Effects of land-use change and management on soil carbon and nitrogen in the Brigalow Belt, Australia: II. Statistical models to unravel the climate-soil-management interaction

The impact of grazing on soil carbon (C) and nitrogen (N) cycles is complex, and across a large area it can be difficult to uncover the magnitude of the effects. Here, we have linked two common approaches to statistical modelling – regression trees and linear mixed models – in a novel way to explore various aspects of soil C and N dynamics for a large, semiarid bioregion where land use is dominated by grazing. The resulting models, which we term RT-LMM, have the pleasing visual appeal of regression trees, and they account for spatial autocorrelation as per a linear mixed model. Our RT-LMM were developed from explanatory variables that related information on climate, soil and past land management. Response variables of interest were: stocks of soil total organic carbon (TOC), soil total nitrogen (TN), and particulate organic C (POC); the ratio of TOC stock to TN stock; and the relative abundance of stable isotopes δ13C and δ15N in the soil. Each variable was sampled at the depth interval 0–0.3 m. The interactions of land use with, in particular, air temperature and soil phosphorus were strong, but three principal management-related effects emerged: (i) the use of fire to clear native vegetation reduced stocks of TOC and TN, and the TOC : TN ratio, by 25%, 19% and 9%, respectively, suggesting that TOC is more sensitive to fire than TN; (ii) conversion of native vegetation to pasture enriched soil with δ13C by 1.7 ‰; subsequent regrowth of the native vegetation among the pasture restored δ13C to its original level but there was no corresponding change in TOC stock; and, (iii) the time elapsed since clearing reduced POC stocks and the TOC : TN ratio.