Abstract: Researchers are increasingly turning to network theory to understand the social nature of animal populations. We present a computational framework that is the first step in a series of works that will allow us to develop a quantitative methodology of social network sampling to aid ecologists in their social network data collection. To develop our methodology, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures, as network structure might affect the robustness of any particular sampling methodology. Thus, we present a computational tool for generating network structures that have user-defined distributions for network properties and for key measures of interest to ecologists. The user defines the values of these measures and the tool will generate appropriate network randomizations with those properties. This tool will be used as a framework for developing a sampling methodology, although we do not present a full methodology here. We describe the method used by the tool, demonstrate its effectiveness, and discuss how the tool can now be utilized. We provide a proof-of-concept example (using the assortativity measure) of how such networks can be used, along with a simulated egocentric sampling regime, to test the level of equivalence of the sampled network to the actual network.

Abstract: Social network analysis is an increasingly popular tool for the study of the fine-scale and global social structure of animals. It has attracted particular attention by those attempting to unravel social structure in fission–fusion populations. It is clear that the social network approach offers some exciting opportunities for gaining new insights into social systems. However, some of the practices which are currently being used in the animal social networks literature are at worst questionable and at best over-enthusiastic. We highlight some of the areas of method, analysis and interpretation in which greater care may be needed in order to ensure that the biology we extract from our networks is robust. In particular, we suggest that more attention should be given to whether relational data are representative, the potential effect of observational errors and the choice and use of statistical tests. The importance of replication and manipulation must not be forgotten, and the interpretation of results requires care.

Abstract: The abstract concept of equivalence is considered one of the bases of higher-order cognition, and it has been the subject of considerable research in comparative cognition. This study examined the conditions under which tufted capuchin monkeys (Cebus apella) are able to acquire an identity concept. Six capuchin monkeys were trained to solve a visual matching-to-sample (MTS) task on the basis of perceptual identity. The acquisition of the identity rule was inferred from the subject’s ability to solve transfer tests with novel stimuli. We evaluated the ability of the capuchin monkeys to match the shape of novel stimuli after training with both several small stimulus sets (Experiment 1) and a large stimulus set (Experiment 2). Moreover, we examined the ability of capuchins to transfer the concept to novel visual dimensions, such as colour and size and to transfer to novel spatial arrangements of the stimuli (Experiment 2). We demonstrated that the ability of capuchins to match novel stimuli was improved by increasing the number of stimuli used during training (Experiments 1 and 2) and that after a widely applicable identity concept based on the stimulus shape was acquired, the capuchins were able to match stimuli according to an identity rule based on both the colour and size of the stimuli and when the spatial arrangement of the stimuli was varied (Experiment 2). This study is the first to demonstrate that the size of the training set affects the acquisition of an abstract identity concept in an MTS task in non-human primates.

Abstract: The formation of collaborating pairs by individuals belonging to two different classes occurs in the contexts of reproduction and intea-specific cooperation as well as of inter-specific mutualism. There is potential for partner choice and for competition for access to preferred partners in all three contexts. These selective forces have long been recognised as important in sexual selection, but their impact is not yet appreciated in cooperative and mutualistic systems. The formation of partnerships between members of different classes has much in common with the conclusion of trade agreements in human markets with two classes of traders, like producers and consumers, or employers and employees. Similar game-theoretical models can be used to predict the behaviour of rational traders in human markets and the evolutionarily stable strategies used in biological markets. We present a formal model in which the influence of the market mechanism on selection is made explicit. We restrict ourselves to biological markets in which: (1) Individuals do not compete over access to partners in an agonistic manner, but rather by outcompeting each other in those aspects that are preferred by the choosing party. (2) The commodity the partner has to offer cannot be obtained by the use of force, but requires the consent of the partner. These two restrictions ensure a dominant role for partner choice in the formation of partnerships. In a biological market model the decision to cooperate is based on the comparison between the offers of several potential partners, rather than on the behaviour of a single potential partner, as is implicitly assumed in currently accepted models of cooperation. In our example the members of one class A offer a commodity of fixed value in exchange for a commodity of variable value supplied by the other class, B. We show that when the B-class outnumbers the A-class sufficiently and the cost for the A-class to sample the offers of the B-class are low, the choosiness of the A-class will lead to selection for the supply of high value commodities by the B-class (Fig. 3a). Under the same market conditions, but with a high sampling cost this may still be the evolutionariy stable outcome, but another pair of strategies proves to be stable too: relaxed choosiness of class A coupled with low value commodities supplied by class B (Fig. 3b). We give a number of examples of mating, cooperative and mutualistic markets that resemble the low sampling cost situation depicted in Fig. 3a.

Abstract: There is evidence that individuals in animal groups benefit from the presence of knowledgeable group members in different ways. Experiments and computer simulations have shown that a few individuals within a group can lead others, for a precise task and at a specific moment. As a group travels, different individuals possessing a particular knowledge may act as temporary leaders, so that the group will, as a whole, follow their behaviour. In this paper, we use a model to study different factors influencing group response to temporary leadership. The model is based on four individual behaviours. Three of those, attraction, repulsion, and alignment, are shared by all individuals. The last one, attraction toward the source of a stimulus, concerns only a fraction of the group members. We explore the influence of group size, proportion of stimulated individuals, number of influential neighbours, and intensity of the attraction to the source of the stimulus, on the proportion of the group reaching this source. Special attention is given to the simulation of large group size, close to those observed in nature. Groups of 100, 400 and 900 individuals are currently simulated, and up to 8,000 in one experiment. We show that more stimulated individuals and a larger group size both induce the arrival of a larger fraction of the group. The number of influential neighbours and the intensity of the stimulus have a non-linear influence on the proportion of the group arrival, displaying first a positive relationship and then, above a given threshold, a negative one. We conclude that an intermediate level of group cohesion provides optimal transfer information from knowledgeable to naive individuals.