A Proximity to the nearest neighbour

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B Adjacent neighbour of each age-sex class

Figure 10.6 Exploration of patterns of spatial proximity can reveal some unexpected structure to what appears superficially to be a random gathering. In the case of farm cats, these graphs, based on G. Kerby's field study in Macdonald et al. (in press), reveal (A) that different age-sex classes of individuals positioned themselves at significantly different distances to their nearest neighbors and (B) that these positionings differed significantly depending on the age-sex class to which that neighbor belonged. AF = adult female, AM = adult male, JF = juvenile female, JM = juvenile male, KF = female kitten, KM = male kitten.

Figure 10.6 Exploration of patterns of spatial proximity can reveal some unexpected structure to what appears superficially to be a random gathering. In the case of farm cats, these graphs, based on G. Kerby's field study in Macdonald et al. (in press), reveal (A) that different age-sex classes of individuals positioned themselves at significantly different distances to their nearest neighbors and (B) that these positionings differed significantly depending on the age-sex class to which that neighbor belonged. AF = adult female, AM = adult male, JF = juvenile female, JM = juvenile male, KF = female kitten, KM = male kitten.

Figure 10.7 An ultimate goal of many ethological descriptions is to translate indices of social behavior into evolutionary consequences. In the case of Kerby and Macdonald's (1988) and Macdonald et al's (in press) farm cat study, the spatial arrangement of female cats around the farmyard resource center was correlated with the number of kittens raised annually per female.

Figure 10.7 An ultimate goal of many ethological descriptions is to translate indices of social behavior into evolutionary consequences. In the case of Kerby and Macdonald's (1988) and Macdonald et al's (in press) farm cat study, the spatial arrangement of female cats around the farmyard resource center was correlated with the number of kittens raised annually per female.

Macdonald et al.'s (1987, in press) and Kerby and Macdonald's (1988) cat study shows how even simple quantification can reveal unexpected layers of structure in unsophisticated mammalian societies.

In summary, to define social groups and to describe social dynamics one must describe interactions that may be positive, tolerant, or negative in terms of their consequences for those involved. However, the choice of interaction type, or of the way of quantifying it, may radically affect the researcher's interpretation of the outcome. This should not surprise us. An analogy with human social dynamics shows us that very different patterns of interaction appear if we view exchange of such commodities as money, conversation, or affection. And the picture changes yet again if we look at frequency rather than quantity or quality of the exchange. The most pernicious problem lies in correct interpretation of the context of the interchange. Is the individual to which the most money is observed to be given beloved kin, despised extortionist, or scarcely known shopkeeper?

Figure 10.8 The same observations of social interactions can be expressed in three ways: as the total flux of a given behavior pattern, as a rate, or as a proportion. In this case, the total frequency is greater between A and B than between A and C (b > c), but qualitatively the components of their relationship are the same.

Figure 10.8 The same observations of social interactions can be expressed in three ways: as the total flux of a given behavior pattern, as a rate, or as a proportion. In this case, the total frequency is greater between A and B than between A and C (b > c), but qualitatively the components of their relationship are the same.

■ Methods for Behavioral Measurement

Although our goal is not to provide an encyclopedic guide to the formidable practical problems faced by the field biologist, we briefly review several methodologies relevant to measuring social dynamics.

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