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This paper is motivated by examples from stochastic reaction network theory. The Q-matrix of a stochastic reaction network can be derived from the reaction graph, an edge-labelled directed graph encoding the jump vectors of an associated continuous time Markov chain on the invariant space . An open question is how to decompose the space into neutral, trapping, and escaping states, and open and closed communicating classes, and whether this can be done from the reaction graph alone. Such general continuous time Markov chains can be understood as natural generalizations of birth-death processes, incorporating multiple different birth and death mechanisms. We characterize the structure of imposed by a general Q-matrix generating continuous time Markov chains with values in , in terms of the set of jump vectors and their corresponding transition rate functions. Thus the setting is not limited to …