Distinct spatial dependency of carbon distribution between soil pools in grassland SOIL

Grassland soils play a key role in climate change and food security, and carbon (C) and nitrogen (N) mineralization is central to this. Although there are a number of mathematical models available to estimate C and N mineralization, they do not encompass the variability of the process and there is uncertainty in their predictions. The input parameters of the SOMA model (Soil Organic Matter “A”) have been conceptualized and validated to predict mineralization in arable soils. The objective of this research was to measure the spatial dependence of the input parameters in order to further ob - tain spatial predictions of mineralisation in a grassland system. A nested design was applied using sampling intervals of 30 m, 10 m, 1 m, and 0.12 m as sources of variation. From each sampling point a soil sample was taken (0-23 cm) and physical sequential fractionation was applied to obtain the free light fraction (FLF) and intra-aggregate light fraction (IALF). The C and N contents in the fractions were measured by mass spectrometry, and the results analysed by residual maximum likelihood (REML) to obtain components of variance at each stage, and then accumulated to plot the approach to a variogram. Both fractions showed spatial dependence at the finest scales measured, and the general pattern was different from that in an arable site. The recommended soil sampling interval where C and N mineralization predictions would be spatially distributed according to the correlation of input light fractions parameters of SOMA is 0.5m.