Effects of cattle grazing on shoot dynamics of beaked sedge
by Douglas Richard Allen
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in
Range Science
Montana State University
© Copyright by Douglas Richard Allen (1992)
Abstract:
We studied the effect of cattle grazing on shoot density and flux in 4 southwest Montana beaked sedge
(Carex rostrata Stokes ex With.) stands over 2 years. Forty plots were protected and 40 plots were
grazed by cattle in June and September of 1989 and 1990. Mean shoot density and emergence changed
differently over time (P<0.001 and P=0.003 respectively) in the grazed compared with ungrazed plots.
Mean new shoot emergence was greater (P=0.006) in the grazed than in the ungrazed plots. Shoot
density of the grazed plots increased linearly at a faster rate than the ungrazed plots during spring of
1990, when shoot emergence was greater in the grazed plots, and rodent grazing may have increased
mortality in the ungrazed plots. Mean shoot density remained 12-16% higher in the grazed plots than
the ungrazed plots during the last 6 months of the study. Mean shoot height declined similarly from
June 1989 to June 1990 in the grazed and ungrazed plots. Our data indicate that beaked sedge in our
study site was tolerant of light to moderate grazing, given adequate regrowth between spring and fall
grazing events. However cumulative treatment effects and environmental factors such as water level
may have influenced our results. EFFECTS OF CATTLE GRAZING ON SHOOT DYNAMICS
OF BEAKED SEDGE
by
Douglas Richard Allen
A thesis submitted in partial fulfillment
of the requirements for the degree
of
Master of Science
in
Range Science
MONTANA STATE UNIVERSITY
Bozeman, Montana
January 1992
ii
APPROVAL
of a thesis submitted by
Douglas Richard Allen
This thesis has been read by each member of the thesis
committee and has been found to be satisfactory regarding
content, English usage, format, citations, bibliographic
style, and consistency, and is ready for submission to the
College of Graduate Studies.
Chai
Date
Approved for the Major Department
///3 / f T Date
'
Head, Major Departme
Approved for the College of Graduate Studies
Date
Graduate Dean
iii
STATEMENT OF PERMISSION TO USE
In presenting this thesis in partial fulfillment of the
requirements for a master's degree at Montana State
University, I agree that the Library shall make it available
to borrowers under rules of the Library.
Brief quotations
from this thesis are allowable without special permission,
provided that accurate acknowledgement of source is made.
Permission for extensive quotation from or reproduction
of this thesis may be granted by my major professor, or in
his absence, by the Dean of Libraries when, in the opinion
of either, the proposed use of the material is for scholarly
purposes.
Any copying or use of the material in this thesis
for financial gain shall not be allowed without my written
permissionr
Signature.
Date
/
iv
ACKNOWLEDGEMENTS
This project would not have been possible without the
generous assistance of many people.
Special thanks to my
advisor, Clayton B. Marlow, whose support and direction I
could always count on.
The rest of my graduate committee.
Dr. Bret Olson, Dr. Carl Wambolt, and Dr. John Taylor
provided sage advice at crucial times.
Invaluable
statistical assistance came from Don Daly, Robert Boik and
Rick Rossi of the Mathematics Department, and from Richard
Lund and Bill Moody of the Montana Agriculture Experiment
Station.
Thanks to Curt Stroebel for assistance with field
research, und vielen dank to Kathryn Olson-Rutz, for helping
me over a variety of research and computer program hurdles.
Thanks to the Department of Animal and Range Sciences
Secretarial Staff, for help with countless items, and to the
Division of Communication Services for drafting my maps.
am grateful to the Red Bluff Research Ranch staff for
providing the cows when I needed them, and always having a
good word.
Special thanks to my parents, Richard and Katherine
Allen, for many years of encouragement.
Last, but not
least, thanks to Maggie Emmet for her love, patience, and
support during my graduate program.
I
V
TABLE OF CONTENTS
Page
LIST OF T A B L E S ......................................
vi
LIST OF F I G U R E S ....................................
vii
A B S T R A C T .............................................. viii
INTRODUCTION ......................
I
LITERATURE REVIEW ..................................
Soil Moist u r e ..................................
Compensation For Herbivory ....................
Nutrient Cycling ..............................
Population Dynamics ............................
Characteristics Of Beaked Sedge ................
2
2
3
7
8
9
M E T H O D S ............................................
Site D e s c r i p t i o n ..............................
Experimental Design ............
Statistical Analysis ..........................
13
13
16
19
R E S U L T S ............................................
21
DISCUSSION..........................................
Shoot Population Response ......................
Shoot Mortality................................
Response to Water Level ........................
Physiological Responses ........................
Management Implications ........................
31
31
33
36
38
40
C O N C L U S I O N S ........................................
42
LITERATURE C I T E D ...........
43
APPENDIX
51
vi
LIST OF TABLES
Table
1.
2.
Page
■ Multivariate analysis of mean shoot density and
mean shoot emergence profiles ....................
Mean percent flowering shoots per plot in June
1989 and 1990
23
24
3.
Shoot mortality per plot during Year Iand Year
4.
Rodent-caused shoot mortality during Year I and
Year 2 ........................................... 26
5.
Mean shoot heights (cm) in June 1989 and 1990
6.
Mean percent height removed per grazed plot for
1989 and 1990
27
Maximum densities of beaked sedge in reported in
North A m e r i c a .....................
32
I .
8.
2
. 25
...
Results of rodent trapping in June and July of
1990 ............................................
26
34
9.
NOAA winter climate data - Norris Pump House,
1988 through 1 9 9 1 ............................... 37
10.
Mean shoot density per plot by m o n t h ............. 51
II.
Analysis of variance for mean shoot density
12.
Mean shoot emergence per plot by m o n t h ........... 53
....
52
vii
LIST OF TABLES-continued
Table
Page
13.
Analysis of variance for mean shoot emergence
...
54
14.
Water well levels (cm below soil surface), 1989
through 1991, Stands I and 2 . . .
.............. . 55
15.
Water well levels (cm below soil surface), 1989
through 1991, Stands I and 2 ....................... 56
16.
Mean penetration resistance index (top 30 cm)
estimated at each study plot on three different
d a t e s ........................
57
viii
LIST OF FIGURES
Figure
Page
1.
Cottonwood Creek Study Area, Montana Agricultural
Experiment Station’s Red Bluff Research Ranch near
Norris, M o n t a n a .............................. . . 14
2.
Cottonwood Creek controlled grazing system with
locations of beaked sedge study stands ............ 15
3.
Schematic drawing of a typical beaked sedge study
stand with layout of grazed and ungrazed plots and
water w e l l s ....................................... 17
4.
Profile of mean shoot density per plot byjmonth
and year. 95% Confidence Interval (Cl) = X t +
t39,0.025 * SE(Xt) ................................. 22
5.
Profile of mean shoot emergence and mortality per
plot by month and year. 95% Confidence Interval
(Cl) = [Xt ± t39,0.025 * SE(Xt) ] .................. 22
6.
Profiles of mean shoot density of combined grazed
and ungrazed plots for each stand by month and
year. Sx=Stand(x)
28
Profiles of mean shoot density of combined grazed
and ungrazed plots for each stand by month and
year. Sx=Stand(x)
28
Weekly precipitation (mm) for summer 1989 at the
Cottonwood Creek study site ......................
29
Weekly precipitation (mm) for summer 1990 at the
Cottonwood Creek study site ......................
29
7.
8.
9.
ix
LIST OF FICURES-continued
Figure
10.
11.
Bi-weekly water well level (cm) for Stand 2 from
July 1989 through June 1990 ........ ..
Page
30
Bi-weekly water well level (cm) for Stand 3 from
July 1989 through June 1990 ....................... 30
ABSTRACT
We studied the effect of cattle grazing on shoot density
and flux in 4 southwest Montana beaked sedge (Carex rostmta
Stokes ex With.) stands over 2 years. Forty plots were
protected and 40 plots were grazed by cattle in June and
September of 1989 and 1990. Mean shoot density and
emergence changed differently over time (P<0.001 and P=O.003
respectively) in the grazed compared with ungrazed plots.
Mean new shoot emergence was greater (P=0.006) in the grazed
than in the ungrazed plots. Shoot density of the grazed
plots increased linearly at a faster rate than the ungrazed
plots during spring of 1990, when shoot emergence was
greater in the grazed plots, and rodent grazing may have
increased mortality in the ungrazed plots. Mean shoot
density remained 12-16% higher in the grazed plots than the
ungrazed plots during the last 6 months of the study. Mean
shoot height declined similarly from June 1989 to June 1990
in the grazed and ungrazed plots. Our data indicate that
beaked sedge in our study site was tolerant of light to
moderate grazing, given adequate regrowth between spring and
fall grazing events. However cumulative treatment effects
and environmental factors such as water level may have
influenced our results.
I
INTRODUCTION
Riparian plant communities comprise only I to 2% of the
total land area of the western United States, but provide a
disproportionately greater amount of cover and forage for
wildlife and livestock (Tiner 1984, US Government Accounting
Office 1988).
Although most riparian forage is produced by
rhizomatous graminoids in moist or wet soils, most grazing
strategies have been developed for upland range dominated by
caespitose grasses in water-limited soils.
Although the grazing responses of upland forages have
been extensively studied, the grazing responses of many
riparian species, particularly sedges, are poorly
understood.
We wanted to determine if beaked sedge (Carex
rostrata Stokes ex With.) would compensate for moderate grazing
by cattle by increasing shoot density.
We also wanted to
determine how dynamics of natality and mortality affected
changes in shoot density.
We tested the null hypotheses
that cattle grazing had no effect on shoot density over the
two-year experiment, and that cattle grazing had no effect
on the total number of new shoots produced during the study.
2
LITERATURE REVIEW
Soil Moisture
Riparian areas typically have greater water availability
late in the growing season than surrounding uplands.
While
upland graminoids are approaching dormancy due to lack of
soil moisture, the growth rate and potential for regrowth
remains relatively high for riparian forages.
In areas
where soils are saturated throughout the year,
photosynthesis continues until freezing temperatures damage
plant tissues.
Respiration, growth and shoot emergence may
continue throughout winter for plants covered by ice or snow
(Gorham and Somers 1972, Bernard and Hankinson 1979).
Diminishing forage quality generally coincides with
declining water availability (Kamstra 1973, Willard and
Schuster 1973, Adams et al 1987).
Although riparian forages
follow this general trend (Heyes 1979, Steele et al 1986),
they tend to emerge later and retain forage quality longer
than in upland species (Bernard and Hankinson 1979, Neel
1986).
Because domestic cattle select for high-quality green
forage, they tend to concentrate in riparian areas in mid­
summer through early fall (Bryant 1982, Gillen et al 1985,
Senft et al 1985, Marlow and Pogacnik 1985).
Extended use
3
during this period can lead to excessive trampling, and
repeated grazing of plants, which can affect the regrowth
and reproductive ability of these forages.
Moist or saturated soils are generally more sensitive to
trampling by herbivores than dry soils.
Compaction and
displacement may reduce water holding capacity and plant
productivity (Platts 1981, Kauffman and Krueger 1984,
Skovlin 1984)-, or stimulate shifts in plant composition
(Millar 1973).
The susceptibility of these areas to
disturbance varies with fluctuations in water tables and
resultant changes in soil penetration resistance.
Groundwater levels have been shown to vary seasonally
(Marlow and Pogacnik 1987, Myers 1989) and annually (Aspie
1989, Siemer 1990).
Compensation For Herbivorv
The fitness of a grazed plant depends on its ability to
overcome the detrimental effects of grazing.
The main
negative effects of herbivory include depletion of
carbohydrate reserves, increased shoot mortality, delayed
flowering, diminished root production and soil compaction or
displacement (Jameson 1963, Crawley 1984).
The main
processes by which graminoids are thought to compensate for
tissue damage by herbivory include: (I) increased
photosynthetic rates of remaining leaves and those produced
after grazing; (2) increased growth of newly formed leaves.
4
increased new leaf development from axillary buds and
increased tillering; (3) enhanced conservation of soil
moisture by reduction of transpiration; and (4) nutrient
recycling of dung and urine (McNaughton 1979, Hilbert et al
1981).
Defoliation may enhance photosynthesis by increasing the
amount of light (Jameson 1963) or changing the quality of
light (Ballare et al 1990) reaching plant bases, or by
initiating new, more photosynthetically efficient leaf
material (Branson 1953, Sosebee and Wiebe 1971).
Light
typically is not limiting in arid and semi-arid grasslands,
but may become limiting in meadows and pastures where
production may be depressed by a buildup of dead,
undecomposed plant material (Jameson 1963).
Increases in
soil heat due to greater short wave radiation may often have
as much or more of an effect on new leaf or shoot
development as increased photosynthetic rate of plant
tissues (Savage and Vermuelen 1983, Parsons et al 1984).
This effect may be especially important in moist soils with
frigid or mesic temperature regimes such as those commonly
found in the Northern Rocky Mountains.
Increased light stimulates plants to produce new, more
photosynthetically active leaf material.
New leaf material
is produced more by the elongation of newly formed leaves or
by the development of axillary buds, than by the elongation
of defoliated mature leaves (Jameson 1963).
For grazed
5
plants, this increase in photosynthetic activity of new leaf
and shoot tissue is thought to result from two main
processes:
(I) release of growing points from growth
inhibitors; and/or (2) increase in flow of available
nutrients along osmotic pressure gradients to new leaf or
shoot growing points.
Stem apices produce the hormone auxin, which inhibits
cell differentiation and elongation of other growing points
(Hillman 1984).
Auxin production ceases when stem apices
are removed, allowing new leaves and shoots to develop.
Nutrients flow through phloem sieve tubes along osmotic
pressure gradients.
Since growing points use nutrients at a
faster rate than other plant tissues, there is a constant
flow of nutrients from areas of greater concentration
(sources) to areas of lower concentration (sinks). When
defoliation removes leaf tissue and growing points,
including stem apices, nutrients are allocated to remaining
leaf growing points and shoot primordia (Canny 1984, Hillman
1984) .
Researchers have disagreed regarding the ability of
graminoids to compensate for tissue removal by grazing, and
the effects of this process on fitness of the grazed plant
(McNaughton 1979, Crawley 1983, Belsky 1986, McNaughton
1986).
Maschinski and Whitham (1989) suggest that grazed
plants respond along a continuum (from undercompensation to
overcompensation), depending on many factors such as type of
6
tissue grazed, plant species, nutrient and water
availability, and grazing management).
Olson and Richards (1988) reported "diminished" tiller
replacement of grazed crested wheatgrass (Agropyron desertorum
Fisch. ex Link) tussocks compared with ungrazed tussocks,
although tussocks grazed twice within a growing season
produced slightly more tillers than those grazed once.
Santos and Trlica (1978) found reductions in aboveground
biomass production of western wheatgrass {Agropyron smithii
(Pursh) Scribn. & Smith) with all clipping treatments, but
no significant reductions in aboveground biomass production
of blue grama (Bouteloua gracilis (H.B.K.) Lag. ex Steudel) with
clipping.
There is little evidence that fitness of an
individual plant is enhanced by defoliation, when compared
to an undefoliated plant under similar conditions (Crawley
1983, Caldwell 1984, but see Paige and Whitham 1987).
The grazing optimization hypothesis states that
compensation increases with greater tissue removal up to an
optimum point, beyond which plant growth is reduced (Vickery
1972, McNaughton 1979, Hilbert et al 1981).
Hilbert et al
(1981) theorized that plants growing at or near their
maximum relative growth rate have little opportunity to
respond positively to grazing since a relatively large
increase in growth rate would be required to increase
production compared with undefoliated plants.
Slower
growing plants require much smaller proportional increases
7
in relative growth rate to increase production compared with
undefoliated plants.
Nutrient Cycling
Soil nutrient availability has been shown to affect
plant yield (Pringle and van Ryswyk 1964, Solander 1983) ,
growth rate (Veerkamp et al 1980), tillering rate (Veerkamp
and Kuiper 1982, Carlsson and Callaghan 1990), and
flowering/vegetative shoot ratio (Carlsson and Callaghan
1990).
In wetland habitats, nutrient availability is often
limited by temperature, parent material, or anaerobic soil
conditions which.inhibit microbial breakdown of organic
matter (Chapin and Slack 1979, Solander 1983, Ohlson 1987).
Plant growth may be stimulated by nutrients recycled by
herbivore dung and urine (McNaughton 1979, Day and Detling
1990).
Some researchers, however, have concluded that
herbivory usually results in net losses of nitrogen
(Woodmansee 1978, Tiedeman et al 1986), the nutrient that
most frequently limits productivity in grasslands.
Nitrogen
may be lost through exportation of animal tissue (Senft et
al 1987, Tiedeman 1986), through volatization of excretal
nitrogen and through uneven distribution of fecal and
urinary nitrogen (Woodmansee 1978, Tiedeman et al 1986)
Impacts of grazing on nitrogen flux vary with management
as well as environmental factors (Woodmansee 1978, Schimel
et al 1988).
Higher stocking rates of cattle in riparian
8
areas may result in greater loss of nitrogen in animal
tissues, but these animals may graze in adjacent uplands and
return to riparian areas to rest and ruminate, thus
depositing relatively greater amounts of excretal nutrients.
Chapin and Slack (1979) and Chapin (1980) found that
defoliation of 2 tundra graminoids, Carexaquatilus and Eriophorum
vaginatum increased root phosphate absorption and respiration
rates.
Chapin and Slack (1979) suggested that increased
root activity resulted from phosphorus depletion as nutrient
reserves were allocated to support shoot regrowth.
Thus
nutrient uptake in grazed wet meadows may increase with
greater availability of excretal nutrients, and may be
stimulated further by the removal of leaf tissue and
subsequent regrowth.
Population Dynamics
Population dynamics studies describe changes in the
number of genetic individuals per unit area by determining
rates of birth, death, immigration and emigration (Crawley
1983) .
Since the identification of genetic individuals of
patch forming rhizomatous or stoloniferous species is
difficult or impossible, ecologists typically study the
dynamics of modular units such as tillers or shoots.
Plant or shoot natality and mortality are density
dependent (Crawley 1983), thus work interactively to
regulate population densities (Bernard 1976, Carlsson and
9
Callahan 1990, de Kroon and Kwant 1991) .
However population
dynamics of plants with interconnected root systems may vary
greatly from caespitose or taprooted plants.
Cook (1985)
reviewed population dynamics studies of clonal plants,
summarizing that: (I) vegetative reproduction was dominant
and seedling recruitment is rare; (2) rates of mortality and
natality are relatively constant over years, but vary
seasonally; (3) population numbers remain relatively
constant despite great flux in ramets because birth and
death rates are synchronous; and (4) an increase in
availability of resources increases both birth and death
rates.
Other studies have shown that factors such as soil
fertility and soil moisture also affect population density
as well as plant size (Solander 1983, Crawley 1983, Hultgren
1988, Hultgren 1989a, 1989b).
How herbivory affects each of
these general responses is poorly understood for many
rhizomatous riparian forages, and particularly for many wet
meadow sedges.
Characteristics Of Beaked Sedge
Beaked sedge has a wide circumpolar distribution in
temperate climates and is a dominant herbaceous component of
hydric riparian communities in the northern Rocky Mountains
(Hansen et al 1988, Kovalchik 1987).
Although beaked sedge
is moderately palatable to cattle and moderately tolerant of
grazing (Hermann 1970, Ratliff 1983) the species may be
10
invaded or replaced by other riparian graminoids when
subjected to prolonged heavy grazing (Kovalchik 1987).
Previous beaked sedge research has focused primarily on
natural history , the effects of water level and
fertilization on productivity, and nutrient content of the
species (Heyes 1979).
Beaked sedge shoots are essentially biennial (Bernard
and Gorham 1978), but may be photosynthetically active for
up to four years (Hultgren 1989b).
Survival to maturity is
low, and shoot flux is high (Bernard and Gorham 1978).
Although studies by Gorham and Somers (1972) in Minnesota
and Bernard (1976) in New York reported small variation in
shoot density throughout the year, Hultgren1s (1988) work in
Sweden found wide seasonal fluctuations with changes in
water level and other environmental variables.
Peak shoot density has been recorded in April (Gorham
and Somers 1972), mid-May with a smaller peak in Iate-July
(Bernard and Hankinson 1979), and mid-summer (Hultgren
1988).
Gorham and Somers (1972) reported peak new shoot
emergence in spring from shoots formed the previous fall,
with a smaller peak in August.
Hultgren (1988) observed
maximum new shoot emergence in late spring and summer.
Hultgren (1988) reported peak mortality in autumn, whereas
Gorham and Somers (1972) found highest mortality during the
peak flowering stage in mid-summer.
Beaked sedge has a low flowering to vegetative shoot
11
ratio, which is typical of grazing-tolerant species
(Minnesota 1972).
Bernard (1974) reported 14.5% of total
shoots flowering in late June, with a peak of about 18.5%
flowering shoots in late July in a New York wetland.
Gorham
and Somers (1972) found 40% of mature shoots bearing
fruiting spikelets in Minnesota.
Beaked sedge is strongly rhizomatous (Bernard and Gorham
1978) which allows for translocation of nutrients and water
between shoots.
When defoliated, rhizome-integrated shoots
can be subsidized by other connected shoots, or dormant buds
may be stimulated to initiate new shoot growth (Jonsdottir
and Callaghan 1989).
Pitelka and Ashmun reviewed studies of
nutrient transport in Carexarenaria L., concluding that mature
shoot support growth of rhizomes and younger shoots.
This
integration of shoots conveys a collective advantage to the
genet (genetic individual) through rapid replacement of
photosynthetic tissue.
The growth form of beaked sedge appears to be similar to
that of Nebraska sedge (Carex nebraskensis Dewey), which has been
described as essentially culmless until flowering (Ratliff
1983).
Culmless vegetative growth protects leaf primordia
from removal by grazing, allowing for rapid initiation of
new leaves should mature leaves be damaged (Minnesota 1972).
Although the apical growing points of beaked sedge remain
low during the vegetative stage, leaf meristems of the
sedges are typically less developed than other rhizomatous
12
graminoids (Cronquist 1981).
Thus the regrowth ability of
mature leaves may be even more limited than other forages,
and the initiation of new shoots from basal buds or rhizomes
may be the most important compensatory mechanism for many
sedges.
13
METHODS
Site Description
The study area lies along an upper reach of Cottonwood
Creek, a first order stream (Strahler, blue line) in the
Montana Agricultural Experiment Stations *s (MAES) Red Bluff
Research Ranch in southwest Montana (Fig. I).
Elevation is
about 1700 m and the site receives about 480 mm annual
precipitation (NOAA 1990).
Over 30% of the average annual
precipitation falls in May and June, and only about 15%
falls from November through February.
The Soil Conservation
Service has identified two dominant soil complexes in the
Cottonwood Creek watershed; the Oro-Fino Poin complex and
the Shurley-Rock Outcrop complex.
Soils of both complexes
are primarily coarse sandy loam from coarse grained gneiss,
schist and amphobolite (USDA 1989).
We studied four beaked sedge dominated stands located in
perennial seeps along Cottonwood Creek (Aspie 1989, Fig. 2).
Co-dominant herbaceous species included Nebraska sedge,
redtop {Agrostis stolonifera L.) and Kentucky bluegrass (Poapratensis
L.).
Other common herbaceous species included Carexlanuginosa
Michx., Carexspringellii Dewey, Carexmicroptera Mackenzie, avens (Geum
macrophyllum Willd.), monkey flower (Mimulus guttatus DC.) and
14
RANCH HEADQUARTERS
MONTAff A AGRICULTURAL
EXPERIMENT STATION'S RED
b l u f f Re s e a r c h r a n c h
NORRIS
STUDY SITE
LEGEND
U.S. HIGHWAY
STATE HIGHWAY
X NOAA CLIMATE STATION
DIRT ROAD
MONTANA
RIVER
STREAM
ENNIS DAM
NOAA CLIMATE STATION
SCALE
i ............. I_________ I________ I________ I________ I_________ I
1
O
1
2
3
4
5
km
Fig. I. General location map of the Cottonwood Creek
Study Area, Red Bluff Research Ranch near Norris
Montana.
Not u sed
Stand 3
Stand 2
Stand I
Stand 4
SCALE
i i i i
m eters
From: Aspie 1989
ROAD
STUDY SITE
FENCE LINE
STREAM
Fig. 2. Map of Cottonwood Creek controlled grazing system with locations
of beaked sedge study stands.
16
American brookline (Veronica americana Schwein.) .
Dominant woody
species were quaking aspen (Populus tremuloides Michx.) , Bebb
willow (Salix bebbiana Sarg.) and yellow willow (Salix lutea Nutt.).
We classified the soil Family from a soil profile in Stand I
as a sandy, mixed, frigid Fluvaquentic Haplaquoll (USDA Soil
Survey Staff 1989)
Grazing in the Cottonwood Creek study area was generally
light and sporadic prior to the early 1940s, when large
flocks of sheep were introduced.
Sheep use declined by the
early 1960s, replaced by cattle and horses.
An experimental
grazing system was established in 1980 and moderately
stocked with Hereford-Angus cross heifers for several years.
More pastures were added in 1985, and moderately stocked
with Hereford-Angus cross cow/calf pairs.
Experimental Desicrn
We selected 4 beaked sedge stands in 4 paddocks of an 8
paddock controlled grazing system along Cottonwood Creek in
June 1989 (Fig. 2).
Eighty-400 cm2 round plots were
systematically distributed among the pastures (Fig. 3) and
were the experimental units (true replication within
pastures).
Forty plots were grazed and 40 were protected
from grazing by 1.0 m diameter cages.
To minimize
immigration of shoots from grazed areas to ungrazed plots,
we severed rhizomes around the cage perimeters of the
ungrazed plots to a depth of 30 cm.
We randomly assigned
17
SCALE
O
1
m ete rs
GRAZED STUDY PLOT
UNGRAZED STUDY PLOT
26
W ater Well #3
WATER WELL
SHRUBS
FENCE LINE
rater Well #2
□ WaterlWeII #1
Stand 3
Fig. 3. Schematic diagram of a typical beaked sedge
study stand with layout of grazed and ungrazed plots and
water wells.
18
the treatment of the first plot in each stand, then
alternated treatments every 2.0 m.
Stands were grazed in
late June and mid-September of 1989 and 1990 by 12 cow/calf
pairs until utilization of preferred riparian vegetation,
mainly Kentucky bluegrass, reached 60-80%.
All existing shoots were marked with red wires in June
1989, and all emerging shoots in subsequent months were
marked with wires of different colors.
Mortality was also
monitored monthly within each plot and wires of dead shoots
removed.
Stand, initial shoot counts, soil penetration
resistance and basal groundcover of competing vegetation
were used as covariates in the statistical analysis.
Penetration resistance of each plot was estimated in
September 1989 and 1990 with a Soiltest proving-ring
penetrometer.
We measured penetration resistance 1.0 m
north, south, east and west of each plot and averaged the 4
measurements.
Combined basal groundcover of all species
other than beaked sedge was estimated in each plot in
September 1989 and 1990.
Three water wells (7.6 cm diameter
perforated PVC pipe, 100 cm deep) were set in each stand in
mid-July 1989.
Water levels were monitored bi-weekly during
the growing season throughout the study.
We also monitored
weekly precipitation with a static gauge and a recording
gauge at the study site in Cottonwood Creek.
Winter
precipitation was estimated from National Oceanographic and
Atmospheric Administration (NOAA) data from the recording
19
station located at Montana Power's Madison Powerhouse,
approximately 7 km south of the study basin (Fig. I).
We estimated percent height removed by measuring
greatest extent of green material on all shoots in the
grazed plots before and after grazing treatments.
We
counted the number of flowering shoots before the June
grazing treatment in 1989 and 1990.
Statistical Analysis
We estimated sample adequacy from a preliminary sample
of 10 randomly placed plots in spring of 1989.
Our results
indicated that we should be able to detect a 10% difference
between two treatment means of total shoots per plot at
P<0.10 with 40 plots per treatment.
We used the SAS (SAS
Institute 1987) General Linear Model (GLM) Repeated Measures
procedure for the analysis of variance with covariates for
shoot density and shoot emergence for 1989 and 1990.
A
square-root transformation was used for our new shoot
emergence data, which is suggested for enumerative data with
low counts (Sokol and Rohlf 1981).
The mortality data were
highly variable, with many low counts and occasionally large
numbers, thus they did not approach a normal distribution
even when using standard transformations.
Mortality data
were summarized graphically without statistical analysis.
We used the time by treatment interaction to test the
null hypothesis (Gurevitch and Chester 1986).
Beaked sedge
20
did not respond to grazing if the time by treatment
interaction was not significant (P<0.05).
We also tested
the main treatment effect using overall mean shoot density
and emergence.
The Block by Treatment Mean Square Error
combined with Model Error was the error term in the tests of
significance.
We back-transformed (squared) the shoot emergence Least
Square Means (LS Means) for graphic display of actual means.
We estimated 95% confidence intervals (CIs) taking into
account the heterogeneous variance of monthly counts, which
is compatible with Hotelling's T .
For emergence data the
CIs were calculated using the transformed results, then
back-transformed.
We compared the difference in mean shoot height (LS
Means) between June 1989 and June 1990 by treatment using
SAS (1987) GLM procedure for the analysis of variance.
21
RESULTS
The time by treatment interaction was significant for
mean shoot density (PcO.OOl), indicating that the grazing
treatments affected shoot density differently over time.
Overall mean shoot densities of the grazed and ungrazed
plots were not statistically different (P=O.073, Fig. 4,
Tables 10 and 11 in Appendix).
At the end of the study,
grazed plots had 28.7% more shoots per plot and ungrazed
plots 11.3% more shoots per plot than the initial count.
Mean shoot densities in grazed and ungrazed plots were not
statistically distinguishable at the initiation of the study
(16.1 and 16.9 shoots per plot respectively).
In the model,
stand (P<0.001), penetration resistance (P<0.054) and
initial shoot count (P<0.001) were important as covariates,
but did not interact with the grazing treatments (Table 11
in Appendix).
We also found a time by treatment interaction for shoot
emergence (P=0.003), thus our grazing treatments affected
new shoot production differently over time.
Overall shoot
emergence (Fig. 5) was greater in the grazed plots than the
ungrazed plots (P=0.006, Tables 12 and 13 in Appendix)
during the study.
Stand (P<0.001), penetration resistance
(P=0.003), initial shoot count (PcO.OOl), and competition
(P=0.09) were all important as covariates, but did not
22
M o n th /Y e a r
Fig. 4. Profile of mean shoot density per plot
by month and year. 95% Confidence Interval (Cl)
= X ± t39,0.025 * SE(X).
■oGrazed
^ Ungrazed
I Cl
M o n th /Y e ar
Fig. 5. Profile of mean shoot emergence and
mortality per plot by month and year. 95% Confidence
Interval (Cl) = [xt ± t39,0.025 * SE(Xt)]2.
23
interact with the grazing treatments (Table 13 in Appendix).
As expected, shoot density and shoot emergence responded
differently to our grazing treatments, as indicated by the
time by treatment interactions (P=O.001 and P=O.003
respectively).
To further characterize response
differences, we selected periods within the mean shoot
density and mean shoot emergence profiles for additional SAS
GLM Procedure multivariate contrasts.
We tested linear,
quadratic, and cubic responses, and main treatment effect
(Table I).
P values for these a posteriori tests were not
adjusted for experiment-wise error over multiple
observations (Sokol and Rohlf 1981), thus should not be used
for estimates of Type I error.
Table I. Multivariate analysis of mean shoot density
_________ and mean shoot emergence profiles.______________
Response Variable P Values
Overall
Mean
Linear
Quadratic
Cubic
7/894/90
0.760
0.065
0.003
0.005
5/907/90
0.084
0.001
0.963
NA
8/906/91
0.018
0.395
0.957
0.886
7/895/90
0.532
0.028
O'.024
0.049
6/909/90
0.001
0.528
0.636
0.077
Profile
Period
Mean Shoot
Density
Mean Shoot
Emergence
Shoot densities were similar from July 1989 through
24
April 1990 (P=0.76).
Only in September 1989 was shoot
density in the ungrazed plots greater (11%) than in the
grazed plots (Table I , Fig. 4).
During May-July 1990 mean
shoot density of the grazed plots increased linearly while
shoot density of ungrazed plots remained relatively
unchanged (Table I, Fig. 4).
From July 1990 through the end
of the study (June 1991) grazed plots supported 12% to 16%
more shoots per plot than ungrazed plots (Table I, Fig. 4).
Other than in June 1989 when 31% more new shoots emerged
in grazed plots than ungrazed plots, mean shoot emergence
per plot was similar through May 1990.
From June 1990
through September 1990 mean shoot emergence was greater in
the grazed plots than the ungrazed plots.
Averaged over both years (1989 and 1990), only 7.8% of
all shoots flowered by the first grazing treatment in late
June (Table 2).
The number of flowering shoots was similar
for the grazed and ungrazed treatments (8.1% and 7.5%
respectively).
Only 4.8% of all shoots had flowered by late
June in 1989, compared with 10.8% in 1990.
Table 2.
Mean percent flowering shoots per plot in June
1989 and 1990.
June
1989
SE
June
1990
SE
Average
SE
Grazed
5.9
9.0
10.4
10.2
8.1
9.8
Ungrazed
3.7
6.0
11.3
11.7
7.5
10.0
7.7
10.8
10.9
7.8
9.9
Treatment
4.8
Combined
SE - Standard Error
25
Mean overall shoot mortality per plot combined over both
years was similar for the grazed and ungrazed plots (29.2
and 28.9 respectively. Table 3).
Mortality tended to be
greater in the ungrazed plots in Year I, and greater in
grazed plots in Year 2.
Table 3.' Mean overall shoot mortality per plot during
Year I and Year 2.
Year I
SE
Year 2
SE
Combined
SE
Grazed
11.0
1.0
18.2
1.4
29.2
1.8
Ungrazed
13.0
1.0
15.9
1.0
28.9
1.6
12.0
Combined
SE - Standard Error
0.7
17.0
0.8
29.0
1.2
Treatment
Rodent grazing of beaked sedge shoots increased sharply
in Apfil-June 1990, particularly in the ungrazed plots
(Table 4).
Although rodent-caused mortality was greater in
the grazed plots in spring 1991, overall shoot deaths from
rodent grazing in the ungrazed plots was nearly double that
of grazed plots.
{Microtuspennsylvanicus
Primary rodent grazers were meadow voles
Wagner) and deer mice
(Peromyscus maniculatus
Ord) .
Mean shoot heights of grazed and ungrazed plots declined
slightly from June 1989 to June 1990 (Table 5).
The change
in mean shoot height was similar between treatments.
Percent green material removed in the grazed plots by
each grazing treatment averaged about 33% over all
26
Table 4.
Rodent-caused shoot mortality during Year I and
Year 2.
Apr-Jun 1990
Apr-Jun 1991
Overall
Un­
grazed
Grazed
Un­
grazed
53
13
63
73
12
20
20
58
57
8
77
6
16
21
132
4
11
26
I
I
16
28
Total
27
149
90
50
158
290
Stand
Grazed
Un­
grazed
I
6
34
2
2
3
Table 5.
Grazed
Mean difference in mean shoot heights (cm)
between grazed and ungrazed plots measured in
June 1989 and June 1990.
Stand
Grazed
SE
Ungrazed
SE
Mean Height
Year 2-Year I
-3.3*
1.5
-2.5*
1.5
Mean Height
Year I
52.6
0.6
50.6
0.6
48.1
0.6
0.5
Mean Height
49.3
Year 2
SE - Standard Error
* - not significantly different (P<0.05)
treatments (Table 6).
Percent height removed was least in
June of both years (20.3 and 32.2% respectively) and
greatest in September (44.2 and 40.5 % respectively).
Using
a height-weight curve for Nebraska sedge (McDougald and
Platt 1976), 35% height removed converts to 15% air dry
weight removed and 50% height removed represents 30% of
weight removed.
Because our method of estimating percent
27
height removed did not account for uneven use of individual
leaves of a given shoot, our estimates were conservative.
Table 6.
Mean percent height removed per grazed plot for
1989 and 1990.
1990
1989
Stand
June
SE
Sept
SE
June
SE
Sept
SE
I
14.2
8.4
36.9
25.2
37.8
11.6
35.2
11.6
2
29.3
21.2
48.3
11.4
23.5
16.1
39.3
12.0
3
4.9
10.1
49.7
14.9
26.0
19.8
34.2
14.5
4
15.9
15.5
34.7
20.3
20.5
17.6
53.4
15.2
15.2 17.2
Comb­
ined
SE - Standard Error
43.6
17.9
25.3
17.8
40.9
15.5
Mean shoot density was greater for Stand I than the
remaining stands (Fig. 6).
were more variable.
Profiles of emergence by stand
Although Stand I appeared to produce
the most shoots during the growing seasons (Fig. 7),
overwinter shoot production was similar for all stands.
Both shoot density and shoot emergence tended to be
greater in plots with high initial shoot counts.
Although
penetration resistance and competition were significant as
covariates, there was no clear association of these
covariates with shoot density or shoot emergence.
Summer precipitation data for 1989 and 1990 is
summarized in Figs. 8 and 9.
Water well data for stands 2
and 3 are displayed in Figs. 10 and 11 (Tables 14 and 15 in
Appendix).
28
S2 "■ S 3 -O S 4
Month/Year
Fig. 6. Profiles of mean shoot densities of
combined grazed and ungrazed plots for each stand
by month and year. Sx = Stand(x).
S2 -" S 3 -0 S4
Month/Year
Fig. 7. Profiles of mean shoot emergence of
combined grazed and ungrazed plots for each
stand by month and year. Sx = Stand(x).
29
<o c N a ><o o o r ^'a-v- o'>rr
» » »
^
^ r
u> in m
IO I- CO IO CM <n CD
r- M CM p-
r> Zr r r* r* ^
N N ^ m m co
o)S Sr2 o o o
M o n th /W e e k
Fig. 8. Weekly precipitation totals (mm) for
summer 1989 at the Cottonwood Creek study site.
E
c
30
I
5-20
Q>
CL
Jl I Il III
C O l O C M O l D O O C D O O r ^ i y v - C O l O i - O O l O C M O l l O C M O C O C O O r ^ ^ 1 '-
V
V
IOIOlO
CO
to
CD
r-
h-
r-
COCOCO
0 > 0 > 0 > T - 0 0 0 0
Month/Week
Fig. 9. Weekly precipitation totals (mm) for
summer 1990 at the Cottonwood Creek study site.
30
20
-T -
Well #1 -a Well # 2 > Well # 3
-20 -
CD
- 4 0 ----
5* - 6 0 ----
- 8 0 ----
-100
7 7 8 9 9 9
89
1011 4 4 5 5 6 6 7 7 8 8 9 9
|
90
1010 5 6
| 91
Biweekly Measurements
Fig. 10. Bi-weekly water well levels (cm) for
Stand 2 from July 1989 through June 1991.
20-T-
-2 0
5
Well #1 o Well # 2 + Well #3
- -
-60 - -
- 8 0 ----
7 7 8 9 9 9 1011 4 4 5 5 6 6 7 7 8 8 9 9
89
I
90
10 10 5 6
I 91
Biweekly Measurements
Fig. 11. Bi-weekly water well levels (cm) for
Stand 6 from July 1989 through June 1991.
31
DISCUSSION
Shoot Population Response
Since mean shoot density responded differently in grazed
plots compared with ungrazed plots over time, particularly
in Spring 1990, our hypothesis that light to moderate cattle
grazing has no effect on shoot density is rejected.
In
spring 1990, shoot density increased sharply in the grazed
plots while remaining relatively unchanged in the ungrazed
plots.
I attributed this short-term response to the
cumulative effects of our grazing treatments, combined with
environmental conditions favorable to new shoot emergence
during this period.
Shoot density remained greater in the
grazed plots compared with the ungrazed plots throughout the
rest of study.
In September 1989 shoot density was greater
in the ungrazed plots than the grazed plots, which was
unexpected.
A lag in response of the grazed plots to
September grazing, or natural variation in the system may
explain this result.
I concluded that our grazed beaked
sedge plots overcompensated for cattle grazing in spring
1990, and maintained that advantage.
Peak shoot density occurred in September of both years,
which is slightly later than Hultgren1s (1988) finding of
mid-summer peak shoot density.
Shoot density ranged from
32
about 400 m’2 to 680 m"2 in our stands.
This is high
compared with most recent studies (Table 7), but similar to
densities reported by Mornsjo (1969).
Shoot density
fluctuated widely, about 40% in the grazed plots and 38% in
the ungrazed plots.
These results support those of Hultgren
(1988) who reported fluctuations of 30% to 50% in her study
areas over a 4 year period.
Bernard (1976) found that shoot
densities changed only 24% over a 2 year study, and Bernard
and Gorham (1978) report a fluctuation of 17% over a single
year.
Table 7.
Maximum densities of beaked sedge reported in
North America.
Location of study
Author
Density
(Shoots m )
Mornsjo (1969)
Sweden
600-700
Gorham and Somers
(1973)
Alberta
370
Bernard (1974)
Minnesota
238
Bernard and
Hankinson (1979)
New York
264
Hultgren (1988)
Sweden
128-476
Because mean shoot emergence responded differently over
time with our grazing treatments (P=O.003), I rejected the
hypothesis that cattle grazing had no effect on shoot
emergence.
Overall shoot emergence was greater in the
grazed plots than the ungrazed plots (P=0.006).
I concluded
that beaked sedge in grazed plots overcompensated for shoot
33
defoliation by producing more new shoots.
The greatest differences in emergence between grazed and
ungrazed treatments occurred in July 1989, July 1990 and
September 1990.
The July shoot counts followed the June
grazing treatments by 4 to 5 weeks, whereas the September
counts followed the September grazing treatments by about 2
weeks.
Peak shoot emergence was concentrated in June
through August in both treatments, which supports Hultgren1s
(1988) findings of peak emergence in late spring-early
summer.
Relative differences in shoot emergence between
grazed and ungrazed plots were greatest during the
comparatively rapid growth period of late June-early July,
although the slightly lower use of the grazed plots in June
of both years may have affected this result.
Grant et al (1981) reported increased rates of new leaf
and tiller production in clipped plots of perennial ryegrass
(Loliumperenne L.).
New leaf and tiller production were
greatest during the first and second weeks of the regrowth
period, disappearing after 3 to 4 weeks.
Increased shoot
emergence observed in our study in July of both years and in
September of 1990 may have been due more to the temporal
proximity of these counts to grazing treatments than an
effect of season.
Shoot Mortality
In our study, shoot mortality was greatest during winter
34
and late summer, which supports the findings of Gorham and
Somers (1972, Fig. 5).
Shoot mortality was greater in the
ungrazed plots in April through July 1990.
During this
period rodent-caused shoot mortality was much greater in the
ungrazed than in the grazed plots (Table 4).
However how
rodent grazing influenced shoot emergence and density in our
experiment cannot be determined.
Rodents removed entire shoots, which were cut into small
segments to access inflorescences for food (Getz 1985), or
removed stem bases or root crowns.
To minimize this
influence we removed rodents from the stands in spring of
1990 (Table 8) using Sherman live traps.
Table 8.
Results of rodent trapping in June and July of
1990.
June
July
Total
Microtus
oennsvlvanicus
52
23
76
Peromvscus maniculatus
16
10
26
Sorex oalustris
22
5
27
Sorex vacrrans
6
' 15
21
ZaDDus DrinceDs
0
4
4
Eutamias minimus
0
2
2
97
59
156
Species
Total
The greater use of ungrazed plots by rodents in our study
area is explained by the positive response of both meadow
voles and deer mice to increasing vegetative cover (Birney
et al 1976, Getz 1985) . Microtus populations fluctuate
35
annually as much as 5-fold, and vary over multi-year cycles
10-fold or greater (Taitt and Krebs 1985).
Fluctuations in
vole numbers may be affected by food or cover availability,
density dependent mechanisms, predation, or a combination of
these factors.
Drost and Fellers (1991) found cyclic
increases in a deer mouse population following winters with
high rainfall, and declines with dry winters.
The increase
in rodent grazing on beaked sedge in our study area in
spring 1990 may have reflected a cyclic population peak of
meadow voles and deer mice, or may have resulted from the
wet spring and high forage production following the drought
year of 1988.
In our study, shoot mortality generally peaked later
than shoot emergence, which leads to the question of how
shoot density dependence affected these cycles.
Noble et
al. (1979) asserted that increased shoot natality and
resultant increased shoot density leads to increased
competition for resources and a subsequent increase in
mortality.
Shoot mortality in our study plots was generally
lower in summer 1989 than in summer 1990, as was shoot
density.
Greater mortality may have been a density
dependent response, or may have been due to lower 1990 water
levels.
Although density dependence undoubtedly affected
relative rates of natality and mortality, stochastic
environmental variables such as temperature and
precipitation may have been more important influences on
36
shoot flux (Hultgren 1988).
Response To Water Level
Water levels varied in space and time in our stands
(Figs. 10 and 11).
Some areas were inundated virtually
year-round, whereas others were inundated part of the year
and essentially saturated due to capillary action the
remainder of the year.
The amount of snow persisting into
early spring appeared to be the most important factor in our
study area, although water levels also responded to periods
of heavy summer precipitation.
Snowpack accumulation and
persistence depends on winter temperatures as well as amount
of snowfall.
Much lower late-winter (February) temperatures
in 1989 (Table 9) contributed to greater residual snowpack.
in the Cottonwood Creek basin in 1989 than in 1990, which
caused higher summer water levels in all of our beaked sedge
stands (Figs. 10 and 11) in 1989.
Although summer
precipitation patterns do not noticeably differ between 1989
and 1990 (Figs. 8 and 9), water levels were higher in 1989
(Figs. 10 and 11).
Water levels increased during 2 periods
of high rainfall (>40cm) in July and August 1990.
The
responses varied greatly between wells, however, and water
levels declined rapidly when rains ceased.
37
Table 9 .
NOAA winter climate data - Norris Powerhouse,
1988 through 1991.
Month
Winter
Precipitation
19881989
Nov
Dec
Jan
Feb
Mar
Dev. (in.)
from Monthly
Mean
+0.11
-0.19
+0.25
-0.15
+0.18
19891990
Dev. (in.)
from Monthly
Mean
-0.73
+0.31
-0.03
-0.49
M
19901991
Dev. (in.)
from Monthly
Mean
-0.04
—0.48
-0.27
-0.22
Winter
Temperature
Nov
Dec
Jan
Feb
Mar
19881989
Dev. (#F)
from Monthly
Mean
-0.8
—2.2
+1.7
-15.2
+0.8
19891990
Dev. (#F)
from Monthly
Mean
+4.1
— 1.2
+5.3
—0.6
+3.1
19901991
Dev. (#F)
from Monthly
Mean
+5.0
-11.6
0.0
+8.7
+2.3
M
M - Data inadequate or unavailable.
Shoot density of the grazed and ungrazed plots varied
seasonally with water level and/or temperature.
Neither
shoot density nor emergence responded predictably to changes
in water level.
Hultgren (1988, 1989b) found that shoot
emergence was lower at high water levels than at more
moderate levels.
Portions of beaked sedge stands covered
with standing water throughout most of the growing season
produced fewer but taller shoots with larger bases.
In our
38
study, ungrazed plots supported more shoots in the first
year when water levels were highest, which differs from
Hultgren*s (1988) findings.
Shoot densities of grazed plots were more consistent
between 1989 and 1990 than densities of ungrazed plots,
which may indicate that beaked sedge was better able to
compensate for grazing during periods when soils were at
field capacity (oxidizing soil conditions) rather than
saturated (reducing soil conditions).
Ratliff (1987) found
that shoot densities of heavily grazed (64%) Nebraska sedge
were not different than shoot densities in an exclosure in a
dry year.
However after examining maximum possible
differences (95% confidence) in shoot density the following
spring, Ratliff (1987) noted that species composition may
have been changing in favor of Nebraska sedge in grazed
areas.
Shoot densities of grazed beaked sedge stands may
show a similar response during years of below average water
levels.
Physiological Responses
Our results support the literature reporting that
rhizomatous graminoids with low growing points and few
flowering stems are grazing tolerant.
Our results also
support findings that removing standing material,
particularly on rhizomatous graminoids, stimulates the
initiation of new shoots.
Whether this response is more
39
attributable to nutrient allocation and/or uptake, or to .
changes in microclimate is unclear.
We did not measure the effects of grazing on root
biomass or rate of nutrient absorption in this study.
Without this information we cannot fully assess the degree
of compensation of the grazed plots.
Plants typically
respond to defoliation by increasing nutrient allocation to
new leaf production (Jameson 1963).
In Alaska, Chapin and
Slack (1979) found that defoliation stimulated nutrient
uptake but decreased root growth rate of
water sedge
{Carex aquatilus
Eriophorum vaginatum
and
Wahl.), although water sedge
responded only after repeated defoliations.
Strongly
rhizomatous species translocate nutrients between shoots,
thus nutrients are typically allocated to plants tissues
most capable of rapid production (Jdnsdottir and Callaghan
1989) .
Beaked sedge roots in our study plots should have
benefitted from these responses with light to moderate
grazing and 60 days summer regrowth.
The mean percent flowering shoots in June 1989 (5%) and
1990 (8%) is lower than that found by Bernard (1974, 14.5%).
This result is generally consistent with the literature that
beaked sedge has a low ratio of flowering to vegetative
shoots, which typically indicates greater grazing tolerance
than species with a greater percentage of flowering shoots.
40
Management Implications
The results of our study reflect the response of beaked
sedge to light or moderate grazing with at least 60 days
regrowth between grazing treatments.
Different grazing
intensities and frequencies might produce different results,
and could provide an indication of compensatory response
thresholds.
Santos and Trlica (1978) reported greater
reductions in aboveground production of western wheatgrass
with increased clipping frequency and intensity, while
clipping frequency and intensity had little affect on
aboveground biomass of blue grama.
Frame and Hunt (1971)
found that aboveground production of perennial ryegrass
decreased with increased defoliation frequency, but
increased with intensity of defoliation.
Our results tend to support current ecological theory
that ecosystems are not stable, but fluctuate over time and
space with changing physical and biotic circumstances
(Westoby et al 1989).
Consequently, grazing management
should not be directed toward trying to maintain a stable
state of community succession, but should concentrate more
on capitalizing on opportunities when conditions are
favorable, and avoiding management caused stresses during
periods of high risk (Maschinski and Whitham 1989, Westoby
et al 1989).
With this approach management flexibility and
timing should be emphasized rather than fixed systems.
41
Although it is not clear how water level affected all
aspects of our study, it appears that grazed plots responded
to grazing with higher shoot densities in spring 1990 when
water levels were low.
How much of this response is a
factor of cumulative treatment effects is also not known.
Deferring grazing of beaked sedge stands in very wet years
until fall when soils are less susceptible to trampling
(Marlow et al 1987, Table 15 in Appendix), and grazing
beaked sedge earlier and heavier in dry years may optimize
shoot natality and soil stability of these communities.
Long term monitoring programs will help to determine
cumulative effects of defoliation and soil displacement by
trampling.
42
CONCLUSIONS
Grazing by cattle affected shoot density and shoot
emergence, as indicated by the time by treatment
interactions (P=O.001 and P=O.003 respectively).
I
concluded that grazed beaked sedge populations
overcompensated for light to moderate cattle grazing by
increasing the production of new shoots.
Given an adequate
regrowth period, beaked sedge should tolerate light to
moderate, early summer and fall grazing in our southwest
Montana willow/beaked sedge study area.
However, the degree
of response was influenced by fluctuations in environmental
conditions, particularly precipitation and temperature.
Conditions most favorable to new shoot initiation may occur
in spring following relatively dry winters.
To properly
manage beaked sedge stands we can limit the duration of
grazing and allow for adequate regrowth, particularly during
the hot portion of the grazing season. We can also identify
scenarios of high risk, such as when soil moisture is high,
and minimize impacts during these periods.
43
LITERATURE CITED
Adams, D.C., R.C. Cochran, and P.O. Currie. 1987. Forage
maturity effects on rumen fermentation, fluid flow, and
intake in grazing steers. J. Range Manage. 40:404-408.
Aspie, J.M. 1989. Influence of groundwater on streambanksoil-moisture content, storm-runoff production, and
sediment production in a semi-arid watershed, southwest
Montana. MS Thesis, Montana State Univ. Bozeman,
Montana.
Ballare, C.L., A.L. Scopel, and R.A. Sanchez. 1990. Far-red
radiation reflected from adjacent leaves: an early
signal of competition in plant canopies. Science
247:329-331.
Belsky, A.J. 1986. Does herbivory benefit plants? A review
of the evidence. Am. Nat. 127:870-892.
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51
APPENDIX
Table 10.
Mean shoot density per plot by month.
Grazed
Ungrazed
Month/Year
Mean
Jun 89
16.12
18.06-14.18
16.88
18.57-15.19
Jul 89
23.08
26.09-20.07
22.02
24.45-19.59
Aug 89
26.38
29.91-22.85
26.38
29.18-23.58
Sep 89
24.48
27.38-21.58
27.38
30.26-24.50
Apr 90
23.18
25.88-20.48
23.00
25.81-20.19
■ May 90
23.58
26.45-20.71
23.10
26.17-20.03
Jun 90
24.40
27.17-21.63
22.12
24.86-19.38
Jul 90
26.98
30.42-23.54
22.88
25.85-19.91
Aug 90
27.25
30.84-23.66
23.98
27.44-20.52
Sep 90
25.30
28.99-21.61
22.00
25.51-18.49
Oct 90
22.22
25.64-18.80
18.90
22.18-15.62
May 91
20.78
23.87-17.69
17.40
20.87-13.93
Jun 91
22.60
25.62-19.58
19.02
22.38-15.66
Cl1
95% confidence interval
Mean
Cl1
52
Table 11. Analysis of variance for mean shoot density.
Source
DF
Mean Square
F Value
Pr>F
Stand
3
2402.96
7.46
0.0002
Treatment
I
1070.09
3.32
0.0728
Stand*Trmt
3
318.07
0.99
0.4042
Penetration
Resistance
I
1239.19
3.85
0.0539
Initial Shoot
Density
I
19546.17
60.65
0.0001
Competition
I
446.71
1.39
0.2431
69
322.28
Initial*Trmt
I
30.65
0.09
0.7614
Penetration*
Trmt
I
137.75
0.42
0.5204
Competition*
Trmt
I
363.86
1.10
0.2979
Error
66
329.86
Time*Trmt
11
67.37
4.20
0.0001
759
16.04
Error
Error (Time)
53
Table 12.
Mean shoot emergence per plot by month.
Grazed
Ungrazed
Month/Year
Mean
Cl1
Mean
Cl1
Jul 89
7.15
8.54-5.90
4.91
5.93-3.97
Aug 89
3.81
4.47-3.21
4.36
4.80-3.94
Sep 89
1.22
1.59-0.89
1.72
2.15-1.34
Apr 90
2.68
3.03-2.35
2.22
2.71-1.78
May 90
0.70
0.95-0.49
0.83
1.11-0.58
Jun 90
1.53
2.05-1.08
1.04
1.34-0.78
Jul 90
3.09
3.80-2.42
1.78
2.23-1.37
Aug 90
2.45
3.10-1.87
2.14
2.96-1.45
Sep 90
2.26
2.90-1.69
1.10
I.65—0.66
Oct 90
0.22
0.33-0.13
0.10
0.17-0.05
May 91
2.51
3.10-1.97
2.15
2.82-1.57
Jun 91
2.68
3.18-2.22
1.92
2.59-1.36
Total
30.03
95% confidence interval
24.27
54
Table 13. Analysis of variance for mean shoot emergence.
Source
DF
Mean Square
F Value
Pr>F
Stand
3
6.49
8.55
0.0001
Treatment
I
6.20
8.16
0.0056
Stand*Trmt
3
0.98
1.29
0.2859
Penetration
Resistance
I
7.27
9.58
0.0028
Initial Shoot
Density
I
13.22
17.42
0.0001
Competition
I
2.27
2.99
0.0885
69
0.76
Initial*Trmt
I
0.01
0.01
0.9157
Penetration*
Trmt
I
0.37
0.48
0.4906
Competition*
Trmt
I
0.30
0.04
0.8456
Error
66
0.78
Time*Trmt
11
. 1.00
2.58
0.0032
759
0.39
Error
Error (Time)
55
Table 14. Water well levels (cm below soil surface) , 1989
through 1991 in Stands I and 2.
Stand I
Stand 2
Well I
Well 2
Well 3
7/14/89
0
0
0
10
-5
0
7/28/89
-I
0
2
2
-4
0
8/11/89
-8
0
0
2
-10
-I
9/1/89
-11
0
0
2
-2 0
-11
9/15/89
-15
0
-3
2
-26
-19
9/29/89
-13
-2
-4
I .
-33
-26
10/14/89
-14
-I
-2
0
-33
-26
11/4/89
-7
0
0
I
-23
-8
4/11/90
—16
-3
-5
-8
-14
-38
4/25/90
-16
0
-8
-8
-49
-41
5/9/90
-18
0
-5
-7
—50
-42
5/23/90
-21
-I
-11
-9
-40
—41
6/13/90
-17
0
-11
-7
—46
-38
6/27/90
-21
-I
-20
-13
-52
-43
7/11/90
-30
-3
-30
-21
-60
-50
7/25/90
-21
-4
-25
-16
—60
—56
8/8/90
-38
-12
-37
-31
-72
-63
8/22/90
-26
-9
-31
-24
-73
-63
9/12/90
-42
-13
-42
-40
-87
>-90
9/26/90
-42
-11
-43
-39
>-90
>-90
10/10/90
-29
-10
-38
-31
>-90
>-90
10/24/90
-29
-8
-36
-29
-88
>-90
5/19/91
-21
-10
-18
-9
-35
-14
6/1/91
-20
-6
-8
-7
-19
—10
6/29/91
-16
-3
-3
-7
-11
—6
Date
Well I
Well 2
Well 3
56
Table 15. Water well levels (cm below soil surface), 1989
__________ through 1991 in Stands 3 and 4.
Stand 3
Date
Well I
Stand 4
Well 2
Well 3
Well I
Well 2
Well 3
7/14/89
-11
0
0
0
0
0
7/28/89
-18
2
2
2
0
0
8/11/89
-33
-2
0
2
0
0
9/1/89
-38
-7
0
I
-I
0
9/15/89
-42
-6
0
0
-2
0
9/29/89
-44
-8
0
2
-I
-I
10/14/89
-38
-2
I
I
-I
0
11/4/89
-20
4
2
0
I
0
4/11/90
-23
-6
0
0
0
5
4/25/90
M
M
M
M
M
M
5/9/90
-30
-3
0
0
0
4
5/23/90
-32
—6
0
2
0
4
6/13/90
-36
-7
0
2
0
4
6/27/90
-43
-9
-I
2
-2
2
7/11/90
-57
-18
-28
-2
-12
-8
7/25/90
-58
-15
-4
I
-5
-11
8/8/90
-68
-32
-44
0
-15
-16
8/22/90
-67
-28
-22
I
-7
-13
9/12/90
-73
-29
-39
-3
-12
-21
9/26/90
-78
-36
-48
-3
-9
-23
10/10/90
-70
-32
-25
-3
-4 .
-21
10/24/90
-71
-28
-16
-2
-4
-7
5/19/91
-14
-22
2
M
M
M
6/1/91
-12
-2
2
3
-2
17
-7
0
4
10
-I
15
6/29/91
M - Missing data
57
Table 16. Mean penetration resistance index (top 30
cm) estimated at each study plot on three
different dates.
Stand
Sept 89
June 90
Sept90
I
11.6
15.1
22.7
2
18.2
21.8
32.7
3
16.4
22.5
24.8
4
10.6
14.8
15.9
Combined
14.7
19.3
24.1
MONTANA STATE UNIVERSITY LIBRARIES
762 10
59 4
HOUCHEN
B IN D E R Y LTD
UTICA/OMAHA
NE.