The acceptability of climate change in agricultural communities: Comparing responses across variability and change

Journal of Environmental Management 115 (2013) 69e77

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The acceptability of climate change in agricultural communities: Comparing responses across variability and change Christopher M. Raymond a, b, *, John Spoehr c a

Institute for Land, Water and Society, Charles Sturt University, Elizabeth Mitchell Drive, Albury, NSW 2640, Australia Enviroconnect Pty Ltd., PO Box 190, Stirling, SA 5152, Australia c Australian Workplace Innovation and Social Research Centre, The University of Adelaide, Level 2, 230 North Terrace, SA 5005, Australia b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 11 January 2012 Received in revised form 26 August 2012 Accepted 1 November 2012 Available online 12 December 2012

This study examined how the terms used to describe climate change influence landholder acceptability judgements and attitudes toward climate change at the local scale. Telephone surveys were conducted with landholders from viticultural (n ¼ 97) or cereal growing (n ¼ 195) backgrounds in rural South Australia. A variety of descriptive and inferential statistics were used to examine the influence of human-induced climate change and winter/spring drying trend terms on adaptation responses and uncertainties surrounding climate change science. We found that the terms used to describe climate change leads to significant differences in adaptation response and levels of scepticism surrounding climate change in rural populations. For example, those respondents who accepted human induced climate change as a reality were significantly more likely to invest in technologies to sow crops earlier or increase the amount of water stored or harvested on their properties than respondents who accepted the winter/spring drying trend as a reality. The results have implications for the targeting of climate change science messages to both rural landholders and communities of practice involved in climate change adaptation planning and implementation. Ó 2012 Elsevier Ltd. All rights reserved.

Keywords: Social limits Social barriers Adaptation Acceptability Agriculture Farmers Adaptive capacity

1. Introduction Over the past five years, researchers have recognised that the social barriers to climate change adaptation need to be understood alongside ecological, economic and technological limits in order to influence adaptation decisions (Adger et al., 2009; Lorenzoni et al., 2007). Social barriers have been broadly defined as normative, cognitive and institutional. Normative barriers relate to the ways in which cultural ‘norms’ influence responses to climate change, cognitive barriers relate to how psychological and thought processes influence individual attitudes toward climate change, including denial and apathy, and institutional barriers relate to how both formal and informal institutions influence adaptation opportunities (Jones and Boyd, 2011). These social barriers are reflected in public acceptability of climate change science. Lack of acceptability can be attributed to uncertainty and distrust in information sources, and uncertainty and scepticism about the causes of climate change, seriousness, necessity and effectiveness of actions (Lorenzoni et al., 2007), * Corresponding author. Institute for Land, Water and Society, Charles Sturt University, Elizabeth Mitchell Drive, Albury, NSW 2640, Australia. Tel.: þ61 423 299 986. E-mail address: [email protected] (C.M. Raymond). 0301-4797/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jenvman.2012.11.003

active and casual denial which avoid exposure to and dismiss uncomfortable facts, blame-shifting, deliberate apathy and unrealistic/wishful thinking (Stafford-Smith et al., 2011) and lack of experience with a phenomena and its potential consequences (Spence et al., 2011). Gifford (2011) also cites lack of trust in and respect for experts and authorities, perceived risks of change, worldviews that preclude pro-environmental attitudes and lack of knowledge of climate change impacts and adaptation responses as major barriers to acceptability. A parallel literature has focussed on the role of message framing in influencing attitudes toward climate change and adaptation responses. Framing refers to the communication in words, images and phrases for the purposes of relaying information about an issue or event (Chong and Druckman, 2007), in this case climate change issues and events. The current public debate about the existence and influence of human-induced climate change on human wellbeing reflects how different message frames influence individual conceptualisation of an issue (see Gifford and Comeau, 2011; Morton et al., 2011; Spence and Pidgeon, 2010 for recent studies). Climate change issues have been presented in terms of gain frames (e.g., individuals and communities financially benefiting from adaptation responses) and loss frames (e.g., high energy use companies moving off-shore as a result of costs associated with climate policy). Prospect theory (Tversky and Kahneman, 1981)

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proposes that that people are less inclined to take risks when considering gains because the perceived subjective value of gains is fairly low whilst people will take risks to avoid losses because the subjective value of losses are relatively high. In this light, loss frames are more effective in changing behaviours considered risky whilst gain frames are more effective within behaviours considered safe (Banks et al., 1995; Edwards et al., 2001). Outside of the framing literature, researchers are calling for a greater examination of the influence of climate change discourse on policy maker and local actor perceptions of the phenomenon. Recent studies highlight a ‘discursive complexity’ where different researchers and policy actors do not perceive climate change in the same manner because they hold different definitions of the phenomenon. The different definitions are the result of different discourses on climate change and variability which represent different approaches to science and political responses (Demeritt, 2001; Forsyth, 2003). This complexity has been seen post-Kyoto negotiations whereby policy actors have constructed climate change from sustainable development, economic development, migration and national security perspectives (Vlassopoulos, 2012). Multiple understandings of climate change also exist among local actors. Hulme (2008) and Bailey (2008) contend that climate change is not making sense to citizens because we have detached it from its cultural setting and failed to examine how the knowledge claims related to climate science change as they are disseminated from region to another. Climate change understandings are also disrupted by new and contested forms of knowledge, different ascriptions of responsibility, alternative views of scale, new sites for activism (Barr et al., 2011), as well as the culture and values by which individuals and organisations make decisions (Hoffman, 2010). In agriculture, there is growing recognition that adaptive processes are influenced by social phenomena which have effects beyond the farm or climate system (Crane et al., 2011; Marshall, 2010). The recent work on social vulnerability of farming communities indicate that decisions to adapt to climate change are not only influenced by the environmental system but also the cultural and social space in which a landholder is embedded (Nelson et al., 2010a, 2010b). For example, the degree of adaptation increases when landholders have access to local organisations who accept climate change, and have a role in prioritising promising technologies and identifying the cheapest providers of those technologies (Alpizar et al., 2011). These multiple understandings are consistent with the ‘contextual vulnerability’ framework offered by O’Brien et al. (2007). Contextual vulnerability is based on a multidimensional view of climateesociety interactions. Both climate variability and change are considered to occur in the context of political, institutional, economic and social structures and changes. Whilst the contextual basis of climate change framing is important in this framework, we are not aware of any studies which have investigated how the terms used to describe climate change (e.g., ‘human-induced climate change’ or ‘a drying trend’) has on attitudes toward adaptation. These attitudes include the level of importance of the phenomena with respect to other farm risks, the acceptability of the existence of the phenomena and level of concern about the phenomenon. Such research may assist in the development of alternative communication and engagement strategies for encouraging rural landholders to understand the importance of weather and climate patterns which are projected to have dramatic impacts on the structure of agriculture over the coming century. In this study, we examine how the terms used to describe climate phenomena influence landholder acceptability judgements and attitudes toward climate change at the local scale. Specifically, we examine the level of acceptability of human-induced climate change and the winterespring drying trend across grain and grape growers (n ¼ 292) in three sub-regions of rural South Australia, and then compare acceptability judgements across environmental

concerns and current adaptation responses. We then discuss the implications of the results for climate change adaptation policy. First, we provide a history of climate variability in South Australia in order to elucidate the challenges facing farmers in this state. 1.1. Climate variability in South Australia Over the last 100 years, South Australia has not been immune from climate variability, including successive years of below annual average rainfall or drought. Since accurate records have been kept, South Australia has experienced several severe droughts which affected the River Murray in South Australia in the following years: 1884e86, 1895e98, 1901e03, 1911e15, 1927e29, 1943e46, 1959, 1961, 1967, 1976e77, 1982e83, 2005e09 (Bureau of Meteorology, 2012). The 1895e1903 drought period was one of Australia’s worst droughts on record, in terms of both its severity and area. Stock and crop losses were the highest in Australian history. Early records in 1895 indicate that large areas of the pastoral country in South Australia were in a bad state. Thomas Pearse, a South Australian pastoralist, personalised their desperation in a letter to the Burra Record in May 1898: While I am writing this the dust is blowing in clouds; no lambing for the last three years, and a bad prospect for one this year; high rents, and wild dogs galore; three parts of this country blown further east. It will take three good seasons for the country in question to be of [the] same value as it was before the drought set in (cited in Garden, 2010 p. 276). The most recent drought in South Australia was between 2006 and 2009. From 1 March 2006 to 29 February 2008 the state received 50% of its long-term (1961e1990) mean annual rainfall. The Flinders Ranges, in the mid-north of South Australia, recorded rainfall in the lowest 5e10% of long-term observations for the period from 1 February 2006 to 30 June 2009 (Bureau of Meteorology, 2008). The pressure of drought in arid and semiarid parts of Australia has been predicted to increase over the next few decades (Hennessy et al., 2008; McMullen, 2009). Both Australian and South Australian governments now acknowledge that drought is part of the natural variability of the Australian climate, with drought relief for farmers and agricultural communities being restricted to times of so-called ‘exceptional circumstances’. In other words, the agricultural sector is expected to cope with the occasional drought, and relief would be available only for droughts of unusual length or severity, such as the South Australian Government’s phased approach to drought delivery and support between 2006 and 2008, with in excess of $80 million of drought response implemented (Government of South Australia, 2008). Recent research suggests that there is a general acceptance of drought and climate variability in South Australia. In a study of communities in the northern Flinders Ranges, Pearce et al. (2010) found that local landholders were generally ‘accepting’ of the drought, having survived worse droughts in the past and over many years. They were therefore of the sentiment that they would cope with future droughts. Despite the sentiments of acceptance, the continued lack of rainfall was leading to growing concerns for the future. Their research, like the work of others (e.g., Lorenzoni et al., 2007), emphasises the need for policies to integrate societal perspective of climate change within the policy process. 2. Methods 2.1. Study areas The Mid-North region covers an area of 2.7 million ha, which includes the coastal plain, the southern part of the Flinders Ranges,

C.M. Raymond, J. Spoehr / Journal of Environmental Management 115 (2013) 69e77

and the northern part of the Mount Lofty Ranges (Fig. 1) and eight district council areas of Clare and Gilbert Valleys, Goyder, Mount Remarkable, Northern Areas, Orroroo/Carrieton, Peterborough, Port Pirie and Wakefield. It has a moderate-dry and cool climate (annual rainfall 250e500 mm) and predominantly winter rainfall. The

71

region is sparsely populated, with approximately 48,600 persons. Approximately 41% of males and 42% of females are over 50 years of age (ABS, 2010). Proportionately more of the land in the Mid-north region is used for primary production compared with the Fleurieu region

Fig. 1. The three study areas, namely the Fleurieu, Mid-North and Riverland areas.

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(92% vs. 70%). Agriculture comprises 62.5% of the region and livestock 29.7%. A smaller proportion of the region is used for residential (3.7%) and conservation (1.6%) than the Fleurieu region (21% and 6%, respectively). A total of 13 individual conservation and recreation parks and reserves are encompassed by the study boundary. Native vegetation covers approximately 1.1 million ha or 41% of the region, but much of this is semi-arid to arid native vegetation found on private land in the north of the region. The Riverland region covers an area of 1.2 million ha, which includes the River Murray Floodplain from Morgan to the SAVictoria border and the district council areas of Berri Barmera, Loxton/Waikerie and Renmark/Paringa. A small proportion of MidMurray council area also exists in the Riverland region, but for aggregation purposes, we chose to omit it from our analyses. The region has a population of approximately 41,300, with 36% of males and 38% of females in the region over 50 years of age (ABS, 2010). The Riverland climate can be described as warm to temperate, much of the land around it is semi arid country. Consequently, the region is prone to hot spells in summer and winters tend to be mild. Like the Mid-North region, primary production is the dominant land use in the region (89%). Agriculture comprises 61% of the region and livestock 21%. The Riverland is Australia’s largest wine producing region, accounting for over one quarter of the national grape crush (Wine Australia, 2011). Conservation land use covers 6% of the region or 18 individual conservation and recreation parks and reserves. The total area with native vegetation is 470,000 ha or 40% of the region. 2.2. Sample We used a stratified random sampling strategy to select 300 rural landholders to be involved in the study. We firstly divided the state of South Australia into a NortheSouth Transect from Hawker through to Goolwa and an EasteWest transect from the South Australian border to Wallaroo. Three geographical areas were then selected along the transect; namely the Fleurieu Peninsula, MidNorth and Riverland areas. The Fleurieu Peninsula included the townships of Victor Harbor, Goolwa, Langhorne Creek, Yankalilla and Strathalbyn; the Riverland area included the townships of Renmark, Berri and Barmera, and; the Mid-North area included the townships of Hawker, Jamestown, Clare and Eudunda. Within each geographical area, we stratified the sample frame into two dominant land uses of viticulture and grains. We generated the cereal growing land-use by identifying those landholders who owned >10 ha of land and used >50% of their land for cereal production. We generated the grain growing land-use by identifying those landholders who owned >10 ha of land and used >50% of their land for viticulture. The initial sampling goal was to obtain 100 participants from each of the three regions, and 50 participants from each land use in each region. However, sampling revealed only 20 grape growers in the Mid-North region and 26 grape growers in the Fleurieu region. We therefore decided to conduct a census of these grape growers and randomly sample an additional 30 grain growers in the midNorth and 24 grain growers in the Fleurieu in order to ensure sufficient numbers for statistical analyses. The grains industry sector is the highest contributing sector in the South Australian food industry. In 2005/06, the sector made up 28% (or $2.8 billion) of the Gross State Food Revenue of $10.1 billon. In addition to the food revenue, the sector also provides an important feed (grain and fodder) input to the livestock industry worth an additional $0.6 billion. In total, this values the food and feed grain industry sectors at $3.4 billion (PIRSA, 2011). Climate variability has influenced the grains industry in South Australia in recent years. In 2008e2009, a high proportion of grain farmers in

South Australia reported adverse seasonal conditions (Crooks and Levantis, 2009). However, overall total winter grain production increased by approximately 15% in 2009e2010. A comparison of time periods shows a slowdown in productivity growth in the grains industry. Many factors could explain this decline, with two major influences likely to be extended poor seasonal conditions and a long-term slowdown in growth in public research and development investment (Sheng et al., 2008). In 2008e2009, SA’s gross wine revenue totalled $2.15 billion, 73% of which was generated through wine exports (Government of South Australia, 2010). Recently, there has been a major structural imbalance in the wine industry. James and Liddicoat (2008) engaged experts in an assessment of the threats and opportunities posed by climate change to the viticultural industry in the McLaren Vale region. The main issues identified for the McLaren Vale region’s viticulture industry was the potential emergence of soil salinity and water insecurity. There were additional concerns that industry-wide salinity flushing practices (i.e. excess irrigation water applied to leach accumulated salts) may cause watertables to rise, and potential salinity impacts to soil and groundwater may be a risk to the industry’s branding. Further high risks were associated with potential heat impacts causing yield and quality problems, and increased cost pressures on viticultural businesses. 2.3. Survey A survey was administered via computer-assisted telephone interview (CATI) to 292 landholders in August 2011. In total, 66.8% of respondents were from grain producing backgrounds and 33.2% of respondents were from grape growing backgrounds. Proportionately more respondents were from grain growing than grape growing backgrounds in the Mid-North (85.1% vs. 14.9%) and Fleurieu regions (61.2% vs. 38.8%). No proportional differences exist between grain and grape growers in the Riverland region (44.0% vs. 56.0%). The survey instrument was divided into eight parts as follows: 1. 2. 3. 4. 5. 6. 7.

Property characteristics; Challenges on the property; Attitudes toward human-induced climate change; Managing human-induced climate change; Attitudes toward the winter/spring drying trend; Managing the projected winter/spring drying trend; Reasons for scepticism about human-induced change, and; 8. Socio-demographics

climate

The survey was structured so as to enable three types of responses: 1) Responses from landholders who accept human-induced climate change is a reality; 2) Responses from landholders who reject human-induced climate change but accept the parallel concept of the projected winter/spring drying trend, and; 3) Responses from landholders who are sceptical about both human-induced climate change and the projected wintere spring drying trend. Participants only responded to one of the above categories. 2.4. Analysis We used cross-tabulations with a Chi-square statistic to examine proportional differences in acceptability of human-induced climate change and the winterespring drying trend across categorical

C.M. Raymond, J. Spoehr / Journal of Environmental Management 115 (2013) 69e77

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Table 1 Influence of socio-demographic characteristics on acceptance of climate change and the winter/spring drying trend. Respondent variable

Gender

Highest level of education

Proportion of family income earned off-farm in 2010e11

Proportion of family income earned off-farm in 2009e10

Farm income in 2009e10

Categories

Male Female Total Primary school or high school TAFE course University or postgraduate degree Total 0% 1e50% 50e99% 100% Total 0% 1e50% 50e99% 100% Total 0 <$50,000 $51,000e100,000 $101,000e200,000 $201,000e500,000 >$500,000 Do not know or refused Total

n

Believe in HI climate change? Yes %

No %

Unsure %

217 73 290 168

74.3 25.7 100.0 54.1

74.7 25.3 100.0 65.9

75.6 24.4 100.0 63.2

49 61

18.0 27.9

17.6 16.5

17.1 19.7

278 96 124 22 29 271 86 106 24 23 239 31 53 51 38 31 45 41 290

1.0 32.7 52.9 4.8 15.9 1.0 32.2 51.1 7.8 8.9 100.0 6.2 18.6 20.4 16.8 9.7 18.6 9.7 100.0

1.0 37.5 35.2 11.4 6.3 1.0 38.8 33.8 13.8 13.8 100.0 20.0 14.7 13.7 8.4 8.4 13.7 21.1 100.0

1.0 36.7 48.1 8.9 6.3 1.0 37.7 47.8 8.7 5.8 100.0 6.1 22.0 18.3 13.4 14.6 13.4 12.2 100.0

X2

p

0.042

4.54

0.338

10.10

0.120

7.91

0.244

24.70

0.016

n

Believe in winter/spring drying?

0.979 44 177 65

62 69 17 19 167 57 60 17 15 149 24 32 28 19 20 24 30 177

Yes %

No %

69.0 31.0 100.0 65.0

77.0 23.0 100.0 64.6

12.5 22.5

18.9 16.5

100.0 31.7 56.1 2.4 9.8 100.0 37.1 54.3 5.7 2.9 100.0 9.5 26.2 19.0 14.3 9.5 11.9 9.5 100.0

100.0 38.9 36.5 12.7 11.9 100.0 38.6 36.0 13.2 12.3 100.0 14.8 15.6 14.8 9.6 11.9 14.1 19.3 100.0

X2

p

1.10

0.295

1.32

0.517

6.63

0.085

5.91

0.116

5.73

0.454

Bolded numbers indicate significant proportional differences (p < 0.05).

variables such as gender, level of education, and farm income. We used independent samples t-test to examine mean differences in level of skepticism about climate change and adaptation response. 3. Results 3.1. Socio-demographic factors, farm characteristics and climate change acceptability We examined proportional differences in acceptance of climate change across the socio-demographic variables of gender, level of forma education, off-farm income earned in each of 2010e11 and 2009e10 and farm income earned in 2009e10 (Table 1). Proportionately more respondents who had earned no farm income in 2009e2010 financial year rejected rather than accepted human induced climate change (20.0 vs. 6.2%), whereas proportionally more respondents who had earned greater than $500,000 that financial year accepted rather than rejected the phenomenon (18.6% vs. 13.7%). No proportional differences in gender, level of education and off-farm income were identified for both acceptance of climate change and the warming/drying trend. We also examined mean differences in property characteristics by acceptance of climate change or the warming/drying trend. There were no proportional differences in acceptance of climate change or the warming drying trend by dominant land uses of grain and grapes or sub-region of residence (p > 0.05). However, those grape growers who owned larger areas of land for grape production were more likely to accept than reject climate change (t (156) ¼ 2.00, p ¼ 0.04). Further, farming families who had owned their property for a shorter period of time (mean ¼ 64.91 years) were significantly more likely to accept climate change than those farming families who had owned their property for a longer period of time (mean ¼ 81.95 years) (t (156) ¼ 2.37, p ¼ 0.019).

3.2. Comparing acceptability of climate change and the winter/spring drying trend A diversity of views were found with respect to the existence of climate change across the sampled areas. Equal proportions of respondents accepted, rejected or were unsure about whether human-induced climate change exists. However, those respondents who rejected or were unsure about human-induced climate change were more likely to reject the concept of a projected winter/spring drying trend than accept it (Table 2). No proportional differences in the level of acceptance of climate change exist across dominant land-uses of grains and grape. 3.3. Reasons for scepticism about human-induced climate change We asked those survey participants who rejected the concepts of both human-induced climate change and the winter/spring drying trend to respond to a series of statements about different views on human-induced climate change. We then compared responses across those respondents who accepted and those Table 2 Cross-tabulation of acceptance of climate variability and change and dominant land-use.

Does human-induced climate change exist? If no or unsure, do you believe that there will be less rainfall in winter and spring in the long-term?

Yes No Unsure Total Yes No Total

n

Grains %

Grape %

X2

p

115 95 82 292 42 135 177

38.9 31.7 29.2 100.0 26.1 73.9 100.0

40.2 34.0 25.7 100.0 19.0 81.0 100.0

0.40

0.819

0.32

0.819

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Table 3 Mean differences in attitudes toward human-induced climate change.

It is climate variability rather than human induced climate change Human induced climate change models are unreliable Climate change scientists are alarmist Animals and plants can adapt to human induced climate change There is no consensus on human induced climate change science There’s no evidence to support human induced climate change We need to keep global warming below 2  C Carbon dioxide in the atmosphere was higher in the past I am concerned about the impact of human induced climate change on future generations Human induced climate change has the potential to seriously damage farming The earth is cooling, rather than warming

N

Accepted HI climate change

Unsure about HI climate change

t

p

Rank

138 127 126 121 124 121 109 91 125 127 102

4.24 4.15 4.03 3.75 3.53 3.51 3.00 3.27 2.59 2.66 2.89

4.10 3.72 3.63 3.67 3.38 3.09 3.74 3.11 3.61 3.24 2.88

0.94 2.52 2.23 0.46 0.72 2.16 3.77 0.77 5.87 2.98 0.07

0.351 0.013 0.027 0.646 0.471 0.032 0.000 0.444 0.000 0.003 0.948

1 2 3 4 5 6 7 8 9 20 11

Note: bolded numbers reflect significant mean differences (p < 0.05). Scores reflect mean differences on a scale where “1 ¼ Strongly Disagree” and “5 ¼ Strongly Agree”.

respondents who were unsure about human-induced climate change (Table 3). Compared with those respondents who were unsure about human-induced climate change, respondents who rejected the phenomenon held significantly stronger beliefs that climate change models are unreliable, climate change scientists are alarmist, and there is no evidence to support human induced climate change (t > 2.15, p < 0.05). Conversely, those respondents who were unsure about human induced climate change were more concerned about the impact of human induced climate change on future generations and were more likely to believe that human induced climate change has the potential to seriously damage farming (t > 2.98, p < 0.001). Respondents who accepted and were unsure about humaninduced climate change also shared similar views in a number of areas. Both groups agreed that climate change is related to climate variability rather than human-induced climate change, animals and plants can adapt to human-induced climate change and that there is no consensus on climate change science. There was uncertainty across both groups that carbon dioxide in the atmosphere was higher in the past and disagreement across both groups that the earth is cooling rather than warming. 3.4. Differences among acceptability and response We examined mean differences in on-farm responses to climate phenomena based upon level of acceptability of climate change and the winterespring drying trend (Table 4). On average, respondents who accepted human induced climate change or the winter/spring drying trend noted that they had invested a fair amount in the use

of cover crops to improve soil structure and water penetration, technologies to control summer weeds and assess the moisture holding capacity of the soil. However, uptake of some technologies varied according to the level of acceptance of climate change. Those respondents who accepted human-induced climate change had invested significantly more in technologies to sow crops earlier than those respondents who rejected climate change, but accepted the winterespring drying trend, F(2, 59) ¼ 5.04, p ¼ 0.010. Those respondents who accepted human induced climate change had also invested significantly more in technologies to increase the capacity to harvest or store water than those respondents who were unsure or did not believe in human induced climate change, F(2, 77) ¼ 4.55, p ¼ 0.014; however, those respondents who rejected the humaninduced climate change but accepted the winter/spring drying trend were more likely to invest in technologies to lower seeding rates, F(2, 53) ¼ 5.38, p ¼ 0.007. 3.5. Capacity factors which influence adaptive response Finally, we examined different elements of capacity which may influence investment in technologies to increase capacity to harvest or store water (Table 5). We chose this adaptation measure because we found significant differences in level of response across landholders who believe, are unsure or don’t believe in human induced climate change (see Table 4). Survey participants were asked to rate the extent to which a variety of financial, physical, natural and social capital factors would be affected by human-induced climate change on a “1 ¼ not at all” through to “4 ¼ a great deal” scale. Linear regression analyses revealed that risks to social capital factors of

Table 4 Differences in adaptive responses to climate phenomenon among landholders who believe, are unsure or don’t believe in human induced climate change.

Used cover crops to improve soil structure and water penetration Paid greater attention to summer weed control Assessed the moisture holding capacity of the soil Minimised water loss through the use of mulches Monitored salinity build up in the soil profile Sowed crops earlier Used salinity flushing irrigation applications Delayed nitrogen fertilizer application Significantly increased your capacity to harvest or store water Used global positioning system technologies to improve crop management Trialled earlier maturing varieties of crop Trialled low water use varieties of crop Practiced inter row sowing Used a disc seeder Used lower seeding rates

Accept HI CC

Unsure about HI CC, believe in drying

Reject HI CC, believe in drying

df

3.29 3.21 3.06 3.03 3.03 2.76a 2.75 2.71 2.62a 2.58 2.35 2.25 2.00 1.80 1.60a

2.75 3.31 3.25 2.50 3.00 2.00ab 3.00 2.22 1.82b 2.54 2.08 1.77 1.33 1.00 1.00ac

2.20 3.00 2.20 2.00 2.60 1.63b 3.00 2.83 1.82b 2.36 2.25 1.92 2.71 1.57 2.50b

2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,

Note: different lettered superscripts reflect significant differences, based upon Bonferroni post-hoc analyses; ns ¼ not significant (p > 0.05).

F 37 92 39 39 39 59 38 54 77 88 90 90 55 57 53

5.04

4.55

5.38

p

Rank

ns ns ns ns ns 0.010 ns ns 0.014 ns ns ns ns ns 0.007

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

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Table 5 Factors which influence rural landholders to invest in technologies to increase their capacity to harvest or store water.

Your ability to diversify your on farm income (F) The amount of time you invest in natural resource management activities (S) The operation of your property machinery (P) The quantity of water for primary production (N) Your level of trust in advice provided by natural resource management agencies (S) Your ability to conserve natural resources (N) The life of your property machinery (P) Your source of support in time of crisis (S) R2 0.54

b

t

p

0.29 0.25 0.53 0.19 0.39 0.46 0.22 0.46

1.87 1.63 2.81 1.48 2.85 2.64 1.24 2.51

0.069 0.111 0.008 0.148 0.007 0.012 0.222 0.017

Adj. R2

F

df

p

0.44

5.57

8.00

0.000

DV: Significantly increased your capacity to harvest or store water; bolded numbers reflect significant predictors (p < 0.05).

level of trust in advice provided by natural resource management and source of support in time of crisis were significant predictors of the level of investment in technologies to increase capacity to harvest or store water (b > 0.39, p < 0.05). Risks posed by climate change to the operation of property machinery (a physical capital) and ability to conserve natural resources (a natural capital) were additional predictors of investment in technologies to increase capacity to harvest or store water (b > 0.46, p < 0.05). 4. Discussion The aim of this study was to examine how the framing of different climate change terms influences social acceptance and adaptation responses at the local scale. We found different levels of acceptance of climate change terms among grain and grape growers in rural South Australia. One third of the sample accepted climate change, one third was unsure but accepted the concept of a winter/spring drying trend, and one third of the sample rejected both human-induced climate change and the winter spring drying trend. We add to existing literature on message framing by highlighting that the terms used to define climatic events have a significant influence on self-reported adaptation responses, not solely whether they are defined as gain or loss frames as proposed by other authors (Gifford and Comeau, 2011; Morton et al., 2011; Spence and Pidgeon, 2010). Those landholders who accepted human-induced climate change had invested more effort into adaptation technologies to mitigate risk than those landholders who rejected or were unsure about human-induced climate change. One possible reason for this relationship is that rural landholders in Australia believe that climate change will have an adverse affect on their farming enterprise, whereas a wintere spring drying trend is perceived to be natural variability in a system and thus of lower impact. This view concurs with prospect theory: individuals are more likely to take action to avoid losses because the subjective value of losses is relatively high (Tversky and Kahneman, 1981). An alternative reason is that those landholders who rejected human-induced climate change had low farm incomes between 2009 and 2011 and therefore had less capacity to invest in changes. This is particularly relevant for grape growers in the Riverland region who experienced substantial reductions in water allocations during the 2009e10 financial year, leading to the generation of little or no on-farm profits during that period. The different levels of acceptance of climate change and the winter/spring drying trend presents challenges to environmental management agencies seeking to administer adaptation programs. Climate change reflects a socio-ecological conflict between the acceptance of one set of ecological knowledges and rejection or

contextualisation of other knowledges (Barr et al., 2011). A key question that arises is how do we target our communication and community engagement strategies to those who accept or reject the concept of climate change? The following implications section addresses this question with respect to the results of this study. 4.1. Implications for environmental management We question whether the current approach to prioritising and implementing climate change adaptation programs is effective given the divergent levels of acceptance of climate change. In Australia, climate change priorities are largely set by federal or state governments who then establish adaptation frameworks and investment plans largely in isolation of those responsible for implementing adaptation responses. For example, the Federal Government established the National Climate Change Adaptation Research Facility (NCCARF) which is led by Griffith University, Queensland. NCCARF distributes funding to universities and project partners around Australia who have an interest and demonstrated capability in climate change adaptation research. The assumption is that all project stakeholders accept that humaninduced climate change is a reality and that regional communities “must adapt”. However, the findings of this study suggest that such an approach is only likely to engage one third of the rural or regional population in Australia, i.e., those landholders who accept human-induced climate change is a reality. It is therefore important to tailor climate change communications to different audiences (concurring with Poortinga et al., 2011), including those landholders who accept, reject or are unsure about human-induced climate change. Framing technologies with respect to the management of everyday farm risks is one approach to tailoring communications. This approach is likely to engage landholders who reject human-induced climate change, but accept the winterespring drying trend. We found that a high proportion of respondents engaged in activities to manage on-farm risks, even though they did not accept the concept of human-induced climate change. Other studies also support the need to reframe climate change in order to address conflict among individuals who have different understandings and levels of acceptance of the phenomenon. Nisbet (2009) outlines that climate change conflicts in the United States is in part driven by the different ways in which trusted sources have framed the nature and implications of climate change for Republicans and Democrats over the past decade. Democrat leaders such as President Obama have invoked a public accountability frame (i.e., listening to what scientists have to say) and an increasing majority of Republicans have questioned the validity of climate science and have dismissed the problem. To increase public engagement in climate change, Nisbet suggests moving to

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a unifying interpretation frame of climate change adaptation not only involving science, but also which has health implications for citizens and embraces moral and ethical concerns. A unifying interpretation frame has also been referred to as ‘dormant broker categories’ (e.g., technology and national security) whereby there is a level of acceptance for the categories across groups experiencing conflict (Hoffman, 2011). Changing the terms used to communicate climate change is needed to effectively engage rural landholders in climate change adaptation. The results of this study suggest that rural landholders may be more receptive of presenting climate change in terms of climate variability, including the increasing incidences and severity of dry spells. Recent planning documents designed to engage rural landholders in climate change in South Australia do not reflect these terms. For example, the South Australian Government has invited rural landholders to be involved in undertaking ‘integrated climate change vulnerability assessments’ (Balston and Associates, 2012) despite the findings of this study showing that there is little consensus in rural communities about the meaning of the climate change term and its likely impact on the farm enterprise. A more beneficial approach may be to assess the multiple ways in which rural farming communities are already managing property risks (their capacity strengths), such as significant investments the development of new crop varieties to manage shorter growing seasons, and then identify ways to improve the efficiency and effectiveness of such investments across multiple farming regions. Environmental management bodies also need to consider how they can develop communication aids, policies and programs which support individual landholders to holistically manage property risks. One possible model is for agencies to support communities of practice, including farm systems groups in rural areas of Australia, which are actively trialling new crops and technologies to address a warming drying trend. Raymond and Robinson (in press) found that these groups present their technologies with respect to the management of water availability, pest, plant and soil structure risks. Support may entail the provision of direct or in-kind assistance to communities of practice, in addition to the provision of the latest research and development findings and the support of knowledge exchange programs such as field days, workshops and newsletters. Whilst these approaches may be more effective in engaging rural landholders in adaptation, it is still questionable whether they will lead to incremental or transformational adaptation, or simply maladaptation. Adger and Barnett (2009) suggest that there is widespread existing maladaptation in rural agriculture and encourage decision makers to adjust the practices and decisionmaking frameworks to account for these realities. Selecting ‘noregret’ strategies that yield benefits even in absence of climate change; favouring reversible and flexible options, buying safety margins in investments, promoting soft adaptation strategies and reducing decision time horizons. The results of our study support this conclusion. Many respondents chose to adopt soft adaptation strategies, such as increasing capacity to harvest or store water, leading to incremental changes in adaptation. Further, those landholders who accepted human-induced climate change as a reality invested in these adaptation strategies significantly more than those landholders who were unsure about climate change or did not accept it. Hence, environmental managers need to continue to support landholders who accept climate change with their adaptation efforts, but also target engagement efforts at those who are unsure or reject climate change, but accept the need to adopt strategies even in the absence of climate change. One approach is to invest in the social predictors of adaptation; for example, threats to sources of support during time of crisis, trust in advice provided

by government agencies and the operation of farm machinery, which were significant predictors of investment in building water capacity. The longer-term challenge is to encourage transformational decisions in adaptation which change variables that control a systems functioning (Stafford-Smith et al., 2011), rather than just encourage management of the status-quo. Focusing on adaptation as a continual incremental process of adjustment is useful for decision-makers but it does not help cope with larger climate changes, such as an increase in global temperatures of 4  C. Coping with such temperature rises require deep structural changes such as shifting out of farming to another land-use, which may be unpalatable to rural landholders who currently reject or are unsure about the existence of climate change. Factors which influence these deep structural changes were not considered in this study, although we agree with Alpizar et al. (2011) that local organisations which prioritise promising technologies and identify the cheapest providers of those technologies will have an important role in supporting such transformational change. Future research should consider how organisations, including farm system groups, could be used as agents to support transformational decisions in farming. 5. Conclusion This study examined how the terms used to describe climate change terms influences social acceptance and adaptation responses in rural South Australia Describing the phenomenon as “humaninduced change” or a “winterespring drying trend” influences both acceptance and adaptation response. One third of the rural landholder sample accepted change, one third was unsure but accepted the winterespring drying trend and one-third rejected both humaninduced climate change and the winterespring drying trend. Those respondents who accepted human-induced climate change had invested significantly more responses in some adaptation responses than those who rejected the phenomenon, including increasing water capacity on their farms and sowing crops earlier. Current policies and programs to support adaptation to climate change in the rural agricultural sector are often led by federal or government bodies and research institutions. However, we suggest that much greater effort needs to be devoted to exploring the different levels of acceptance of climate change in rural communities, as well as the development of new models of engagement for supporting the management of on-farm risks, not solely climate change risks. Engagement programs need to be tailored at landholders based upon their level of acceptance of the terms used to describe climate change. Programs must also be channelled through trusted and respected communities of practice which operate at the local and regional scale. Acknowledgements This project was funded by the Premiers Science and Research Fund, Government of South Australia. We acknowledge the valuable support provided by Truscott Research in administering the telephone survey. References ABS, 2010. National Regional Profile: Riverland (Statistical Local Area). Accessed Online: http://abs.gov.au/AUSSTATS/[email protected]/781eb7868cee03e9ca2571800082 bece/aa3752163c7d34e6ca257713001812ab!OpenDocument. Adger, W.N., Barnett, J., 2009. Four reasons for concern about adaptation to climate change. Environment and Planning A 41, 2800e2805. Adger, W.N., Dessai, S., Goulden, M., Hulme, M., Lorenzoni, I., Nelson, D.R., Naess, L.O., Wolf, J., Wreford, A., 2009. Are there social limits to adaptation to climate change? Climatic Change 93, 335e354.

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