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Ecosystem invasibility is determined by combinations of environmental variables, invader attributes, disturbance regimes, competitive abilities of resident species and evolutionary history between residents and disturbance regimes. Understanding the relative importance of each factor is critical to limiting future invasions and restoring ecosystems.We investigated factors potentially controlling Bromus tectorum invasions into Artemisia tridentata ssp. wyomingensis communities across 75 sites in the Great Basin. We measured soil texture, cattle grazing intensity, gaps among perennial plants and plant cover including B. tectorum, biological soil crusts (BSCs) and bare soil. Using a priori knowledge, we developed a multivariate hypothesis of the susceptibility of Artemisia ecosystems to B. tectorum invasion and used the model to assess the relative importance of the factors driving the magnitude of such invasions.Model results imply that bunchgrass community structure, abundance and composition, along with BSC cover, play important roles in controlling B. tectorum dominance. Evidence suggests abundant bunchgrasses limit invasions by limiting the size and connectivity of gaps between vegetation, and BSCs appear to limit invasions within gaps. Results also suggest that cattle grazing reduces invasion resistance by decreasing bunchgrass abundance, shifting bunchgrass composition, and thereby increasing connectivity of gaps between perennial plants while trampling further reduces resistance by reducing BSC.Synthesis and applications. Grazing exacerbates Bromus tectorum dominance in one of North America's most endangered ecosystems by adversely impacting key mechanisms mediating resistance to invasion. If the goal is to conserve and restore resistance of these systems, managers should consider maintaining or restoring: (i) high bunchgrass cover and structure characterized by spatially dispersed bunchgrasses and small gaps between them; (ii) a diverse assemblage of bunchgrass species to maximize competitive interactions with B. tectorum in time and space; and (iii) biological soil crusts to limit B. tectorum establishment. Passive restoration by reducing cumulative cattle grazing may be one of the most effective means of achieving these three goals.
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Conditions favouring Bromus tectorum dominance of
endangered sagebrush steppe ecosystems
Michael D. Reisner
1
*
,
, James B. Grace
2
, David A. Pyke
3
and Paul S. Doescher
4
1
Department of Environmental Studies, Augustana College, Rock Island, IL 61201, USA;
2
US Geological Survey,
National Wetlands Research Center, 700 Cajundome Blvd., Lafayette, LA 70506, USA;
3
US Geological Survey,
Forest and Rangeland Ecosystem Science Center, 3200 SW Jefferson Way, Corvallis, OR 97331, USA; and
4
Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
Summary
1. Ecosystem invasibility is determined by combinations of environmental variables, invader
attributes, disturbance regimes, competitive abilities of resident species and evolutionary
history between residents and disturbance regimes. Understanding the relative importance of
each factor is critical to limiting future invasions and restoring ecosystems.
2. We investigated factors potentially controlling Bromus tectorum invasions into Artemisia
tridentata ssp. wyomingensis communities across 75 sites in the Great Basin. We measured soil
texture, cattle grazing intensity, gaps among perennial plants and plant cover including B. tec-
torum, biological soil crusts (BSCs) and bare soil. Using a priori knowledge, we developed a
multivariate hypothesis of the susceptibility of Artemisia ecosystems to B. tectorum invasion
and used the model to assess the relative importance of the factors driving the magnitude of
such invasions.
3. Model results imply that bunchgrass community structure, abundance and composition,
along with BSC cover, play important roles in controlling B. tectorum dominance. Evidence
suggests abundant bunchgrasses limit invasions by limiting the size and connectivity of gaps
between vegetation, and BSCs appear to limit invasions within gaps. Results also suggest that
cattle grazing reduces invasion resistance by decreasing bunchgrass abundance, shifting
bunchgrass composition, and thereby increasing connectivity of gaps between perennial plants
while trampling further reduces resistance by reducing BSC.
4. Synthesis and applications. Grazing exacerbates Bromus tectorum dominance in one of
North America’s most endangered ecosystems by adversely impacting key mechanisms medi-
ating resistance to invasion. If the goal is to conserve and restore resistance of these systems,
managers should consider maintaining or restoring: (i) high bunchgrass cover and structure
characterized by spatially dispersed bunchgrasses and small gaps between them; (ii) a diverse
assemblage of bunchgrass species to maximize competitive interactions with B. tectorum in
time and space; and (iii) biological soil crusts to limit B. tectorum establishment. Passive res-
toration by reducing cumulative cattle grazing may be one of the most effective means of
achieving these three goals.
Key-words: bare ground, biological soil crusts, cattle grazing, disturbance, diversity, inva-
sion, plant gaps
Introduction
Ecosystem invasibility is governed by a complex collection
of biotic and abiotic factors including environmental
conditions, disturbance regimes and responses of native
species to those regimes, as well as the biotic resistance
provided by the resident community (Lonsdale 1999;
Richardson & Pysek 2006). Biotic resistance is especially
important in limiting the magnitude of invasive species
after they have established (Levine, Adler & Yelenik
2004). Changes that increase resource availability are
likely to increase susceptibility to invasion (Davis, Grime
& Thompson 2000). Further, the introduction of an
exotic herbivore with which resident species have no
Present address: Environmental Studies Department, Augustana
College, Rock Island, IL 61201, USA.
*Corresponence author. E-mail: michaelreisner@augustana.edu
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society
Journal of Applied Ecology 2013, 50, 1039–1049 doi: 10.1111/1365-2664.12097
evolutionary history may exacerbate the magnitude of
non-native plant invasions if it reduces the competitive
abilities of native plants and increases resource availability
(Parker, Burkepile & Hay 2006). Developing a predictive
understanding of invasibility requires that we develop an
understanding of how the various factors work together
to limit invasion (Agrawal et al. 2007).
Artemisia tridentata big sagebrush ecosystems of the
Intermountain West, USA, evolved with little herbivore
pressure until the introduction of livestock (Mack &
Thompson 1982). Within these ecosystems, lower eleva-
tion, more arid, A. tridentata ssp. wyomingensis (hence-
forth Artemisia) communities are the most common, but
least resistant to invasion by exotic annual plants and least
resilient to disturbance (Miller et al. 2011). Even in the
absence of fire, these communities are especially vulnerable
to invasions by Bromus tectorum L, and under some
circumstances, B. tectorum can dominate the herbaceous
understorey community (Miller et al. 2011). Previous stud-
ies have demonstrated the importance of several factors in
the invasion process (soil texture, landscape orientation,
competition-driven biotic resistance from native bunchg-
rasses and biological soil crust (BSC) communities
(Table 1). Livestock grazing has been implicated in the
spread and dominance of B. tectorum via several mecha-
nisms (Mack & Thompson 1982; Table 1). Nonetheless,
we have a poor understanding of how these factors work
together and their relative importance in determining the
magnitude of B. tectorum invasions (Miller et al. 2011).
Once B. tectorum sufficiently dominates the understorey
and fills interspaces among plants, it creates a continuous,
highly flammable fuel that significantly increases the risk
of fire (Pyke 2011). Once a fire occurs, B. tectorum
increases the frequency of fires. This change in fire regime
may lead to a ‘catastrophic regime shifts’ (Scheffer et al.
2009), whereby native shrubsteppe communities are
transformed into annual grasslands dominated by B. tec-
torum and other invasives (Miller et al. 2011). For practi-
cal purposes, these shifts are irreversible because of the
significant investments necessary to restore these systems
(Pyke 2011).
Preventing such regime shifts will require a better
understanding of the simultaneous interacting factors that
determine the magnitude of B. tectorum invasion once it
has established in pre-fire Artemisia communities (Miller
et al. 2011). Managers would benefit from understanding
the causal network of mechanisms by which these factors
interact with each other and how they collectively influ-
ence B. tectorum dominance. They would also benefit
from an early warning indicator that the cumulative resis-
tance of the resident community has been compromised
to the point that B. tectorum likely dominates the under-
storey and thereby potentially setting the stage for a
regime shift with the next fire.
Using a priori knowledge, we developed a multivariate
hypothesis of the invasibility of Artemisia ecosystems to
B. tectorum invasion in the absence of fire based upon the
findings of previous studies in this system. The model
included abiotic (soil physical properties, landscape orien-
tation), cattle grazing disturbance and biotic factors (resi-
dent community abundance, composition and structure),
predicted to be important determinants of B. tectorum
dominance (Fig. 1, Table 1). Our analyses addressed the
following questions: (i) What combination of abiotic and
biotic conditions limit the magnitude of B. tectorum domi-
nance? (ii) Can shifts in community structure, measured
by the size and connectivity of gaps between native plants,
serve as an indicator of susceptibility to B. tectorum
Table 1. Components of hypothesis represented by initial metamodel (Fig. 1)
Path Hypothesized mechanism
1() Cattle herbivory decreases Bromus tectorum abundance (Hempy-Mayer & Pyke 2009). (+) Cattle increase abundance by
dispersing seeds and increasing propagule pressure (Schiffman 1997)
2 Cattle trampling decreases biological soil crusts cover and increases safe sites for B. tectorum establishment (Ponzetti, McCune &
Pyke 2007)
3 Cattle herbivory decreases bunchgrass abundance (Briske & Richards 1995)
4 Cattle herbivory alters bunchgrass community composition by favouring more grazing-resistant species (Briske & Richards 1995)
5 Higher heat loads and spring insolation increase B. tectorum abundance (Stewart & Hull 1949; Chambers et al. 2007)
6 Lower heat loads increase bunchgrass productivity (Davies, Bates & Miller 2007)
7 Deeper, coarser-textured soils increase B. tectorum abundance (Stewart & Hull 1949)
8 Changes in bunchgrass composition influence community structure because species have different life forms (Grime 1977;
James et al. 2008)
9 Changes in bunchgrass composition influence invasibility because species have different competitive abilities (Goldberg &
Barton 1992) and patterns of resource use (James et al. 2008)
10 Bunchgrass abundance is inversely related to the size of and connectivity between gaps in perennial vegetation (Herrick
et al. 2005)
11 Native bunchgrass abundance decreases B. tectorum abundance by reducing resource availability (Chambers et al. 2007)
12 Safe sites increase B. tectorum establishment rates (Fowler 1988).
13 Sagebrush abundance may increase B. tectorum abundance via facilitation (Griffith 2010) or decrease abundance via competition
(Reichenberger & Pyke 1990).
14 Increases in the size of and connectivity between gaps in perennial vegetation increase B. tectorum abundance by increasing
general resource availability (James et al. 2008; Okin et al. 2009)
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society, Journal of Applied Ecology,50, 1039–1049
1040 M. D. Reisner et al.
dominance and thereby vulnerability to a regime shift
with the next fire?
We used structural equation modelling (SEM) to evalu-
ate a multivariate hypothesis across 75 sites already invaded
by B. tectorum. SEM provides a means of representing
complex hypotheses about causal networks and testing for
model data consistency (Grace 2006). It represents an
advance over classical regression approaches (e.g. multiple
regression) when used with observational data (Grace,
Youngblood & Scheiner 2009). The advance provided by
SEM comes partially from incorporating the associations
among predictors into the overall hypothesis rather than to
simply ignore or control for them. This is accomplished by
extending the univariate model (y=a+bx+e) to allow ys
to depend on other ys and thereby represent networks of
relationships in SEMs (y=a+bx+cy+e).
Because of this capability, SEM models can be used to
specify hypotheses about mediating pathways and address
questions, such as Can an association between Aand Cbe
explained by the factor B? This is achieved by evaluating a
model such as A?B?Cand determining whether or not
r
AC
=r
AB
r
BC
. By assuming (and justifying based on prior
information) that if Awere manipulated, Bcould show a
response, and similarly, if Bwere manipulated, Ccould
show a response, then a test of the conditional indepen-
dence of Aand Cin our example (AC|B) could permit a
result leading us to reject that possibility (Anot indepen-
dent of Cwhen conditioned on B). SEMs thus build on
causal assumptions to yield testable implications that can
be evaluated with data. Estimated parameters obtained for
a selected model then represent a set of predictions for fur-
ther testing. The ultimate test of an SEM model is its ability
to correctly predict future samples. For individual applica-
tions, the plausibility of causal assumptions (e.g. previous
demonstrations that varying Acan lead to response in Bor
known mechanisms whereby Acan influence B) is often
sufficient for reasonable inferences to be made.
Our results suggest that bunchgrass community struc-
ture, abundance and composition, and BSCs all play
critical roles in limiting the magnitude of B. tectorum domi-
nance. Cattle grazing may exacerbate the magnitude of
invasion by reducing biotic resistance. Model evaluations
imply that cattle grazing can reduce bunchgrass cover and
shift bunchgrass community composition towards grazing-
tolerant species and thereby increase the size and connectiv-
ity of gaps among perennial vegetation exacerbating
invasion. Cattle trampling may also exacerbate invasion by
reducing BSC cover. Ultimately, increases in the size and
connectivity of gaps among native perennial vegetation
may provide managers with an early warning indicator of
increased susceptibility to B. tectorum dominance of Arte-
misia communities and thereby increased vulnerability to
regime shifts in one of North America’s most widespread
but endangered ecosystems.
Materials and methods
STUDY AREA AND SAMPLING DESIGN
The study examined 75 Artemisia sites scattered across 4700 km
2
(roughly the size of state of Rhode Island) with elevations
between 1265 and 1580 m across five Artemisia-dominated plant
associations of the northern Great Basin floristic province of
Oregon, USA. Natural Resource Conservation Service (NRCS)
Ecological Site Descriptions and digital soil maps (http://websoil-
survey.nrcs.usda.gov) were used to ensure coverage of spatial
variation in water stress driven by soil texture. Plant communities
varied in dominant perennial tussock grasses and included the
following ecological sites (ES): (i) loamy 254308 mm precipita-
tion zone (PZ) with Pseudoroegneria spicata and Achnatherum
thurberianum; (ii) sandy loam 203254 mm PZ with Hesperostipa
comata and P. spicata; (iii) clayey 254308 mm PZ with A. thur-
berianum and Poa secunda; and (iv and v) north slopes and south
slopes 152254 mm PZ with P. spicata and A. thurberianum
co-dominating north and south slopes, respectively.
Fig. 1. Conceptual a priori multivariate
model of Artemisia ecosystem susceptibil-
ity to Bromus tectorum dominance in the
absence of fire. Dotted-line boxes represent
conceptual variables hypothesized to influ-
ence invasibility. Components of the over-
all hypothesis are described in Table 1.
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society, Journal of Applied Ecology,50, 1039–1049
Invasibility and spatial gaps among plants 1041
Each ES was delineated into three landscape substrata using
10-m resolution US Geological Survey Digital Elevation Models
(DEM) to ensure variation in heat loads and water stress associ-
ated with changes in landscape orientation: (i) northerly aspects
(090°, 270360°), (ii) southerly aspects (90270°) or (iii) flat.
Study plots were located at different distances from the nearest
livestock watering locations to capture variation in cattle grazing
intensity. Random points were selected and field verified to
ensure that plots were located: (i) every 200400 m, starting at
100 m and extending to >3200 m from the nearest water; (ii) in
as many soillandscape strata combinations as possible; and
(iii) >200 m from the nearest road to minimize related effects. To
reduce potential confounding effects of time since fire, all sites
burned since 1930 were excluded using a fire perimeter data base
(http://sagemap.wr.usgs.gov accessed 17/3/2008).
SAMPLING
Thirty of the 039-ha study plots were sampled in 2008 and another
45 in 2009. Six 25-m transects were established in each plot using a
spoke design, and herbaceous, shrub and BSC cover measured
using linepoint intercept (Herrick et al. 2005). All sampling
occurred between 10 May and 15 July in both years to capture peak
herbaceous biomass. Aspect and slope of each plot were calculated
from DEM using Arc-GIS 130 and, with latitude, used to calculate
potential heat loads for each plot (McCune 2007).
Potential variation in water stress was inferred by the following
measurements: (i) soil texture at 015 cm soil depth; (ii) potential
effective rooting depth, which was measured by digging a soil pit
until bedrock, a restrictive layer (clay accumulation layer) or 2 m
depth was reached; and (iii) amount and timing of precipitation
for each study site derived from PRISM at 2-km
2
cell resolution
(Daly et al. 2008). Sampling-year precipitation for all study plots
was estimated for three seasons: 1 August to 31 October (fall),
1 November to 31 March (winter) and 1 April to 31 July (spring
summer).
Cattle grazing intensity was quantified by four measurements:
field-verified distance from the nearest water; dung frequency and
dung density from 12, 1 925 m belt transects; and bunchgrass
(tussock) basal area. Basal circumference (C) of 30 randomly
selected bunchgrasses was measured in each plot and used to cal-
culate bunchgrass basal area (cm
2
) using the following formula:
Area =p(C/2p)
2
.
Bare soil cover was calculated using linepoint intercept data to
represent exposed soil surface not covered by vegetation, visible
BSC, dead vegetation, litter or rocks (Herrick et al. 2005). Soil sur-
face aggregate stability was assessed in interspace microsites at 18
random sampling points along transects using soil from the upper
04 mm (Herrick et al. 2005). Two indicators of soil erosion resis-
tance were calculated: mean soil stability and proportion of sam-
ples rated as extremely stable (Beever, Huso & Pyke 2006).
We assessed the structure of the native perennial community
by quantifying the size of and connectivity of gaps between such
vegetation using the basal gap intercept method (Herrick et al.
2005). We calculated mean gap length and the proportion of
transects covered by large gaps (>200 cm in length).
MULTIVARIATE ANALYSIS
Species cover, distance from nearest water, dung density, bunch-
grass basal area, heat loads, soil depth, precipitation, gap size
and herbaceous biomass data were log-transformed to improve
distributional properties, correlations with ordination axes and
variation explained by ordinations (McCune & Grace 2002).
Other variables were not transformed.
Non-metric multidimensional scaling (NMS) ordination was
used to relate patterns in community composition to environmen-
tal gradients (PC-Ord
TM
; McCune & Grace 2002). Joint plots and
Pierson’s correlations were used to describe relationships between
environmental gradients and the strongest patterns of community
composition.
We used nonparametric multiplicative regression (NPMR) in
HyperNiche
TM
to quantify the relationship between species’ cover
and environmental gradients (McCune 2009). Predictors were
scores of the three ordination axes. These scores represented an
integrated measure of complex environmental gradients associ-
ated with dominant patterns of herbaceous community composi-
tion. Response variables were the cover of each species using a
local mean estimator and Gaussian kernel function. To control
for potential interactions between axes, response curves were
generated using partial models and focal variables (McCune
2009). A final NPMR model was run using the three axes’ scores
as predictors. Final model fit was assessed with a cross-validated
R
2
(McCune 2009).
Hierarchical agglomerative cluster analysis was used to identify
groups of sites differing in community composition (McCune &
Grace 2002). Multivariate differences in community composition
between identified groups were tested using multiresponse permu-
tation procedures (MRPP) (a=005). Identified groups were
overlaid onto ordinations to accentuate relationships between
groups and environmental gradients. Multivariate differences in
relativized environmental variables between groups were tested
with MRPP. Differences in individual environmental variables
between groups were assessed with ANOVA (a=010), and Bonfer-
roni-adjusted 90% confidence intervals were used to quantify
differences between groups.
STRUCTURAL EQUATION MODELLING
In our study, an initial conceptual model was used as a SEM meta-
model, representing a family of possible models (Fig. 1, Table 1).
Our modelling process considered the available observed variables
to identify ‘indicator variables’ (the observed variables that will
serve as proxies for conceptual variables in the meta-SEM) using
procedures described in Grace et al. (2012). Except for ‘Potential
Safe Sites’, all model constructs were represented using single indi-
cator variables. Bromus tectorum cover was selected as the indica-
tor to measure ‘Invasion Magnitude’. Bunchgrass and sagebrush
cover were selected to measure their abundances. The three NMS
ordination axes of bunchgrass species’ cover data were used to
develop an indicator of ‘Bunchgrass Community Composition’.
Distance from nearest water was selected as the indicator to mea-
sure cumulative ‘Cattle Grazing Intensity’. Heat load was selected
to measure ‘Heat load Exposure’, and percent sand content at
015 soil depth was selected to measure ‘Soil Physical Properties’.
The proportion of transects covered by large gaps (>200 cm in
length) was selected as the measure of ‘Community Gap Struc-
ture’. Two indicators were selected to represent ‘Potential Safe
Sites’ BSC and cover of bare soil.
All SEM analyses were conducted using AMOS 18.0 software
(SPSS 2010). Maximum likelihood procedures were used for
model evaluation and parameter estimation. Model fit was
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society, Journal of Applied Ecology,50, 1039–1049
1042 M. D. Reisner et al.
evaluated by sequentially evaluating likelihood ratios by using
the single-degree-of-freedom chi-squared goodness-of-fit statistic.
Modification indices were used to evaluate the need to include
links or error correlations not in the original model. This process
produced a final inferential model. The stability of the final
model was evaluated by introducing other available indicators to
determine whether they represented additional contributing infor-
mation. For example, our initial indicator for cattle grazing
intensity was ‘distance from nearest water’. The three alternative
potential indicators (cow pie frequency, cow pie density and
bunchgrass basal area) for this construct did not improve model
fit or amount of variation in cheatgrass dominance explained and
were no longer included.
Results
PATTERNS OF INVASIBILITY CONVENTIONAL
MULTIVARIATE RESULTS
Nearly 92% of variation in community composition was
explained by the final ordination (Fig. 2). Axis 1 was the
dominant axis explaining 609% of variation in composi-
tion data. Axis 1 was a strong gradient of decreasing
cattle grazing disturbance and heat stress (Fig. 2): dung
density (r=035); dung frequency (r=036); distance
from water (r=041); deep-rooted bunchgrass basal area
(r=071); and heat loads (r=044). In addition, BSC
cover, soil aggregate stability and proportion of soil
aggregate stability values rated as highly stable increased
along Axis 1 (Fig. 2). The size of and connectivity
between gaps and amount of bare soil decreased strongly
along Axes 1 and 2 (Fig. 2) (see Table S1, Supporting
Information).
Axes 2 and 3 represented weaker relationships explain-
ing 193% and 116% of the variation, respectively. Axis
2 showed a strong gradient of decreasing sand, increasing
clay and increasing fall and winter precipitation (Fig. 2).
Axis 3 demonstrated a weaker gradient of decreasing cat-
tle grazing associated with decreasing dung density and
frequency and increasing deep-rooted bunchgrass basal
area (see Table S1, Supporting Information).
Nonparametric multiplicative regression model sensitivi-
ties indicate that Axis 1 was the best predictor of non-
native species. The strength of the relationship between
cover of native species and these three axes varied consid-
erably (Fig. 3; see Table S2, Supporting Information).
P. spicata,A. thurberianum,P. secunda and forbs had
strong positive relationships with Axis 1, P. secunda and
forbs had strong positive relationships with Axis 2, and
Elymus elymoides had a strong positive relationship with
Axis 3 (Fig. 3).
Cluster analysis identified five distinct groups of com-
munities with 0% of the information remaining (MRPP
using species data: A=033, P<001; Fig. 4; See Tables
S3 and S4, Supporting Information). Several species were
uniquely associated with one or more groups (Fig. 4; See
Table S3, Supporting Information). Combined heat loads,
soil physical properties, BSC cover, bare soil cover, soil
stability, community gap structure and cattle grazing
intensity differed significantly among groups (MRPP
using environmental data: A=059, P<00001; Fig. 5;
See Table S4, Supporting Information).
State 1 consisted of two groups (1A and 1B) of commu-
nities with an intact herbaceous understorey dominated by
native bunchgrasses and forbs (Fig. 4). Thirty-one
percentage of study plots were in one of these groups. State
1 also contained phase-at-risk communities (communities
at risk of crossing a biological threshold to being domi-
nated by B. tectorum; 25% of study plots) with an under-
storey co-dominated by native species and B. tectorum.
States 2 (23% of study plots) and 3 (21% of study plots)
consisted of communities that have crossed a biological
threshold and had understories dominated by B. tectorum
and the non-native annual forb, Lepidium perfoliatum.
Communities in Groups 1A and 1B had the lowest levels
of cattle grazing combined with the smallest and least con-
nected gaps between perennial vegetation (Fig. 5). Group
1B communities had higher heat loads and finer-textured
soils compared to those of Group 1A. Communities com-
prising phase-at-risk communities were characterized by
intermediate levels of cattle grazing, heat loads, water
stress and size of and connectivity between gaps (Fig. 5).
State 2 communities were characterized by intermediate
to high levels of cattle grazing and intermediate levels of
heat loads and water stress. State 3 communities had the
highest levels of cattle grazing and bare soil cover, largest
and most connected gaps and lowest soil aggregate stabil-
ity (Fig. 5).
heat
distance
cp.freq/den
b.basal
sand
clay
gaps>200
gap.size bare.soil
s.stab.
sp-su.prec
f-win.prec
bsc
Axis 1
Axis 2
Co mmuni ti e s
State 1
State 1
Phase-at-risk
State 2
State 3
A
B
Fig. 2. Ordination of plots in community composition space.
Non-metric multidimensional scaling ordination with final stress
of 992; final instability of <001; Monte Carlo test
P-value <005. Vectors show the strength and direction of corre-
lations between environmental variables and axes. Only variables
with significant R
2
(>020) are shown. Different plot symbols
show groups derived from cluster analysis that differ in composi-
tion and environmental factors. State 1A and 1B communities
have understoreys dominated by native bunchgrasses; phase-
at-risk communities are co-dominated by bunchgrasses and non-
natives, and State 2 and State 3 communities are dominated by
non-native species.
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society, Journal of Applied Ecology,50, 1039–1049
Invasibility and spatial gaps among plants 1043
STRUCTURAL EQUATION MODELLING RESULTS
The final SEM model (v
2
=1888; P=054; 20 d.f.)
showed very close fit between model and data. A number of
the initially hypothesized relationships (Table 1) were not
supported by data. Sagebrush abundance did not help
explain invasion magnitude, either directly or indirectly. As
a result, that variable was removed from the final model.
Heat load exposure, cattle grazing intensity and native
bunchgrass cover were indirect predictors of invasion mag-
nitude in the final model (Fig. 6). Unanticipated in the ini-
tial model was dependence of safe sites on heat loads and
sand, and dependence of bunchgrass composition on sand
content. The final model explained 72% of the variation in
the magnitude of invasions among sites.
Concerning strengths of linkages in the final model,
changes in community gap structure, that is, increases in
the size of and connectivity between gaps among native
plants, were predictive of higher levels of B. tectorum
cover (r=083). Native bunchgrass cover and composi-
tion were not direct predictors of B. tectorum cover,
rather they were indirect predictors through their
relationship to gaps. Gaps characterized by bare soil had
a strong positive association with B. tectorum cover
(r=038), whereas gaps characterized by BSC cover had
a strong negative association with B. tectorum cover
(r=026).
Cattle grazing intensity was positively associated with
B. tectorum cover through three independent pathways.
Because distance from water is inversely related to cattle
grazing levels, positive path coefficients indicate a negative
relationship between cattle grazing and the response
variable in the model (Fig. 6). Thus, model results imply
that pathways from cattle grazing to B. tectorum cover
propagate through (i) negative influences on bunchgrass
abundance (034), (ii) negative influences on BSC abun-
dance (029) and (iii) impacts on bunchgrass community
composition (Axis 2) (022). There was no evidence that
cattle grazing directly decreased or increased B. tectorum
cover independent of these stated routes.
High levels of heat load exposure were associated with
lower levels of bunchgrass (046) and BSC (036)
abundance. Coarser-textured soils were more likely to
have higher levels of B. tectorum, regardless of the other
factors (i.e. a direct linkage of 048). Coarser-textured
soils also had an indirect path through effects on bare soil
cover and bunchgrass community composition (Axis 3)
that increased B. tectorum cover.
By adding up the path strengths, it is possible to com-
pute what is referred to as ‘total effects’ of predictors on
NMS Axis 1
–1·5 –1·0 –0·5 0·0 0·5 1·0
Cover (log)
0·0
0·2
0·4
0·6
0·8
1·0
1·2
1·4
B. tectorum
P. spicata
E. elymoides
L. perfoliatum A. thurberianum
P. secunda
Forbs
H. comata, A. hymenoides, K. macrantha
Forbs
NMS Axis 2
–0·5 0·0 0·5 1·0
Cover (log)
0·0
0·2
0·4
0·6
0·8
1·0
1·2
1·4
B. tectorum
P. spicata
P. secunda
H. comata
Forbs
L. perfoliatum
E. elymoides
A. hymenoides K. macrantha
A. thurberianum
NMS Axis 3
–0·8 –0·6 –0·4 –0·2 0·0 0·2 0·4 0·6 0·8
Cover (log)
0·0
0·2
0·4
0·6
0·8
1·0
E. elymoides
P. spicata Forbs
A. thurberianum
L. perfoliatum
B. tectorum
P. secunda
H. comata, A. hymenoides, K. macrantha
(a) (b)
(c)
Fig. 3. Nonparametric multiplicative regression response curves showing relationship between species cover and gradients represented by
non-metric multidimensional scaling ordination axes. Axis 1 is a gradient of decreasing cattle grazing intensity and heat load exposure
(a), Axis 2 is a gradient of decreasing water stress (b), and Axis 3 is a gradient of decreasing cattle intensity (c).
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society, Journal of Applied Ecology,50, 1039–1049
1044 M. D. Reisner et al.
State 1A-Intact P. spicata -A. thurberianum communities
Species
E. elymoides
A. thurberianum
P. spicata
P. secunda
A. hymenoides
H. comata
K. macrantha
Forbs
B. tectorum
L. perfoliatum
Abundance (% cover)
0
2
4
6
8
10
12
14
16
*
*
*
(22%) (19%)
(32%)
(2%)
State 1B-Intact P. secunda-E. elymoides communities
Species
E. elymoides
A. thurberianum
P. spicata
P. secunda
A. hymenoides
H. comata
K. macrantha
Forbs
B. tectorum
L. perfoliatum
Abundance (% cover)
0
10
20
30
40
50
*
*
*
(20%)
(71%)
(12%) (5%)
Phase-at-Risk communities
Species
E. elymoides
A. thurberianum
P. spicata
P. secunda
A. hymenoides
H. comata
K. macrantha
Forbs
B. tectorum
L. perfoliatum
Abundance (% cover)
0
2
4
6
8
10
12
14
**
*
(26%)
(3%)
(2%)
(17%)
(2%)
State 2-B. tectorum -L. perfoliatum-P. secunda
co-dominated communities
Species
E. elymoides
A. thurberianum
P. spicata
P. secunda
A. hymenoides
H. comata
K. macrantha
Forbs
B. tectorum
L. perfoliatum
Abundance (% cover)
0
2
4
6
8
10
12
14
16
18
20
(25%)
(36%)
(15%)
*
*
*
State 3-B. tectorum -L. perfoliatum
dominated communities
Species
E. elymoides
A. thurberianum
P. spicata
P. secunda
A. hymenoides
H. comata
K. macrantha
Forbs
B. tectorum
L. perfoliatum
Abundance (% cover)
0
2
4
6
8
10
12
14
16
18
20
22
24
*
*
*
(11%)
(51%)
(24%)
Fig. 4. Community composition of five groups derived from cluster analysis. *Denotes species with highest three indicator values for the
group from indicator species analysis. Reported values are back-transformed means, and error bars are 90% Bonferroni-adjusted
confidence intervals. (%) is the relative abundance of the species calculated as the proportion of total cover of the group.
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society, Journal of Applied Ecology,50, 1039–1049
Invasibility and spatial gaps among plants 1045
Landscape orientation
Communities
State 1A
State 1B
Phase-at-Risk
State 2
State 3
Calculated potential head loads
0·0
0·2
0·4
0·6
0·8
1·0
a
bb
b
ab
Soil physical properties
Communities
State 1A
State 1B
Phase-at-Risk
State 2
State 3
% sand and clay content 0-15cm soil
depth and soil depth (cm)
0
10
20
30
40
50
60
70
% sand
% clay
Soil depth
aa
aaa
b
a
ab
ab
a
aaa
a
a
Cattle Grazing Disturbance Intensity
Communities
State 1A
State 1B
Phase-at-Risk
State 2
State 3
Distance from nearest water (m)
0
500
1000
1500
2000
2500
3000
3500
a
ab
ab ab
b
Cattle Grazing Disturbance Intensity
Communities
State 1A
State 1B
Phase-at-Risk
State 2
State 3
Cow pie density (pies/ha2), cow pie
frequency (%), and bunchgrass basal area (cm2)
0
200
400
600
800
1000
1200
1400
Cow pie density
Cow pie frequency
Bunchgrass basal area
a
b
d
b
c
a
ab
ab
b
b
aa
a
bb
Bare soil and biological soil crust cover
Communities
State 1A
State 1B
Phase-at-Risk
State 2
State 3
Percent Cover
0
10
20
30
40
Bare soil cover
Biological soil crust cover
a
b
b
a
ab
ab
a
ab
cc
Basal gaps between perennial vegetation
Communities
State 1A
State 1B
Phase-at-Risk
State 2
State 3
Basal gap length (cm) and percent
of transect in gaps >200cm in length
0
25
50
75
100
125
150
175
275
300
325
350
375
Basal gap length
Percent of transect in gaps >200cm in length
aab
b
d
aa
bb
c
Fig. 5. Differences in heat loads, soil physical properties, biological soil crusts, bare soil cover, soil stability, community gap structure
and cattle grazing intensity of five groups identified by cluster analysis. Error bars represent Bonferroni-adjusted 90% confidence
intervals. Different lower-case letters above bars indicate significant differences between groups (a=010).
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society, Journal of Applied Ecology,50, 1039–1049
1046 M. D. Reisner et al.
downstream responses. Computed total effects of predic-
tor variables on B. tectorum in order of importance were
as follows: (i) community gap structure (068), (ii) soil
physical properties (042), (iii) safe sites (bare soil cover,
038), (iv) heat load exposure (037), bunchgrass commu-
nity composition (NMS#1, 031), (v) safe sites (BSC
cover, 026), (vi) cattle grazing disturbance (026),
(vii) bunchgrass abundance (024) and (viii) bunchgrass
community composition (NMS#3, 004).
Discussion
By combining SEM with an observational approach, we
were able to gain important new insight into the relative
importance of the numerous factors determining the mag-
nitude of B. tectorum invasions of Artemisia ecosystems
and gain valuable insight into potential underlying mecha-
nisms. Our results provide strong support for some a
priori hypothesized mechanisms (i.e. cattle trampling
reduces bunchgrass and BSC abundance) and no support
for others (i.e. cattle reduce invasions by grazing B. tecto-
rum). Our SEM findings should help prioritize future
experiments to test our inferences regarding underlying
mechanisms and more landscape-scale observational stud-
ies to further evaluate and refine the model and construct
predictive models (Grace 2006).
In this study, model results support the idea that a
complex causal network of simultaneously operating fac-
tors and mechanisms are driving invasion of B. tectorum
in Artemisia ecosystems. Based upon the SEM results,
shifts in community structure, as measured by the size of
and connectivity of gaps between native plants, exert a
strong positive effect on the magnitude of B. tectorum
invasion. This finding is consistent with growing evidence
in semi-arid and arid ecosystems showing that increases in
gap connectivity (Busso & Bonvissuto 2009; Okin et al.
2009) and changes in how species abundance is
distributed in a community (James et al. 2008) are associ-
ated with a loss of ecosystem resistance to invasion
(Scheffer et al. 2009). We define resistance as the collec-
tive ability of the resident sagebrush community to limit
B. tectorum dominance in the face of invasion (Chambers
et al. 2007). Increases in the connectivity of these gaps
were associated with a dramatic increase in the magnitude
of such invasions (Okin et al. 2009). This loss of resis-
tance to invasion probably increases the magnitude of
B. tectorum dominance after subsequent disturbances and
may set the stage for a regime shift to B. tectorum-domi-
nated grasslands with the next fire (Scheffer et al. 2009).
Our research suggests that two environmental factors
influence the inherent resistance of Artemisia ecosystems to
B. tectorum invasion. Communities located on coarser-
textured soils or characterized by higher potential heat
loads (Stewart & Hull 1949) were inherently least resistant
to B. tectorum invasion. These communities are character-
ized by higher levels of water stress and lower productivity.
The inherent structure of these communities that consists of
larger and more connected gaps among perennial vegetation
and higher amounts of bare soil may make them vulnerable
to other disturbances that increase the size of gaps.
Consistent with other studies, biotic resistance from resi-
dent bunchgrass and BSC communities played pivotal roles
and appears to limit the magnitude of B. tectorum invasion
(Richardson & Pysek 2006). Water availability is the pri-
mary controlling factor of seedling establishment in these
ecosystems (Schupp 1995). Several studies have found a
strong negative association between BSC community integ-
rity and B. tectorum abundance (Ponzetti, McCune & Pyke
Fig. 6. Final inferential model of Artemisia
ecosystem invasibility. Single-headed
arrows represent significant linkages
(a=005). Double-headed arrows indicate
significant correlations between variables
and their residuals. The magnitudes of
standardized path coefficients are repre-
sented by line thicknesses. Dotted grey
lines are unanticipated significant paths.
Because distance from water is inversely
related to cattle grazing intensity (i.e. graz-
ing intensity increases with decreasing
distance), positive path coefficients and
correlations between grazing intensity and
variables indicate an inverse relationship
(i.e. increasing cattle grazing intensity
decreases bunchgrass abundance). R
2
val-
ues depict the proportion of variation of
endogenous variables explained by the
model. The dotted boxes depict conceptual
variables of the meta-structural equation
modelling (Fig. 1).
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society, Journal of Applied Ecology,50, 1039–1049
Invasibility and spatial gaps among plants 1047
2007; Ponzetti & McCune 2008) and showed that BSCs
reduce B. tectorum germination and establishment rates by
impeding root penetration and growth (Serpe et al. 2008).
Our findings suggest that BSC communities are especially
important in limiting the magnitude of B. tectorum inva-
sions in gaps between perennial vegetation by minimizing
potential safe sites for establishment.
Consistent with other studies, we found that bunchg-
rasses reduced the magnitude of B. tectorum invasions
most likely by reducing water and nutrient availability
(Chambers et al. 2007; Prev
ey et al. 2010). Our findings
provide important insight into this mechanism. Nearly all
the biotic resistance effect was indirect through a strong
direct effect of bunchgrass abundance and composition
on community structure. By limiting the size and connec-
tivity of gaps, bunchgrasses likely minimize resources
available to B. tectorum spatially. Further, three species,
P. spicata,A. thurberianum and P. secunda, appear to be
especially important determinants of such resistance.
P. spicata and A. thurberianum are dominant deep-rooted
bunchgrasses with most active growth in later spring,
whereas P. secunda is a shallow-rooted bunchgrass that is
active in late winter and early spring. This combination of
differing structure and phenology reflects their differing
abilities to acquire resources at different soil depths
(James et al. 2008) and seasons and thereby provide con-
tinuous interaction with B. tectorum and collectively limit
available resources temporally and at different soil depths.
By controlling for several potentially confounding
factors (Knick et al. 2011), we gained important insights
into the role of cattle grazing as a determinant of ecosystem
resistance to B. tectorum invasion. We found no evidence
that cattle grazing, even at the high intensities 100 m from
the nearest water development, reduced B. tectorum cover.
To the contrary, we found strong evidence that increasing
cattle grazing intensity indirectly promotes an increase in
the magnitude of B. tectorum dominance. Cattle herbivory
was found to be associated with reduced native bunchgrass
abundance, shifts in bunchgrass composition to only the
most grazing-tolerant species and aggregated bunchgrasses
beneath protective sagebrush canopies (Reisner 2010).
These collective cattle-induced changes thus appear to rip-
ple through the community by increasing the size and con-
nectivity of gaps between perennial vegetation. As gaps get
bigger and more connected, both live and dead (litter) her-
baceous soil cover decreases and the amount of bare soil
increases. Cattle trampling reduced resistance within these
larger gaps by reducing BSC cover.
Changes in community structure and how species’
abundance is distributed in the community may increase
general resource availability (James et al. 2008). As cattle
grazing increased, P. spicata,A. thurberianum and
P. secunda cover decreased, E. elymoides cover did not
change, and B. tectorum cover increased. These shifts
parallel the relative differences in grazing avoidance and
tolerance mechanisms among these species. Cattle grazing
introduced a novel disturbance regime into this system
where most bunchgrasses are highly sensitive to herbivory
(Mack & Thompson 1982). To the contrary, B. tectorum
exhibits a collection of grazing avoidance and tolerance
attributes that makes it extremely tolerant of even highly
intensive grazing (Vallentine & Stevens 1994; Hempy-
Mayer & Pyke 2009). Because of its attributes (Chambers
et al. 2007), B. tectorum is well positioned to take maxi-
mum advantage of this window of invasion opportunity
by exploiting larger and more connected gaps.
If the goal is to conserve and restore resistance of these
systems to invasion, managers should consider focusing
their efforts on maximizing the pre-emption of resources
provided by BSC and bunchgrasses. We suggest three
priorities: first, maintain and/or restore high overall
bunchgrass cover and community structure characterized
by spatially dispersed bunchgrasses in interspaces and
small gaps between such individuals to maximize the
capture of resources; second, maintain and/or restore a
diverse assemblage of bunchgrass species with different
spatial and temporal patterns of resource use to maximize
capture of resources at different soil depths and times;
third, maintain and/or restore a BSC community to limit
safe sites for B. tectorum establishment within gaps.
Our findings suggest that multiple factors (bunchgrass
cover, BSC cover, cattle grazing, etc.) may influence the
susceptibility of these ecosystems to B. tectorum invasion.
Importantly, many of these influences are mediated by the
size and connectivity of gaps, as well as the conditions of
gaps. Thus, gaps in perennial vegetation may serve as an
important early warning indicator of when cattle grazing
or other stressors are compromising resistance of these
systems to B. tectorum invasion. Our findings raise serious
concerns regarding proposals to use cattle grazing to
control B. tectorum in these systems where remnant
bunchgrass communities persist (Vallentine & Stevens
1994). In contrast, our findings support recent guidance
for passively restoring resistance of these systems by
reducing grazing levels (Pyke 2011). Future research
should focus on gathering information concerning the size
of and connectively of such gaps across a range of ES
consistent with maintaining resistance. These data could
be used to develop indicators for adaptive management
frameworks to conserve and restore these endangered
systems.
Acknowledgements
We thank our field assistants and families. This is contribution #71 from
the Sagebrush Steppe Treatment and Evaluation Project, funded by the
US Joint Fire Sciences Program and by the US Geological Survey Forest
and Rangeland Ecosystem Science Center and Oregon State University.
The use of any trade, product or firm name is for descriptive purposes
only and does not imply endorsement by the US Government.
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Received 28 November 2012; accepted 27 March 2013
Handling Editor: Andy Sheppard
Supporting Information
Additional Supporting Information may be found in the online version
of this article.
Table S1. Relationships between environmental variables and
ordination axes.
Table S2. Relationships between species abundance and ordina-
tion axes.
Table S3. Indicator species analysis of groups.
Table S4. Pairwise MRPP comparisons of groups.
©2013 The Authors. Journal of Applied Ecology ©2013 British Ecological Society, Journal of Applied Ecology,50, 1039–1049
Invasibility and spatial gaps among plants 1049
... Because livestock grazing is so pervasive throughout sagebrush ecosystems (Williamson et al. 2020), we assume our literature-derived recovery rates for the baseline passive scenario are impacted by livestock grazing pressure. Livestock disperse annual grass seeds, and grazing reduces native herbaceous cover while trampling disturbs biological soil crusts that typically fill interspace and prevent invasion by annual grass (Reisner et al. 2013;Ellsworth et al. 2016;Condon and Pyke 2018;Williamson et al. 2020). The grazing exclusion scenario assumed an increased probability of sagebrush establishment promoted by reduced competition from annual grass (Reisner et al. 2013;Ellsworth et al. 2016;Condon and Pyke 2018) and soil disturbance. ...
... Livestock disperse annual grass seeds, and grazing reduces native herbaceous cover while trampling disturbs biological soil crusts that typically fill interspace and prevent invasion by annual grass (Reisner et al. 2013;Ellsworth et al. 2016;Condon and Pyke 2018;Williamson et al. 2020). The grazing exclusion scenario assumed an increased probability of sagebrush establishment promoted by reduced competition from annual grass (Reisner et al. 2013;Ellsworth et al. 2016;Condon and Pyke 2018) and soil disturbance. We simulated this effect by increasing the range of recruitment probability to 15-30%, which still accounts for the independent negative impact of wildfire on annual grass colonization (Condon and Pyke 2018;Williamson et al. 2020) and sagebrush seedbank depletion (Baker 2011;Wijayratne and Pyke 2012). ...
... We accounted for four restoration options across a range of intervention efforts: passive, grazing exclusion, seeding, and seedling transplant. Excluding livestock following wildfire promotes the regrowth of native herbaceous vegetation that can compete with non-native invasive annual grasses (Reisner et al. 2013;Ellsworth et al. 2016;Condon and Pyke 2018), reduces additional disturbance to biocrust communities that infill the interspace that annual grasses colonize, and disrupts the spread of annual grass seed throughout the burn scar. Therefore, the primary benefit of our livestock exclusion scenario was an improved probability of sagebrush establishment, a benefit that would be realized within a few years post-wildfire and would not impose long-term grazing exclusion or significant costs to implement. ...
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Unprecedented conservation efforts for sagebrush (Artemisia spp.) ecosystems across the western United States have been catalyzed by risks from escalated wildfire activity that reduces habitat for sagebrush-obligate species such as Greater Sage-Grouse (Centrocercus urophasianus). However, post-fire restoration is challenged by spatial variation in ecosystem processes influencing resilience to disturbance and resistance to non-native invasive species, and spatial and temporal lags between slower sagebrush recovery processes and faster demographic responses of sage-grouse to loss of important habitat. Decision-support frameworks that account for these factors can help users strategically apply restoration efforts by predicting short and long-term ecological benefits of actions. Here, we developed a framework that strategically targets burned areas for restoration actions (e.g., seeding or planting sagebrush) that have the greatest potential to positively benefit sage-grouse populations through time. Specifically, we estimated sagebrush recovery following wildfire and risk of non-native annual grass invasion under four scenarios: passive recovery, grazing exclusion, active restoration with seeding, and active restoration with seedling transplants. We then applied spatial predictions of integrated nest site selection and survival models before wildfire, immediately following wildfire, and at 30 and 50 years post-wildfire based on each restoration scenario and measured changes in habitat. Application of this framework coupled with strategic planting designs aimed at developing patches of nesting habitat may help increase operational resilience for fire-impacted sagebrush ecosystems.
... Finally, livestock are vectors for the spread of exotic species and create conditions for their establishment. Grazing spreads invasive annual grasses by removing native perennial grasses (Reisner et al. 2013;Rosentreter 1994;Chambers et al. 2007;Belsky and Blumenthal 1997), by disturbing soils (Olff and Ritchie 1998), and by damaging biological soil crusts (Belnap 2006;Chambers et al. 2014;Reisner et al. 2013;Ponzetti et al. 2007;Warren and Eldridge 2001;Belnap 1995). Livestock also distribute annual grass seeds across the landscape through their hooves, fur, and digestive tracts (Schiffman 1997;Olff and Ritchie 1998;Chambers et al. 2014;Mack 1981;Knapp 1996). ...
... Finally, livestock are vectors for the spread of exotic species and create conditions for their establishment. Grazing spreads invasive annual grasses by removing native perennial grasses (Reisner et al. 2013;Rosentreter 1994;Chambers et al. 2007;Belsky and Blumenthal 1997), by disturbing soils (Olff and Ritchie 1998), and by damaging biological soil crusts (Belnap 2006;Chambers et al. 2014;Reisner et al. 2013;Ponzetti et al. 2007;Warren and Eldridge 2001;Belnap 1995). Livestock also distribute annual grass seeds across the landscape through their hooves, fur, and digestive tracts (Schiffman 1997;Olff and Ritchie 1998;Chambers et al. 2014;Mack 1981;Knapp 1996). ...
... Cheatgrass exhibits various attributes that makes it extremely tolerant of even highly intensive grazing (Reisner et al. 2013). The expansion of cheatgrass across much of the western USA associated with livestock grazing has long been known (Franklin and Dyrness 1973;Mack and Thompson 1982), but its implications on carbon cycling have been overlooked (Bradley et al. 2006;Meyer 2011). ...
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Public lands of the USA can play an important role in addressing the climate crisis. About 85% of public lands in the western USA are grazed by domestic livestock, and they influence climate change in three profound ways: (1) they are significant sources of greenhouse gases through enteric fermentation and manure deposition; (2) they defoliate native plants, trample vegetation and soils, and accelerate the spread of exotic species resulting in a shift in landscape function from carbon sinks to sources of greenhouse gases; and (3) they exacerbate the effects of climate change on ecosystems by creating warmer and drier conditions. On public lands one cow-calf pair grazing for one month (an “animal unit month” or “AUM”) produces 875 kg CO 2 e through enteric fermentation and manure deposition with a social carbon cost of nearly $36 per AUM. Over 14 million AUMs of cattle graze public lands of the western USA each year resulting in greenhouse gas emissions of 12.4 Tg CO 2 e year ⁻¹ . The social costs of carbon are > $500 million year ⁻¹ or approximately 26 times greater than annual grazing fees collected by managing federal agencies. These emissions and social costs do not include the likely greater ecosystems costs from grazing impacts and associated livestock management activities that reduce biodiversity, carbon stocks and rates of carbon sequestration. Cessation of grazing would decrease greenhouse gas emissions, improve soil and water resources, and would enhance/sustain native species biodiversity thus representing an important and cost-effective adaptive approach to climate change.
... However, many sagebrush rangelands have also burned without converting to exotic annual grasslands ( Davies et al. 2007 ;Rhodes et al. 2010 ;Ellsworth et al. 2016 ). Similarly, grazing by domestic livestock has also been suggested to promote exotic annual grasses ( Knapp 1996 ;Reisner et al. 2013 ;Williamson et al. 2020 ), but the relationship between grazing and exotic annual grasses is more intricate. Studies suggesting that grazing is a driver of exotic annual grass increase often are referencing heavy and repeated growing-season grazing. ...
... Of great interest is comparing off-season grazing effects to fire effects to determine their relative contribution to the annual grass problem. Prior studies that have suggested that grazing is a major contributor to increases in exotic annual grasses have not compared grazing and fire effects, did not experimentally apply grazing treatments, and therefore, could not determine causation (e.g., Reisner et al. 2013 ;Williamson et al. 2020 ). Yet these studies have encouraged land managers to reduce or remove livestock grazing from western rangelands at risk of exotic annual grass dominance. ...
... While annual grass invasion has frequently been attributed to fire (e.g., Steward and Hull 1949 ;Keeley and McGinnis 2007 ) and grazing (e.g., Knapp 1996 ;Reisner et al. 2013 ;Williamson et al. 2020 ), our study provides one of the first experimental tests to compare their relative effect. We assumed that off-season grazing and fire would increase the abundance and cover of exotic annual grasses compared with an ungrazed, unburned control; however, exotic annual grasses only increased with burning. ...
Article
Exotic annual grass invasion is a pressing concern in sagebrush rangelands of the western United States. Overgrazing and fire have historically both been implicated in the rise of annual grasses, but experiments that compare the effect of grazing versus fire are lacking, particularly for contemporary grazing practices such as off-season (fall and winter) grazing. We compared 1) burned and ungrazed (burned), 2) off-season, moderately grazed and unburned (grazed), and 3) ungrazed and unburned (control) treatments at five Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis [Beetle & A. Young] S.L. Welsh) sites in southeastern Oregon for half a decade. Fire, but not off-season grazing, substantially increased exotic annual grass cover and abundance. Vegetation cover and density were generally similar between grazed and control areas. In contrast, at the end of the study exotic annual grass cover and density were over fourfold greater in burned areas. Exotic annual grass became the dominant plant group in burned areas, but not in grazed and control areas. Cover and density of annual forbs, predominately non-native species, were generally greater in the burned compared with grazed and control treatments. Fire also decreased soil biological crust cover and sagebrush cover and density compared with grazed and control treatments. This study provides strong evidence that fire is a threat to the sustainability of Wyoming big sagebrush communities at risk of exotic annual grass dominance, but that off-season, moderate grazing poses little risk. However, considering the spatial extent of our study was limited, further evaluations are needed across a larger geographic area. Given that off-season grazing can decrease the probability of fire, off-season grazing may be a valuable tool to reduce the risk of exotic annual grass dominance.
... From a co-evolutionary perspective, there is the potential for biocrusts to inhibit non-native grasses compared with native grasses (Warren and Eldridge 2003). For example, an inverse relationship between biocrust and B. tectorum cover has been observed in the Great Basin (Peterson 2013, Reisner et al. 2013 and Columbia Basin (Ponzetti et al. 2007). Furthermore, a recent global meta-analysis indicated that biocrusts reduce the germination/emergence of non-native species, while having a neutral effect on that of natives (Havrilla et al. 2019). ...
... Globally, lichen biocrusts reduce plant germination/emergence, whereas cyanobacteria, moss, and lichen/moss biocrusts have a neutral effect (Havrilla et al. 2019). This supports the notion that biocrusts potentially differ with respect to the extent to which they provide "safe sites" for grass recruitment (Bowker 2007, Reisner et al. 2013. Accordingly, we sought to determine whether native/non-native grass emergence/early establishment varied among light and dark biocrusts from pinnacled Colorado Plateau and rugose Sonoran Desert biocrusts. ...
... In addition, emergence on bare soil (both deserts) and on Colorado Plateau light biocrusts was accelerated, which may have been related to the bare soil micropatches within the Colorado Plateau light biocrusts. Within biocrusted soils, some have observed seeds emerging more often from noncrusted patches interspersed with biocrusts (Sylla 1987) while others have suggested that bare soil is itself a "safe site" for seed germination/seedling establishment (Reisner et al. 2013). The difference may also be due to an increased availability of safe sites on the Colorado Plateau biocrusts as some have speculated that rougher biocrusts have more safe sites for germination relative to flat biocrusts (Johansen 1986). ...
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Biological soil crusts (biocrusts) cover the soil surface of global drylands and interact with vascular plants. Biocrusts may influence the availability and nature of safe sites for plant recruitment and the susceptibility of an area to invasion by non‐native species. Therefore, to investigate the potential role of biocrusts in invasive species management, we sought to determine whether native and non‐native grass recruitments in two North American deserts were differentially affected by biocrusts. We conducted a series of coordinated experiments in field, semi‐controlled, and controlled environment settings in the Colorado Plateau and Sonoran Desert using contrasting biocrust and grass functional types. Experiments in field environments focused on early establishment of grass seedlings whereas controlled environment experiments focused on seedling emergence. Within each experiment, we compared responses (frequency, magnitude, and timing of emergence/establishment) both across species (biocrust types pooled) and across species and levels of biocrust development. Native grasses varied by experiment and included Aristida purpurea, A. purpurea var. longiseta, Bouteloua gracilis, and Vulpia octoflora. Emergence of non‐native Bromus tectorum was similar to that of native grasses on the Colorado Plateau. Differences in emergence of native vs. non‐native grasses in the Sonoran Desert were species‐ and response‐specific. Emergence of the non‐native Bromus rubens was comparable to that of native grasses whereas emergence frequency and magnitude of the non‐native Pennisetum ciliare was lower compared with two of four native species. Within a grass species, emergence was higher and faster on bare soil compared with biocrusts in the Sonoran Desert semi‐controlled and greenhouse environment experiments. However, the pattern was not consistent across other experiments. When comparing across Colorado Plateau and Sonoran Desert biocrusts in greenhouse experiments, we found that emergence of native grasses was higher on Colorado Plateau biocrusts. Based on the lack of consistent results across our experiments, grass recruitment on biocrusts appears to be driven more by species‐specific traits than species provenance. Our greenhouse experiments suggest that biocrust topographic relief is an important safe site trait influencing plant recruitment.
... Responses to disturbances, such as fuel treatments that eliminate shrubs in arid sagebrush ecosystems, are strongly influenced by pretreatment cover and density of perennial herbaceous plants that can regrow and establish in gaps created after death of the dominant shrubs (Chambers et al., 2007Chambers, Maestas, et al., 2017;. In addition, community resistance to cheatgrass invasion and expansion is aided by maintaining or increasing lichens and mosses and increasing growth and establishment of perennial grasses, which reduces distances among perennial herbaceous plants (Chambers et al., 2007;Chambers, Bradley, et al., 2014;Condon & Pyke, 2018;Reisner et al., 2013;Roundy et al., 2018). Our sites all began with moderate cover of perennial grasses and forbs, but relatively high cover of lichens and mosses before treatment (Figure 9a). ...
... Shorter gap distances among perennial plants and higher cover of lichens and mosses have been noted as key characteristics that lead to higher cheatgrass resistance (Condon & Pyke, 2018;Reisner et al., 2013). Gap distances between perennial plants increased in the early years after prescribed fire but returned surprisingly to pretreatment levels by year 10, especially in the fire and tebuthiuron treatments that killed sagebrush. ...
Article
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Sagebrush ecosystems of western North America are threatened by invasive annual grasses and wildfires that can remove fire‐intolerant shrubs for decades. Fuel reduction treatments are used ostensibly to aid in fire suppression, conserve wildlife habitat, and restore historical fire regimes, but long‐term ecological impacts of these treatments are not clear. In 2006, we initiated fuel reduction treatments (prescribed fire, mowing, and herbicide applications [tebuthiuron and imazapic]) in six Artemisia tridentata ssp. wyomingensis communities. We evaluated long‐term effects of these fuel treatments on: (1) magnitude and longevity of fuel reduction; (2) Greater Sage‐grouse habitat characteristics; and (3) ecological resilience and resistance to invasive annual grasses. Responses were analyzed using repeated‐measures linear mixed models. Response variables included plant biomass, cover, density and height, distances between perennial plants, and exposed soil cover. Prescribed fire produced the greatest reduction in woody fuel over time. Mowing initially reduced woody biomass, which recovered by year 10. Tebuthiuron did not significantly reduce woody biomass compared to controls. All woody fuel treatments reduced sagebrush cover to below 15% (recommended minimum for Greater Sage‐grouse habitat), but only prescribed fire reduced cover to below controls. Median mowed sagebrush height remained above the recommended 30 cm. Cheatgrass (Bromus tectorum) cover increased to above the recommended maximum of 10% across all treatments and controls. Ecological resilience to woody fuel treatments was lowest with fire and greatest with mowing. Low resilience over the 10 posttreatment years was identified by: (1) poor perennial plant recovery posttreatment with sustained reductions in cover and density of some perennial plant species; (2) sustained reductions in lichen and moss cover; and (3) increases in cheatgrass cover. Although 10 years is insufficient to conclusively describe final ecological responses to fuel treatments, mowing woody fuels has the greatest potential to reduce woody fuel, minimize shrub mortality and soil disturbance, maintain lichens and mosses, and minimize long‐term negative impacts on Greater Sage‐grouse habitat. However, maintaining ecological resilience and resistance to invasion may be threatened by increases in cheatgrass cover, which are occurring regionally.
... Heavy, repeated grazing during the growing season has promoted exotic annual grasses by decreasing competition from native perennial bunchgrasses ( Daubenmire 1970Mack 1981Knapp 1996 ). Subsequently, some have recommended reducing livestock grazing to decrease exotic annual grasses (e.g., Reisner et al. 2013 ;Williamson et al. 2020 ), while others have found that grazing can reduce annual grasses and promote native perennials ( Davies et al. 2020 ;Porensky et al. 2021 ). Reductions in grazing have also been suggested to be a contributing factor to the recent expansion of exotic annual grasslands ( Perryman et al. 2018 ). ...
... The differing response of Sandberg bluegrass and large bunchgrasses to off-season grazing is likely a product of their differences in stature and response to disturbances. Sandberg bluegrass may be especially sensitive to annual grass competition because it usually grows in the interspaces between large perennial bunchgrasses, the location where annual grasses proliferate during invasion ( Reisner et al. 2013 ;Rayburn et al. 2014 ). In the current study, where annual grasses were not dominant and large bunchgrasses plentiful, reductions in annual grass abundance likely opened safe sites for Sandberg bluegrass, but not necessarily for large bunchgrasses. ...
Article
Exotic annual grass invasion and dominance of sagebrush-bunchgrass steppe is a concern because it decreases biodiversity and promotes frequent wildfires. Management is needed to reduce exotic annual grasses to prevent sagebrush-bunchgrass communities from transitioning to annual grasslands. Grazing during the off season (fall-winter) has shown promise at reducing exotic annual grasses, but it has not been evaluated in plant communities dominated by sagebrush and native bunchgrasses. We compared moderate grazing during the off season with not grazing in five Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis [Beetle & A. Young] S.L. Welsh)−bunchgrass communities in the northern Great Basin. Treatments were applied annually for 10 yr (2009−2010 through 2018−2019). Plant community characteristics were measured after treatments had been applied from 6 to 10 yr. Off-season grazing reduced exotic annual grass density and cover. After a decade, annual grass cover was twofold greater in ungrazed areas. Sandberg bluegrass (Poa secunda J. Presl) density increased with off-season grazing, but large bunchgrass density was similar between off-season grazed and ungrazed areas. Perennial and annual forb density and cover were similar between off-season grazed and ungrazed treatments. Biological soil crust cover was also similar between off-season grazed and ungrazed areas. The results of this study provide strong evidence that off-season grazing has application for managing exotic annual grasses in sagebrush-bunchgrass steppe. Considering the vast scope of the exotic annual grass problem, properly applied grazing may be the most cost-efficient tool to mediate the impacts of annual grass invasion.
... Native bunchgrasses produce deep roots and stabilize soils [167]. As gaps between bunchgrass plants decrease in size, their ability to compete and limit soil and water availability to invasive grasses is enhanced, naturally limiting their further spread [168]. Suitable habitat and forage availability for both native ungulates and the regionally important greater sage-grouse are also enhanced when bunchgrass cover exceeds 10% [169,170]. ...
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Effective native plant materials are critical to restoring the structure and function of extensively modified ecosystems, such as the sagebrush steppe of North America’s Intermountain West. The reestablishment of native bunchgrasses, e.g., bluebunch wheatgrass (Pseudoroegneria spicata [Pursh] À. Löve), is the first step for recovery from invasive species and frequent wildfire and towards greater ecosystem resiliency. Effective native plant material exhibits functional traits that confer ecological fitness, phenotypic plasticity that enables adaptation to the local environment, and genetic variation that facilitates rapid evolution to local conditions, i.e., local adaptation. Here we illustrate a multi-disciplinary approach based on genomic selection to develop plant materials that address environmental issues that constrain local populations in altered ecosystems. Based on DNA sequence, genomic selection allows rapid screening of large numbers of seedlings, even for traits expressed only in more mature plants. Plants are genotyped and phenotyped in a training population to develop a genome model for the desired phenotype. Populations with modified phenotypes can be used to identify plant syndromes and test basic hypotheses regarding relationships of traits to adaptation and to one another. The effectiveness of genomic selection in crop and livestock breeding suggests this approach has tremendous potential for improving restoration outcomes for species such as bluebunch wheatgrass.
... While grazing is used to control some invasive species in grasslands ( Menke 1992 ;Porensky et al. 2020 ), studies have also demonstrated a connection between overgrazing by livestock and the invasion of exotic grasses such as cheatgrass ( Bromus tectorum L.) ( Young 1943 ;Reisner et al. 2013 ). Grazing by large ungulates such as cattle (Bos taurus) and elk (Cervus canadensis) can contribute to invasion by spreading seeds via endozoochary (passage through digestive track) and epizoochary (attachment to body) ( Janzen 1984 ). ...
Article
The exotic annual grass ventenata (Ventenata dubia L.) is raising concern as it rapidly invades multiple ecosystem types within the United States, including sagebrush steppe, ponderosa pine forests, woodlands, and much of the Palouse and Pacific Northwest Bunchgrass Prairie (PNB). Despite increasing attention, little is known about the invasion dynamics of ventenata, especially its response to disturbances such as grazing and fire. In this study, we examined how cattle grazing and prescribed fire affect the abundance (standing crop, cover, frequency, and density) of ventenata and other plant groups on the PNB over time using two separate long-term studies established in 2004. The first study (Cattle Grazing) looked at the 14-yr effect of cattle grazing exclusion on ventenata aboveground biomass and cover. Our second study (Grazing and Prescribed Fire) examined main and interactive effects of cattle exclusion and prescribed fire on ventenata over three sampling periods (2008, 2016, and 2018). We documented a 30% increase in ventenata cover and 55% increase in frequency on the PNB over the past 15 yr, including areas that were not disturbed by fire or cattle grazing. We found only weak evidence that cattle grazing increased ventenata standing crop when compared with cattle-excluded paddocks, something that could be related to timing of use. There was no evidence that prescribed burning impacted the response of ventenata on its own. However, we found some evidence of interactions between cattle grazing and prescribed fire that suggests prescribed burning could help reduce the abundance of ventenata in areas grazed by livestock. These studies reinforce the important differences between ventenata and other invasive winter annuals in grasslands and clarify a need for research that focuses primarily on the dynamics between this relatively new exotic species in grasslands and the many ecosystems it now inhabits.
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A bulldozed fire line is a fire-suppression technique that limits fire movement by altering fuel continuity through vegetation removal and mineral soil exposure. The ecological impacts of a bulldozed fire line may exceed the effects of the fire itself through lasting changes in the soil and vegetation properties; however, little research has been performed to quantify these impacts in grassland systems. In this study, we compared vegetation properties among burned, unburned, and bulldozed fire line conditions on two August 2012 grassland wildfires in Montana. Standing biomass, by growth form, was quantified in 2013 and 2014, and compared using a generalized linear model. Perennial grass production was significantly reduced, while annual grass and annual forb biomass increased in response to the fire line treatment. Shrub and total vegetation standing crop were reduced in response to the fire line in 2013; however, the treatment effects were diminished by 2014. The burned and unburned treatments were generally similar within two years post-fire. The loss of perennial grasses and invasion of competitive annual grasses such as cheatgrass (Bromus tectorum L.) may limit the vegetation recovery of the fire line and promote further invasion of annual grasses into these systems. The marginal impact of the fires on these plant communities suggests the need to limit the use of ad hoc bulldozed fire lines as a suppression activity. If a bulldozed fire line is constructed, we suggest limiting soil disturbance by restricting blade depth to remove only surface vegetation and restricting bulldozer use to flat slopes, even if working with the contour, and incorporating re-seeding as part of or immediately after fire line construction.
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On the Ground •land resilience is influenced by a variety of ecosystem properties that fall into two broad categories, 1) abiotic and 2) biotic. •Abiotic properties cannot be directly influenced with management. •In contrast, biotic properties of the ecosystem can be readily influenced by management. The formula for robust biotic resilience to wildfire and resistance to invasive annual grasses in the northern Great Basin sagebrush ecosystem is largely about maintaining and promoting perennial bunchgrasses. Meeting these imperatives in a highly variable, invasive annual grass-prone environment modifies the very nature of the problem from seemingly simple, to one that is highly complex, particularly in areas where bunchgrasses are depauperate. •Success in such an environment requires a process- rather than an event-based approach. It is unlikely that a singular management treatment will be effective, so the problem should be managed accordingly. •The management system itself must also possess properties of resilience if we hope to promote ecosystem resilience in an ever-changing risk and recovery environment. A successful strategy will first require securing the necessary components of a resilient management system, and a shift in paradigm from random acts of opportunistic restoration to a sustained, organized, process-based approach for promoting ecosystem resilience.
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Structural equation modeling (SEM) is increasingly being chosen by researchers as a framework for gaining scientific insights from the quantitative analyses of data. New ideas and methods emerging from the study of causality, influences from the field of graphical modeling, and advances in statistics are expanding the rigor, capability, and even purpose of SEM. Guidelines for implementing the expanded capabilities of SEM are currently lacking. In this paper we describe new developments in SEM that we believe constitute a third-generation of the methodology. Most characteristic of this new approach is the generalization of the structural equation model as a causal graph. In this generalization, analyses are based on graph theoretic principles rather than analyses of matrices. Also, new devices such as metamodels and causal diagrams, as well as an increased emphasis on queries and probabilistic reasoning, are now included. Estimation under a graph theory framework permits the use of Bayesian or likelihood methods. The guidelines presented start from a declaration of the goals of the analysis. We then discuss how theory frames the modeling process, requirements for causal interpretation, model specification choices, selection of estimation method, model evaluation options, and use of queries, both to summarize retrospective results and for prospective analyses. The illustrative example presented involves monitoring data from wetlands on Mount Desert Island, home of Acadia National Park. Our presentation walks through the decision process involved in developing and evaluating models, as well as drawing inferences from the resulting prediction equations. In addition to evaluating hypotheses about the connections between human activities and biotic responses, we illustrate how the structural equation (SE) model can be queried to understand how interventions might take advantage of an environmental threshold to limit Typha invasions. The guidelines presented provide for an updated definition of the SEM process that subsumes the historical matrix approach under a graph-theory implementation. The implementation is also designed to permit complex specifications and to be compatible with various estimation methods. Finally, they are meant to foster the use of probabilistic reasoning in both retrospective and prospective considerations of the quantitative implications of the results.
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There is increasing recognition that overall interactions among plant species are often the net result of both positive and negative effects. However, the positive influence of other plants has rarely been examined using detailed demographic methods, which are useful for partitioning net effects at the population level into positive and/or negative effects on individual vital rates. This study examines the influence of microhabitats created by the native shrubs Artemisia tridentata and Purshia tridentata on the demography of the invasive annual grass Bromus tectorum in the Great Basin Desert, California, USA. Shrub understory environments differed significantly from intershrub space and were characterized by higher soil fertility and less extreme microclimates. There existed a strong spatial association between B. tectorum and the shrubs across four years, with more than double the density of B. tectorum in shrub microhabitats compared to intershrub space. Periodic matrix models were used to calculate population growth (lamda) and reproductive potential (RP, expected lifetime fecundity of seedlings) of B. tectorum in different microhabitats over two years. Modeled population growth was significantly increased in shrub microhabitats in the first of two years. This was primarily due to increased seedling establishment in Artemisia microhabitats, rather than effects during the growing season. In the following year, B. tectorum individuals in shrub microhabitats had a significantly greater reproductive potential than those in intershrub microhabitats, indicating shrub facilitation during the growing season. Loop analysis revealed an interacting effect of year and microhabitat on B. tectorum life history pathway elasticity values, demonstrating a fundamental influence of spatiotemporal factors on which life history pathways are important and/or possible. Life table response experiment (LTRE) analysis showed that increased survival and growth rates positively contributed to population growth in both years under Purshia, but only in the second year under Artemisia. This research provides evidence that the positive effects of native shrubs on B. tectorum can be strong enough to produce net positive effects at the population level, although positive effects were variable. In this study, a rigorous demographic approach was particularly useful in partitioning overall interactions into positive and negative components.
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