Stochastic models of kleptoparasitism

Yates, G. E. & Broom, M. (2007). Stochastic models of kleptoparasitism. Journal of Theoretical Biology, 248(3), pp. 480-489. doi: 10.1016/j.jtbi.2007.05.007

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Abstract

In this paper, we consider a model of kleptoparasitism amongst a small group of individuals, where the state of the population is described by the distribution of its individuals over three specific types of behaviour (handling, searching for or fighting over, food). The model used is based upon earlier work which considered an equivalent deterministic model relating to large, effectively infinite, populations. We find explicit equations for the probability of the population being in each state. For any reasonably sized population, the number of possible states, and hence the number of equations, is large. These equations are used to find a set of equations for the means, variances, covariances and higher moments for the number of individuals performing each type of behaviour. Given the fixed population size, there are five moments of order one or two (two means, two variances and a covariance). A normal approximation is used to find a set of equations for these five principal moments. The results of our model are then analysed numerically, with the exact solutions, the normal approximation and the deterministic infinite population model compared. It is found that the original deterministic models approximate the stochastic model well in most situations, but that the normal approximations are better, proving to be good approximations to the exact distribution, which can greatly reduce computing time.

Item Type: Article
Uncontrolled Keywords: Analysis of Variance, Animals, Behavior, Animal, Food, Game Theory, Markov Chains, Mathematics, Models, Psychological, Models, Statistical, Probability, Stochastic Processes
Subjects: H Social Sciences > HA Statistics
Q Science > QH Natural history
Divisions: School of Engineering & Mathematical Sciences > Department of Mathematical Science
URI: http://openaccess.city.ac.uk/id/eprint/981

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