Articles | Volume 13, issue 13
https://doi.org/10.5194/bg-13-3863-2016
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, Peter A. Henrys, Rebecca L. Rowe, and Niall P. McNamara

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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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Short summary
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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