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Application of regression-kriging and sequential Gaussian simulation for delineation of forest areas potentially suitable for liming in the Jizera Mountains region, Czech Republic

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020702%3A_____%2F20%3AN0000044" target="_blank" >RIV/00020702:_____/20:N0000044 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/abs/pii/S2352009420300353" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S2352009420300353</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.geodrs.2020.e00286" target="_blank" >10.1016/j.geodrs.2020.e00286</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Application of regression-kriging and sequential Gaussian simulation for delineation of forest areas potentially suitable for liming in the Jizera Mountains region, Czech Republic

  • Original language description

    Acidification due to acid atmospheric deposition affected strongly soils of many forested areas with long-term consequences. Liming is often used for amelioration, however, detailed assessment of soil and stand conditions is necessary to avoid possible undesirable effects. The aim of this paper is to apply and compare two spatial modelling methods to delineate probability that the criteria for potential liming in the Jizera Mountains region strongly impacted by acidification are met and to assess the uncertainty. Soil characteristics from the last ten years were evaluated. Specific stands were excluded from consideration (peats, too skeletic stands, waterlogged stands, protected areas). Soils have low pH, low base saturation, and low content of base cations, so that most soil criteria required for potential liming approval are met. Only the ratios C/N and C/P in organic horizons fluctuate around thresholds of 20 and 250, respectively, and their distribution is thus crucial for decision making on liming. Two methods were tested: i) indicator regression-kriging with elevation as a covariate to map the probability that both criteria are met at once, ii) sequential Gaussian simulation to map the probabilities separately and then combining them by multiplying the probabilities. While both methods yielded similar maps of probabilities that the criteria are met, the second approach provided a more diverse map of error distribution, which may play an important role in the decision-making process.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    40102 - Forestry

Result continuities

  • Project

    <a href="/en/project/QK1920163" target="_blank" >QK1920163: Development and verification of spatial models of forest soil properties in the Czech Republic</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Geoderma Regional

  • ISSN

    2352-0094

  • e-ISSN

  • Volume of the periodical

    21

  • Issue of the periodical within the volume

    Jun 2020

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    11

  • Pages from-to

    e00286

  • UT code for WoS article

    000550227900006

  • EID of the result in the Scopus database

    2-s2.0-85085120720