A method for assessing the relative sociability of individuals within groups: an example with grazing sheep

Applied Animal Behaviour Science 91 (2005) 57–73 www.elsevier.com/locate/applanim

A method for assessing the relative sociability of individuals within groups: an example with grazing sheep A.M. Sibbalda,*, D.A. Elstonb, D.J.F. Smithc, H.W. Erharda b

a Macaulay Institute, Craigiebuckler, Aberdeen AB15 8QH, UK Biomathematics and Statistics Scotland, Craigiebuckler, Aberdeen AB15 8QH, UK c Institute of Ecology and Resource Management, School of Agriculture, West Mains Road, Edinburgh EH9 3JG, UK

Accepted 8 September 2004 Available online 27 October 2004

Abstract We describe a method for quantifying relative sociability within a group of animals, which is defined as the tendency to be close to others within the group and based on the identification of nearest neighbours. The method is suitable for groups of animals in which all individuals are visible and identifiable and has application as a tool in other areas of behavioural research. A sociability index (SI) is calculated, which is equivalent to the relative proportion of time that an individual spends as the nearest neighbour of other animals in the group and is scaled to have an expectation of 1.0 under the null hypothesis of random mixing. Associated pairs, which are animals seen as nearest neighbours more often than would be expected by chance, are also identified. The method tests for consistency across a number of independent observation periods, by comparison with values obtained from simulations in which animal identities are randomised between observation periods. An experiment is described in which 8 groups of 7 grazing sheep were each observed for a total of 10, one-hour periods and the identities and distances away of the 3 nearest neighbours of each focal animal recorded at 5min intervals. Significant within-group differences in SIs were found in four of the groups (P < 0.001). SIs calculated using the nearest neighbour, two nearest neighbours or three nearest neighbours, were generally highly correlated within all groups, with little change in the ranking of animals. There were significant negative correlations between SIs and nearest neighbour distances in five of the groups. It was concluded that there was no advantage in recording more than one neighbour

* Corresponding author. Tel.: +44 1224 498200; fax: +44 1224 311556. E-mail address: [email protected] (A.M. Sibbald). 0168-1591/$ – see front matter # 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.applanim.2004.09.002

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to calculate the SI. Advantages of the SI over other methods for measuring sociability and pair-wise associations are discussed. # 2004 Elsevier B.V. All rights reserved. Keywords: Association; Grazing; Nearest neighbour; Sheep; Sociability; Social behaviour

1. Introduction One of the main characteristics of the social behaviour of grazing animals is how they distribute themselves across the landscape. Sheep are highly social grazers, but different breeds vary in the degree of group cohesion that they display and lowland breeds generally graze closer together than hill breeds (Arnold and Dudzinski, 1978). Even within breeds, cohesion can vary with the terrain and type of vegetation (Dwyer and Lawrence, 1999), the type of behaviour, e.g. resting versus grazing (Lynch et al., 1985) and with the degree of familiarity within the group (Boissy and Dumont, 2002). Distances between grazing animals are also affected by the perceived risk of predation and most breeds of sheep will flock together in response to a fearful stimulus; a behaviour thought to have survival value since individuals near the centre of any group are less vulnerable to predation (e.g. Krause, 1994). Within groups of sheep, some individuals tend to stay closer to their neighbours than others (Lynch et al., 1985), which could be due to differences in the fear of predators and/or differences in social motivation. The concept of using the spacing between individuals to describe their social relationships was first discussed by Hediger (1950, 1963) and later by McBride (1971). McBride (1971) used the term personal field to define the area around an individual that is normally not entered by other animals and determines the minimum distance found between nearest neighbours. The mechanism for this will vary, with dominant individuals tending to defend their personal fields and more subordinate ones tending to avoid entering the personal fields of others. Hediger (1963) referred to the maximum distance an animal will readily move away from the group, which determines group cohesion, as the social distance. It is useful to think of animals as normally staying somewhere between the personal fields of their neighbours and the social distance, moving in an area which has been referred to as a living space (McBride, 1971) or neutral zone (Gueron et al., 1996). The more sociable individuals are then those which tend to be closer to the limit of the personal field than the social distance. Although absolute distances between animals can be used to assess sociability (e.g. Lynch et al., 1985), we propose a method which requires only the identities of nearest neighbours to be recorded, since this will be less vulnerable to external factors which alter the distances between individuals (see above) and have less opportunity for observer bias. A method for quantifying sociability has valuable potential as a tool in other areas of behavioural research, where the effects of social motivation on other behaviours are of interest, or as a means of assessing the effects of a disease or drug on the social motivation and behaviour of individuals. In controlled experiments, the ranking of group members on the basis of their sociability can be used to allocate individuals to treatments.

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The method, which has been developed from an earlier version reported briefly elsewhere (Sibbald et al., 1998), involves the calculation of a sociability index (SI) which is equivalent to the relative proportion of time that each individual is the nearest neighbour of any other animal in the group. Associations between pairs of individuals are also identified, wherever particular pairs of animals are nearest neighbours more often than would be expected by chance. The method is suitable for any size of group, provided it is discrete and all individuals are visible and identifiable during the observation periods. Differences between the relative sociability of individuals are tested for statistical significance, by determining whether they are more extreme than would be expected by chance. This is done by taking measurements over several independent observation periods and constructing statistical hypothesis tests by repeated simulations, in which animal identities are randomised between observation periods. An experiment is described in which the method is demonstrated for a number of small groups of sheep grazing in homogeneous grass plots. The data are used to calculate SIs and to identify pair-wise associations within the groups. The data are also used to compare results obtained from observations of one, two or three nearest neighbours and to examine the relationships between the SI and the mean distance and relative orientation of the animals.

2. Materials and methods 2.1. Animals, plots and experimental design Fifty-six, 1-year-old, female Scottish Blackface sheep were drawn from a single flock and allocated to eight groups of seven animals, which were balanced for live weight and condition score (Russel et al., 1969). In each group, the sheep were randomly allocated the numbers 1–7 and their fleeces marked to allow identification during field observations. The eight groups grazed in separate plots, each consisting of predominantly perennial ryegrass pasture and each measuring approximately 33 m  60 m. Two 33 m  30 m experimental plots of the same pasture type, which were flat and featureless with sward heights of around 5–6 cm, were used for the observations. Ten 1-h observation periods were carried out for each group over a 4-week period in May and June, and two groups of sheep were observed on each occasion. Five sets of observations were carried out for groups 1–4 in each of weeks 1 and 3, and for groups 5–8 in weeks 2 and 4. Each group was observed in each of the two experimental plots the same number of times. The sheep were returned to their home plots for a minimum of 1 h and generally at least 24 h between observation periods, in order to attempt to ensure that data for consecutive periods were independent. During the observation periods one group of sheep grazed in each of the experimental plots, but the groups were unable to see one another due to a screen of horticultural shade netting covering the dividing fence. 2.2. Behavioural observations All 1-h observation periods were carried out between 09:30 and 16:00 h, while the sheep were grazing. On each occasion the two groups of sheep to be observed were moved into

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the experimental plots approximately 10 min before the observation period began. The observer sat on a raised platform, approximately 10 m from the end of each plot and moved into position immediately after the sheep entered the plots. During the 1-h observation periods, the observer scanned the two groups alternately at 2.5-min intervals, so that each sheep was sampled every 5 min and a total of 12 times during each 1-h period. The first scans for the two groups therefore started at time 0 and after 2.5 min and the final scans started 55 and 57.5 min after the observation period began. For each group at each scan, focal sheep were observed in order from 1 to 7 and the identities and distance away of the nearest, the second nearest and the third nearest neighbour recorded for each animal in turn. In each case, the nearest neighbours were taken to be the animals whose shoulders were closest to the shoulders of the focal sheep at the moment of the scan. In rare cases where two or more sheep appeared to be at exactly the same distance from the focal sheep, the observer made a decision based on the relative positions of the animals immediately before and after the scan. Distances between focal sheep and their nearest neighbours were also estimated by eye, using marker pegs placed at 5 m intervals around the perimeters of the plots, and classified as close (<2 m), intermediate (2–10 m) or far (>10 m). This was done as a separate exercise, in order to compare SIs with mean distances later on and these distance estimates were not used for identification of the three nearest neighbours. Classification of the distances was based on previous observations of Scottish Blackface sheep in grass plots of the same type (Sibbald et al., 2000), where 12.5% of all recorded nearest-neighbour distances were less than 2 m and 17.5% were more than 10 m. The orientations of the nearest neighbours relative to the focal sheep were classified as facing towards, parallel or facing away. The classification of orientations was carried out later, on the basis of maps drawn at the time of the observations showing the relative positions of each pair of sheep and the angle between them. Pairs that were classified as parallel were always alongside one another, but not necessarily facing in the same direction. 2.3. Data processing 2.3.1. Calculation of SI and identification of associated pairs SIs were calculated within groups of sheep and in three different ways, using data for the nearest, the two nearest or the three nearest neighbours. In each case, for each of the observation periods, a matrix was constructed in which rows represented the focal sheep and columns represented the potential neighbours (e.g. Table 1a). When using only the nearest neighbour, each cell of the matrix contained the number of scans in which the individual in that column was recorded as the nearest neighbour of the focal sheep in that row. When using two or three neighbours, each cell contained the number of scans in which an individual was one of the first two, or one of the first three nearest neighbours of the focal sheep. In each case, whether one, two or three neighbours were used, a single summary matrix of percentages (e.g. Table 2) was then obtained for each group, by summing the matrices from all 10 observation periods and dividing the count in each cell by the number of possible scans (total scans per observation period  no of observation periods = 120). SIs were then calculated from each summary matrix by dividing the column totals by 100. SIs therefore indicate the relative proportions of time that individuals were the nearest neighbours of any of the focal sheep in the group, scaled to have an expectation of 1.0 under

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the null hypothesis of random mixing. Variability between observation periods was examined by calculating the standard deviations of the cell values for each pair-wise sheep combination and the standard deviations of the column totals for each focal sheep, using 10 values in each case. 2.3.2. Sampling interval In order to examine the effects of sampling interval on the likelihood of a sheep having the same nearest neighbour in two different scans, nearest neighbour identities were compared for all pairs of scans across the full range of time intervals, from consecutive scans (5 min) to the first and last scan in each observation period (55 min). The overall mean proportions of observations for which the same nearest neighbour was identified for a particular focal sheep, were then calculated for each time interval and the relationship between proportion and time interval examined. 2.4. Statistical analyses All programming and statistical analyses were carried out using the statistical package Genstat (Genstat, 1998), except where stated otherwise. 2.4.1. Randomisation procedure To test for within-group differences in sociability, SIs calculated from observations were compared with SI values calculated from simulations, which are considered to be equivalent to the values that would be expected by chance. In each case, simulations were carried out using the original field data, rather than random pairings of animals, and were therefore based on authentic sheep behaviour within that group. In the simulations there was assumed to be no continuity in sheep identity from one observation period to the next. This was modelled by randomly reallocating sheep identity numbers in each observation period and reordering the rows and columns of the matrices accordingly. This process is demonstrated in Table 1b. As with the observed data, a summary matrix was then produced from the 10 reordered matrices and SIs calculated. This process was carried out 1000 times for each group. 2.4.2. Test for sociability indices As a global test to determine whether the spread of SI values within a group was different from the spread that would be expected by chance, the variance of the observed SIs was compared with the 1000 variances of SIs calculated from the simulated matrices. If the variance of the observed values was outside the central 0.95 of the simulated values, this was considered to be the evidence that the spread of SIs was different, at the 0.05 probability level, from that which would be expected by chance (Manly, 1991). Values outside the 0.991 range of simulated values were considered to be significant at the 0.001 probability level. Since 1000 simulations were carried out for each group, P-values of 0.05 and 0.001 would be estimated with standard errors of 0.0022 and 0.0000991. For groups in which the global test, based on within-group variances, was significant, ranked SI values were then compared with simulated SI values. The highest SI in the group was compared with the range of highest values produced by the simulations, the second highest SI

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compared with the range of second highest values produced by the simulations and so on. Individual SIs which were above or below the central 0.95 range of simulated values, for an individual with that particular ranking, were identified as more or less sociable than would be expected by chance. 2.4.3. Test for pair-wise associations As a global test for pair-wise associations, the variance of the cells in the summary matrix of observed values was compared with the range of cell variances from the simulated matrices. As in the global test for SIs, a matrix variance outside the central 0.95 or 0.991 of simulated values indicated that some pairs of individuals were seen as nearest neighbours more or less often (at P < 0.05 or < 0.001) than would occur by chance. For groups in which the variance of the matrix cells was significantly greater than simulated values, the ranked means of the cell values for each pair of sheep were then compared with the simulated mean values. As with the SIs, the highest mean cell value for a pair of sheep was compared with the highest mean cell values produced by the simulations, the second highest compared with the second highest and so on. Those which were outside the central 0.95 of the range of simulated values, for pairs of individuals of the equivalent ranking, were identified as being nearest neighbours more or less often than would be expected by chance. 2.4.4. Other investigations The extent to which nearest neighbours remained unchanged over time was investigated by selecting all pairs of scans separated by some time interval (e.g. 5 or 10 min) and then calculating the proportion of nearest neighbour pairs which remained unchanged over this time interval. This proportion was calculated separately for each group, and evidence for a higher proportion of sheep having the same nearest neighbour after short time intervals than after longer time intervals was assessed using a t-test for paired data (n = 8). Pearson correlation analysis was used, within each group, to compare SIs calculated using one, two or three nearest neighbours. Pearson correlation analysis was also used to determine the relationships across all groups (n = 56) and within-groups (n = 7) between individual SI values and the proportion of values in each of the nearest neighbour distance and orientation categories. Student’s t-test and correlations were carried out using Minitab (Release 13.1 # 2000 Minitab Inc.)

3. Results 3.1. Sociability indices Data for group 3 are presented as examples of the matrices used to calculate SIs, using the nearest neighbour only. Table 1a contains scan data from the first observation period and Table 1b shows one of the reordered matrices used for the simulations. Table 2 is the summary matrix used to calculate SI values and contains the percentages of all observations in which each potential neighbour was the nearest neighbour of each focal sheep. The mean of the standard deviations for the individual cell values used to make up

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Table 1a Matrix for the first observation period for group 3, containing the number of scans in which each potential neighbour (columns) was the nearest neighbour of each focal sheep (rows) ID

Potential neighbour

Focal

1

2

3

4

5

6

7

1 2 3 4 5 6 7

* 1 0 2 1 1 0

7 * 3 9 0 1 6

2 2 * 0 0 1 2

2 1 6 * 1 0 0

1 1 1 1 * 6 3

0 7 1 0 6 * 1

0 0 1 0 4 3 *

Table 1b Example of simulated matrix, based on the first observation period for group 3, in which ID numbers for sheep have been randomly reallocated and rows and columns of data reordered accordingly ID Old

Old New

3 1

4 2

7 3

1 4

6 5

2 6

5 7

3 4 7 1 6 2 5

1 2 3 4 5 6 7

* 0 2 2 1 2 0

6 * 0 2 0 1 1

1 0 * 0 3 0 4

0 2 0 * 1 1 1

1 0 1 0 * 7 6

3 9 6 7 1 * 0

1 1 3 1 6 1 *

the summary matrix for group 3 was 1.56 (range 1.21–1.85) and the mean of the standard deviations for the focal sheep column totals was 3.45 (range 2.91–3.89). Table 3a–c shows the SI values within each of the groups, calculated using one, two and three nearest neighbours. In each case SI values are shown in rank order within the group. Table 2 Summary matrix for group 3, containing the percentages of all possible scans (n = 120) in which each potential neighbour (columns) was the nearest neighbour of each focal sheep (rows), with column totals expressed as proportions to show sociability indices (SI) ID

Potential neighbour

Focal

1

2

3

4

5

6

7

1 2 3 4 5 6 7 SI

* 13.3 11.7 17.5 17.5 11.7 15.0 0.867

20.0 * 35.8 36.7 5.8 15.8 23.3 1.375

18.3 21.7 * 9.2 18.3 14.2 10.8 0.925

15.8 29.2 13.3 * 6.7 17.5 23.3 1.058

10.0 9.2 14.2 5.8 * 21.7 10.8 0.717

14.2 15.0 11.7 10.8 30.8 * 16.7 0.992

21.7 11.7 13.3 20.0 20.8 19.2 * 1.067

Percentages for pairs of sheep, whose mean value falls outside the 95% range of simulated mean values for pairs, are emboldened.

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Table 3 Sociability indices (SI) in rank order within groups, from observations of (a) one (b) two and (c) three nearest neighbours, showing probability (P) that the within-group spread of values is greater than would be expected by chance Rank

(a) 1 2 3 4 5 6 7 P (b) 1 2 3 4 5 6 7 P (c) 1 2 3 4 5 6 7 P

Group 1

2

3

4

5

6

7

8

1.109 1.067 1.050 1.042 1.025 0.867 0.842 NS

1.292 1.183 1.075 1.017 0.858 0.842 0.733 NS

1.375 1.067 1.058 0.992 0.925 0.867 0.717 <0.001

1.192 1.175 1.067 1.025 0.917 0.825 0.800 NS

1.192 1.167 1.125 1.092 1.075 0.758 0.592 <0.001

1.442 1.125 1.058 1.017 0.958 0.792 0.608 <0.001

1.200 1.175 1.083 1.050 0.900 0.808 0.783 <0.001

1.240 1.165 1.090 0.975 0.935 0.815 0.775 NS

1.079 1.071 1.050 1.050 0.996 0.892 0.862 NS

1.279 1.225 1.071 0.946 0.912 0.800 0.767 <0.01

1.267 1.133 1.050 1.025 1.013 0.838 0.675 <0.001

1.213 1.158 1.138 0.996 0.929 0.854 0.713 <0.01

1.187 1.167 1.125 1.104 1.062 0.775 0.579 <0.001

1.308 1.062 1.017 1.008 0.979 0.879 0.746 <0.001

1.246 1.142 1.133 0.987 0.867 0.825 0.800 <0.001

1.146 1.133 1.125 1.054 0.863 0.846 0.833 NS

1.131 1.042 1.039 1.036 1.006 0.908 0.839 NS

1.272 1.233 1.069 0.953 0.925 0.806 0.742 <0.001

1.217 1.183 1.061 1.014 0.981 0.833 0.711 <0.001

1.142 1.131 1.103 1.050 0.942 0.864 0.711 <0.05

1.197 1.169 1.142 1.089 1.039 0.800 0.564 <0.001

1.303 1.119 1.003 0.986 0.917 0.914 0.758 <0.001

1.258 1.247 1.092 0.969 0.847 0.794 0.792 <0.001

1.164 1.103 1.069 1.033 0.953 0.861 0.817 NS

Individual SIs that fall outside the 95% range of expected values are emboldened.

Using data for the nearest neighbour only (Table 3a), the global test showed that four of the groups had a wider spread of values than would be expected by chance. As an example, Fig. 1 shows the relationship between observed and simulated values for group 3, with observed SIs plotted beside the 95% range of simulated SIs. When two or three neighbours were used (Table 3b and c), six of the groups had a wider spread of values than would be expected by chance. In the tables, individual SIs which fell outside the 95% range of simulated values are indicated in each case. 3.2. Comparison of SIs derived from one, two and three nearest neighbours The matrices in Table 4a and b compare the SI rankings calculated using the nearest neighbour only with SI rankings using the first two (Table 4a) or the first three (Table 4b) nearest neighbours. For example, in Table 4a, the first row of the matrix shows that, in five of the groups, the same individual was ranked highest whether one or two nearest neighbours were

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Fig. 1. Observed sociability indices (*) together with the 95% range of simulated values from 1000 simulations (dotted lines) for group 3, plotted in rank order.

used. In another group, the individual ranked highest using one nearest neighbour was ranked second highest when two neighbours were used. In the last two groups, the individual ranked highest using one nearest neighbour was ranked third when two neighbours were used. Table 4 Matrices in which the value in each cell represents the number of individuals with that particular combination of SI rankings, when comparing results from observations of one nearest neighbour (NN) with (a) two NNs or (b) three NNs (a) SI rank from one NN

SI rank from two NNs 1

2

3

1 2 3 4 5 6 7

5 1 2

1 4 1 2

2

(b) SI rank from one NN

SI rank from three NNs

1 2 3 4 5 6 7

3 3

4

5

2 2 3 1

1

1

2

3

4

1 3 3 1

3 2

3 1 3

1 1 2 4

2 1 1

6

7

4 2 1

3 4 1

2 6

5

6

7

4 3 1

1 2 5

1 1 2 2 2

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Table 5 Pearson correlation coefficients (rP) with probability values (P) for within-group correlations (n = 7) between sociability indices measured using different numbers of nearest neighbours Group

Number of nearest neighbours 1 vs. 2

1 2 3 4 5 6 7 8

1 vs. 3

2 vs. 3

rP

P

rP

P

rP

P

0.97 0.98 0.89 0.96 0.98 0.98 0.79 0.90

<0.001 <0.001 <0.01 <0.001 <0.001 <0.001 <0.05 <0.01

0.84 0.96 0.82 0.90 0.97 0.89 0.69 0.72

<0.05 <0.001 <0.05 <0.01 <0.001 <0.01 =0.089 =0.067

0.90 0.99 0.96 0.95 0.99 0.96 0.96 0.92

<0.01 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.01

Similarly, the second row shows that in one group an individual was ranked second using one neighbour and first using two, in four groups an individual was ranked second with both methods and so on. The empty cells in the matrices show that, in general, sheep were not given high rankings by one method and low rankings by another. Within-group correlations between SIs calculated for one, two and three nearest neighbours are shown in Table 5. 3.3. Pair-wise associations Fig. 2 shows the pair-wise mean values for the percentage of observations in which all possible pairs of sheep in group 3 were seen as nearest neighbours, together with the

Fig. 2. The mean percentage of scans in which pairs of sheep were nearest neighbours (*), together with the 95% range of simulated values from 1000 simulations (dotted lines) for group 3, plotted in rank order.

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95% range of simulated values. Individual values for the three pairs of sheep whose mean values are above and the two pairs of sheep whose mean values are below the 95% range, are indicated in the matrix in Table 2. The global test showed significant differences between pairs of sheep in groups 3, 5, 6 and 7 (P < 0.05). When compared with simulated values, 3 pairs in group 3 (Table 2) and group 5, 2 in group 6 and 4 in group 7 were found to be nearest neighbours more often than would be expected by chance, from which they were identified as associated pairs. When the three nearest neighbours were taken into account, the global test was significant for groups 2, 3, 4, 5, 6 and 7 (P < 0.001) and 4 pairs of sheep in groups 2, 3, 4 and 5, 2 in group 6 and 4 pairs in group 7 were subsequently identified as associated pairs. Two of the pairs in groups 3 and 5, 1 of the pairs in group 6 and 3 of the pairs in group 7, were identified by both methods. 3.4. SIs and the distance and orientation of nearest neighbours Across all groups, sheep with higher SI values tended to have a higher proportion of nearest neighbours that were close (rP = 0.66, n = 56, P < 0.001), although there were no within-group correlations between SI and the proportion of close distances for two of the groups (Table 6). Sheep with a higher proportion of close nearest-neighbour distances were more likely to be parallel to one another (rP = 0.51, P < 0.001) than facing towards (rP = 0.35, P < 0.01) or away (rP = 0.33, P < 0.05). Sheep with higher SIs also tended to have nearest neighbours which were parallel to them, but the correlation with SI was weak (rP = 0.31, P < 0.05). 3.5. Sampling interval Fig. 3 shows the relationship between the proportion of focal sheep with the same nearest neighbour in two different scans and the time interval between the scans. The proportion of sheep with the same nearest neighbour in a pair of scans was significantly higher for consecutive scans, which were separated by 5 min, than for scans separated by 10 or 15 min (P < 0.001), with a further decrease between intervals of 15 min and intervals of 30 min or longer (P < 0.05).

Table 6 Pearson correlation coefficients (rP) with probability values (P), for within-group correlations (n = 7) between sociability indices and the proportion of nearest neighbour distances that were less than 2 m (‘close’) Group

rP

P

1 2 3 4 5 6 7 8

0.74 0.37 0.96 0.97 0.92 0.91 0.58 0.85

=0.058 NS <0.001 <0.001 <0.01 <0.01 NS <0.05

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Fig. 3. The mean proportion of sheep having the same individual identified as the nearest neighbour in pairs of scans, plotted against the time interval between scans. Error bars indicate S.E. The expected proportion of sheep having the same nearest neighbour by chance is 0.167.

4. Discussion The motivation to be close to social companions has been assessed in tests which involve a response to social isolation (Faure et al., 1983; Syme, 1981) or measure the distance or speed that animals run towards conspecifics (Mills and Faure, 1990; Sibbald et al., 2000), but the interpretation of the results is inevitably complicated by the fear and stress experienced by the animals. Another approach to measuring social motivation is to use operant conditioning to obtain social contact with companions (Holm et al., 2002), but differences between individuals in their willingness to work for social contact may partly reflect their ability to learn the task or perform the mechanical operation required. The method described here measures sociability in a situation where the behaviour of the animals is not complicated by any of these factors. The development of the method was inspired by an observation that when mean nearest-neighbour distances within groups of grazing sheep were being recorded by scan sampling, some individuals were identified as nearest neighbours more often than others. It has been shown before that, even in a group of unrelated animals, certain individuals tend to have their nearest neighbours closer than others (Lynch et al., 1985) and it is widely recognised that associated pairs of animals can be identified by their proximity to one another (Arnold, 1985). However, individual variation in general sociability has not been quantified using the proportion of time spent as a nearest neighbour. This method is intended as a tool for quantifying individual variation in social motivation within groups. It does not provide any information about the relative sociability of an animal with respect to individuals in other groups. However, this distinction is not just a question of measurement technique, since the apparent sociability of an individual is likely to vary with the composition of the social group that it belongs to

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at the time. The method has been demonstrated here with small groups of sheep, although it can be applied to any size of group that is discrete and in which all the members of the group are visible during observation periods. The group sizes used here may well be particularly appropriate for Scottish Blackface sheep, since there is some evidence that they operate as social subgroups of 5–10 animals in free-ranging situations (Lawrence and Woodgush, 1988). In this experiment, measurements were made during grazing periods, although the method can be applied to animals engaged in other activities. However, the results are likely to be different for different activities. As well as affecting the magnitude of the distances between animals, activity type can also affect apparent associations. For example, it has been shown in both horses (Wells and Goldschmidt-Rothschild, 1979) and sheep (Morgan and Arnold, 1974) that mothers spend more time with their young when they are resting than when they are grazing. Other methods have been described which measure the extent to which particular individuals associate with one another and several coefficients of association have been devised (Cairns and Schwager, 1987; Ginsberg and Young, 1992). Generally these are based on a ratio of the number of observations of two individuals when together and when apart. The method proposed here uses the same principle, in that it looks at the probability of being seen together over a fixed number of observations. However, because this method requires that the whole group is visible at each scan, it takes account of all other possible nearest neighbours and thereby avoids a major source of bias in such data. For example, bias can arise when the failure to locate a pair of animals is caused by some factor correlated with the probability of their being together. Differences in the relative contributions of each member of a pair to the maintenance of proximity are not taken into account in this method, as they are in the method used by Hinde and Atkinson (1970) for monkeys, although it is well known that associations between individuals in groups of sheep and cattle are not necessarily reciprocal (Arnold, 1985). Because of the way the data are collected, with sheep being scanned in order of their identifying numbers, nearest neighbour relationships are also not necessarily reciprocal. From the nearest neighbour matrices it is easy to identify pairs where one individual is the nearest neighbour of the other more often, for example, sheep 2 and 7 in Table 2. However, the ranking of pair-wise associations is based on the mean values for the pairs and will therefore tend to pick out pairs which both have high values, suggesting a mutual social attraction. A significantly wider spread in observed, compared to simulated sociability indices was found in four of the groups. Since SIs are compared with simulated values based on the actual field data for that group, rather than a standard set of values, the magnitude of the difference between the highest and lowest SIs is not always a good indicator of significance. For example, using only one nearest neighbour, groups 2 and 8 have a slightly larger spread of values than group 7 but it is only the data for group 7 that are significant (Table 3a). The groups with a significant spread in SIs were also the ones which showed evidence of pair-wise associations, although it is not necessarily the case that animals in associated pairs will have high individual SIs. High SIs can be the result of a general tendency to be the nearest neighbour of other animals in the group and individuals with associations can just as easily have low SIs, for example, sheep 5 in group 3 (Table 2). In fact, in three of the groups with pair-wise associations the individual with the highest SI

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was paired with an animal of rank 5 or below and in the fourth group the highest ranking individual was not paired at all. Observation periods of 1 h were chosen since this was assumed to be long enough for sheep to have moved around the plot and passed close to all other members of the group several times. The scan rate of 12/h was chosen in order to maximise the number of observations, while giving the observer enough time to record the data. The observer started a new scan every 212 min and scans normally took between 1 and 2 min to complete. The assumption that an hour would be long enough for sheep to move around the plot several times is supported by results from a previous study of Scottish Blackface sheep in the same plots (Sibbald and Hooper, 2003), where distance moved was measured as the number of 5 m  5 m squares entered and each sheep moved through an average of 52 squares/h of grazing. Even so, it is possible that pairs of animals could remain close together for reasons other than social attraction, such as the adoption of similar grazing strategies or the tendency to follow whichever animal happens to be close at the time. More of a problem is the fact that being found in close proximity to one another over a long period of time could be due to a shared preference for particular parts of the plot. For example, if a couple of animals were more highly motivated to avoid the observer than the rest, this might lead to their frequently being observed together at the far end of the plot. However, informal observations indicated that all the sheep in this experiment moved throughout the plots quite freely, although in order to completely rule out the possibility that pairing has occurred because of positional preferences, it would be necessary to record the actual locations of the animals at each scan. Because there are some ephemeral reasons why particular sheep might be close together, the statistical tests for SIs and pair-wise associations are based on independent observation periods and the SI is calculated using only one value (the column total) from each period. Since independence of scan data within periods is not an issue for these tests, we recommend using the shortest sampling interval that is practical, since this will give the best estimate of the proportion of time spent as a nearest neighbour in any particular observation period. If the same two animals are repeatedly observed to be nearest neighbours over a number of observation periods, which are separated by a period of at least an hour, preferably at least 24 h, during which the sheep are moved into a different plot, it is most likely that there is an association between them. A rather stronger argument can be made for SIs. If one animal is a frequent nearest neighbour of any or all of the others across a number of observation periods, it is likely to indicate a real tendency to stay close to other animals, although the same caveats about position preferences should still apply. Possible advantages of recording the second and third nearest neighbours were investigated because of a perceived disadvantage in ignoring the positions of other members of the group, when only one neighbour was observed. For example, a highly sociable sheep might keep within a fairly close distance of its companions, but not always be recorded as the nearest neighbour of the sheep it is close to, because other individuals sometimes move between them. This is inevitable because of the way that nearest neighbours are defined, as the nearest animal at the time of the scan, with no requirement for that individual to spend a particular period of time in the vicinity of the focal sheep. It was thought that recording the second and third nearest neighbours would increase the probability of picking up the behaviour of the highly sociable animal. However, recording

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the second and third neighbours also introduces ‘noise’ into the system, as the second and third neighbours will be further away from the focal sheep and, in general, less likely to be responding to it. Indeed, the greater the number of neighbours taken into account and given equal weight in calculating SIs, the closer all individual SI values will come to the average value of 1.0. In this experiment, a greater number of pairings of animals were detected when the three nearest neighbours were taken into account, although only some of the pairs that were originally detected using one neighbour were amongst them. This is because some of the original pairs will no longer be detected due to the extra ‘noise’ mentioned above, while new ones may appear as a secondary effect of other pairings. For example, if sheep A and B are a pair and sheep B and C are a pair, then A and C may often be seen together. Indeed, with groups as small as seven individuals, recording three neighbours tends to become an exercise in identifying sub-groups. These considerations, together with the fact that the sociability rankings within the various groups in this experiment were essentially the same with the different methods, suggest that there is no benefit from recording more than one nearest neighbour to measure sociability. In most of the groups, SIs were closely related to nearest neighbour distances. This is to be expected, since a nearest neighbour is, by definition, the individual which is the shortest distance away from the focal sheep. However, the relationship is not always strong, since the spread of the animals can vary with external influences and sometimes nearest neighbours can be several metres away from the focal animals. This is one of the reasons why the method ignores distances and uses only the proportion of time spent as a nearest neighbour. In turn, ignoring distances between animals will introduce some noise into the system, due to the fact that being a nearest neighbour to an outlying individual, when you are several metres away and closer to other animals at the centre of the group, does not in itself indicate sociability. However, selecting data on the basis of distances would give rise to both practical and statistical problems. From the practical point of view, there would be difficulty in choosing the distance beyond which an animal would not be considered to be another sheep’s nearest neighbour. Such a cut-off point would have to depend on breed and environmental factors, as mentioned in the introduction. Another problem is that the index is a within-group measure and depends on having a complete set of data for the group. For these reasons, a nearest neighbour is recorded on each occasion, however far it is from the focal sheep. However, the contribution of inappropriate observations to the final result should be minimal if enough data are collected. This is another argument for keeping the sampling interval short. In conclusion, this is a method for measuring relative sociability which can be applied to any animals in groups, engaged in any type of behaviour, provided the following criteria are met. It is necessary for all animals in the group to remain visible and to be individually identifiable, which will limit its use for some wild animals and large groups. It is also important, to ensure independence of data, that the time interval between observation periods reflects the movement rate of the particular animals being studied. It is self-evident that it should only be used in situations where the spatial distribution of the animals is primarily determined by social factors and where other environmental influences, such as weather conditions, the distribution of food resources or the presence of a predator, do not have significant differential effects on the behaviour and movements of individual animals. The method can be used to quantify sociability or simply to rank the animals within a group.

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It is easy to carry out in the field and avoids some of the sources of bias associated with other methods.

Acknowledgements This work was funded by the Scottish Executive Environment and Rural Affairs Department. The authors acknowledge the valuable contribution made by Trevor Smart during the initial stages of this work and wish to thank David Cope, Russell Hooper, Bertrand Dumont and Graham Horgan for helpful comments on an earlier version of the manuscript.

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