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    Introducing a mechanistic model in digital soil mapping to predict soil organic matter stocks in the Cantabrian region (Spain)

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    Journal Article (2.900Mb)
    Date
    2021-03
    Author
    Hendriks, C.M.J.
    Stoorvogel, J.J.
    Álvarez‐Martínez, J.M.
    Claessens, L.
    Pérez‐Silos, I.
    Barquín, J.
    Type
    Journal Article
    Review Status
    Peer Review
    Target Audience
    Scientists
    Metadata
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    Abstract/Description
    Digital soil mapping (DSM) is an effective mapping technique that supports the increased need for quantitative soil data. In DSM, soil properties are correlated with environmental characteristics using statistical models such as regression. However, many of these relationships are explicitly described in mechanistic simulation models. Therefore, the mechanistic relationships can, in theory, replace the statistical relationships in DSM. This study aims to develop a mechanistic model to predict soil organic matter (SOM) stocks in Natura2000 areas of the Cantabria region (Spain). The mechanistic model is established in four steps: (a) identify major processes that influence SOM stocks, (b) review existing models describing the major processes and the respective environmental data that they require, (c) establish a database with the required input data, and (d) calibrate the model with field observations. The SOM stocks map resulting from the mechanistic model had a mean error (ME) of −2 t SOM ha−1 and a root mean square error (RMSE) of 66 t SOM ha−1. The Lin's concordance correlation coefficient was 0.47 and the amount of variance explained (AVE) was 0.21. The results of the mechanistic model were compared to the results of a statistical model. It turned out that the correlation coefficient between the two SOM stock maps was 0.8. This study illustrated that mechanistic soil models can be used for DSM, which brings new opportunities. Mechanistic models for DSM should be considered for mapping soil characteristics that are difficult to predict by statistical models, and for extrapolation purposes.
    https://dx.doi.org/10.1111/ejss.13011
    Multi standard citation
    Permanent link to this item
    https://hdl.handle.net/20.500.12478/7113
    IITA Authors ORCID
    Lieven Claessenshttps://orcid.org/0000-0003-2961-8990
    Digital Object Identifier (DOI)
    https://dx.doi.org/10.1111/ejss.13011
    Research Themes
    Natural Resource Management
    IITA Subjects
    Agronomy; Natural Resource Management; Plant Breeding; Plant Production; Soil Surveys and Mapping
    Agrovoc Terms
    Soil Surveys; Soils; Soil Organic Matter; Spain; Soil Mapping
    Regions
    ACP; Europe
    Countries
    Spain
    Hubs
    Eastern Africa Hub
    Journals
    European Journal of Soil Science
    Collections
    • Journal and Journal Articles4835
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