Ecological restoration is notoriously unpredictable because similar actions can result in different outcomes. Outcomes can also differ for species and functional components of communities depending on how restoration actions and abiotic conditions alter community assembly trajectories. Quantifying variation in community trajectories across restorations for both species and traits is rare, but can help to resolve underlying assembly processes and refine strategies to maximize restoration success. We quantified the importance of soil resources, seed mix richness, and prescribed fire for variation in plant species and functional trait trajectories over six years across 20 restored tallgrass prairies in the midwestern United States. We predicted stronger convergence for traits than species, with species and trait compositions converging more across restorations on resource-poor soils and with frequent fires due to stronger abiotic filtering. In contrast, we predicted species and trait compositions would converge more slowly or diverge across restorations with resource-rich soils, with less frequent fires, and seeded with more species due to weaker filtering and more stochasticity. Communities generally converged over time; however, the rate of convergence was determined by soil resources, not restoration actions. Restorations converged more across resource-rich sites. In contrast to patterns of species convergence, variation in trait composition remained stable over time regardless of soil resources or restoration actions. The unexpected pattern of species, but not trait, convergence during community assembly appears to result from increasing dominance of a native C4 bunchgrass, Andropogon gerardii, that coincides with proportional declines of other C4 grasses that share similar traits. Synthesis and applications: restoration outcomes may be more predictable than typically considered. Trait compositions were stable and variation in species compositions decreased over time owing to site conditions, where resource-rich soils produced more consistent outcomes. Our study shows monitoring multiple facets of biodiversity across restorations can reveal why outcomes vary and inform broad-scale restoration planning.

The datasets were collected in 20 restored tallgrass prairies in southwestern Michigan, USA. The raw data and code provided were used to derive the analysis dataset (also included) to produce all results and figures reported in the main paper referenced above. species_plot_data.csv: This data file includes herbaceous plant community composition data sampled in 2011, 2013, and 2016 for each of 20 restored tallgrass prairies in Southwestern Michigan. Values denote the percent cover of each plant in 10 1-m2 plots spaced evennely along 45-m transects randomly oriented in the center of each site. Species percent cover in a given plot can sum to more than 1 if individuals are overlapping, or sum to less than 1 when bareground is present. site_predictors.csv: This data file includes all the site identifiers and predictor variables (soil types, prescribed fire frequency, seed mix richness) used in the analyses. DATA_model_metrics: This data file includes the final species and trait dissimilarities, along with all relevant predictor variables, used to model changes in variation in community composition across restorations. Species and trait dissimilarity values are the distance from the centroids of all sites in principal coordinate space. These values are calculated from the raw composition data using the accompanying R scripts.

See README_catano_datasets.txt for metadata and usage notes The readme file contains descriptions for each dataset and variables. It also details script used to produced the derived data used in analyses. Full details of analyses and methods are described in the associated manuscript referenced above.