Transcript Document

Analysis of Influences on Vegetative Cover: A Monitoring Case Study
Glenn Owings1 Daren Many1 Loren Racich1 Albert Sommers2
Introduction
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-toyear 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.
Site Description
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.
2.Upper Green River Cattlemen’s Association, Pinedale, WY
Methods
Results Cont.
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.
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.
Regression for Foliar Cover vs Date of Snow Disappearance
Y: Foliar Cover
X: Date of Snow Disappearance
Fitted Line Plot for Linear Model
Y = 21.33 + 0.4516 X
100
95
Foliar Cover
Sublette County Conservation District, Pinedale, WY
90
85
80
130
140
150
Date of Snow Disappearance
160
170
Discussion/Management Implications
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)
Results
Significant Predictor Variables
n
p-value
R-squared
Annual Precipitation
17
0.030*
27.7%
June Precipitation
17
0.043*
24.7%
Date of Snow Disappearance
17
<0.001*
52.7%
*Statistically significant relationship (p<0.05).
-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.
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.
Acknowledgements: The authors wish to thanks the Upper Green River Cattlemen’s
Assocation for the use of their cooperative monitoring data.