Modification of the SPUR rangeland model to simulate species composition and pasture productivity in humid temperate regions

Plant, water, and soil components of the Simulation of Production and Utilization of Rangelands model (SPUR 2.4) were incorporated into the Integrated Farm System Model (IFSM 1.2) to represent the growth and competition of multiple plant species in pastures and their effects on pasture productivity and botanical composition in temperate climates. Developed for semi-arid rangelands, SPUR required major adjustment to represent temperate pastures adequately. In particular, the effects of soil moisture on root and shoot mortality and photosynthetic rates were adjusted to represent greater susceptibility of temperate plants to drought. Sensitivity analysis showed that predicted total shoot dry matter appeared most sensitive to photosynthesis and growth parameters in the spring, soil moisture parameters in the summer, and senescence parameters in autumn. Across all seasons, shoot dry matter appeared most sensitive to optimum photosynthetic temperatures, specific leaf area, start and end dates of senescence, maximum nitrogen concentration in live shoots, and a maximum shoot specific growth rate. The revised pasture model incorporated into IFSM was calibrated with 2002 field data from experimental pastures in central Pennsylvania, USA containing primarily orchardgrass (Dactylis glomerata) and white clover (Trifolium repens). Predictive accuracy of the model was then further evaluated by comparing 2003 data from the same pastures to simulated production. The integrated submodel predicted soil water content and dry matter production relatively well. It did not achieve a desired degree of accuracy in predicting the dynamics of botanical composition; however, adjustment of SPUR subroutines to allow variable maximum root:shoot ratios and competition for light and water may improve predictions. Further development and use of this integrated model can help researchers improve their understanding of temperate pasture systems, identify gaps in knowledge, and prioritize future research needs. Ultimately, the integrated model could provide more accurate assessment of the influence of management strategies on pasture productivity, animal production, and economics at the whole-farm scale.