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The stochastic modelling of kleptoparasitism using a Markov process

Broom, M., Crowe, M. L., Fitzgerald, M. R. and Rychtar, J. (2010). The stochastic modelling of kleptoparasitism using a Markov process. Journal of Theoretical Biology, 264(2), pp. 266-272. doi: 10.1016/j.jtbi.2010.01.012

Abstract

Kleptoparasitism, the stealing of food items from other animals, is a common behaviour observed across a huge variety of species, and has been subjected to significant modelling effort. Most such modelling has been deterministic, effectively assuming an infinite population, although recently some important stochastic models have been developed. In particular the model of Yates and Broom (Stochastic models of kleptoparasitism. J. Theor. Biol. 248 (2007), 480–489) introduced a stochastic version following the original model of Ruxton and Moody (The ideal free distribution with kleptoparasitism. J. Theor. Biol. 186 (1997), 449–458), and whilst they generated results of interest, they did not solve the model explicitly. In this paper, building on methods used already by van der Meer and Smallegange (A stochastic version of the Beddington-DeAngelis functional response: Modelling interference for a finite number of predators. J. Animal Ecol. 78 (2009) 134–142) we give an exact solution to the distribution of the population over the states for the Yates and Broom model and investigate the effects of some key biological parameters, especially for small populations where stochastic models can be expected to differ most from their deterministic equivalents.

Publication Type: Article
Publisher Keywords: Stealing, Finite population, Uptake rate, Interference, Detailed balance, IDEAL FREE DISTRIBUTION, TRICHOTROPIS-CANCELLATA, FUNCTIONAL-RESPONSE, GAME-THEORY, BEHAVIOR, INTERFERENCE, PREDATORS, THERIDIIDAE, EVOLUTION, CONSEQUENCES
Subjects: H Social Sciences > HA Statistics
Q Science > QH Natural history
Departments: School of Mathematics, Computer Science & Engineering > Mathematics
URI: http://openaccess.city.ac.uk/id/eprint/982
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