Analysis of variation in sheep/beef data

4.4.1 PCA analysis of variation

Table 4.24 shows the results of the PCA on the variation of the core variables. PC1 measures variation in profit in terms of both Effective Farm Surplus (EFS) whatever the units and NFPBT/farm. However, the variation in efficiency as measured by EFS/su and FWE/GFR is balanced again the other profit measures indicating that a low variation in efficiency is countered by a high variation in EFS/ha or per farm and NFPBT/farm. PC2 is a measure of the change in efficiency in terms of the change in profit made per stock unit, and the NFPBT/ha and the variation in equity. This makes sense as changing a farm’s equity will be affected by the NFPBT.28 PC3 is a measure of the variation of the soil resource and its association with the lambing%, whereas PC4 is a measure of how the variation in the meat production/ha, seems to be associated with variation in Olsen P. This relationship has also occurred elsewhere, indicating the importance of phosphate fertilisers in pastoral farming. PC5 measures the variation in cropping.

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The cluster analysis using the four PC scores assigned to each farm gave a best solution of five clusters/groups (Table 4.25) – though it did not separate out PC4. Again, it did not give a good scatter of farms across the clusters with one cluster having a majority of farms and another having only one member. It is clear from the Table 4.25 that Cluster 2, the one with only one member, has the most extreme value for PC2. Also, overall there seems to be high positive values for each PC but not very low values. Again, there is one large group into which most farmers fitted.29

The results from the unbalanced anovas for the original core variables, which help to describe the clusters/gropups, are in Table 4.26. What is immediately apparent is that the cluster analysis did not discriminate between the variables carcase weight and equity. This means that the variations in these variables for most of the farms were very similar. Tables 4.26 to 4.33 are used to provide a greater description of each group.

Group 1 – Greatest variability of soil resource and lambing

2A, 5A, 6B, 12C (2 organic, 1 integrated, 1 conventional)

The farmers in this group had the most variable NFPBT (per ha or su) and efficiency in terms of profit/su and lambing percentage, but the lowest variability in the other measure of efficiency, FWE/GFR. This indicates that they manage their expenses in order to maintain this.

Additional variables: This group had the lowest percentage of sheep, indicating that cropping and/or cattle were also important parts of these farms. The farmers in these groups had the highest expenditure on vehicles and fuel, overheads, C & NC labour and the largest increase in fertiliser and weed and pest expenses.

Attitudinal data: Farmers in this group do not find it important to pay attention to FWE/GFR (even though they maintain a consistent level of this measure of efficiency). They find it important to produce a competitive yield/ha and a mix of products from their farms (the latter an indication of resilience). They are the least interested in birds, possibly because three of them are cropping farmers. They have the highest level of agreement about the relationship between farming emissions and climate change and see the importance of planting trees as carbon sinks.

Group 2 –High variability in equity and efficiency

11C (1 conventional)

This farmer had a very high variability in equity and appeared to make have a large variation in efficiency measure per su. However, this can be explained by the addition to his farm of a more extensive property.

Group 3 – lower variability across most variables – the consistent, reliable farmers

7A, 9A, 10A, 11A, 12D, 3B, 4B, 8B, 9B, 10B, 2C, 7C, 8C (5 organic, 5 integrated, 3 conventional)

These farms were the most consistent across all variables except for soil N. However, there is no indication of why this should be so as the application of N does not appear to have changed, or may have even dropped in contrast with Group 1.

Additional variables: Group 3 has the lowest expenses and the least change in fertiliser costs, and the least variability in cash cropping, repairs and maintenance, C and NC labour and feed

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expenses. The farms in this group have the least variation in introduced insectivorous birds. The farmers have also made the least changes in their application of N (however measured), Ca, P and S (measured per su), and hence have the lowest variation in these fertiliser components as well. This indicates that they probably put on the same fertiliser year after year. (Note that five of them are organic so this impacts on the use of chemical fertiliser.)

Attitudinal data: The members of Group 3 place most importance on profits and financial efficiency (FWE/GFR) as financial indicators, but do not place importance of high yields. They are the least concerned about climate change and dispute its relationship to farming, and do not see their practices as having an effect on the global environment. They are the least likely to experiment.

Group 4 – greatest variability in profit

8A, 2B, 9C (1 organic, 1 integrated, 1 conventional)

These three farmers had the greatest variability in their profit as measured by EFS (/ha, su, farm) and NFPBT/farm, and in the measure of efficiency FWE/GFR. They had the lowest profit (NFPBT/ha, su), the least change in equity and the greatest increase in EFS/su and lambing percentage. Two of these farms have experienced great change over the time of ARGOS, with one farm being combined under the management of a relative and another to being managed with the owner leaving farming.

Additional variables: These farmers have made the greatest changes and have the largest variation in their fertiliser applications of Ca, P and S per su. They have the largest variation in C and NC feed, and have made the biggest change in the percentage of sheep on their farms.

Attitudinal data: The change in the bank balance is the most important financial indicator for this group of farmers. They do not think it is important for the farm to have a mix of productive nad non-productive uses, but are the most bird friendly group. They expect to be farming the longest into the future. (However, since filling in this questionnaire, one farmer had put a manager on his farm!)

Group 5 - variability of cropping and profit per su

4A, 11B (1 organic, 1 integrated)

The two farmers in this group appeared to have a low variability in the efficiency of their farming as measured by FWE/GFR but a high variability of the profit per su. This can probably be explained by the way the two of them manage sheep finishing around their cropping enterprise.

Additional variables: The two farmers in Group 5 have the most expenses related to cash cropping and repairs and maintenance. They have the largest variability in repairs and maintenance and C and NC labour expenses. They have made the least changes in the percentage of sheep on their farms.

Attitudinal variables: These farmers place the least importance on profit/loss as a financial indicator and they are the most likely to experiment. They have the highest awareness of the impact of their farming practices on the global environment, though they are not so keen on introduced birds. They are less interested in trees for practical and aesthetic purposes except for growing them to supply logs/timber.

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