De la caducidad originaria, pura o de pleno derecho

The aim of Chapter 2 was to examine baseline attitudes, priorities, and constraints pertaining to herd reproductive management perceived by farmers in the study, and to explore how these varied with socio-demographic and biophysical factors. The broader aim was to identify predictors of attitudes about reproductive performance. Where predictors of particular attitudes, such as satisfaction with reproductive performance, are associated with biophysical or socio-demographic factor such as farmer age, extension messages can be targeted more specifically. This is potentially important when designing and implementing extension programmes to influence the behaviour of farmers.

This was the first published attempt to formally characterise the attitudes of dairy farmers in New Zealand; consequently, there are no comparative studies. Other attitudinal studies conducted in dairy industries abroad focussed on differing aspects of farmer attitudes, so direct comparison of results is inappropriate (Garforth et al., 2006; Jansen et al., 2009; Kuiper et al., 2005; Rehman et al., 2007).

In the early study design, the social science questionnaire was expected to be an additional component to run alongside the main biophysical study. However, as the study progressed, it began to take a more central position in my understanding of the process behind adoption of practice change. Consequently, the scope of the annual social science questionnaire was augmented and a greater range of data were collected in subsequent years including a series of questions concerning attitudes, beliefs, social norms and perceived control based on the theory of planned behaviour (Ajzen, 1991a). While examining the data from those interviews was outside the scope of this thesis; it is hoped that future analysis of that data will explore the hypothesis that the intention to change management factors to improve reproductive performance is effected by participation in the InCalf programme.

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The questionnaires principally captured quantitative responses from participants. Evident in these quantitative responses was that with increased specificity of questioning, there was greater diversity of response between farmers. For example, where farmers were asked to rate their self-motivation for their job, the majority rated this highly with little variation between KDMs whereas rating specific perceived constraints on their herd reproductive performance had greater variation between KDMs. Ideally, the questionnaires would have captured qualitative answers allowing for greater personal expression and greater specificity from each farmer. Predominantly qualitative interviews were beyond the experience and budget of the study team as they require specialist interview technique and even greater experience to fully interpret the results. Ultimately, a quantitative style was appropriate as the interviews were conducted by veterinary technicians with only rudimentary interview training. The majority of questions were closed-ended (i.e. finite options were given) and most responses were recorded on Likert type scales (1 to 5 where 1 might be very unhappy and 5 might be very happy) which improved the reproducibility of the questions within technician as well as between technicians.

The results highlighted a potential barrier to herd-improvement in that the majority of farmers indicated that they were satisfied with the reproductive performance of their herd. When considered alongside the decline in national average performance over the last 20 years (Harris, 2005), this suggests a disconnection between farmer perception of satisfactory performance and the industry target for performance. This represents a real barrier to the dairy industry achieving targets. A belief exists that there needs to be a ‘tension for change’; that a perception by the decision maker that something is required to change, before any actual change will occur. Currently, national and regional benchmarking of reproductive performance is not available in New Zealand. Promotion of reproductive benchmarks and targets should create tension in some farmers. Although no regional difference was detected in this study, anecdotal evidence would suggest that regional benchmarking would be necessary to account for farmer belief of regional differences.

A second finding that reflects anecdotal experience was the perception of farmers that the non- cycling (including true anoestrus cows) proportion of the herd during mating was the biggest constraint on reproductive performance and oestrus detection had a lower impact. Whereas the non-cycling proportion might be perceived by farmers as inherent in the phenotype of the modern dairy cow and thereby outside their control, oestrus detection is fundamentally a reflection of farmer expertise. To rank oestrus detection as a constraint would be a self-criticism of a farmer’s ability and where oestrus detection is poor, cows not detected in oestrus would be considered in anoestrus. However, this is over-simplistic and both the rate of anoestrus cows and submission rate are interdependent. Despite these rankings, the findings in Chapter 5 indicate that the submission

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rate of mature early calved cows was improved significantly as a result of participation in InCalf. However, despite ranking anoestrus cows as the highest perceived constraint, farmers participating in the Farmer Action Group adopted a less effective approach to anoestrus interventions. This paradox might be explained in two ways: firstly, good oestrus detection practices were positively encouraged during the Farmer Action Group and the immediate benefits of these practices could be measured by an increased submission rate in the first study-year and secondly, the Farmer Action Group facilitated prioritising management factors. Potentially, non-cycling cows might not have been proposed as a high priority and this secondary importance to other management factors may explain the less timely intervention regime. An anecdotal effect of the Farmer Action Group was farmers focussing on the management factors with the greatest gaps in performance, sometimes to the detriment of other factors.

This disconnection between farmer attitude and management practice change is an area for development within the InCalf programme. A British study on adoption of heat detection methods, discussed in Chapter 1, identified ‘not acknowledging farmer expertise’ as a barrier to uptake of novel oestrus detection technology (Garforth et al., 2006). It is reasonable to assume that this opinion would also be valid in New Zealand. Strategies to improve submission rates should not circumvent farmer expertise as the conclusions of the British study suggest this would be a barrier to adoption.

The study also identified biophysical and socio-demographic variables associated with attitudes, priorities and perceived constraints. These chosen variables are commonly used as factors used to differentiate dairy farmers and their farming operation (for example, farmer age or the predominant breed of the herd). Most extension developers and rural professionals (including veterinarians) would have an understanding of these same descriptive variables for their clients.

A targeted development of extension for different farmer age categories was recommended due to the greater proportion of the variability in attitude being explained by age category than other factors. This recommendation was based on the assumption that certain attitudes (such as satisfaction with reproductive performance) correlate with reproductive performance. In Chapter 4, the same biophysical and socio-demographic factors did not predict reproductive performance however. This paradox suggests that biophysical and socio-demographic variables are unlikely to exert a confounding effect on any association between farmer attitude and reproductive performance. There is a need to further examine this relationship. If a significant association exists between one or more attitudes and reproductive performance, a greater advantage would be found if the intermediate step(s) (management factor(s)) were also identified.

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The research in the current study does not create a complete picture of farmer attitudes and beliefs, but provides a starting point for further research. Future questionnaires might increase focus on farm staffing matters and external factors, such as the weather. It was felt that these were not addressed in sufficient detail by the current questionnaires.

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