Assessing management impacts on soil organic matter quality in subtropical Australian forests using physical and chemical fractionation as well as 13C NMR spectroscopy

Successful soil organic matter (SOM) quality assessment is needed to improve our ability to manage forest soils sustainably. Our objective was to use a multivariate data set to determine whether the land use conversion from native forest (NF) to hoop pine plantation and the following rotation and site preparation practices had altered SOM quality at three adjacent sites of NF, first (1R) and second rotation (2R, including tree planting row (2R–T) and windrow of harvest residues (2R–W)) of hoop pine plantations in southeast Queensland, Australia. Cross-polarization magic angle spinning 13C nuclear magnetic resonance (CPMAS 13C NMR) spectroscopy and sequential hot water and acid hydrolysis were conducted on SOM fractions separated by wet-sieving and density fractionation procedures to characterize SOM quantitative and qualitative relevant parameters, including carbon (C) functional groups, C and nitrogen (N) contents, C/N ratios, and C and N recalcitrant indices. Analysis of variance (ANOVA) and principal component analysis (PCA) of these multivariate parameters together indicated a complicated interaction between physical protection and biochemical recalcitrance, making the land use and management induced changes of SOM quality more complex. Knowledge of PCA based on the refined set of 41 SOM quantitative and qualitative parameters identified that principal component 1 (PC1), which explained 55.7% of the total variance, was most responsible for the management induced changes in soil processes. This was reflected by the dynamics of SOM regarding the aspects of total stock, soil basal and substrate induced respirations, gross and net N mineralization and nitrification, and microbial biomass, microbial diversity of C utilization patterns. Further, the macroaggregates (F250–2000 μm) and the C/N ratio of acid extracts of SOM physical fractions, which represented the most informative and unique variables loading on PC1, might be the most promising physical and chemical measures for SOM quality assessment of land use and management impacts in subtropical Australian forests.