Evaluate the spatial distribution of trace elements in soil of a karst terrain

Abstract

Karst regions represent fragile landscapes that are particularly vulnerable to environmental changes. The study aims to assess the soil quality in the karst basin of Ioannina, which is located in the north-western region of Greece. Factor analysis was employed to evaluate the concentrations of trace elements in the soil. Additionally, Geographical Information Systems (GIS) was utilized to visualize the spatial distribution of these trace elements and their potential sources in relation to the local geology and land use. The study findings underscored that most of the karst landscape in the research area is comprised of Quaternary deposits and it is predominantly occupied by agricultural land. The soil displays substantial levels of clay and silt, with noticeably elevated concentration of iron (Fe), manganese (Mn), nickel (Ni), chromium (Cr), lead (Pb), copper (Cu), vanadium (V), and phosphorous (P) compared to the median concentrations observed in European topsoil. The factor analysis is applied to the dataset of elements content in soil to identify the factors controlling their distribution. Factor 1 involves the geological contribution and the adsorption of Fe–Ni–Cr–Pb–V and lithium (Li) into clay minerals. Factor 1 may be termed as “lithogenic factor”. The cultivated land and road network showed a significant correlation with the higher positive loadings of Fe, Mn, Pb and Cu for Factor 2 which may be termed “agricultural-road network factor”. Agricultural activities and cultivated land presented a significant correlation with the higher positive loadings of nitrate (NO₃⁻), nitrite (NO₂⁻), organic matter (OM), ammonium (NH₄⁺) and P for Factor 3 which may be termed as “agricultural” factor. The higher positive loadings of Factor 4 suggest a variation in the mechanical properties of the Quaternary deposits and may be termed as “soil texture factor”. Quaternary deposits and agricultural land exhibit a strong spatial relationship with factor scores of each factor. Combining factor analysis and GIS proved to be an effective method for identifying and confirming the sources of elements content in soil.