Evaluation of the upgraded spur model (spur2.4)
Introduction
Models have great potential as research tools to enhance our knowledge of ecosystem function and as decision aids for natural resource managers. spur (Simulation of Production and Utilization of Rangelands) was designed to simulate rangeland ecosystem function and predict ecosystem response to changing determinants and various management practices (Wight and Skiles, 1987, Baker et al., 1993, Carlson and Thurow, 1996). It has the potential to evaluate the environmental and economic impact of different management alternatives at the landscape or whole ranch scale. The output from spur can be selected to include rainfall run-off, soil loss, soil organic matter, plant production, forage selected and harvested by livestock and wildlife, animal weight and gain, and estimates of net economic return. Once spur is calibrated for a particular location, the model can be run to predict the long-term outcome of management strategies and weather sequences and to assess best management strategies or combinations of management practices (Baker et al., 1993).
Models must provide reliable results when measured against field data to be useful as a decision aid for resource managers. Modifications to improve the capability and accuracy of predictions of spur were made separately by Carlson and Thurow (1992) (spur91), Hanson et al. (1992) (spur2) and Foy (1993) (spur2.3). These improvements to spur have been combined to produce spur2.4. This paper compares the output from spur2.4 with data from the Texas Experimental Ranch (TER), Throckmorton, Texas to determine how well we can currently predict the outcome of climate, physical environment and different management, in this environment. Results on hydrology, soil organic carbon, herbaceous vegetation and cow-calf production are presented. Since spur91 has provided superior results when evaluated in the southern Great Plains against the original spur (Carlson and Thurow, 1996), differences between spur2.4 and spur91 are emphasized. spur2.4 was not tested against spur2 and spur2.3 since neither of these models include the changes to improve plant–water interactions made by Carlson and Thurow (1996) in spur91.
Section snippets
Model description
spur is composed of six basic submodels (Fig. 1) (see Carlson and Thurow, 1992, Hanson et al., 1992). The climate record provides daily inputs of precipitation, maximum and minimum temperature, solar radiation, and wind run. The hydrology component maintains daily water balance, calculates snow accumulation, snowmelt and sediment transport. The soil module tracks soil moisture by soil layer according to soil series characteristics and soil carbon and nitrogen levels. The plant module tracks
Hydrology
Monthly run-off was not adequately predicted by both models (R=0.66–0.76)(Table 1). Monthly wet year run-off (1986) was more highly correlated (R=0.76 in both models) than monthly dry year run-off (1988) (R=0.66 in both models). This is an inherent problem with the curve number technique used in the model (Carlson and Thurow, 1996). Total simulated run-off for 3 years was twice the observed run-off (Table 1). However, the amount of run-off as a percentage of precipitation in this area is <8% (
Conclusions
The changes made to spur in creating first spur91 and then spur2.4 have improved the utility and accuracy of the model considerably. The model is now able to do more than just predict general trends of management responses. The potential for aiding in the assessment of various management strategies and practices is now possible in limited areas, but much work remains to be done to expand this capability. The hydrology component, in particular, is not nearly accurate enough and this is one of
Future use of spur in natural resource management
spur in its upgraded form can evaluate climatic change consequences, stocking rate decisions, timed rotational grazing systems, enterprise-level economic consequences and the management impacts on water harvest, erosion, vegetative quality and quantity, and soil carbon and nitrogen dynamics. The impact of treatments can be simulated for 100 years or more. With this model, rangeland ecosystem and enterprise sustainability can be addressed at the ranch scale by assessing cumulative effects over
Acknowledgements
We would like to thank Mike Coughenour for providing the initial FORTRAN code for the century soil organic matter submodel. Bill Bailey and Jon Hanson facilitated transfer of the spur2.3 code from ARS so that the development of this model could proceed. Rick Bourdon assisted in initializing the cow-calf model. Steve Dowhower and Bill Pinchak provided data from the Texas Experimental Ranch. Dee Carlson and Tom Thurow kindly reviewed an earlier draft.
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