IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0152098.html
   My bibliography  Save this article

Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe

Author

Listed:
  • Ece Aksoy
  • Yusuf Yigini
  • Luca Montanarella

Abstract

Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because of playing key roles in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distribution of SOC content for Europe. Therefore this study aims searching for another aspect of this issue by looking to the performances of using aggregated soil samples coming from different studies and land-uses. The total number of the soil samples in this study was 23,835 and they’re collected from the “Land Use/Cover Area frame Statistical Survey” (LUCAS) Project (samples from agricultural soil), BioSoil Project (samples from forest soil), and “Soil Transformations in European Catchments” (SoilTrEC) Project (samples from local soil data coming from six different critical zone observatories (CZOs) in Europe). Moreover, 15 spatial indicators (slope, aspect, elevation, compound topographic index (CTI), CORINE land-cover classification, parent material, texture, world reference base (WRB) soil classification, geological formations, annual average temperature, min-max temperature, total precipitation and average precipitation (for years 1960–1990 and 2000–2010)) were used as auxiliary variables in this prediction. One of the most popular geostatistical techniques, Regression-Kriging (RK), was applied to build the model and assess the distribution of SOC. This study showed that, even though RK method was appropriate for successful SOC mapping, using combined databases was not helpful to increase the statistical significance of the method results for assessing the SOC distribution. According to our results; SOC variation was mainly affected by elevation, slope, CTI, average temperature, average and total precipitation, texture, WRB and CORINE variables for Europe scale in our model. Moreover, the highest average SOC contents were found in the wetland areas; agricultural areas have much lower soil organic carbon content than forest and semi natural areas; Ireland, Sweden and Finland has the highest SOC, on the contrary, Portugal, Poland, Hungary, Spain, Italy have the lowest values with the average 3%.

Suggested Citation

  • Ece Aksoy & Yusuf Yigini & Luca Montanarella, 2016. "Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-17, March.
  • Handle: RePEc:plo:pone00:0152098
    DOI: 10.1371/journal.pone.0152098
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152098
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0152098&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0152098?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mareike Ließ, 2022. "Modeling the Agricultural Soil Landscape of Germany—A Data Science Approach Involving Spatially Allocated Functional Soil Process Units," Agriculture, MDPI, vol. 12(11), pages 1-31, October.
    2. Guiomar, N. & Godinho, S. & Pinto-Correia, T. & Almeida, M. & Bartolini, F. & Bezák, P. & Biró, M. & Bjørkhaug, H. & Bojnec, Š. & Brunori, G. & Corazzin, M. & Czekaj, M. & Davidova, S. & Kania, J. & K, 2018. "Typology and distribution of small farms in Europe: Towards a better picture," Land Use Policy, Elsevier, vol. 75(C), pages 784-798.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0152098. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.