Comprehensive Soil Classification System 2.0 (CSCS2.0): A comprehensive soil classification system for quantitatively identifying soils across the world Abstract submitted to 22nd World Congress of Soil Science - Glasgow 2022 Authors: Alex B. McBratney1, Budiman Minasny1, Jingyi Huang2, Dominique Arrouays3, Anne C. Richer-de-Forges3, Igor Savin4, Erika Michéli5, Lúcia Helena Cunha dos Anjos6, Yuri Gelsleichter6, Sang Ho Jeon6 1 School of Life and Environmental Sciences & Sydney Institute of Agriculture, The University of Sydney, NSW, 2010, Australia 2 Department of Soil Science, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA 3 INRAE, InfoSol, 45075, Orléans, France 4 Dokuchaev Soil Science Institute, 119017 Moscow, Russia 5 Hungarian University of Agriculture and Life Sciences, Institute of Environmental Sciences, H-2100, Gödöllő, Hungary 6 Soils Department, Graduate Program in Agronomy-Soil Science (PPGA-CS), Federal Rural University of Rio de Janeiro (UFRRJ), Seropédica, Rio de Janeiro, 23897-000, Brazil 7 National Institute of Agricultural Sciences, Rural Development Administration, Wanju 54875, Republic of Korea
Soil classification enables understanding of the variation and sustainable use of soil across the landscape and ultimately across the world. Due to the different criteria used in soil classification, cross-referencing between systems is difficult. Although efforts have been made to build classification systems representing the world’s soils (e.g., World Reference Base for Soil Resources – WRB, Soil Taxonomy – ST), adopting these more global systems is often difficult given the intensive soil information previously collected and characterized using existing national systems. Recent research organized via the IUSS Working Group on Advances in Universal Soil Classification has attempted to build a dynamic Comprehensive Soil Classification System (CSCS) sequentially merging existing soil taxa (approximately at the Great Group level) from global, regional and national systems. Here, we present an updated system (CSCS2.0) comprising centroids of soil morphological (e.g., color), physical (e.g., particle size), and chemical (e.g., pH, exchangeable cations) properties measured in the 0–1.5 m depth. The optimized soil taxa originate from ST, WRB, Australian Soil Classification (ASC), New Zealand Soil Classification (NZ), French Soil Classification (Fr), Russian Soil Classification (Ru), Brazilian Soil Classification (Br), and Korean Soil Classification (Kr). CSCS2.0 characterizes soil taxa in the principal component space of the soil properties defining the centroids and allows identifying unknown soils quantitatively using names of existing soil taxa from various classification systems which are combined, or via a new systematic nomenclature created for the CSCS2.0. We hope to sequentially add taxa from other soil classification systems to build up a truly global representation.
In this GitHub Repository, we provided the R function and some sample data to demonstrate the use of the CSCS2.0 to allocate any unknown soil profile data to the CSCS2.0. If the distance of the unknown soil profile to the closest taxa in the CSCS2.0 is small than 25, we can assign the existing name of the closest taxa to this unknown profile. Otherwise, we would most likely need to add this profile as a new taxa in the CSCS2.0. For reference, please refer to our previously published papers on CSCS from here: Hughes, P., McBratney, A., Huang, J., Minasny, B., Hempel, J., Palmer, D. J., & Micheli, E. (2017). Creating a novel comprehensive soil classification system by sequentially adding taxa from existing systems. Geoderma regional, 11, 123-140.