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