首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Hierarchical Bayesian scaling of soil properties across urban, agricultural, and desert ecosystems.
Authors:J P Kaye  A Majumdar  C Gries  A Buyantuyev  N B Grimm  D Hope  G D Jenerette  W X Zhu  L Baker
Institution:Department of Crop and Soil Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA. jpk12@psu.edu
Abstract: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 urban, agricultural, and desert areas by the aerial coverage of each land-use type. Both approaches suggest that oC, N, and avP are correlated with each other and are higher (in g/m2) in mesic residential and agricultural areas than in deserts or xeric residential areas. In addition to traditional biophysical variables, cultural variables related to impervious surface cover, tree cover, and turfgrass cover were significant in regression models predicting the regional distribution of soil properties. We estimate that 1140 Gg of oC have accumulated in human-dominated soils of this region, but a significant portion of this new C has a very short mean residence time in mesic yards and agricultural soils. For N, we estimate that 130 Gg have accumulated in soils, which explains a significant portion of "missing N" observed in the regional N budget. Predictions for iC differed between the approaches because the Bayesian approach predicted iC as a function of elevation while the traditional approach employed only land use. We suggest that Bayesian scaling enables models that are flexible enough to accommodate the diverse factors controlling soil chemistry in desert, urban, and agricultural ecosystems and, thus, may represent an important tool for ecological scaling that spans land-use types. Urban planners and city managers attempting to reduce C emissions and N pollution should consider ways that landscape choices and impervious surface cover affect city-wide soil C, N, and P storage.
Keywords:
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号