Abstract: In recent years evidence has been accumulating that personalities are not only found in humans but also in a wide range of other animal species. Individuals differ consistently in their behavioural tendencies and the behaviour in one context is correlated with the behaviour in multiple other contexts. From an adaptive perspective, the evolution of animal personalities is still a mystery, because a more flexible structure of behaviour should provide a selective advantage. Accordingly, many researchers view personalities as resulting from constraints imposed by the architecture of behaviour (but see ref. 12). In contrast, we show here that animal personalities can be given an adaptive explanation. Our argument is based on the insight that the trade-off between current and future reproduction often results in polymorphic populations in which some individuals put more emphasis on future fitness returns than others. Life-history theory predicts that such differences in fitness expectations should result in systematic differences in risk-taking behaviour. Individuals with high future expectations (who have much to lose) should be more risk-averse than individuals with low expectations. This applies to all kinds of risky situations, so individuals should consistently differ in their behaviour. By means of an evolutionary model we demonstrate that this basic principle results in the evolution of animal personalities. It simultaneously explains the coexistence of behavioural types, the consistency of behaviour through time and the structure of behavioural correlations across contexts. Moreover, it explains the common finding that explorative behaviour and risk-related traits like boldness and aggressiveness are common characteristics of animal personalities.

Abstract: In studies of animal behaviour investigators correlate dominance with all kinds of behavioural
variables, such as reproductive success and foraging success. Many methods are used to
produce a dominance hierarchy from a matrix reflecting the frequency of winning dominance
interactions. These different methods produce different hierarchies. However, it is difficult to
decide which ranking method is best. In this paper, we offer a new procedure for this decision:
we use an individual-based model, called DomWorld, as a test-environment. We choose this
model, because it provides access to both the internal dominance values of artificial agents
(which reflects their fighting power) and the matrix of winning and losing among them and,
in addition, because its behavioural rules are biologically inspired and its group-level patterns
resemble those of real primates. We compare statistically the dominance hierarchy based on
the internal dominance values of the artificial agents with the dominance hierarchy produced
by ranking individuals by (a) their total frequency of winning, (b) their average dominance
index, (c) a refined dominance index, the David`s score, (d) the number of subordinates each
individual has and (e) a ranking method based on maximizing the linear order of the hierarchy.
Because dominance hierarchies may differ depending on group size, type of society, and the
interval of study, we compare these ranking methods for these conditions.We study complete
samples as well as samples randomly chosen to resemble the limitations of observing real
animals. It appears that two methods of medium complexity (the average dominance index
and David`s score) lead to hierarchical orders that come closest to the hierarchy based on
internal dominance values of the agents. We advocate usage of the average dominance index,
because of its computational simplicity.