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    Teleconnections in spatial modelling

    Access Status
    Fulltext not available
    Authors
    Behrens, T.
    MacMillan, R.A.
    Viscarra Rossel, Raphael
    Schmidt, K.
    Lee, Juhwan
    Date
    2019
    Type
    Journal Article
    
    Metadata
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    Citation
    Behrens, T. and MacMillan, R.A. and Viscarra Rossel, R.A. and Schmidt, K. and Lee, J. 2019. Teleconnections in spatial modelling. Geoderma. 354: 113854.
    Source Title
    Geoderma
    DOI
    10.1016/j.geoderma.2019.07.012
    ISSN
    0016-7061
    Faculty
    Faculty of Science and Engineering
    School
    School of Molecular and Life Sciences (MLS)
    URI
    http://hdl.handle.net/20.500.11937/76701
    Collection
    • Curtin Research Publications
    Abstract

    © 2019 Elsevier B.V. In pedology, spatial context is relevant to soil-landscape systems on at least three different scales: i) the scale of quasi-local processes, which are independent of influence from the direct or wider neighborhood, ii) the scale of short-range processes for example on the local hillslope or catena, and iii) the scale of long-range processes, or teleconnected systems. We can represent the effects of teleconnections using existing tools and covariates, but we cannot easily infer or identify their controls, landscape processes or landscape units. We consider that an ability to identify the relevant controls in teleconnected systems would greatly improve pedological interpretation and understanding. Such understanding relates to the interaction of environmental factors and processes in the spatial context, which is relevant for environmental mapping generally. Here we show that teleconnected systems can be disassembled and interpreted using contextual modelling in such a way that the controls, i.e. the cause, can be localized in space. We present examples of how teleconnected systems can be deciphered. The methodology is based on the previously described ConMap approach in combination with Random Forest's measures of local feature importance. ConMap uses elevation differences, computed along multiple rays radiating out from a center grid cell, as predictors instead of complex surface derivatives or decomposed scales of a digital elevation model (DEM) or terrain attribute. Using synthetic and real-world data sets, we show how to identify and interpret teleconnections in soil environmental systems. In the synthetic example, elevation peaks are shown to produce larger values of soil properties, while, in contrast, a valley-mountain system is the main control of soil texture in the real-world example. Our analyses of teleconnected soil environmental systems illustrate that the stochastic component of the universal model of spatial variation is an integral but typically unresolved part of the deterministic component.

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