Influence of land type on pasture productivity under variable rainfall: evidence from six SWIFTSYND sites in northern Queensland

Abstract

Inter-annual rainfall variability across northern Australia presents major challenges for grazing management across landscapes characterised by diverse land types and variable pasture responses. Matching livestock numbers to available forage remains fundamental to sustainable and profitable grazing systems. The Queensland FORAGE decision-support system uses the GRASs Production (GRASP) soil-water-pasture growth model to estimate pasture production across contrasting grazing land types. This study integrated measured soil and pasture data with calibrated GRASP simulations to investigate the drivers of pasture productivity across six long-term SWIFTSYND sites representing contrasting Grazing Land Management (GLM) land types in northern Queensland, Australia. Model calibration incorporated land type-specific parameter sets implemented within FORAGE together with detailed soil, pasture and climate measurements collected between 2013 and 2021. Measured soil water holding capacity (SWHC) and maximum pasture nitrogen (N) uptake were evaluated alongside modelled pasture growth and rainfall-use efficiency (RUE). Despite a relatively narrow range in median annual rainfall (485-582 mm), median pasture growth varied markedly among land types, ranging from 1133 to 4147 kg DM ha-1. Box country and Box and napunyah exhibited the lowest SWHC, N uptake and pasture productivity, whereas Loamy alluvials and Yellowjacket with other eucalypts supported greater pasture production. Although Narrow-leaved ironbark on deeper soils had the highest measured SWHC, only moderate pasture growth was simulated, indicating that soil water storage alone did not explain productivity. Yellowjacket with other eucalypts exhibited the highest pasture growth, RUE and N uptake, reflecting the combined influence of soil fertility and pasture composition. These findings demonstrate that land type mediates pasture productivity through interactions among nutrient availability, soil water storage and pasture composition rather than rainfall alone. Integrating measured soil and pasture information with GRASP simulations strengthens FORAGE outputs and supports more informed, land-type-specific grazing and stocking decisions under variable climatic conditions.