The main goal of this session is to illustrate how we can harness the Ecological Data Revolution to improve our understanding and management of biological invasions. Speakers will present their work leveraging distributed plant surveys, e.g., Forest Service Forest Inventory Analysis (FIA) data, The National Park Service’s Inventory & Monitoring datasets (NPS) and the National Ecological Observatory Network (NEON), in addition to remote sensing data. Their work will showcase the use of freely-available spatial data sets that are directly linked to the distribution and abundance of invasive species as predictors of invasion risk, impact and vulnerability. Considerable resources are spent each year to combat non-native invasive species. As a whole, invasive species have significant negative impacts on native communities. Reducing environmental and economic effects of non-native species invasions depends critically on understanding and predicting impact. A primary limiting factor for assessing characteristics of recipient ecosystems that increase vulnerability has been the lack of consistent data collected across a range of ecosystems and encompassing a range of scales. To date, macroscale studies of invasion have focused on invader richness or presence. These metrics address whether a species has successfully been introduced, but provide no insight into impacts on ecological communities. Fortunately, this data limitation has been overcome recently. For example, FIA data, NPS data and NEON data all provide consistently collected, community-level native community surveys across a range of U.S. ecoregions. These data make it possible to quantify invasive species impacts across broad geographic scales and thereby address the key question of what influences the vulnerability of ecosystems to invasion.