Study of the tree species effect on the soil by means of discriminant analysis

Abstract

A multi-sided study of the interactions between forest and soil requires choosing sample plots in such a way when their soil characteristics are as similar as possible but the types of biocoenoses are different. This study employed materials from the database “Soils of Karelia”, which has pooled together long-term data on soils of the Republic of Karelia. The aim of the analysis was to identify the soil traits that are the most sensitive to the type of biocoenosis. The biocoenoses chosen for the analysis were automorphic pine, spruce and birch communities, collectively accounting for 99 % of forest stands in Karelia, growing on podzolic-type Al-Fe-humus soils with sandy texture over sandy or loamy-sand till, which represent the most widespread type of soils in the study area. The analysis was performed for the following soil horizons: forest floor (O), eluvial (E) and illuvial (B). In order to characterize the soil horizons the physico-chemical parameters were used: рН (KCl), total С and N content, labile P205 and K20 compounds content, and gross content of SiO2, TiO2, Al2O3, Fe2O3, MnO, MgO, CaO, Na2O, K2O, P2O5. Discriminant analysis was employed to determine the traits contributing the most to the differentiation of biocoenosis types. The contribution of the traits to differentiation between groups was measured by Wilks’ lambda. Overall, the analysis has shown that N and C content the most significantly reflect the changes happening under the effect of the forest, both in the organic and in the mineral parts of the soil, as corroborated by the findings of numerous Russian and foreign researchers.

Keywords

• forest type effect on soil
• database
• statistical methods