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Range Approach
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Objective 1:

Develop strategies and decision tools to proactively manage livestock grazing, fire, and drought impacts on Great Plains community structure and function.

Sub-objective 1.A.

Determine plant community and livestock response to post-fire grazing deferment.

Hypothesis 1.A.1. -

Standing crop and plant species composition are similar across postfire grazing deferment periods by the following growing season. (Vermeire and Reinhart)

Hypothesis 1.A.2. -

Sheep weight gain and diet quality decrease with increasing grazing deferment period. (Waterman and Vermeire)

Experimental Design:

Land management agencies currently recommend spring and early summer deferment, if not two years complete rest from grazing after summer fire.

Recent LARRL research indicated that 17, 34, or 50% late spring use did not negatively affect perennial graminoids following fire.

Delays in grazing can be economically costly, so it is imperative that the ecological costs and benefits associated with grazing deferment be determined. Standing crop and species composition will be estimated for 18 pastures (1.5 ha each)on a silty ecological siteby clipping 30 randomly placed 0.25-m2 quadrats in each pasture during July. Species composition will be estimated using the dry-weight-rank method, weighted to standing crop (Gillen and Smith 1986). Dry-weight-rank groups will include western wheatgrass, needle-and-thread, threadleaf sedge, fringed sage, and 4 composite groups, other C3 perennial grasses, C4 perennial grasses, annual grasses, and forbs. Grasses, forbs, and fringed sage will be collected separately in the field. Summer fire will then be applied to 9 pastures one year and 9 others the next.Summer fire will be used because 75% of wildfires in the Northern Great Plains occur in July and August.Pastures will be randomly assigned one of three grazing periods, late spring (5/17 - 7/26, active plant growth), early summer (6/21 - 8/30, flowering through summer quiescence), or late summer (8/2 - 10/11, summer quiescence and potential late season growth) to determine effects of post-fire grazing deferment. Pastures will be stocked with 10 ewes (45kg) the first growing season after fire. Stocking densities will be adjustedthrough minor changes in animal numbers and grazing periodto achieve 60% utilization during the prescribed period.

This level of utilization will reflect potentially greater livestock use occurring with fire-induced reductions in standing crop and increases in forage quality. Furthermore, 60% utilization will facilitate detection of plant responses to deferment by increasing the probability of negative grazing effects.

Utilization will be based on standing crop inside and out of 8 sheep exclosures (2x1 m) in each pasture. Two fistulated sheep will be used in addition to the 10 other sheep in each replication to assess diet quality via proximate analysis of rumen contents. Rumen contents will be collected 2 weeks after grazing initiation and every 2 to 3 weeks after to assess changes within the grazing period and coincide with rumen collections from other treatments. Sheep will be weighed at the beginning, midpoint, and end of the grazing period. All pastures will be released from grazing the following spring and reassessed with the same protocol as the pre-treatment period to determine deferment period effects on species composition, standing crop, and current-year biomass. Data will be analyzed using analysis of variance on deferment period, year of treatment, and their interaction, with standing crop and current-year biomass for each plant component, diet quality, and sheep weight gain as the response variables. Pre-treatment means will be used as a co-variable if initial differences exist among response variables. Additional analyses will be conducted to determine economics of post-fire grazing management, using forage response and livestock performance data from this research and forage response data from completed post-fire stocking rate research.Following this experiment, one of the same general design will be conducted with cattle to assess livestock species differences.


If prescribed fire is banned, timing of burns will be adjusted to windows of opportunity within the ban period, treatment will be delayed until later in summer, or treatment will be delayed until the following summer.


Larry Brence (Economic analyses, Montana State University Extension)

Sub-objective 1.B. Determine plant community response to fire return interval and seasonality.

Hypothesis 1.B -

Plant biomass and species composition vary with fire frequency and seasonality. (Vermeire and Reinhart)

Experimental Design:

Interests in fire stem from its use as a management tool and as an unplanned event. Plant community response is expected to vary with fire return interval as it relates to species-specific resilience, and fire seasonality relative to life stage and growth pattern. A full factorial arrangement of 4 fire return intervals and 3 seasons will be randomly assigned to 36 plots (15x20 m) on a silty ecological site(the same ecological site as sub-objective 1.A)and 3 seasons with a non-burned control will be assigned to 12 plots on a clayey site with 3 replicates for each treatment combination.

Return intervals will be 0 (no fire), 1, 3, and 6 years. Fire seasons will be spring (blue grama initiation), summer (Jul-Sep), and autumn (after killing frost). All burn treatments will be initiated the same year, starting with summer so all seasonal fire treatments have the same post-fire growing seasons. Permanent 10-m point-intercept transects will be read at 20-cm intervals to determine basal and aerial cover by species, bare ground, and litter. Four 0.25 m2 quadrats will be clipped per plot in July each year, separating by dominant species and functional group. Samples will be separated into current-year and older material. To isolate fire effects, plots will not be grazed during the growing season. Dormant-season grazing may be applied if weather conditions are such that litter accumulation becomes excessive. Response variables will be subjected to analysis of variance with pre-treatment data as a co-variable if initial differences exist.

Data will first be analyzed to assess seasonal effects after a single burn, using season and ecological site as independent variables. Data from the silty site will be analyzed as a 4x3 factorial with years as repeated measures 1 year after all treatments have again burned in the same year (i.e., the seventh annual burn, third 3-year interval burn, and second burn for the 6-year interval). The proposed research is uniquely designed to reduce unexplained variation by having the number of post-fire growing seasons equal across seasonality treatments and timing interval treatments such that all are initiated and ended in a common year. The experiment will be repeated concurrently in Woodward, OK using 0, 3, and 6-year intervals during spring and summer and in Cheyenne, WY using 0, 1, and 3-year intervals during spring and autumn, allowing synthesis of data across a north-south gradient through the western Great Plains.


If prescribed fire is banned, timing of burns will be adjusted to windows of opportunity within the ban period, or the burning schedule will be adjusted and the treatment will be changed to the fire frequency prescribed by the return interval treatment.


Justin Derner (Shortgrass steppe response, USDA-ARS Rangeland Resources Research Unit), Phil Sims (Southern mixed prairie response, USDA-ARS Southern Plains Range Research Station).

Sub-objective 1.C. Determine patch burning effects on plant community dynamics, animal performance, grazing distribution, and foraging efficiency.

Hypothesis 1.C.1. -

Plant heterogeneity is greater with patch burning than uniform management. (Vermeire and Waterman)

Hypothesis 1.C.2. -

Patch burning alters grazing distribution with no effect on cattle weight gain. (Waterman, Vermeire and Rinella)

Hypothesis 1.C.3. -

Foraging efficiency will be greater within recently or previously burned areas compared to non-burned areas within the same pasture. (Grings, Vermeire, and Waterman)

Experimental Design:

Demands for biological diversity and reintroduction of fire are coalescing into management models using fire to shift spatial and temporal grazing distribution and increase heterogeneity of rangeland structure. To date, most applications of the model have been limited to mesic grasslands and quantification of animal responses is limited. Two pasture-level treatments, homogeneous and heterogeneous management, will be assigned to six, 12.1-ha pastures in a completely randomized design. Three pastures will be managed homogeneously by broadcast burning once in 4 years. Three pastures will be managed heterogeneously by burning 25% of each pasture in an annual rotation such that each quarter is burned once in 4 years. Fire will be applied in summer to coincide with the natural fire season. Each pasture will be grazed annually June through August by 8-11 stocker cattle (275 kg) with free access within the pasture and a target utilization of 50% by herbage weight. Vegetation data will be collected before initial treatment and annually throughout treatment. Twenty permanent 10-m pointintercept transectsper pasturewill be read at 20-cm intervals to determine basal and aerial cover by species, bare ground, and litter.Five transects will be placed in each quarter of the heterogeneously managed pastures to asses treatment effect by patch.A circular 1.9-m2 exclosure near each transect and paired grazed site will be clipped from 0.25 m2 quadrats at the end of the grazing period to determine utilization and standing crop, separating by dominant species and functional group. Samples will be separated into current-year and older material. Cattle will be weighed at the beginning, midpoint, and end of the grazing period to assess animal performance. Distribution of cattle will be monitored using GPS units attached to 2 steers per pasture, recording weeklong data in 1-minute intervals every other week.Handheld Garmin GPS units will be modified for additional battery power and harnessed dorsally behind the shoulders of steers. Data will be differentially corrected and analyzed for time spent in patches, time spent at water, time spent traveling, time spent lying down (sleeping and ruminating), and time spent standing or grazing. Steers will be periodically monitored in the field to cross-reference livestock activities with GPS data.The gradient in stand structure and forage quality across sites created by time since fire and resulting spatial and temporal differences in grazing intensity will be used to determine how these factors affect foraging efficiency. Foraging efficiency will be evaluated by introducing 6 ruminally cannulated cows to pens (4.9x9.75 m) placed within burned and unburned areas within these sites at least three times in the grazing season, observing bite counts during 45-minute grazing bouts, and recovering consumed forage via rumen cannulae to calculate dry matter mass per bite. Sampling for foraging efficiency will occur in grazed and non-grazed (protected by panels) areas within burned and unburned quarters of pastures. Response variables, including cover, biomass, Simpson's diversity, proportional dissimilarity, and animal weight gain will be subjected to analysis of variance with pre-treatment data as a co-variable if pre-treatment differences exist. Data will be analyzed at the pasture level to assess effects of management scheme and as individual patches, with time since fire as the independent variable to assess resilience. Animal distribution data will be evaluated with chi-squared analysis of differences between observed and expected use. Foraging efficiency will be analyzed using repeated measures analysis of variance techniques with burn treatment within a pasture and grazed and non-grazed plots as class variables. The vegetation experiment will be repeated concurrently in Woodward, OK and Cheyenne, WY. Results will be synthesized across locations.


If prescribed fire is banned, timing of burns will be adjusted to windows of opportunity within the ban period, or seasonality will be adjusted to autumn that year.

Collaborations: Justin Derner (Shortgrass steppe response, USDA-ARS Rangeland Resources Research Unit), Phil Sims (Southern mixed prairie response, USDA-ARS Southern Plains Range Research Station).

Sub-objective 1.D. Characterize grazing history effects on rangeland integrity and stability.

Hypothesis 1.D -

Exclusion of large grazers reduces rangeland stability. (Vermeire)

Experimental Design:

Livestock exclusion has been proposed to restore rangeland healthwith the assumption that livestock are deleterious. However, exclusion of large grazers may be a greater disturbance than livestock grazing, given the evolutionary history of herbivory in the Great Plains.In 1993, four 12.1-ha livestock exclosures were establishedto examine effects of livestock removal on rangelands that had been moderately grazed by cow-calf herds for decadesand paired with adjacent sitesscheduled for continuedmoderateuseby cow-calf herds. Within each exclosure and grazed site, an area was permanently marked for sampling. Current-year biomass is clipped by species each July from twenty 0.25 m2 quadrats. Annual sampling of current year biomass by species will continue to assess effects of livestock exclusion and precipitation on plant community composition, diversity, and biomass.Permanent 15-m point-intercept transects will be installed in each sampling area to determine basal area by species, litter, and bare ground.Data will be analyzed as a repeated measures analysis of variance for a randomized block design, with grazing treatment blocked by location. Resilience and resistance to drought will be assessed by comparing relative change and recovery rate during natural droughts and compared between grazing treatments. Within the exclosures and grazed sites, but outside the key areas, 6 levels of controlled disturbance will be applied once to 25x25-m plots in a factorial arrangement to determine grazing history effects on ecosystem resistance and resilience. Disturbances will be sheep grazing at 0, 45 and 75% use and summer fire or no fire. Two permanent 15-m point-intercept transects in each plot will be read at 30-cm intervals to determine basal and aerial cover by species, bare ground, and litter before disturbance and the following 3 years. Five 0.25 m2 quadrats per plot will be clipped in July each year, separating by dominant species and functional group. Samples will be sorted into currentyear and older material.Soils will be cored to 30 cm and analyzed for nitrogen and organic carbon content.Response variables will be subjected to analysis of variance with pre-treatment data as a co-variable if initial differences exist. Data will be analyzed as a factorial within the randomized block design, using grazing history, recent grazing, and fire as independent variables. Response variables will be resistance, measured as first-year change in biomass and composition, and resilience, measured as rate of recovery in biomass and compositionover 3 years.


If prescribed fire is banned, timing of burns will be adjusted to windows of opportunity within the ban period, fire season will be adjusted to early autumn, or treatment will be changed to the following year.



Objective 2:

Improve animal productivity and product quality based on predicted nutrient intake, forage dynamics, and diet selection processes in the northern Great Plains.

Sub-objective 2.A. Determine effects of forage quality on autumn forage intake as it interacts with cow lactation and gestation status.

Hypothesis 2.A -

Autumn forage intake is altered by the interaction of cow physiological state and forage quality. (Waterman)

Experimental Design:

Quantifying interacting effects of forage quality and cow physiological state (state of gestation and lactation) could improve predictions of forage intake during a critical period of nutritional limitations. Cows calving during late winter (n = 40, average calving date = February 7) or late spring (n = 40; average calving date = May 31) will be subjected to one of twotwice-replicatednutritional (seeded or native forage) environments for approximately 60 days during autumn and early winter, creating four treatments in a 2x2 factorial arrangement.Seeded pastures contain a mixture of alfalfa, Altai wildrye, 'NewHY' hybrid wheatgrass, Russian wildrye, smooth brome, red clover, and trefoil. Each physiological state will be tested on alternate years due toin uteroeffects on the calf.Differences in calving season will be elected to provide cows in two physiological states, mid- to late gestationversuslactation and early gestation, which can be exposed to varied nutritional regimens with similar climatic conditions and the same forage base. Forage intake will be measured using sustained release external non-digestible marker technology (Burns et al. 1994)and fecal output from cannulated and non-cannulated cows. Associated forage and diet quality will be defined through laboratory measures.Two rumen-cannulated cows that are not associated with the experimental herds being evaluated will be used to collect extrusa samples from each pasture. This project is concurrent with sub-objective 4.B in the LARRL NP101 project plan (101 MacNeil 5434-31000-014-00D).


Research will be delayed in the event that inadequate forage resources of varied quality to support the required number of cattle for valid intake measures are available.



Sub-objective 2.B. Determine rumen microbial response to noxious weed consumption by sheep and cattle.

Hypothesis 2.B -

Leafy spurge intake reduces fermentation and rumen bacterial species diversity. (Waterman)

Experimental Design:

Preliminary data from current Fort Keogh research indicate marked differences in rumen microbial ecosystems exist between cattle and sheep. Rumen microbial attributes allowing sheep to consume invasive weeds, such as leafy spurge, could increase weed consumption by cattle if those attributes could be identified and transferred to cattle via modification of the bovine rumen environment.In vivoandin vitroexperiments will be implemented using like-age ruminally fistulated cows and sheep of similar genetic background. Animals will be randomly assigned to two groups, each with 2 cows and 2 sheep, then fed dietsat two percent of body weightcomposed of either barley hay or barley hay [(85% of dry matter intake (DMI)] and leafy spurge (15% of DMI).Sheep will readily consume leafy spurge, up to 30% of their diet without visible signs of digestive upset. Because cattle are perceived to be much less tolerant, 15% leafy spurge will be used in the experimental diet to avoid digestive upset and subsequent refusal to consume test diets.For thein vivoexperiment, diets will be applied in a switchback design with three 28-day feeding periods. At the end of each feeding period, rumen contents will be collected and analyzed forfermentation characteristics includingruminal pH, ammonia, and volatile fatty acids. For thein vitroexperiment, animals on the barley hay and barley hay plus 15% leafy spurge will serve as rumen liquor donors after feeding these diets for more than 14 days.In vitrotreatments will include a gradient in 10% increments of barley hay and leafy spurge in separate gas production (5 tubes per treatment) andin vitrodry matter disappearance (IVDMD) (10 tubes per treatment) systems.Aliquots from thein vitrostudies will be used to measure rumen fermentation characteristics which include gas production, IVDMD, ruminal pH, ammonia, volatile fatty acids, and methane production.Microbial DNA will be isolated in both experiments to increase the resolution of diversity estimates. Denaturing gradient gel electrophoresis (DGGE) and RT-PCR will be used to examine the variable V3 region of 16S ribosomal RNA genes. Lanes of the DGGE gels are scored for presence or absence of bands at different migration distances (pixels on the image file) and their relative intensities. Across gels, banding patterns will be standardized with a reference pattern included in all gels. These generated banding patterns will be considered as images of the respective bacterial communities (Fromin et al., 2002).

Euclidean distances between profiles will be calculated and summarized using AMOVA implemented in ARLEQUIN (Schneider et al., 2000). Results, along with concurrent research (see contingencies), will identify rumen microbes and explain whether rumen microbial population shifts occur due to consumption of leafy spurge. Data for the in vitro gas production and IVDMD will be analyzed using analysis of variance on forage treatment, species, exposure (inoculum from animals with or without leafy spurge in their basal diet), pull time and appropriate interactions. In vivo data will be analyzed by analysis of variance for a switchback design on forage treatment, period, and appropriate interactions.


Approximately 10% of the species believed to colonize the rumen have been identified. However, concurrent research in the LARRL NP101 project plan (101 MacNeil 5434-31000-014-00D) is designed to isolate more microbial species. This subobjective is not dependent on successful completion of the NP101 objective, but is designed to capitalize on potential discoveries that expand the scope if inference.

Collaborations: Shanna Lodge-Ivey (analytical support; New Mexico State Univ.)

Objective 3:

Develop management strategies to restore rangelands degraded by weeds and prevent weed invasions in the northern Great Plains.

Sub-objective 3.A. Determine interacting effects of fire and grazing on annual brome dynamics.

Hypothesis 3.A.1. -

Control of annual brome abundance, in order of greatest to least impact, occurs with post-fire grazing, fire, grazing, then no fire or grazing. (Vermeire, Rinella, and Reinhart)

Hypothesis 3.A.2. -

Perennial plant biomass will be greater on summer-burned than autumn-, spring-, or non-burned sites. (Vermeire, Rinella, and Reinhart)

Experimental Design:

Japanese brome and cheatgrass reduce perennial forage production and cure quickly, reducing forage quality and increasing wildfire hazards.

Laboratory experiments at Fort Keogh have indicated potential for control through fire and grazing management. A factorial arrangement of 4 fire treatments and 2 grazing treatments will be applied to 10x10-m plots in a completely randomized design with 4 replications per treatment combination. A 4-m buffer will be mowed between plots and around the perimeter of the study area. Fire treatments will be no fire, summer (Jul-Sep), autumn (after killing frost), and spring (western wheatgrass growth initiation) fire initiated during a productive brome year. Summer fire treatment will initiate the sequence of fires so all treatments have the same number of post-fire growing seasons. Grazing treatments will be no grazing or annual sheep grazing to 50% removal of total herbage weight when brome inflorescences are emerging from the sheath. All fires will be applied once. Grazing treatment will be initiated the first spring following fire and be repeated each spring thereafter. Permanent 10-m point-intercept transects will be established diagonally in the plots and read at 20-cm intervals to determine basal and aerial cover by species, bare ground, and litter. Four 0.25 m2 quadrats will be clipped per plot each year, separating by dominant species and functional group. Nutrient analyses will be conducted on forage samples and 5 soil cores (10 cm) from each plot. Density of annual brome plants and spikelets per plant will be recorded in 8 permanent 0.1 m2 quadrats per plot. Sampling will be conducted in late June before treatment and each year during treatment. A repeated measures analysis of variance will be used to determine cover, biomass, plant and spikelet density response to fire, grazing, and the fire-grazing interaction. Pre-treatment data will be used as a co-variable if pre-treatment differences exist. A stage-structured demographic model will be fit to the data to explore related control options not strictly mimicked by the treatments.

Contingencies: Due to annual brome dependence on autumn moisture and resulting erratic production, duration of the experiment may be extended to ensure a potentially productive brome year post-treatment. In the event of extended drought, plots will receive supplemental water during early autumn and spring.



Sub-objective 3.B. Provide weed management protocols adjusting for inter-annual variation.

Hypothesis 3.B -

Number of defoliations required to maintain leafy spurge control increases with increasing growing season precipitation. (Rinella)

Experimental Design:

Successful weed suppression in water-limited systems can be ephemeral because weeds often recover in atypically wet years. Such a response indicates a potential need to adjust management strategies to account for wet years. A factorial arrangement of 2 water treatments and 3 defoliation treatments will be applied in a completely randomized design, with 2 replications per treatment combination and the experiment will be repeated across 2 sites (Fort Keogh and Phalen ranch). Water treatments will be ambient precipitation and ambient precipitation plus 2.5 cm of supplemental water during mid-May using a portable pump and sprayer. Defoliation treatments will be no defoliation, a single defoliation in mid-May, and 3 defoliations per growing season applied in the middle of April, May, and June. Defoliation treatments will mimic sheep grazing of leafy spurge and associated species. Plots will be 5x5 m, with water treatment applied to the inner 3x3-m area and sampling conducted on the central 1.5x1.5-m area. The outer plot area will be used to prevent edge effects, such as seed deposition or root growth into the sampled area. Analyses will explore changes in leafy spurge biomass (as a percent of total biomass)and seed productionover a 4-year treatment period. A longitudinal mixed model with sites and replications as random effects and other effects fixed will be fit to the data to test the hypothesis. Bayesian time series methods will be used to determine if our study populations continue to be effected by dry periods and/or defoliations that occurred in previous years (West and Harrison 1999).


The success of the study is contingent on at least one growing season being fairly dry so that plots will respond to supplemental watering. If prevailing weather is wet, temporary rain shelters will be deployed to ensure separation in water treatments.



Sub-objective 3.C. Develop an internet-available system to quantify site-specific invasive weed impacts.

Hypothesis 3.C -

Non-hypothesis objective completed by development of a technology. (Rinella)

Experimental Design:

The ability to optimize economic and ecological cost effectiveness of weed control is currently limited by a lack of accurate, site-specific estimates of invasive weed impacts. An impact per unitleafy spurgedensity modelhas beenderived from field studies and meta-analysis(Rinella and Luschei 2007).A similar model will be developed for spotted knapweed. These models will rely onsite-specific data on spatial extent and density of weeds toestimateinvasive weed-induced losses in forage yield and grazing capacity. Because the models will operate on biomassdataand managers may be reluctant to collect such data, allometric relationships predicting weed biomass from surrogate variables (stem length and density)have been developed for leafy spurge (r2 = 0.80) and spotted knapweed (r2 = 0.92).Testing of the leafy spurge model has revealed thatonce weed biomass is accurately estimated from surrogate variables, missing data imputation procedures can accurately estimate biomass of desired species occurring with weeds.Additional testing has revealed that the imputed data are effective in estimating weed impacts on desired species biomass. Remaining tasks include completing the spotted knapweed model and developingan internet sitethat willenable managers to input data into the models andestimate site-specific weed impacts as percent changes in desired plant abundances and livestock carrying capacities.




James Donahue (interface programming, private consultant)

Sub-objective 3.D. Develop grazing strategies to reduce invasive weed population growth rates.

Hypothesis 3.D -

Population growth rates of spotted knapweed, Russian knapweed, and leafy spurge will be reduced to a greater extent by exposure to sheep grazing than cattle grazing alone or livestock exclusion. (Rinella and Reinhart)

Experimental Design:

Exotic weeds threaten to invade millions of hectaresofrangelands in the Great Plains and grazing strategies that limit weed spread are desperately needed. Colonizing populations of spotted knapweed, Russian knapweed, and leafy spurge will be exposed to4 grazing treatments (no grazing, cattle grazing, sheep grazing, and grazing by sheep and cattle) in 3 blocks(degraded, upland, riparian). Paddocks are29x87 mand aligned side-by-side, withgrazing treatment randomly assigned topaddockwithineach site. Paddocks are grazed to 50% use from mid-May to early June.Cattle paddocks will be grazed by 4 heifers (365 kg), sheep paddocks will be grazed by 24 ewes (50 kg), and 2 heifers will simultaneously  raze with 12 ewes for the mixed species treatment to encourage 25% use by each livestock species.Within each paddock and for each weed species, 6 greenhousereared seedlings were planted in two 2-x2-m subplots during spring 2005. Likewise, 1000 germinable seeds of each species were sown in two additional subplots. Subplots were distributed across paddocks in a grid pattern. None of the three weed species naturally occur at the sites, but each occurs within several miles. Data on weed emergence, mortality, over-winter survival, and seed production will be gathered for 7 growing seasons. These data willbe used to modelweed population growth rates as functions of environmental variables and grazing.


Uniform failure of weed establishment across treatments would be addressed with additional weed introductions.If the subplot weed patches become larger than 20 m2 we will discontinue the study and if appreciable weed recruitment occurs away from the subplots those weeds will be controlled to ensure containment within the study area.





USDA, ARS Fort Keogh Livestock and Range Research Laboratory
243 Fort Keogh Rd., Miles City, MT  59301-4016
Phone: 406-874-8200, Fax:  406-874-8289