NEW MONITORING TECHNOLOGIES FOR IMPROVING RANGELAND MANAGEMENT
Location: Range Sheep Production Efficiency Research
Project Number: 5364-31610-004-00
Start Date: Apr 14, 2008
End Date: Apr 13, 2013
The overall objectives are to develop accurate and efficient monitoring methods, management guidelines, and decision support tools for use on rangelands. These methods, guidelines, and tools will help rangeland managers maintain or improve the health of the nation’s rangelands. The following are our specific objectives. Objective 1: Evaluate newly developed monitoring technologies for landscape-scale assessment of the effects of rangeland management activities, including grazing and fire, on vegetation, ground cover, and herbivore selectivity. Subobjective 1.A: Quantify the accuracy, precision, and efficiency of very-large-scale-aerial (VLSA) and close-to-earth (CTE) imagery for measuring rangeland vegetation. Objective 2: Develop science-based grazing management strategies and decision support systems that can be used to guide managers to maintain or improve the ecological function of western rangelands. Subobjective 2.A: Assess the effect of shifts in plant species composition due to grazing and fire disturbance on ecological functions such as productivity, nutrient cycling, and hydrological function. Subobjective 2.B. Develop parameterization algorithms for the Rangeland Hydrology and Erosion Model (RHEM) from existing and newly collected rangeland hydrology data sets. Subobjective 2.C: Assess the indirect effects of sheep grazing activity, such as bedding and stream crossing, on infiltration, soil erosion, and water quality.
Subobjective 1.A. CTE imagery will be collected in 2 yr before and after grazing to determine whether this imagery can be used to accurately assess changes in vegetation due to grazing. The CTE method will be compared with more conventional methods. VLSA imagery will be collected at several scales from pastures that differ with respect to burning and postfire grazing rest to determine the efficiency and degree of specificity that vegetation classification can be accurately made with this methodology. Likewise the VLSA method will be compared with conventional methods. Subobjective 2.A. Prescribed fire in the spring, fall, or an unburned control will be the main plot treatments, and the burns will cause a shift in vegetation composition for the mountain big sagebrush community at the research location. Following the fire disturbances, different periods of postfire grazing rest will be imposed on subplots which may alter the rate of succession toward the preburned state for the burned main plots. Measurements of soil erosion due to wind and simulated rainfall, soil nutrient dynamics, and plant productivity, and animal productivity and behavior will be measured in each burn/postfire grazing rest treatment combination to determine what effect the resulting shifts in vegetation composition have on ecological function of this plant community. Subobjective 2.B. Data from Subobjective 2.A and other collaborators' data will be used to develop parameterization algorithms for RHEM. Multiple regression techniques will be used to develop algorithms that utilize plant and soil characteristics to estimate soil erodibility and hydraulic roughness. Subobjective 2.C. Sheep will be bedded on bedgrounds at our summer range. Measurements of infiltration, erosion, and runoff water quality will be measured from three treatments. The three treatments will be within the bedground and bedded in the measurement year, within the bedground but not bedded in the measurement year, outside the bedground in a similar site but only grazed in the measurement year.