Published: Aug. 1, 2015

EBIO postdoc Julia Ng (Smith lab) and Robert Laport (University of Nebraska, Lincoln) are recent recipients of an NSF grant aimed at understanding how communities of species (plants in particular), are assembled and maintained over time. They will use data from NEON, ecologist's big data, big science project. Congratulations Julia and Robert!

Abstract:

EAGER-NEON: Disentangling the Roles of Ecological and Historical Processes in Community Structure: A Continental-Scale Approach

Overview:

Communities are assembled according to a number of processes operating across spatial and temporal scales. In particular, both ecological (e.g. competitive exclusion, environmental filtering) and historical processes (e.g. speciation, dispersal) are considered central to the assembly process. However, disentangling the roles that these two processes play in shaping community structure remains a major challenge because both ecological and historical processes can give rise to similar patterns, and patterns of diversity within and among communities can vary with spatial and taxonomic scale. The goal of the proposed research is to conduct a large, integrative investigation of the relative roles of ecological and historical processes in governing woody perennial plant communities, by combining NEON-collected plant community data and phylogenetic comparative methods to address three related questions: (1) How have historical processes shaped patterns of community structure? (2) How have species functional traits shaped patterns of community structure? (3) Are communities of closely related species more susceptible to non-native species invasion? This comprehensive, continental-scale window into communities across several ecoregions offers a unique opportunity to combine phylogenetic data with species occurrence, abundance, and trait data to better understand the importance of ecological and historical processes as determinants of community structure at multiple spatial and taxonomic scales. Moreover, this project represents a novel and immediate application of NEON-collected data to address long-standing ecological and evolutionary questions.