Author
Corson, Michael | |
Rotz, Clarence - Al | |
Skinner, Robert |
Submitted to: Agricultural Systems
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 11/24/2004 Publication Date: 10/16/2005 Citation: Corson, M.S., Rotz, C.A., Skinner, R.H. 2005. Modification of the SPUR rangeland model to simulate species composition and pasture productivity in humid temperate regions. Agricultural Systems. 87:169-191. Interpretive Summary: Dairy and beef farmers who graze their cattle tend to rely on only a few forage plant species in their pastures. Recent studies suggest that planting more species in pastures can produce more forage, even out the supply of forage throughout the year, and in some cases reduce the loss of nitrogen and phosphorus to ground and surface waters. Long-term studies evaluating the benefits of these effects for producers are difficult, expensive, and impractical. Computer simulation provides a more feasible approach for evaluating the economic and environmental benefits of management changes over many years of weather. To enable the simulation of multiple species pasture systems on farms, a pasture model was needed that could represent the growth of competing pasture species. A new model was created by adapting portions of an existing rangeland model that was previously developed and widely applied to the semiarid conditions of the western USA. The revised model was integrated with an existing whole-farm model to enable the simulation of pasture systems in dairy and beef production in the northeast. The model will help producers and researchers determine the mix of pasture plant species that best meet the long-term production goals of grass-based animal production in the Northeast. Technical Abstract: 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 effect 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, a phytomass-to-leaf-area conversion factor, start and end dates of senescence, desired 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 the effect of soil water content on spring dry matter production relatively well, but achieved only qualitative agreement with observed dry matter in summer and autumn. It has yet to achieve the 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, calibration, and use of this integrated model will help researchers improve their understanding of temperate pasture systems, identify gaps in knowledge, and prioritize future research needs. Ultimately, the integrated model will provide more accurate assessment of the influence of management strategies on pasture productivity, animal production, and economics at the whole-farm scale. |