Identifying and Separating the Processes Underlying Boreal Forest Understory Community Assembly

Identifying the ecological processes underlying community assembly remains an elusive goal in community ecology. We formalize assembly hypotheses as alternative models and apply each to predict 1,918 out-of-sample boreal forest understory communities to identify and separate the processes driving community assembly. Models are specified within a Bayesian joint species distribution framework that allows for the inclusion and separation of stochastic processes, environmental filtering, and two different species dependence structures. We found clear evidence that study communities are structured by both environmental filtering and compositional dependence highlighting the importance of selection in community assembly. The relative importance of environmental filtering was greater than compositional dependence in predicting both understory communities and the abundance of constituent species across broad suc-cessional and bioclimatic gradients. Contrary to ecological expectations, the inclusion of a flexible residual species dependence structure (accounting for more than compositional dependence) did not improve model predictions after accounting for the strong role of environmental filtering. Our results provide novel inference on the processes underlying community assembly facilitated by applying empirical approximations of alternative assembly processes to predict communities across a range of environmental conditions. ### Competing Interest Statement The authors have declared no competing interest.