Articles | Volume 13, issue 13
Biogeosciences, 13, 3863–3868, 2016
https://doi.org/10.5194/bg-13-3863-2016
Biogeosciences, 13, 3863–3868, 2016
https://doi.org/10.5194/bg-13-3863-2016

Technical note 06 Jul 2016

Technical note | 06 Jul 2016

Technical note: A bootstrapped LOESS regression approach for comparing soil depth profiles

Aidan M. Keith et al.

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Cited articles

Adhikari, K., Hartemink, A. E., Minasny, B., Bou Kheir, R., Greve, M. B., and Greve, M. H.: Digital mapping of soil organic carbon contents and stocks in Denmark, PLoS One 9, e105519, https://doi.org/10.1371/journal.pone.0105519, 2014.
Bishop, T. F. A., McBratney, A. B., and Laslett, G. M.: Modelling soil attribute depth functions with equal-area quadratic smoothing splines, Geoderma, 91, 27–45, 1999.
Clifford, D., Dobbie, M. J., and Searle, R.: Non-parametric imputation of properties for soil profiles with sparse observations, Geoderma, 232–234, 10–18, 2014.
Diggle, P. J., Gómez-Rubio, V., Brown, P. E., Chetwynd, A. G., and Gooding, S.: Second-Order Analysis of Inhomogeneous Spatial Point Processes Using Case–Control Data, Biometrics, 63, 550–557, 2007.
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It is important to be able to assess whether changes in land use or management affect soil properties, but testing differences between soil profiles can be challenging. We developed a straightforward approach that makes use of soil core data (which are not spatially independent) to compare soil properties at specific locations down a depth profile. We hope that this approach can be used more widely, based on new or existing data, to examine the impacts of land use and management on soils.
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