We translate a coagulation-framentation model, describing the dynamics of animal group size distributions, into a model for the population distribution and associate the nonlinear evolution equation with
a Markov jump process of a type introduced in classic work of H. McKean. In particular this formalizes
a model suggested by H.-S. Niwa [J. Theo. Biol. 224 (2003)] with simple coagulation and fragmentation
rates. Based on the jump process, we develop a numerical scheme that allows us to approximate the equilibrium for the Niwa model, validated by comparison to analytical results by Degond et al. [J. Nonlinear
Sci. 27 (2017)], and study the population and size distributions for more complicated rates. Furthermore,
the simulations are used to describe statistical properties of the underlying jump process. We additionally discuss the relation of the jump process to models expressed in stochastic differential equations and
demonstrate that such a connection is justified in the case of nearest-neighbour interactions, as opposed
to global interactions as in the Niwa model.