Search for a command to run...
• Ecological intensification of cow-calf systems on Pampas lacks model support. • Model simulations allow evaluation of grazing strategies across time and space. • Herbage density stoichiometrically accounts for high structural sward diversity. • Forage growth is simulated adequately on 5 years of experimental and on-farm data. • The quality of the simulations allows comparisons of alternative grazing plans. Increasing the sustainability of grassland-based livestock farms in the Pampas region requires ecological intensification to increase beef production while preserving and enhancing ecosystem services. This involves farm-context-specific adjustments that capitalize on the complex interplay between the high-diversity grassland and animal dynamics. Modelling is expected to provide insights to elaborate farm redesign plans. A persistent challenge in grassland modelling is achieving both generality and realism in heterogeneous, multispecies native systems, and most grazing models cannot jointly simulate herbage dynamics, animal performance, and multi-paddock management under contrasting climates. The farm-scale PAmpa Sustainable grAzing Livestock Management ( PASpALuM ) model was developed to help address this limitation and provide a framework for quantifying the effects of different combinations of strategic, tactical, and decision-supporting techniques on herbage and animals. Here, we present the model and evaluate the herbage dynamics module. In an accompanying paper, we demonstrated the suitability of PASpALuM for estimating herbage intake, animal growth, and reproductive performance. Herbage height was used as the key state variable, given its ecophysiological relevance for light interception and biomass accumulation and its practical use in the Pampas region. The module was evaluated with two-year experimental and three-year on-farm datasets covering contrasting soils and weather conditions. RMSE for annual herbage accumulation rate, mass, and height was 7.8 and 5.9 kg DM ha⁻ 1 day⁻ 1 , 578 and 512 kg DM ha⁻ 1 , and 1.7 and 1.7 cm for the experimental and on-farm datasets, respectively. Model performance was stronger in autumn and spring and weaker in winter. Mean Squared Deviation ( MSD ) decomposition for herbage accumulation rate showed that lack of correlation ( LC ) dominated the error structure, particularly on-farm (63–88%), reflecting the high natural variability in heterogeneous grasslands. Contributions of non-unity slope ( NU ) were small to moderate (0.5–38%), and systematic bias ( SB ) was low (2–23%). Modelling efficiency ranged from 0.6 to 0.8, indicating good to very good performance. Sensitivity analyses indicated that outputs were most sensitive to maximum accumulation rate, moderately sensitive to water stress effects, and minimally affected by height and temperature correction factors. Overall, the accuracy of the PASpALuM simulations offers scope to compare grazing strategies aimed at increasing herbage height and allowance under contrasting climate scenarios, supporting seasonal grazing management planning at farm and policy levels.