We review the underlying principles of plant community assembly and build a conceptual model into which we map experiments and simulation approaches. In this model, environmental filtering selects individuals from a species pool based on non-independent traits bounded by trade-offs. The feedback of communities on environmental factors mimics plant-plant interactions, producing fine-scale heterogeneity and spatial/temporal nesting among factors, which affect trait diversity in the communities. Synthetic community experiments focus on the effects of a target species mixture on ecosystem functioning, and weeding non-target species usually halts the assembly process. Experiments on natural communities involve manipulating established assembly processes in pre-existing communities through species removal or addition, altering resources, conditions, or disturbances. Stochastic, individual-based models can simulate plant metacommunities, either based on ecophysiological mechanisms or statistical approaches to predict the successful establishment of individual plants based on their traits and local conditions and implicitly model plant interactions through the feedback of the community on the environment. Synthesis. Experiments and simulation models are promising tools for studying plant community assembly, yet further exploration is needed on the coordination between functional traits during environmental filtering, the feedback from the existing community on environmental factors, and nested environmental factors creating fine-scale heterogeneity.