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Soil organic matter and labile fractions depend on specific local parameter combinations
Soil  (IF5.841),  Pub Date : 2021-08-27, DOI: 10.5194/soil-2021-81
Malte Ortner, Michael Seidel, Sebastian Semella, Thomas Udelhoven, Michael Vohland, Sören Thiele-Bruhn

Abstract. Soil organic matter (SOM) is an indispensable component of terrestrial ecosystems. Soil organic carbon (SOC) dynamics are influenced by a number of well-known abiotic factors such as clay content, soil pH or pedogenic oxides. These parameters interact with each other and vary in their influence on SOC depending on local conditions. To investigate the latter, the dependence of SOC accumulation on parameters and parameter combinations was statistically assessed that vary on a local scale depending on parent material, soil texture class and land use. To this end, topsoils were sampled from arable and grassland sites in southwestern Germany at four regions with different soil parent material. Principal component analysis (PCA) revealed a distinct clustering of data according to parent material and soil texture that varied largely between the local sampling regions, while land use explained PCA results only to a small extent. The obtained global and the different local clusters of the dataset were further analyzed for the relationships between SOC and mineral phase parameters in order to assess specific parameter combinations explaining SOC and its labile fractions. Analyses were focused on soil parameters that are known as possible predictors for the occurrence and stabilization of SOC (e.g. fine silt plus clay and pedogenic oxides). Regarding the global dataset, we found significant correlations between SOC and its labile fractions hot water-extractable C (HWEC) and microbial biomass C (MBC), respectively and the predictors, yet correlation coefficients were partially low. Mixed effect models were used to identify specific parameter combinations that significantly explain SOC and its labile fractions of the different clusters. Comparing measured and mixed effect models-predicted SOC values revealed acceptable to very good regression coefficients (R² = 0.41–0.91). Thereby, the predictors and predictor combinations clearly differed between models obtained for the whole data set and the different cluster groups. At a local scale site specific combinations of parameters explained the variability of organic matter notably better, while the application of global models to local clusters resulted in less sufficient performance. Independent from that, the overall explained variance generally decreased in the order SOC > HWEC > MBC, showing that labile fractions depend less on soil properties than on organic matter input and turnover in soil.