Building geochemically based quantitative analogies from soil classification systems using different compositional datasets.

ABSTRACT: Soil heterogeneity is a major contributor to the uncertainty in near-surface biogeochemical modeling. We sought to overcome this limitation by exploring the development of a new classification analogy concept for transcribing the largely qualitative criteria in the pedomorphologically based, soil taxonomic classification systems to quantitative physicochemical descriptions. We collected soil horizons classified under the Alfisols taxonomic Order in the U.S. National Resource Conservation Service (NRCS) soil classification system and quantified their properties via physical and chemical characterizations. Using multivariate statistical modeling modified for compositional data analysis (CoDA), we developed quantitative analogies by partitioning the characterization data up into three differe

SUBMITTER: Chappell MA 

PROVIDER: S-EPMC6380586 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature