Soil Carbon pp 45-57 | Cite as

Quantitatively Predicting Soil Carbon Across Landscapes

  • Budiman MinasnyEmail author
  • Alex B. McBratney
  • Brendan P. Malone
  • Marine Lacoste
  • Christian Walter
Part of the Progress in Soil Science book series (PROSOIL)


Quantitative prediction of soil carbon (C) in the landscape can be achieved by empirical or mechanistic models, or a combination of both. The empirical approach called digital soil mapping, usually involves: collection of a database of soil carbon observations over an area of interest; compilation of relevant covariates for the area; calibration or training of a spatial prediction function based on the observed dataset; interpolation and/or- extrapolation of the prediction function over the whole area; and finally validation using existing or independent datasets. The resulting digital maps of C can be used in landscape mechanistic models simulating soil organic C evolution laterally and vertically (within the profile). Here we demonstrate the two approaches in predicting C stock evolution in a landscape in Northwest of France. We introduce the pedogeomorphometry approach which can combine the two approaches to map soil carbon dynamics at the landscape scale.


Soil maps Clorpt model Spatial prediction Dynamic soil carbon model 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Budiman Minasny
    • 1
    Email author
  • Alex B. McBratney
    • 2
  • Brendan P. Malone
    • 3
  • Marine Lacoste
    • 4
  • Christian Walter
    • 5
    • 6
  1. 1.Soil Security Laboratory, Faculty of Agriculture and EnvironmentThe University of SydneySydneyAustralia
  2. 2.Faculty of Agriculture, Food & Natural ResourcesThe University of SydneySydneyAustralia
  3. 3.Soil Security Laboratory, Department of Environmental Sciences, Faculty of Agriculture and EnvironmentThe University of SydneySydneyAustralia
  4. 4.Soil Science Research Unit, Centre de recherche d’OrléansOrléans Cedex 2France
  5. 5.INRA, AGROCAMPUS OUEST, UMR 1069, Soil, Agro- and Hydrosystems SpatializationRennesFrance
  6. 6.AGROCAMPUS OUEST, UMR 1069RennesFrance

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