  Quantitative predictions about the processes that promote species coexistence
are a subject of active research in ecology. In particular, competitive
interactions are known to shape and maintain ecological communities, and
situations where some species out-compete or dominate over some others are key
to describe natural ecosystems. Here we develop ecological theory using a
stochastic, synthetic framework for plant community assembly that leads to
predictions amenable to empirical testing. We propose two stochastic
continuous-time Markov models that incorporate competitive dominance through a
hierarchy of species heights. The first model, which is spatially implicit,
predicts both the expected number of species that survive and the conditions
under which heights are clustered in realized model communities. The second one
allows spatially-explicit interactions of individuals and alternative
mechanisms that can help shorter plants overcome height-driven competition, and
it demonstrates that clustering patterns remain not only locally but also
across increasing spatial scales. Moreover, although plants are actually
height-clustered in the spatially-explicit model, it allows for plant species
abundances not necessarily skewed to taller plants.
