Discriminating factors of the spatial variability of soil quality parameters at landscape-scale

The aim of the study was to evaluate the spatial variability pattern of some soil quality parameters at landscape-scale, particularly soil microbial biomass-C (C-mic) and -N (N-mic), and soil microbial activity (respiration) as well as soil organic carbon (C-mic), and hot water extractable carbon (C-hwe) by multivariate analyses of variance and canonical discriminant analyses (CDA). The study area was the Trier region, Rhineland-Palatinate, which is characterized by a wide range of soil types developed from various parent materials. Additionally, the investigated fields differed in soil management intensity (conventional, integrated, organic farming) and crops grown. Within the whole study area CDA revealed a separation into three sub-areas. Within the sub-areas the soil quality parameters were significantly influenced by the soil management systems and the crops grown. Despite the spatial variability and the relationship to soil management, the contents of C-mic could be predicted by stepwise multiple linear regression models, both for arable and grassland soils. The explained variance for the regression models were 72 % for arable soils and 63 % for grassland soils, respectively. Regression models for predicting N-mic and microbial activity revealed an explained variance between 30 and 58 %.