Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 554185
Title Assessing the climate regulation potential of Agricultural soils using a decision support tool adapted to stakeholders' needs and possibilities
Author(s) Broek, Marijn Van de; Henriksen, Christian Bugge; Ghaley, Bhim Bahadur; Lugato, Emanuele; Kuzmanovski, Vladimir; Trajanov, Aneta; Debeljak, Marko; Sandén, Taru; Spiegel, Heide; Decock, Charlotte; Creamer, Rachel; Six, Johan
Source Frontiers in Environmental Science 7 (2019). - ISSN 2296-665X
DOI https://doi.org/10.3389/fenvs.2019.00131
Department(s) PE&RC
Soil Biology
Publication type Refereed Article in a scientific journal
Publication year 2019
Abstract Soils perform many functions that are vital to societies, among which their capability to regulate global climate has received much attention over the past decades. An assessment of the extent to which soils perform a specific function is not only important to appropriately value their current capacity, but also to make well-informed decisions about how and where to change soil management to align the delivered soil functions with societal demands. To obtain an overview of the capacity of soils to perform different functions, accurate and easy-to-use models are necessary. A problem with most currently-available models is that data requirements often exceed data availability, while generally a high level of expert knowledge is necessary to apply these models. Therefore, we developed a qualitative model to assess how agricultural soils function with respect to climate regulation. The model is driven by inputs about agricultural management practices, soil properties and environmental conditions. To reduce data requirements on stakeholders, the 17 input variables are classified into either (1) three classes: low, medium and high or (2) the presence or absence of a management practice. These inputs are combined using a decision tree with internal integration rules to obtain an estimate of the magnitude of N2O emissions and carbon sequestration. These two variables are subsequently combined into an estimate of the capacity of a soil to perform the climate regulation function. The model was tested using data from long-term field experiments across Europe. This showed that the model is generally able to adequately assess this soil function across a range of environments under different management practices. In a next step, this model will be combined with models to assess other soil functions (soil biodiversity, primary productivity, nutrient cycling and water regulation and purification). This will allow the assessment of trade-offs between these soil functions for agricultural land across Europe.
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