’ ability to adapt to climate change was linked to government provision of early warning systems and post-disaster services, technical assistance, and financial support, although relatively few farmers (5%) appeared to have access to such supports. Similar sets of factors have been identified to guide climate change adaption choices of Ethiopian (Deressa, Hassan, Ringler, Alemu, & Yesuf, 2009) and Ghanaian rural villagers (Fosu-Mensah, Vlek, & MacCarthy, 2012). In a 12-country study covering sub-Saharan Africa and South Asia, Wood, Jina, Jain, Kristjanson, and DeFries (2014) found that access to weather information, household and agricultural assets, and participation in local social institutions were associated with smallholder farmers adapting their practices in response to climate variability, with some variation in predictive effects across countries. These studies highlight an important issue. Although worldviews and beliefs are undoubtedly critical variables for understanding farmer responses to climate change, beliefs alone will not necessarily produce desirable behavioral outcomes in the absence of facilitating policy and economic and social supports.

Segmentation of Landholders

Within the climate change communications literature, segmentation approaches have been widely used to identify homogeneous groups within the community (Hine et al., 2014). Identifying groups with similar beliefs and attitudes toward climate change, psychographic profiles, values, and behaviors is helpful for understanding which groups can be most gainfully targeted, as well as which channels and appeals should be used.

Within the agriculture, rural sociology, and natural resource management literatures, there is an extensive literature identifying different landholder segments. This originally involved identification of different farming styles (van der Ploeg, 1985). While initially subject to criticism due to a lack of explanatory power and an inability to uniquely classify farmers (Howden & Vanclay, 2000; Howden, Vanclay, Lemerle, & Kent, 1998), there has been growing use of objective quantitatively based approaches involving techniques commonly used in market research.

Several unique segments have repeatedly emerged in these studies segmenting landholders (Morrison & Lockwood, 2014) (see Table 2). For full-time farmers, two broad categories have been identified, namely (1) the quality operators/multi-objective owners/innovators/progressive farmers and (2) the traditional farmers/resistors/production-oriented landholders. Both groups have a strong economic motivation and are well connected in their communities, but the former is more business oriented, better resourced, makes better use of an array of information sources, is more likely to engage in pro-environmental behaviors, and is more environmentally engaged. Segments have also been identified for lifestylers and hobby farmers.

Table 2. Landholder Segments Previously Identified in the Literature


Names used

Own farm that provides main or some income. Characterized by high business orientation, information-seeking behavior, economic motivation, connectedness, and low capital and time constraints. Have high environmental behaviors, but neutral value for environmental responsibility and nature value.

  • Jennings and van Putten (2006)—Multi-objective owners

  • Karppinen (1998)—Multi-objective owners

  • Morrison et al. (2008), Morrison and Lockwood (2014)—Quality operators

  • Bohnet et al. (2011)—Innovators

  • Sutherland et al. (2011)—Economic land stewards

  • Emtage and Herbohn (2012)—Well connected and progressive

Own farm that provides either the main or some income. Have a high economic motivation and low environmental behaviors, responsibility, and nature value. Have high connectedness, sense of place, value for farming business and tradition, and time and capital constraints.

  • Jennings and van Putten (2006)—Agriculturalists

  • Karppinen (1998)—Self-employed owners

  • Morrison et al. (2008)—Profit first

  • Van Herzele and Van Gossum (2008)—Traditional owner/economist

  • Bohnet et al. (2011)—Traditionalists

  • Barnes et al. (2011)—Resistors

  • Sutherland et al. (2011)—Multi-functionalists

  • Emtage and Herbohn (2012)—Production oriented Landholders

  • Morrison and Lockwood (2014)—Traditional farmers

Lifestlyle/hobby farmer segment with high sense of place, low economic motivation, and high environmental responsibility and value for nature. Comprises predominantly professionals, semi-professionals, and those working in the service sector.

  • Jennings and van Putten (2006)—Non-timber output owners

  • Karppinen (1998)—Recreationists

  • Morrison et al. (2008)—High-end hobby farmers and lifestylers

  • Sutherland et al. (2011)—Community stewards

  • Van Herzele and Van Gossum (2008)—Recreationist

  • Morrison and Lockwood (2014)—Professional and retiree lifestylers

Different to other lifestyle segments. Distinguished by low lifestyle and environmental motivations, connectedness, and sense of place. One of the lowest levels of education.

  • Morrison et al. (2008)—Included in smaller hobby farmers and lifestylers

  • Morrison and Lockwood (2014)—Blue-collar lifestylers

Source: Adapted from Morrison and Lockwood (2014).

To this list of existing studies can be added six additional studies conducted with the objective of segmenting landholders for the purposes of climate change communications and engagement (see Table 3). Before summarizing the results from these five studies, several observations can be made about their theoretical basis and methodology. Having a strong theoretical basis for selecting constructs for segmenting has been previously noted in the literature as being important for accurately generating segments (Morrison, Durante, Greig, Ward, & Oczkowski, 2012). Arbuckle et al.’s (2014) study is based on the approach developed by Maibach and Leiserowitz (Maibach, Leiserowitz, Roser-Renouf, & Mertz, 2011) for segmenting households but is adapted for agriculture, and the selection of variables is carefully justified. Morgan, Hine, Bhullar, and Loi (2015) based their choice of constructs on those found to predict adoption of sustainable farming practices as well as contribute to reducing greenhouse gas emissions within the psychology literature. Constructs are related to beliefs about climate change, environmental values, place attachment, time orientation, self-efficacy, and financial benefit (from adoption of sustainable farm practices). Hyland et al. (2016) select items based on self-identity, climate awareness, and perceived risk and justify these from the literature, but they do not demonstrate the sufficiency of these variables for identifying segments. The remaining studies do not present any theoretical or literature-based rationale for their selection of segmenting variables. Regarding methodology, two of the studies have quite small samples for segmentation (n = 286 and n = 82), and the first of these uses a convenience sample. The Scottish and Australian surveys are of moderate size (n = 550 and n = 561, respectively), and only the U.S. study can be considered large scale. The Australian survey is also a convenience sample. Only the Australian study considers farmers in general, with all others focusing on specific types of farmers. Two of the studies use latent class analysis, which is regarded as the state-of-the-art segmentation approach, while two studies use the tandem approach of factor followed by cluster analysis, which is advised against in the literature (Mooi & Sarstedt, 2011). Thus there is great variability in the type and quality of the methodology used.

Table 3. Summary of Studies Indentifying Farmer Climate Change Segments




Methodology used to generate segments

Barnes and Toma (2012)


Telephone survey of 550 dairy farmers

Factor analysis of 29 attitudinal items related to regulation skepticism, climate change, production orientation, and four types of values (resource, innovation, ecological, and passive) and cluster analysis on 5 or 11 factors.

Barnes, Islam, and Toma (2013)


Telephone survey of 550 dairy farmers

Latent class analysis of 8 questions related to climate beliefs, and costs or benefits of climate change.

Arbuckle et al. (2014)

11 U.S. Corn Belt states

Mail survey of 4778 larger corn farmers

Latent class analysis of 34 questions related to climate beliefs, experience of hazard, perceived risk, efficacy, and support for climate action.

Eggers, Kayser, and Isselstein (2014)

North German plain

On-farm survey of 82 managed permanent grassland farmers

Researchers identified segments a priori and allocated farmers to these segments based on responses to 48 Likert Scale questions.

Morgan et al. (2015)


Convenience sample of 551 Australian farmers

Latent profile analysis conducted using a broad range of psychological variables related to the adoption of low emission agricultural practices.

Hyland et al. (2016)


Convenience sample of 286 beef and sheep farmers

Factor analysis of 29 items related to self-identify, awareness of climate change, and perceived risk of climate change with subsequent cluster analysis.

Notwithstanding these methodological differences and challenges, some common segments can be identified within these studies, as shown in Table 4.1 One segment has low belief in climate change and its negative effects and concern about it risks. Some members of this segment may even consider that climate change has positive effects, particularly if they are located in colder areas. This segment generally has low trust in government and regulation and only adopts sustainable farm practices if they are seen to enhance on-farm profitability. It is consistent with the traditional farmers/resistors/production-oriented landholders identified in Table 2 and also with those landholders who subscribe to the discourse of money as identified by Fleming and Vanclay (2010). It typically represents about 25% of farmers or less. The next segment is a generally disengaged segment. Overall, the segment members may have a slight belief that climate change is occurring, but the defining characteristic of the segment is that the members are generally confused or uncertain about climate change or have no strong opinions. The studies summarized in Table 4 indicate that this segment represents anything from 25 to 60% of landholders. Next is the segment that has strong beliefs in climate change and concern about its impacts. This segment typically represents 20–40% of landholders. A couple of British studies and the one U.S. study have identified a segment that accepts climate change but has little concern about its risk and is confident that they can change management practices to adapt. This segment has been found to have from 15 to 28% of landholders as members. The final segment identified is a group that is environmentally aware but dismissive of climate change. This group was found in one study and comprised 23% of landholders.

Table 4. Climate Change Farmer Segments Identified in the Literature and Studies Where They Were Identified*

Segment characteristics

Low belief and concern about climate change. Production focused.

Distrusts regulation.

Leans slightly toward climate change belief or may have no strong opinion.

Strong climate change belief and concern about impacts.

Accepts climate change but low sense of risk and high on efficacy.

Pro-environmental but low acceptance of climate change.

Names given to these segments in existing literature:

Barnes and Toma (2012)

Regulation skeptic (12%) Positivist (12%)

Disengaged (23%)

Negativist (22%)

Commercial ecologist (15%)

Barnes et al. (2013)

Deniers (18%)

Confused moderates (62%)

Strong risk perceivers (20%)

Arbuckle et al. (2014)

Unconcerned (13%) Detached (5%)

Uncertain (25%)

Concerned (14%) Uneasy (25%)

Confident (18%)

Morgan et al. (2015)

Non-green dismissive (10.9%) Profit-driven adopters (12.0%)

Uncommitted (57.3%)

Green adopters (19.8%)

Hyland et al. (2016)

Productivist (23%)

Dejected (26%)

Environmentalist (28%)

Countryside steward (23%)

What Message to Use and How to Engage with Segments of Concern

From the segmentation analysis reported in the previous section, only one of the segments had a strong climate change belief and concern about impacts. A couple of segments were made up of landholders who are generally environmentally oriented but either believed that climate change presented a low risk or did not accept the existence of climate change. One other segment was more neutral about the issue, having a slight climate change belief, or were uncertain or disengaged. The remaining segment comprised production-oriented farmers who have low trust in government and tended to be unconcerned about climate change or were skeptics or deniers. Given the existence of these segments of concern, what messages should be used, and what engagement strategies should be used?

The question of how to design messages for reaching different farmer segments was investigated by Morrison, Greig, Read, Waller, and McCulloch (2015). They conducted a study of natural resource management practitioners in Australia to understand how to reach three landholder segments typically considered “difficult to reach.” One of these segments was traditional farmers, which is consistent with the first section of Table 4—that is, those with low belief and concern about climate change, who are production focused and distrust regulation. They suggested emphasizing the financial benefits associated with participation and perhaps making use of humor. They also recommended making use of some sort of repeated personal contact with extension officers to build trust and use of other trusted intermediaries (e.g., opinion leaders/local champions, and use of networks).

Similar suggestions were made by Fleming and Vanclay (2010) regarding those landholders who subscribe to the “discourse of money,” who share many similarities with this segment of farmers. Fleming and Vanclay recommended stimulating their desire to maintain competitiveness and encourage their involvement in developing climate solutions with industry on this basis. They also recommended explicitly highlighting the connections between financial problems and climate change and the financial benefits of addressing climate change (e.g., reducing input costs, reduced short-term variability, and certainty of yield), and Hyland et al. (2016) similarly suggest promoting low-cost “win-win” technologies for reducing waste to these farmers. Fleming and Vanclay (2010) also recommended not emphasizing the general impacts of climate change, no matter how catastrophic, to avoid alienating those farmers who hold to this discourse. This is consistent with trying to create a more positive attitude toward climate change, which is a recommendation of the theory of planned behavior. Arbuckle et al. (2014) and Prokopy et al. (2015b) add to this that emphasizing the human role in climate change communications should be avoided. Arbuckle et al. (2014) suggest emphasizing “terminology and narratives that focus on adaptation to weather variability and focus on engaging farmers in creative adaptation to their more immediate experiences (e.g., increased weather variability) rather than causes is a more effective route” (p. 515). This is consistent with the recommendations of the motivation and opportunity and determinants (mode) model, which seeks to encourage more thoughtful decision-making. Others such as Hyland et al. (2016) suggest that knowledge transfer about how agricultural practices influence climate change is needed, but for this group, which is quite low in the decision-making process about the need for changing behaviors due to climate change, we concur with the view of Arbuckle et al. (2013). Creating a more positive attitude will require avoiding discussion of some controversial but correct aspects of climate change (e.g., its anthropogenic origins) not critical for encouraging this segment to change behaviors. For this segment, Barnes et al. (2013) recommend use of publically available farming sources (e.g., agricultural scientists) as well as farmer networks to provide climate change messages. Hyland et al. (2016) also suggest using participatory approaches.

The second segment that leans slightly toward climate change belief or may have no strong opinion appears to adhere to the “discourse of questioning” identified by Fleming and Vanclay (2010). For this group Fleming and Vanclay suggest that building trust in knowledge provided about climate change is needed. This is echoed by Barnes, Islam, and Toma (2013), who note the importance of clarifying the underlying science for this segment, which is consistent with the recommendations of the attitude-to-behavior process model and the motivation to avoid harm model. Robertson and Murray-Prior (2016) go further and urge that to build trust, a “rich picture approach” is needed that seeks to show interactions of and dependency farm-level outcomes and climate. The challenge for those communicating about climate change is to make climate change and the ways farmers can respond to it more real at the farm level (see also Prokopy et al., 2015b). Indeed, Jemison et al. (2014) found that programs dealing with the effects of climate change were more effective if growers learned about farming practices that would help them deal with associated variable weather patterns. Encouraging more careful engagement of landholders in this way is consistent with the motivation and opportunity and determinants (MODE) model. Robertson and Murray-Prior (2016, pp. 195–196) also advocated being clearer about uncertainties, so that advice is seen to be more realistic:

[T]rust will be regained when researchers and extension officers need to try and place the impacts of, and adaptation to, climate change within the realities of farming. Also if R, D and E staff were to show what innovations they are working on to ease the adaptation challenges of farmers, we suspect farmers would be more comfortable discussing climate change if they thought something useful was on offer. We reinforce the point made by others that uncertainty around climate change predictions must be communicated . . . rather than single projections.

This is consistent with the provision of a two-sided appeal, which is where both arguments for and against a position are presented in communication, for example, pessimistic and optimistic forecasts or the range of possible outcomes. Two-sided appeals are thought to be effective because they inoculate the receiver to counterarguments and less source derogation (Kamins & Assael, 1987) and so may be more effective in the contested space of climate change communication. The counter to this view is that when receivers are unfamiliar with the message, a one-sided appeal has been found to be most effective (Dipboye, 1977). Though not dealing specifically with climate change, research by Bright and Manfredo (1997) showed that support for conversation in old-growth forest was more likely to occur with foresters when balanced information was presented. In this context, “balanced” meant provided arguments for and against preservation of old-growth forests.

Fleming and Vanclay (2010) also suggest highlighting the information about the financial benefits of action to this group to help overcome their skepticism. In this recommendation the response is similar to the message recommended for the traditional farmers. A key difference is that with this segment, there should be a greater attempt to explain the science of climate change and consequently how farmers should seek to adapt. Barnes et al. (2013) recommend the use of participatory approaches to engage landholders in this segment, as well as farmer networks to pass on climate messages.

Last, what messages should be used for those segments comprising farmers or landholders who are generally environmentally oriented but either considered climate change presented low risk or did not accept the existence of climate change? Fleming and Vanclay (2010) suggest a couple of options for responding to the “discourse of earth” where humans are seen to be too insignificant to affect global environmental outcomes. First is that farming practices that are desirable from a climate change perspective are consistent with those that demonstrate a respect for nature. Second, communicators should seek to highlight the multiple environmental benefits of climate change action. Fleming and Vanclay (2010) warn against emphasizing the anthropogenic origins of climate change with those who accept this discourse.

Other commentators have made additional suggestions about how to engage with these more environmentally oriented segments. Hyland et al. (2016) recommend activities that involve knowledge transfer about how agricultural practices influence climate change. Many farmers within these two segments have the characteristics of those more likely to have participated in an agri-environmental program (Morrison & Lockwood, 2014). An option, therefore, for building understanding of how farming practices influence climate change suggested by Barnes et al. (2013) is to include climate-related actions in agri-environmental programs. Another option suggested by Arbuckle et al. (2015) is to use strategies that appeal to farmers’ problem-solving ability and feelings of efficacy, which is appropriate considering a characteristic of this segment is both belief in climate change and high efficacy. For example, Barnes and Toma (2012) suggest encouraging use of low-cost “win-win” technologies for reducing waste for this segment, though other practices may also be able to be explored. Finally, Barnes et al. (2013) suggested seeking to raise the social capital of the farming community and using both farmer and family non-farm–based networks to influence farmers to change their behaviors. This latter suggestion is consistent with influencing normative beliefs and motivations to comply with the theory of planned behavior. Certainly social capital has been found to be a strong predictor of environmentally oriented behaviors such as participation in agri-environmental programs (Morrison, Oczkowski, & Greig, 2011), but this is likely to require a medium- to long-term strategy.

Source Trust and Effectiveness

In addition to choosing a message and how to engage, a critical part of communicating with farmers is choosing the source of the communications. An earlier reported finding is that many farmers are distrustful of climate change communications (Fleming & Vanclay, 2010). This is concerning, as the perceived honesty and objectivity of the source of the communication has a substantial influence on how the communication is accepted by the receiver. As noted in the discussion of the elaboration likelihood model, if the source is well respected and highly thought of by the intended audience, the message is much more likely to be believed. Conversely, messages from a source considered unreliable or untrustworthy are more likely to be received with skepticism and may be rejected. Credibility is built on a number of factors, the most important being the perceived intentions of the source.

Within the agriculture and natural resource management literatures, there is evidence of which sources farmers consider to more trustworthy. Kromm and White (1991) reported that farmers found the university extension service, private agricultural consulting firms, trade magazines, local groundwater or resource districts, and the soil conservation service to be the most reliable sources of information about managing water use. Less reliable sources included the local irrigator association and the agricultural stabilization and conservation services (which manages farm subsidies), irrigation equipment dealers, and fertilizer dealers. Kromm and White (1991) also examined the perceived importance of difference sources and found that less educated landholders tended to prefer fertilizer dealers, well drillers, and the agricultural stabilization and conservation services as information sources, while older farmers also favored fertilizer dealers as well as the local irrigator association. Thus, the importance of segments differs across farmer segments. Similar findings about the sources preferred by more traditional farmers have been found in other studies. Wright and Shindler (2001) reported that longer-term landholders with larger properties and lower education distrusted university scientists, government agencies, and environmental groups. However, they tended to trust and found more useful information from industry groups and relatives and friends. Rosenberg and Margerum (2008) also found that less educated landholders were more likely to select friends, family, and neighbors as trusted information sources. This suggests that for traditional farmers using industry groups, farmer networks or (non-university) agricultural extension officers may be most effective, but for more educated and newer farmers, a wider range of sources may be appropriate.

There is also empirical evidence that indicates the importance of source trustworthiness in the context of agriculture. Studies have found that the importance ratings of information sources is correlated with behavioral outcomes such as awareness, environmental concern, and adoption of practices (Kromm & White, 1991; Lichtenberg & Zimmerman, 1999; McCaffrey, 2004). Therefore there is good reason to consider which information sources landholders are more likely to find trustworthy in the context of climate change communications.

Additional evidence is emerging in the climate change communication literature about the importance of source credibility when communicating with farmers. Arbuckle et al. (2015) showed that farmers were suspicious and skeptical of information provided by environmentally orientated interest groups but placed more trust in agricultural interest or industry groups. Conversely, research in the United States shows that agricultural advisors had a high degree of acceptance of climate change—around 75%—and were considered a trusted source by landholders (Prokopy et al., 2015b), implying that this source of information is crucial in communicating information about climate change. However, it also needs to be recognized that only 12.3% of the agricultural advisors surveyed by Prokopy et al. (2015b) believed that climate change is primarily anthropogenic, while another 37.8% believed that it is caused equally by natural changes in the environment and human activities. This highlights the importance of not emphasizing the causes of climate change if using agricultural advisors as an information source. Similar recommendations about the use of agricultural scientists and farm business advisors were made by Robertson and Murray-Prior (2016) in the Australian context. Interestingly, although agricultural advisors in the United States seem convinced about climate change, they often prepare only short-term forecasts for their clients (Prokopy et al., 2015b, p. 185). Nonetheless, agriculture scientists and other farm experts such as farm business advisors and extension officers are regarded as being trusted intermediaries who can more effectively communication with farmers about climate change (Krantz, Monroe, & Bartels, 2013). If the source of information is not specifically about climate change, but perhaps farming practices that take it into account and help mitigate adverse effects, then this type of information is more likely to be trusted and acted on by landholders (Barnes & Toma, 2012; Department of Agriculture, 2012; Franz, Piercy, Donaldson, Richard, & Westbrook, 2010). When discussing how to deal with weather variability, which is likely to be affected by climate change, farmers expressed greater concern and were more receptive to this information (Jemison et al., 2014). This highlights that if communications with farmers about climate is seen to be part of normal advice about farm management, farmers are likely to be more receptive.

Alternative Communication Approaches

In addition to the strategies reviewed in previous sections, researchers and practitioners also have proposed several alternative approaches for engaging landholders about climate change, or sustainability more generally. In this section, we review two such approaches: (1) arts-based interventions and (2) participatory approaches.

Arts-Based Interventions

Art can have profound effects on the attitudes, beliefs, and behavior of individuals, as well as on the development of society more broadly (Belfiore & Bennett, 2008). Some have called for an increased role of the arts—for example, writing, painting, sculpture, and music—in promoting sustainability and pro-environmental behavior (Curtis, 2011; Curtis, Reid, & Reeve, 2014). Curtis et al. (2014) proposed that the arts may influence pro-environmental behavior through three primary pathways: (1) communicating information in an engaging form, (2) creating empathy toward the natural environment, and (3) embedding the arts in ecological sustainable development.

Despite substantial anecdotal evidence about the value of arts-based interventions, Curtis et al. (2014) noted that it has been difficult to obtain “hard evidence” about the impact of the arts on values, attitudes, beliefs, and behavior. A key methodological shortcoming of much of the work in this area is an overreliance on case study designs without appropriate control groups, making it difficult to determine whether any observed changes are due to the intervention or to other uncontrolled factors. There is rarely any systematic evaluation that would enable an objective observer to determine whether the event had any immediate or longer-term causal effects on values, attitudes, beliefs, and behavior.

Randomized controlled trials and well-designed quasi-experiments would go a long way to clarifying the causal effects of art interventions on behavior and how interventions can be best designed to maximize their impacts. Prior to implementing such approaches on a broad scale, it is important to have a strong evidence base supporting their effectiveness.

Participatory Approaches

Climate scientists are generally quite knowledgeable about the drivers and likely consequences of climate change. However, they often do not have detailed local knowledge to make fully informed recommendations about how rural communities can best adapt to climate change. And even if they did, this top-down “scientists-know-best” approach to planning may elicit a considerable backlash from affected landholders. Participatory approaches address these challenges by encouraging climate decision-makers to engage directly with key community stakeholders to facilitate information sharing and the co-development of knowledge and strategies for effectively responding to climate change (Mase & Prokopy, 2014; Roncoli, 2006). This represents an important step toward developing “actionable science.”

Bartels et al. (2013) provided an example of this participatory approach in which climate scientists engaged in a series of workshops with farmers and engagement specialists in the southeastern United States. The workshops involved the use of historical timelines to track local environmental conditions and agricultural production over time, including future projections. These scenarios enabled participants to identify opportunities and barriers to adaptations and co-develop locally relevant solutions that are more likely to be accepted and acted upon by rural residents. Bartels et al. (2013) noted that the thoughtful design of stakeholder engagement plays a vital role in the strengthening the adaptive capacity of rural communities.

In situations where face-to-face engagement between stakeholders is not feasible, Bojovic et al. (2015) found that provision of an online space for farmer interaction (i.e., an eParticipation framework) was an efficient way to rapidly collect information and perspectives from a broad range of stakeholders. Given that Internet access in rural communities is rapidly increasing in many parts of the world, eParticipation represents a promising model for facilitating ongoing consultation and collaboration between farmers, climate scientists, and policymakers. However, more research is still needed about how to design and deploy digital engagement strategies for maximal effect and the relative merits of face-to-face and digital engagement across different stakeholder groups and contexts.

Regardless of whether a face-to-face or digital engagement strategy is used, it is important to appreciate that the way policymakers and scientists typically frame climate change narratives can potentially undermine constructive dialogue with stakeholders and constrain the types of solutions that are proposed and ultimately implemented. Meppem and Bourke (1999) argued for a broader “communicative” approach to participatory planning that involves explicitly surfacing and reflecting upon fundamental assumptions and motivations that underlie contested positions about environmental management and sustainability. They note that the instrumental-rationalist perspective favored by many policymakers and climate scientist represents only one way of viewing issues like climate change and that environmental discourse should incorporate alternative ways of thinking and knowing, with the aim of reaching new shared meaning that more accurately reflects the complexity of the challenges we face.

Computer Simulations

Computer simulations represent another innovative strategy for engaging farmers about climate change. Bert, Satorre, Toranzo, and Podestá (2006) employed a maize production simulation based on predicted climate change conditions in the Argentine Pampas. They created decision maps for regional agricultural advisors that outlined the main decisions and timings involved in maize productions, specific decisions sensitive to climate, and key decision options under different climate scenarios. They found that the advisors were generally risk averse, which ultimately led them to make decisions that resulted in suboptimal productivity outcomes. Such simulations can efficiently surface the decision rules made by farmers when managing their properties and provide feedback about alternative strategies that may produce better economic and environmental outcomes under changing climatic conditions.


While it is heartening that a majority of farmers in developed countries accept that climate change is occurring, it is concerning that only about a third consider that it will have any impact on agriculture. Furthermore, there appears to be no easy fix. Simply providing more information about this issue and/or increasing the quality of information has been shown to be an ineffective form of communication for changing attitudes and behaviors (Prokopy et al., 2015b; Vogel & O’Brien, 2006). Richer forms of communication are needed to change farmer attitudes and behavior.

The reasons why farmers, in general, do not respond well to standard climate change communications are varied. In part it is due to the nature of farming, which is mostly about managing short-term variability in the weather and where the short-term impacts of climate change are seen to be small in comparison. And while the longer-term impacts may be greater, they are more uncertain, and most farmers do not have a longer-term planning horizon. The worldviews of many farmers also desensitize them to climate change messages. The discourse of money described by Fleming and Vanclay (2010)—where the environment is only seen as a means of achieving production, and where there is a general apathy about the environment and distrust of government—makes it difficult for farmers subscribing to this view to hear the message of anthropogenic climate change. The various segmentation studies suggest this worldview is held by up to 20% of farmers. Also prominent is the discourse of questioning, which is a worldview held by about 25–60% of farmers. Here the conflicting views about climate change presented in the media and the related controversies have led to a suspicion about the motives of climate scientists and the veracity of their predictions. Consequently, landholders holding this view are uncertain about the information being provided and the messengers used, which is vital for the acceptance of messages. As a consequence of these realities of farming, and these and other worldviews, many farmers are somewhat impervious to standard communications about climate change.

One option in this relatively challenging situation is to appeal to theory for guidance about how to improve communications. The existing theories do provide guidance on a range of tactics that can be used to improve communications. For example, from the theory of planned behavior we see the importance of encouraging more positive attitudes toward the concept of climate change and the need to seek to influence social norms and the motivation to comply with others. The attitude-to-behavior model suggests that we should provide more evidence that climate change is not consistent with existing patterns of variability. The elaboration likelihood model emphasizes the importance of using trustworthy sources of information. The other models reviewed also provided useful suggestions. However, a careful analysis of the segments, their worldviews, their beliefs, and their position in the consumer decision-making process suggests that the recommendations from these theoretical models should not be implemented uniformly across the farmer segments. Rather, the various theoretical models provide a number of strategies that need to be selectively applied based on knowledge of the target segment.

For members of the traditional farmer segment—who are production focused, have low environmental values, and generally distrust government—there is a need to create a more positive attitude toward climate change (consistent with the theory of planned behavior), which can partly be achieved by de-emphasizing the anthropogenic origins (Arbuckle et al., 2014), highlighting the links between climate change and financial problems, and what can be done to ameliorate these (Fleming & Vanclay, 2010). The latter is also consistent with the motivation to avoid harm model. However, the emphasis should be on helping farmers respond to climate variability rather than reducing emissions, even though collectively that would be a recommendation of the motivation to avoid harm model. Also relevant is demonstrating farming practices that will help farmers adapt to increase climate variability, which is consistent with the motivation and opportunity and determinants (MODE) model, and the use of trusted sources such as agricultural scientists and agribusiness consultants to provide this information, which is consistent with the elaboration likelihood model. However, implementing the recommendations of the attitude-to-behavior process model would need to be done cautiously for this segment given their sensitivity to alarmism. Similarly, harnessing social norms, which is part of the theory of planned behavior, may be ineffectual for this group if most of their contemporaries hold similar views.

The various segmentation analyses have demonstrated the existence of a relatively consistent set of segments, despite some concerns about their methodology. Of interest is that the segments identified are largely different from the segments identified in previous profiling studies with the agriculture and natural resource management literatures. The only consistent segment identified was the traditional farmer segment just mentioned. The other three most frequently identified segments in those studies explicitly focusing on climate change were (1) a segment who accepted that climate change is occurring, is concerned about its impacts, and is seeking to change behavior, (2) a segment comprising those largely uncertain about climate change who are making minimal changes in behavior, and (3) a segment that accepts climate change but is dismissive of its risks. Given the difficulty of shifting the worldviews of traditional farmers, these latter two segments should arguably be the focus of communications campaigns, recognizing that there are still options for communicating with traditional farmers (Morrison et al., 2015, 2017).

Understanding segments does provide greater insight into how to tailor messages based on their worldviews, values, concerns, and obstacles to behavior change. The uncertain segment is of particular concern given its size (approximately 25–60% of farmers). For this segment, a multi-pronged strategy emerges from the literature as being appropriate. This includes seeking to clarify the underlying science and demonstrating the financial benefits of action. However, there is a need to go beyond simple appeals and provide a richer information set to build trust in the knowledge provided. This includes demonstrating uncertainties and much greater effort demonstrating how farmers can respond and the efficacy of potential actions. Engagement and trust building are central, which is consistent with the recommendations of the adaptive co-management literature (Berkes, 2009). This also may involve the use of participatory approaches.

These recommendations are at odds with the suggestion of Barnes et al. (2013) that intrinsic messages based on benevolence and universalism should be activated. Previous research by Morrison et al. (2017) investigated the effectiveness of such community-based appeals among farmers and found them to ineffective. The worldviews of some of the segments identified, such as traditional farmers, suggests that such intrinsic appeals will not resonate, though they may be effective for households in other areas.

We also heed the concerns of Robertson and Murray-Prior (2016) that biophysical science and related communication strategies are best placed to assist with dealing with incremental changes. However, transformative change in agriculture is occurring due to climate change, and some areas are becoming more marginal for existing agricultural systems. This will intensify over time. In such locations, Stafford Smith et al. (2011) recommend that the agriculture industry be involved in monitoring changes in climate and production to help provide information about the need for transformation change. In such a context, as Robertson and Murray-Prior (2016) note, there is a need for soft systems approaches and scenario analysis to effectively plan for the future. We support the need for such industry-level planning and communications to effectively manage future changes.

Further Reading

Arbuckle, J. G., Wright Morton, L., & Hobbs, J. (2013). Farmer beliefs and concerns about climate change and attitudes toward adaptation and mitigation: Evidence from Iowa. Climatic Change, 118, 551–563.Find this resource:

    Buys, L., Aird, R., van Megen, K., Miller, E., & Sommerfeld, J. (2012). Perceptions of climate change and trust in information providers in rural Australia. Public Understanding of Science, 23(2), 170–188.Find this resource:

      Hansen, J., Marx, S., & Weber, E. (2004). The role of climate perceptions, expectations, and forecasts in farmer decision making: The Argentine Pampas and south Florida. International Research Institute for Climate Predictions Tech. Rep. 04–01. Retrieved from

      Hayman, P., Rickards, L., Eckard, R., & Lemerle, D. (2012). Climate change through the farming systems lens: Challenges and opportunities for farming in Australia. Crop & Pasture Science, 63, 203–214.Find this resource:

        Howden, S. M., Soussana, J. F., Tubiello, F. N., Chhetri, N., Dunlop, M., & Meinke, H. (2007). Adapting agriculture to climate change. PNAS, 104, 19691–19696.Find this resource:

          Kates, R. W., Travis, W. R., & Wilbanks, T. J. (2012) Transformational adaptation when incremental adaptations to climate change are insufficient. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 109, 7156–7161.Find this resource:

            Kingwell, R. (2006). Climate change in Australia: Agricultural impacts and adaptation. Australian Agribusiness Review, 14, 1–29Find this resource:

              Pannell, D. J. (2010). Policy for climate change adaptation in agriculture. Paper presented at the 54th annual conference of the Australian Agricultural and Resource Economics Society, Adelaide, February 10–12, 2010.Find this resource:

                Prokopy, L. S., Haigh, T., Mase, A. S., Angel, J., Hart, C., Knutson, C., Lemos, M. C., Lo, Y., McGuire, J., Morton, L. W., Perron, J., Todey, D., Widhalm, M., & Coauthors. (2013). Agricultural advisors: A receptive audience for weather and climate information? Weather, Climate, and Society, 5, 162–167.Find this resource:

                  Rickards, L., & Howden, S. M. (2012) Transformational adaptation: Agriculture and climate change. Crop & Pasture Science, 63, 240–250.Find this resource:


                    Arbuckle, J. G., Hobbs, J., Loy, A., Morton, L. W., Prokopy, L. S., & Tyndall, J. (2014). Understanding Corn Belt farmers’ perspectives on climate change to inform engagement strategies for adaptation and mitigation. Journal of Soil and Water Conservation, 69(6), 505–516.Find this resource:

                      Arbuckle, J. G., Jr., Morton, L. W., & 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. Environment and Behavior, 47(2), 205–234.Find this resource:

                        Asseng, S., & Pannell, D. J. (2013). Adapting dryland agriculture to climate change: Farming implications and research and development needs in Western Australia. Climatic Change, 118, 167–181.Find this resource:

                          Barnes, A. P., Islam, M. M., & Toma, L. (2013). Heterogeneity in climate change risk perception amongst dairy farmers: A latent class clustering analysis. Applied Geography, 41, 105–115.Find this resource:

                            Barnes, A. P., & Toma, L. (2012). A typology of dairy farmer perceptions towards climate change. Climatic Change, 112(2), 507–522.Find this resource:

                              Barnes, A. P., Willock, J., Toma, L., & Hall, C. (2011). Utilising a farmer typology to understand farmer behaviour towards water quality management: nitrate vulnerable zones in Scotland. Journal of Environmental Planning and Management, 54(4), 477–494.Find this resource:

                                Bartels, W. L., Furman, C. A., Diehl, D. C., Royce, F. S., Dourte, D. R., Ortiz, B. V., et al. (2013). Warming up to climate change: A participatory approach to engaging with agricultural stakeholders in the Southeast US. Regional Environmental Change, 13(1), 45–55.Find this resource:

                                  Belfiore, E., & Bennett, O. (2008). The social impact of the arts. An intellectual history. London: Palgrave Macmillan.Find this resource:

                                    Below, T. B., Mutabazi, K. D., Kirschke, D., Franke, C., Sieber, S., Siebert, R., et al. (2012). Can farmers’ adaptation to climate change be explained by socio-economic household-level variables?. Global Environmental Change, 22(1), 223–235.Find this resource:

                                      Berkes, F. (2009). Evolution of co-management: Role of knowledge generation, bridging organisations and social learning. Journal of Environmental Management, 90(5), 1692–1702.Find this resource:

                                        Bert, F. E., Satorre, E. H., Toranzo, F. R., & Podestá, G. P. (2006). Climatic information and decision-making in maize crop production systems of the Argentinean Pampas. Agricultural Systems, 88(2–3), 180–204.Find this resource:

                                          Bohnet, I. C., Roberts, B., Harding, E., & Haug, K. J. (2011). A typology of graziers to inform a more targeted approach for developing natural resource management policies and agricultural extension programs. Land Use Policy, 28, 629–637.Find this resource:

                                            Bojovic, D., Bonzanigo, L., Giupponi, C., & Maziotis, A. (2015). Online participation in climate change adaptation: A case study of agricultural adaptation measures in Northern Italy. Journal of Environmental Management, 157, 8–19.Find this resource:

                                              Bright, A. D., & Manfredo, M. J. (1997). The influence of balanced information on attitudes toward natural resource issues. Society and Natural Resources, 10(5), 469–483.Find this resource:

                                                Buys, L., Miller, E., & van Megen, K. (2012). Conceptualising climate change in rural Australia: Community perceptions, attitudes and (in)actions. Regional Environmental Change, 12(1), 237–248.Find this resource:

                                                  CC Group. (2013). How to talk so farmers and landowners listen: A guide to renewable energy communications. CC Group, U.K.Find this resource:

                                                    Chen, H., Wang, J., & Huang, J. (2014). Policy support, social capital, and farmers’ adaptation to drought in China. Global Environmental Change, 24, 193–202.Find this resource:

                                                      Climate Council. (2014). Relevant, immediate, local: Guide to communicating climate change in Australia. Climate Council. Retrieved from this resource:

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                                                                                                                                                                                      (1.) Segments identified in Eggers et al. (2014) are not included in this table as the segments were identified a priori based on earlier literature.