Forest Soil Physico-Chemical Sorption Spatial Links in Central-European Systems of Site Geographical Divisions

0543707 - ÚVGZ 2022 RIV CZ eng K - Konferenční příspěvek (tuzemská konf.)
Samec, Pavel - Balková, M. (ed.) - Kučera, A. (ed.)
Forest Soil Physico-Chemical Sorption Spatial Links in Central-European Systems of Site Geographical Divisions.
CONTEMPLATING EARTH: SOIL AND LANDSCAPE CONSIDERATIONS. Brno: Mendel university Brno, 2020 - (Balkova, M.; Kucera, A.; Samec, P.), (2020), s. 75-89. ISBN 978-80-7509-766-8.
[Conference on Contemplating Earth - A Solution within Research Project TJ02000265 - Multifunctional Anti-Erosion Measures as part of the Adaptable Landscape. Brno (CZ), 01.10.2020-02.10.2020]
Grant CEP: GA MŠMT(CZ) LM2018123
Institucionální podpora: RVO:86652079
Klíčová slova: cation-exchange capacity * organic-matter * weighted regression * resolution * fractions * ratios * soil aluminium * base saturation * geodiversity * geographically weighted regression
Obor OECD: Forestry

Spatial links among soil property values influence variability of soil sorption. The aim of this study was to compare the effect of geotectonic, soil-and biogeographical divisions on forest soil physicochemical sorption spatial links. The effect was investigated through optimal model selection and its comparison among the soil cover division systems of Central-European Highlands in the Czech Republic. Optimal model was selected through the closest-fitting estimations of linear global and local regressions between sorption and chemical or geomorphological forest soil properties. The optimal model comparison was carried out through linear regression with bedrock type proportion (geodiversity) at units of particular division systems. Chemical properties influenced forest soil sorption more than relief. Soil base saturation (BS) was locally more divided than cation exchange capacity (CEC). Local regression of BS with Al2O3 was divided by geotectonic systems the most, but it was not influenced by geodiversity. Geodiversity influenced local regression of CEC with Al2O3 in soil regions as well as regression with C/N in biogeographical regions. Differences between spatial links of BS and CEC suggest that forest soil sorption is divided into multi-level clusters. Spatial link modelling of soil sorption can optimalize forest growth condition division for effective management use.
Trvalý link: http://hdl.handle.net/11104/0320881