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Ecologists increasingly use plot-scale data to inform research and policy related to regional and global environmental change. For soil chemistry research, scaling from the plot to the region is especially difficult due to high spatial variability at all scales. We used a hierarchical Bayesian model of plot-scale soil nutrient pools to predict storage of soil organic carbon (oC), inorganic carbon (iC), total nitrogen (N), and available phosphorus (avP) in a 7962-km2 area including the Phoenix, Arizona, USA, metropolitan area and its desert and agricultural surroundings. The Bayesian approach was compared to a traditional approach that multiplied mean values for urban mesic residential, urban xeric residential, nonresidential...