Spatial variation and distribution of soil organic carbon in an urban ecosystem from high-density sampling

With acceleration of urban expansion, urban soils are increasingly becoming critical in the global carbon cycle. However, spatial variations and distributions of soil organic carbon (SOC) across urban centers are rarely investigated. Here, 1018 soil samples were collected from the upper 20 cm soil layer in Xi'an — a typical historical city under rapid urbanization in China. The aims were to: i) determine current levels and variations in SOC; ii) identify main driving factors of SOC density (SOCD); and iii) compare different interpolation methods in predicting spatial distributions of SOCD in Xi'an City study area. Results showed that the range of SOC concentration (SOCC) was 1.57–38.58 g kg⁻¹ (mean of 13.59 g kg⁻¹) and the range of SOCD was 0.47–9.48 kg m⁻² (mean of 3.59 kg m⁻²). Analysis of coefficient of variation showed that there were moderate variations in SOCC (54.0%) and SOCD (49.4%) in the study area. Combined correlation analysis, principal component analysis and minimum dataset compilation showed that sand content, distance to civic center, land use type and vegetation type were closely correlated with spatial variations in SOCD. Geostatistical analysis showed that isotropic exponential model with a range of 1776 m was the best fit for SOCD semi-variogram. Spatial distribution of SOCD was further predicted using four approaches — ordinary kriging (OK), inverse distance weighting (IDW), multiple linear regression (MLG) and regression kriging (RK). The spatial prediction accuracy was ranked in order of RK > MLR > OK > IDW. However, there was relatively low interpolation accuracy for the four approaches. This was attributed to the high spatial variations in urban milieu, impacted by intense anthropogenic activities. The findings in this study added to current knowledge on global carbon cycle as influenced by urban soils, which is a critical guide to land management in urban areas.