HIERARCHICAL BAYESIAN SCALING OF SOIL PROPERTIES ACROSS URBAN, AGRICULTURAL, AND DESERT ECOSYSTEMS.

The article presents a study which uses a hierarchical Bayesian model of plot-scale soil nutrient pools to predict storage of soil carbon, nitrogen and phosphorus across a mixed land-use region of central Arizona. The Bayesian approach was compared to a traditional approach that multiplied mean values for urban mesic residential, urban xeric residential, nonresidential urban, agricultural and desert areas by the aerial coverage of each land use. It is noted that both approaches suggest that organic carbon, nitrogen and available phosphorus are correlated with each other and are higher in mesic residential and agricultural areas.