Page Banner

United States Department of Agriculture

Agricultural Research Service

Research Project: NEW MONITORING TECHNOLOGIES FOR IMPROVING RANGELAND MANAGEMENT

Location: Range Sheep Production Efficiency Research

2009 Annual Report


1a.Objectives (from AD-416)
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.


1b.Approach (from AD-416)
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.


3.Progress Report
Objective 1, Experiment 1.A of project 5364-31610-004D treatments have been imposed and the pretreatment and 1st year after treatment imagery has been acquired, and field validation data has been collected. Objective 2, Experiments 2.A project 5364-31610-004D fall and spring burns have been conducted and preburn and postburn vegetation, soil nutrient and productivity data have been collected.


4.Accomplishments
1. Measuring amount of shrub conversion in rangeland using Very Large Scale Aerial (VLSA) imagery. Agencies that manage the nations federal lands lack efficient tools for accurately measuring rangeland attributes. VLSA imagery, a low altitude, small aircraft-based method, has been suggested as an efficient tool for measuring bare ground and total plant cover, but the method had not been validated for measuring shrub cover. Using paired measurements from imagery and the ground, ARS scientists at Dubois, ID were able to determine that the estimates of image- and ground-measured shrub cover were similar. The VLSA imagery could be used to accurately measure the cover of 3 species (mountain big sagebrush, bitterbrush, and horsebrush) common to mountain big sagebrush communities. With the current interest in maintaining sage grouse habitat in the west, this method of cover measurement could be used to rapidly and accurately assess shrub cover.


6.Technology Transfer

Number of Other Technology Transfer1

Review Publications
Moffet, C.A. 2009. Agreement between measurements of shrub cover using ground-based methods and Very Large Scale Aerial (VLSA)imagery-measured shrub cover. Rangeland Ecology and Management. 62:268-277.

Weber, K.T., Seefeldt, S.S., Moffet, C.A. 2009. Fire Severity Model Accuracy Using Short-term, Rapid Assessment versus Long-term, Anniversary Date Assessment. GIScience and Remote Sensing. 46(1):24-38.

Clark, P., Hardegree, S.P., Moffet, C.A., Pierson Jr, F.B. 2008. Point sampling to stratify biomass variablity in sagebrush steppe vegetation. Rangeland Ecology and Management 61:614-622.

Tsagaan Sankey, T., Moffet, C.A., Weber, K.T. 2008. Post-fire recovery of sagebrush communities: Assessment using SPOT5 and very large-scale aerial imagery. Rangeland Ecology and Management. 61:614-622.

Last Modified: 7/31/2014
Footer Content Back to Top of Page