The mechanisms responsible for soil-N-mediated species replacement of native perennial grasses by the invasive annual grasses cheatgrass (Bromus tectorum L.) and medusahead (Taeniatherum caput-medusae [L.] Nevski) on rangelands are not completely understood. In addition, the contributions of distinct forms of inorganic N (i.e., NH4+ and NO3-) to these shifts in species composition are currently unclear. Consequently, we conducted a greenhouse experiment to test 2 hypotheses: 1) that low N availability reduces growth (root and shoot) and N allocation of invasive annual seedlings more than native perennial species, and 2) that seedling growth and N allocation of invasive annual grasses is more responsive than native perennial grasses when supplied with NO3- relative to NH4+. We grew seedlings of 2 annual grasses and the native perennial grasses bluebunch wheatgrass (Pseudoroegneria spicata [Pursh] A. Love), and 4 populations of squirreltail (Elymus elymoides [Raf.] Swezey; E. multisetus [J.G. Smith] M.E. Jones) in separate pots and exposed them to treatments differing in N form and availability for 17 weeks. Unexpectedly, root and shoot growth of annual grasses were equal or greater than native perennial grasses under low N availability. Annual grasses took up more NO3- and allocated more growth and N to shoots than the perennial grasses (P 0.05). Perennial grasses had significantly greater root:shoot dry mass ratios than the invasive annual grasses across treatments (P 0.05). Invasive annual and native perennial grasses both had greater (P 0.05) shoot and root mass and allocated more N to these structures when supplied with NO3- relative to NH4+. The ecological implications of these growth and N allocation patterns in response to N availability and form provide important clues regarding the specific traits responsible for differences in competitive ability between invasive annual and native perennial grasses on semiarid rangelands.

The genus Adesmia (Fabaceae, Papilionoideae) is one of the scarce forage resources at high altitude and arid zones of South America. Its germination behavior has not been examined. Seeds of Adesmia subterranea "Cuerno de Cabra" were pretreated with sulfuric acid (1, 3, and 5 minutes soaking) and mechanical scarification to determine their impact upon dormancy and percentage and speed of germination. Treatments were evaluated under a range of constant temperatures (5 to 30 degrees C) and 2 day/night cycles resembling the extreme environmental conditions of this species habitat. Water uptake and leachate conductivity were higher in the seeds scarified mechanically or with 5 minutes chemical scarification. These treatments also had the greatest total germination and rate at all temperatures in a petri dish germination test. However, in a cell tray experiment using a commercial substrate, the highest seedling emergence and rate were observed with chemical scarification (5 and 3 minutes). The high amount of leakage caused by the scarifications affected emergence in a non-sterile media. The results indicate that A. subterranea seeds have an impermeable seed coat which restricts water uptake, and the efficiency of sulfuric acid scarification to overcome seed coat impermeability and improve germination and emergence.

Many alfalfa (Medicago spp.) cultivars have limited ability to persist under grazing and therefore, a key step in incorporating alfalfa into pastures and rangelands is choosing a grazing tolerant cultivar. In this study, we evaluated the grazing tolerance of 16 alfalfa populations representing a range of potential grazing tolerance. Entries were transplanted on a rangeland site in July 1996 at the Northern Great Plains Research Lab in Mandan, N.D., USA and mob-grazed by cattle from 1997 to 2000. Plant survival, basal area, and stem numbers were recorded in the spring and fall of each year. At the final survival evaluation in May 2001, SCMF 3713 had the highest survival (90%), 'Vernal' had the lowest (23%) and 10 of the 16 entries had greater than 50% survival. A large decline in survival between September 2000 and May 2001 may be attributed to low temperatures in November and December of 2000. Entries such as 'Alfagraze', B-36 and Agripro ZG9415, which were developed in warmer climates, had the largest percentage drop in survival (43.0, 48.6, and 48.6 percentage points respectively) while SCMF 3713, 'Anik' and Alaska Syn A, developed in colder climates, had the least percentage point drops (2.8, 4.1, and 4.1 respectively). The ability to survive over winter contributed more to the different survival rates of these alfalfa populations than did any of the measured plant variables. Producers should know the origins of grazing tolerant alfalfa cultivars and consider selecting cultivars that have been tested in their area.

An experimental design required burn treatments for 10-m2 circular plots. We constructed a fire enclosure for the plots using sheetmetal, electrical conduit, and other commonly available materials. We field tested the enclosure in sagebrush-grass ecosystems in central Nevada and central Utah, and evaluated peak fire temperatures using small metal tags striped with temperature sensitive paint. We obtained average peak surface temperatures of 310, 307, and 381 degrees C in bare ground, under grass, and under shrub microsites, respectively, for the Nevada sites and 253, 299, and 337 degrees C for the same microsites, respectively, in Utah. Subsurface (2-cm depth) temperatures rarely exceeded 79 degrees C, the lowest temperature detectable by our method. The enclosure contained the fire and did not permit escape of any embers or firebrands. The fire enclosure, burn technique and temperature monitoring method used are inexpensive, easily deployed, and desirable for experiments where larger-scale burns are impractical.

The Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE 1.06) were evaluated with rainfall simulation data from a diverse set of rangeland vegetation types (8 states, 22 sites, 132 plots). Dry, wet, and very-wet rainfall simulation treatments were applied to the study plots within a 2-day period. The rainfall simulation rate was 65mm/hr for the dry and wet simulation treatments and alternated between 65-130 mm/hr for the very-wet treatment. Average soil loss for all plots for the representative simulation runs were: 0.011 kg/m2, 0.007 kg/m2, and 0.035 kg/m2 for the dry, wet, and very-wet simulation treatments, respectively. The Nash-Sutcliffe Model efficiencies (R2eff) of the USLE for the dry, wet, very-wet simulation treatments and sum of all soil loss measured in the three composite simulation treatments (pooled data) were negative. This indicates that the observed mean measured soil loss from the field rainfall simulations is better than predicted USLE soil loss. The USLE tended to consistently overpredict soil loss for all 3 rainfall simulation treatments. As the USLE predicted values increased in magnitude, the error variance between predicted and observed soil loss increased. Nash-Sutcliffe model efficiency for the RUSLE was also negative, except for the dry run simulation treatment [R2eff = 0.16 using RUSLE cover management (C) subfactor parameters from the RUSLE manual (C(table)), NRCS soil erodibility factor (K); and R2eff = 0.17 with C(table) and K estimated from the soil-erodibility nomograph]. In comparison to the USLE, there was less error between observed and RUSLE predicted soil loss. The RUSLE error variances showed a consistent trend of underpredicted soil loss among the 3 rainfall simulation treatments. When actual field measured root biomass, plant production and soil random roughness values were used in calculating the RUSLE C subfactors: the R2eff values for the dry, wet, very-wet rainfall simulation treatments and the pooled data were all negative.

Highly intensive stocking of dairy cattle on continuously grazed pasture coupled with liberal applications of commercial fertilizer can lead to increased losses of agricultural nutrients, which is a concern for water quality of receiving lakes and surface water resources. Integrated economic-environmental model simulations performed for the Lake Fork Reservoir Watershed in northeast Texas indicate that appropriate pasture nutrient management including stocking density adjustments and more efficient commercial fertilizer use could lead to significant reductions in nutrient losses. Soluble and organic P losses were predicted to decline by 54 and 13% relative to baseline conditions when manure P was assumed totally plant available (Low P scenario). The soluble and organic P loss reductions declined to 33 and 7% when only inorganic P was assumed plant available (High P scenario). Simulation of an N-based manure management plan resulted in the smallest predicted soluble and organic P loss reductions of 18 and 3%. Nitrogen loss predictions ranged from a 7% decline to a 1% increase for the 3 scenarios as compared to the baseline. The High P and Low P scenarios resulted in estimated aggregate profit reductions of 6 and 18% relative to the baseline. These profit declines occurred because the dairies had to acquire additional pasture land to accommodate the expanded area required for the P-based scenarios. In contrast, the N-based stocking density and nutrient management scenario resulted in an aggregate profit increase of 3% across all dairies. Variations in economic impacts were also predicted across farm sizes.

Russian knapweed (Acroptilon repens (L.) DC.) was introduced to the western United States during the early 1900s. This invasive perennial was a contaminant of alfalfa seed, and was distributed widely across Colorado. Thus, current distributions reflect the climate and soils tolerances of Russian knapweed, and management history, rather than dispersal processes. We surveyed extension and weed agents across Colorado, and were able to locate 528 current or recently eliminated Russian knapweed stands. These patches were superimposed on climate and soils maps to identify 1 km grid cells that were known to contain Russian knapweed. The status of Russian knapweed within a cell was used as the dependent variable in a logistic regression model to define the environmental envelope for this species. At the scale of our analysis, Russian knapweed was most prevalent on fine-textured soils (clay and clay loam), and in warmer, drier regions of Colorado (precipitation 18-73 cm/yr, mean annual temperature 1-12 degrees C). June precipitation was the most important single factor, although nearly all environmental, annual, and monthly climatic factors were significantly related to Russian knapweed occurrence. The multivariate logistic regression model we developed was used to predict the probability of occurrence of Russian knapweed for the entire state of Colorado. Our predictions matched the areas of highest abundance of Russian knapweed from a new field survey, and also indicated areas of high risk that were not identified by the field survey.