Limit distributions of branching Markov chains

We study branching Markov chains on a countable state space (space of types) X with the focus on the qualitative aspects of the limit behaviour of the evolving empirical population distributions. No conditions are imposed on the multitype offspring distributions at the points of X other than to have the same average and to satisfy a uniform LlogL moment condition. We show that the arising population martingale is uniformly integrable. Convergence of population averages of the branching chain is then put in connection with stationary spaces of the associated ordinary Markov chain on X (assumed to be irreducible and transient). Our principal result is the almost sure convergence of the empirical distributions to a random probability measure on the boundary of an appropriate compactification of X. Final considerations concern the general interplay between the measure theoretic boundaries of the branching chain and the associated ordinary chain.