Vegetation surveys at Zion National Park (Zion), Utah, have contributed to our understanding of plant community patterns and their relationship to environmental factors. Previous authors used vegetation plot data to characterize vegetation types at Zion following conventional procedures that emphasize spatial discreteness and dominant species. We developed and applied an alternative approach for community characterization that emphasizes nondiscrete presence-absence patterns and is compatible with the individualistic concept. We reanalyzed existing plot data from Zion using coalition clustering, an algorithm that identifies groups of positively-associated species referred to as coalition groups. Each species and plot in the data set was linked to each coalition group via an “affinity” value obtained through weighted averaging. Affinity values were used to characterize environmental affinities of coalition groups through regression tree modeling and predictive mapping. We also identified species that frequently co-occurred with coalition groups (affiliate species) and those that frequently co-occurred with high cover (dominant-affiliates), viewing these as alternatives to conventional prevalent and dominant species. Following this approach, we identified 10 coalition groups at Zion that overlapped compositionally and spatially to differing degrees. Mesic environments on a gradient from low-elevation riparian zones through mid-elevation narrow canyons to high-elevation plateaus were represented by 3 overlapping groups. Two groups occupying slickrock and sand environments were detected on the Navajo Sandstone, as well as 2 on mesa tops above it. At lower elevations, 3 intergrading xeric coalition groups were distinguished. When previously classified associations of the National Vegetation Classification were clustered based on shared affinities to coalition groups, the arrangement differed from existing classification schemes but was environmentally interpretable. Although these patterns are contingent on conditions at the time of data collection, they provide a baseline that could be used for evaluating and predicting plant community change in the park. With proper attention to sampling and analysis issues, our community characterization approach could be applied in other settings as an alternative or supplement to conventional vegetation classification.