What, when, where, who

Still today little is known about the actual components of conservation attitudes among farmers (Winter et al. 2005, p. 384). Moreover, situational variables commonly found in environmental social psychology literature have shown contradictory results (e.g. income) in sample of farmers, whereas other situational variables, while showing promising results (e.g., direct experience with nature), have seldomly been used in such samples (chapter 4). Such gaps in rural environmental social psychology called for an exploratory study on a large sample, and a postal survey emerged as the best research method to reach as many farmers as possible (Giddens 1997, p. 543-5). One of the great advantages of postal survey resides in allowing people to take part to the survey at their convenience (Bourque and Fielder 2003, p.12), which was particularly relevant for my target population. Furthermore, an anonymous postal survey may appear less frightening to respondents than face-to-face or phone interviews, thus, eliciting more honest answers from respondents, especially about sensitive topics (Bourque and Fielder 2003, p.14). Internet surveys were not considered because, although New Zealand farmers can have access to internet, I was not sure of the familiarity they had with the tool and the frequency at which they used it.

Chapter 5: Research design

b. Timeline

The questionnaire on which this research is based was designed during the austral winter of 2004 and was tested on a sample of 12 experts (academics in ecology and agricultural sciences, and farmers) between the end of October and early November 2004. The pre-test survey led to some amendments of the questionnaire. By March 2005, a questionnaire of 18 pages and 82 questions was sent by post to 17991farmers of two regions in the lower part of the North Island of New Zealand: the Manawatu- Wanganui and Wellington regions (Figures 5.1 and 5.2). This was followed by reminders sent in April (a letter only) and May (a letter with an additional copy of the questionnaire) 2005 to non-respondents.

1_{It was originally planned to send 1800 questionnaires but a mishap during the printing of the survey led}

Chapter 5: Research design

Chapter 5: Research design

Figure 5. 2 Map of the Wellington region

c. Sampling

Farmers’ contact details and information about their farms were obtained from a near-exhaustive survey conducted by AgriQuality six years prior to the present study. A random stratified sample was used: at least 25% of farmers in each of the main regional farm types, with and without native forest on their property and within the Manawatu- Wanganui and Wellington regions were randomly chosen from the AgriQuality database2_{. The three predominant farm types in the two regions and the country in terms}

Chapter 5: Research design

of land area and exports are meat (beef, sheep, beef and sheep, and to a lesser extent deer), dairy, and horticulture (Statistics New Zealand 2003a, Tables 2.03, 3.03; Richardson et al. 2004, p. 34). Because dairy and horticulture farming categories contained few candidates, they were oversampled to ensure they had sufficient statistical power compared to the more numerous category, meat farmers. Additionally, information about organic farmers was hard to obtain in the two regions: only 44 organic farmers were identified in total.3_{As their numbers were low, all organic farmers}

were included in the sample irrespective of their farming categories, whether or not they had native forest on their property, or the region their farm was based.

d. Response rate

After discarding the people wrongly targeted (wrong addresses, people who were no longer farming, and doubled-up questionnaires4), 859 valid completed questionnaires were received. This brought the total response rate to 53.7% of the active and contactable targeted farming community, which is a very satisfactory response rate for a farmer survey. Surveys of farmers can get as low as 12% response rate (Gamble et al. 2000 in Fairweather and Campbell 2003) and commonly get around 30%-40% response rate (Rhodes et al. 2002, p. 673; Fairweather and Campbell 2003; Winter 2005; Michel-Guillou and Moser 2006). Furthermore, Fairweather and Campbell (2003) have noted a decline in response rates to New Zealand farm surveys since the late 1970s – in line with an international trend (Rogelberg et al. 2001).

e. Sample used for the thesis

Out of the 859 valid questionnaires received, 806 were selected for the present research. In order to minimize inconsistency between respondents’ attitudes and behaviour toward native forest on farms, the study was directed at the person in charge of the farm management decisions, which was specified in the cover letter as well as in the questionnaire instructions. Nevertheless, to further ensure that the person in charge of farm decisions was targeted, the power the respondent had over the farm

3_{Thanks to the Wellington and Manawatu-Wanganui Regional Councils.}

4_{Farmers rather than farms were targeted, that is, although one farmer may own several farms, only one}

Chapter 5: Research design

management decisions was assessed via a five-point Likert-scale-like question. Respondents who had chosen the upper part of the scale5_{were selected, amounting to a}

total of 806 farmers.

Based on the farring population size in each region of study, 546 questionnaires were sent to farmers from the Wellington region and 1210 to farmers from the Manawatu-Wanganui region.6_{There was no difference in proportions of questionnaires}

sent back from each region (_2_{= 0.364, df = 1, p = 0.546). However, compared to the} number of questionnaires sent to farmers with and without native forest, the proportions of respondents with and without native forest showed that the sample was biased towards farmers with native forest on their property in both regions and all farm types (Table 5.1). This bias may be due to the topic of the questionnaire. Although it was emphasized that the survey was aimed at farmers with andwithoutnative forest, farmers with native forest may have felt more comfortable or impelled to answer the survey than farmers without native forest.

Table 5. 1 Number of questionnaires per farm region, with and without native forest and per farm type that constitutes the analysis sample (N = 806).

Farm types _{With Forest}Wellington_{No Forest With Forest}Manawatu-Wanganui_{No Forest With Forest}Missing region_{No Forest}

Meat 115 43 246 128 0 3

Dairy 20 13 48 46 0 0

Horticulture 7 7 2 12 1 1

Missing farm type 19 8 57 28 0 2

2. Characteristics and representativeness of the sample