HIERARCHICAL BAYESIAN SCALING OF SOIL PROPERTIES ACROSS URBAN, AGRICULTURAL, AND DESERT ECOSYSTEMS
Jason P. Kaye, Anandamayee Majumdar, Corinna Gries, Alexander Buyantuyev, Nancy B. Grimm, D. Hope, G. Darrel Jenerette, Weixing Zhu, Lawrence A. Baker
Ecological Applications
Urban Farm DB summary
A study in a 7962-km2 area around Phoenix, Arizona, USA, used a hierarchical Bayesian model to predict soil organic carbon (oC), inorganic carbon (iC), total nitrogen (N), and available phosphorus (avP) storage. Both Bayesian and traditional approaches indicated that oC, N, and avP were higher in mesic residential and agricultural areas than in deserts or xeric residential areas. Cultural variables like impervious surface cover, tree cover, and turfgrass cover were significant predictors, and an estimated 1140 Gg of oC and 130 Gg of N had accumulated in human-dominated soils.