PS 2-15 - Drivers shaping plant communities recovering from disturbance at Mount St. Helens

Abstract: Assessing the major drivers of plant community assembly and their changes over time during succession is critical for understanding how plant communities respond to disturbances. Previous studies have identified dispersal limitation and environmental filtering as important drivers of plant community assembly during primary succession, but how these processes shift in relative influence over time remains poorly understood. We used environmental and spatial data to assess differences in plant community composition from 2007–2016 across 165 sites in the Mount St. Helens pumice plains. In our model, we interpreted variation in species composition explained by the environmental data as evidence as environmental filtering, while variation explained by spatial data was interpreted as evidence of dispersal limitation. We expected to find dispersal limitation as the more important driver earlier in succession and for environmental filtering to be more important in later succession because in early succession, community assembly will be governed largely by stochastic colonization events. As the landscape develops and becomes more heterogenous, deterministic processes such as environmental filtering likely exert a greater influence on plant communities. We used a variation partitioning approach to test whether the influence of deterministic community assembly processes increased over time. We found a shift in the relative influence of plant community assembly processes over time, with dispersal limitation being more prominent early in the succession but environmental filtering becoming more important later in the succession. Therefore, our results suggest that deterministic processes are more influential as plant communities recover from disturbance at Mount St Helens. Results of this study provide a more in-depth understanding of the fundamental drivers shaping plant communities after major disturbances and their variable roles over time. Understanding these drivers will not only help answer fundamental questions in community ecology but also inform management decisions after large disturbances.