Revising the trait‐based filtering framework to include interacting filters: Lessons from grassland restoration

Abstract

Abstract A trait‐based framework of community assembly holds great promise for directing ecological restoration, both for selecting species with desirable traits and for manipulating community factors to enhance plant establishment and persistence. Dispersal, abiotic and biotic factors ‘filter’ species into local communities based on their traits, but interactions among these filters may complicate the use of trait‐based assembly models. In this paper, I review recent studies that apply community‐based theory to grassland restoration and propose a framework for incorporating interacting ecological filters into restoration design. Dispersal limits restoration success in many grassland communities while others are simultaneously limited by dispersal, environmental factors and biotic interactions. Furthermore, the relative importance of ecological filters can change over space and time. Species also differentially respond to filter manipulations which suggests that trait–environment relationships should be used to generate planting recommendations based on optimal trait values for interacting filters at a given site. Synthesis. A better understanding of how traits interact with dynamic community assembly filters will allow for site‐specific management recommendations, resulting in restored communities that are resilient to a range of filter modifications including climate change, invasion by non‐native species, and altered disturbance regimes.