1. Analysis of Influences on Vegetative Cover: A Monitoring Case Study Glenn Owings 1 Daren Many 1 Loren Racich 1 Albert Sommers 2 Sublette County Conservation District, Pinedale, WY 2.Upper Green River Cattlemen’s Association, Pinedale, WY Introduction Site Description Methods Results Cont. Measures of ground cover on rangelands are used by managing agencies to assess the ability of the landscape to provide necessary ecological functions (Pellant et al. 2005). Line-point intercept is one of the most commonly used methods for collecting cover data (Herrick et al. 2005). In terms of policy, changes in chosen sample sites are assumed to be indicative of management changes, such that an increase or decrease in cover may be influenced by agency directives. While this may be true in some cases, variable biophysical factors like total precipitation, snowpack, and soil characteristics may have a greater influence on cover than year-to- year management changes. The purpose of this analysis was to quantify the influence of precipitation metrics, livestock numbers, and utilization on first intercept cover in a federal grazing allotment. The study area is located in the Upper Green C & H grazing allotment (USFS) in northeastern Sublette County, WY. It is ecologically important as the headwaters of the Green River, a significant tributary to the Colorado River. Elevation in the allotment varies from ca. 8,000’-10,200’. It is composed of multiple rotational pasture systems and totals 125,663 acres. Livestock arrive on the allotment in late June and leave in early October. The vegetation is characterized by mixed mountain shrub and sagebrush/bunchgrass communities. Dominant shrubs are mountain big sagebrush (Artemisia tridentata Nutt. ssp. vaseyana (Rydb.) Beetle), silver sagebrush (Artemisia cana Pursh), and spiked sagebrush (Artemisia tridentata Nutt. ssp. spiciformis (Osterh.) Kartesz & Gandhi). Common grasses include Idaho fescue (Festuca idahoensis Elmer), Columbia needlegrass (Achnatherum nelsonii (Scribn.) Barkworth), and slender wheatgrass (Elymus trachycaulus (Link) Gould ex Shinners). Ecological site descriptions are simplistic and still under development for the study area, but deviations from historic climax plant communities are minimal and generally associated with a lack of disturbance. Total cover has been high (>87%) for all study sites and there are no noxious weeds present. Long term trend monitoring sites and associated line-point intercept transects were selected for the allotment by the USFS, Upper Green River Cattleman’s Association (UGRCA), and range professionals from the University of Wyoming. Permanent stakes were located at each of twelve locations. Cover data was collected in rested pastures by USFS staff and UGRCA members each September from 1996 to 2012, and compiled in the fall of 2012. One hundred points were collected at one foot intervals for each site reading. Utilization sites were selected by the same interdisciplinary group. Data were collected using the height-weight method for the selected key species, Idaho fescue (Lomasson and Jensen 1943). Utilization data was collected after or near the end of use in sampled pastures, and ranged from 11%-21% over the study period. Multiple observers were present when conducting line-point and utilization measurements. Actual use numbers were recorded by the UGRCA. Date of snow disappearance was converted to Julian date for regression analyses. The Gros Ventre Summit snow telemetry (SNOTEL) site recorded precipitation data for the years of interest (NRCS 2012). It is located within the allotment at an elevation similar to the monitoring sites. Precipitation and snow data were stratified by water year and extracted from the SNOTEL online data library (NRCS 2012). Cover data for each year were averaged across the allotment to combat effects of potentially misplaced transect lines (Bonham and Reich 2009). Total cover is the sum of vegetation, rock, and litter hits along the line-point transect. Foliar cover is the total of vegetative hits on a 100 point transect. Analysis Data were analyzed using Minitab 16 (Minitab 2012). Descriptive statistics were tabulated for cover at all sites. Simple and multiple linear regression were used to detect relationships between the response and predictor variables. The metrics used in analysis were selected based on data availability, quality, and basic ecological theory. The experimental unit is one year of cover data (n=17). Previous year’s stocking and utilization data was used because cover information was collected in rested pastures (n=16). Relationships were considered significant when p<0.05. Dependent Variables: Total Cover, Foliar Cover Independent Variables: Total Precipitation, June Precipitation, July Precipitation, August Precipitation, Summer Precipitation, Maximum Snow Water Equivalent, Date of Snow Disappearance, Stock Numbers (Previous Year Actual Use), Utilization (Previous Year) Regression analysis did not identify any significant predictors for total cover. Foliar cover was significantly correlated with three independent variables. While several iterations of a multiple factor model were significant, none were more predictive than the date of snow disappearance alone. No significant time effect was detected. Significant Predictor Variablesnp-valueR-squared Annual Precipitation170.030*27.7% June Precipitation 170.043*24.7% Date of Snow Disappearance17<0.001*52.7% Discussion/Management Implications -While grazing measures such as utilization may be predictive of ecological metrics under some circumstances, their affects were masked by the larger ecological processes addressed in this study. -Assumptions about standard rangeland monitoring techniques may not apply where systems are in high ecological condition, under light stocking rates, and exhibit a strong precipitation influence. -The application of large scale, region-wide cover estimates to specific monitoring sites is questionable for setting policy in light of current science and known drivers of landscape variability. -If a relationship between change in grazing policy and landscape characteristics is inferred, it is imperative that managing agencies employ monitoring techniques indicative of said relationship. Acknowledgements: The authors wish to thanks the Upper Green River Cattlemen’s Assocation for the use of their cooperative monitoring data. *Statistically significant relationship (p<0.05). References Bonham, C.D. and R.M. Reich. 2009. Influences of transect relocation errors on line-point estimates of plant cover. Plant Ecology 204:173-178. Herrick, J.E., J.W. Van Zee, K.M. Havstad, L. M. Burkett, and W.G. Whitford. 2005. Monitoring manual for grassland, shrubland and savanna ecosystems. USDA-ARS Jornada Experimental Range. Tucson, Arizona: The University of Arizona Press. 236pp. Lommasson, T. and C. Jensen, C. 1943. Determining utilization of range grasses by height–weight tables. Journal of Forestry 41:589–593. Minitab 16 Statistical Software (2012). [Computer software]. State College, PA: Minitab, Inc. (www.minitab.com) NRCS. 2012. USDA, Natural Resource Conservation Service. SNOTEL Data and Products. http://www.wcc.nrcs.usda.gov/snow/. Pellant, M., P. Shaver, D. Pyke and J. Herrick. 2005. Interpreting indicators of rangeland health. Version 4. Technical Reference 1734-6. 122pp. Results