Towards an integrated phosphorus, carbon and nitrogen cycling model for topographically diverse grasslands

Contemporary science on how livestock influence nutrient cycling in grazing systems is limited, particularly in topographically complex (i.e., slopes and aspects) hill country landscapes. Prominent slope and aspect variation affects primary production, animal behaviour and nutrient return. Here, we embed recent scientific advancements in nutrient dynamics across complex landscapes to (1) set up a soil organic carbon (SOC) saturation function to an existing SOC and total soil phosphorus (TSP) model (Bilotto et al. J N Z Grassl 81:171–178, 2019. https://doi.org/10.33584/jnzg.2019.81.397), (2) include total soil nitrogen (TSN) dynamics, and (3) establish if the model (herein the Grass-NEXT model) can simulate the spatial and temporal changes of TSP, SOC and TSN in hill country. A long-term P fertiliser experiment with contrasting different P fertilisation levels and associated sheep stocking regimes (herein, ‘farmlets’) was used for model testing. The Grass-NEXT model predicted TSP and SOC stocks with strong accuracy and precision (model performance), and TSN with a moderate performance across farmlets [Concordance Correlation Coefficient (CCC), 0.75, 0.72 and 0.49, respectively]. Grass-NEXT model simulated TSP, SOC and TSN distribution with moderate/strong performance across slopes (CCC, 0.94, 0.80 and 0.70) and aspects (CCC, 0.83, 0.67 and 0.51). Consistent with observed data, modelled changes in TSP and TSN were greater on low slopes and eastern aspects, but no clear pattern was observed for SOC stocks. The Grass-NEXT model provides an intuitive research tool for exploring management options for increasing SOC and TSN, as well as an instrument for monitoring and reporting on nutrient dynamics in complex landscapes.