AN ABSTRACT OF THE THESIS OF
Taylor K. Fjeran for the degree of Master of Science in Sustainable Forest Management
presented on December 5, 2014.
Title: Treatment Options for Controlling Brachypodium sylvaticum and Impacts on
Native Vegetation
Abstract approved:
John D. Bailey
Invasive vegetation control studies traditionally aim to control existing
populations as well as limit future spread of the species. However, little additional
attention has been dedicated to aiding native communities to recover and reestablish. One
prominent example of a studied invasive is Brachypodium sylvaticum (Huds.) P. Beauv.
(false brome), a bunchgrass native to Europe, Asia, and North Africa but invasive to
North America. B. sylvaticum is capable of forming dense monocultures under forested
canopies in North America. Such invasions can detrimentally affect the ecological
functions and processes of an inhabited ecosystem. To address the negative ecological
effects of this grass’ invasion, this study evaluated how herbicide and prescribed burns,
singly and in combination, affected B. sylvaticum abundance and the surrounding plant
community in western Oregon foothills. The specific objectives of this study were to: 1)
determine the most effective treatment in reducing B. sylvaticum abundance or cover in
the field, 2) evaluate how different treatments alter total plant community cover,
excluding B. sylvaticum, 3) assess residual seed bank following prescribed treatments,
and 4) describe compositional changes in the plant communities after one growing season
following control treatments.
My study was located in Oregon State University’s McDonald Forest under a
split-plot design with 12 blocks total and 10 treatments randomly assigned within each
block, which included the use of two herbicides and prescribed burning in various
combinations, for a total of 9 treatments and a no-treatment control. All treatments that
involved application of an aggressive, broad-spectrum, foliar herbicide applied in the
summer were most effective in reducing not only the existing B. sylvaticum in the field,
but also the residual seed bank one year after application, while maintaining native
community seed bank abundance. A prescribed burn following the aforementioned
summer herbicide demonstrated no added benefit in controlling B. sylvaticum. Less
intense fall prescribed burns without a previous broad-spectrum herbicide treatment may
promote B. sylvaticum growth.
All treatments involving the aggressive summer herbicide displayed significant
reductions in total native species cover and species richness compared to the controls.
Treatments without this herbicide demonstrated richness and diversity similar to the
controls, but the remaining species after one growing season were primarily dominant
shrubs or non-native weeds. Using multivariate community analysis, I documented a shift
in species composition due to treatment in which the strongest effect also associated with
summer herbicide application.
This study now serves as a baseline to develop and refine cost-effective
techniques for both controlling B. sylvaticum populations in the Oregon Coast Range and
restoring invaded native plant communities. Future studies should monitor any
responding B. sylvaticum populations and species composition beyond the first growing
season, consider incorporating multiple applications of such treatments, and quantify seed
recruitment by both B. sylvaticum and native species.
©Copyright by Taylor K. Fjeran
December 5, 2014
All Rights Reserved
Treatment Options for Controlling Brachypodium sylvaticum and Impacts on Native
Vegetation
by
Taylor K. Fjeran
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
Presented December 5, 2014
Commencement June 2015
Master of Science thesis of Taylor K. Fjeran presented on December 5, 2014
APPROVED:
Major Professor, representing Sustainable Forest Management
Head of the Department of Forest Engineering, Resources and Management
Dean of the Graduate School
I understand that my thesis will become part of the permanent collection of Oregon State
University libraries. My signature below authorizes release of my thesis to any reader
upon request.
Taylor K. Fjeran, Author
ACKNOWLEDGEMENTS
I would first like to thank my advisor, John Bailey, for his constant
encouragement, enthusiasm, and support throughout my studies and the development,
implementation, and composition of my research, for introducing me to the world of fire,
and for exposing me to numerous opportunities at the University. I would also like to
thank the rest of my committee: Tom Kaye, Seema Mangla, and Matt Powers, for their
constant willingness to help and their sincere enthusiasm for this project.
I thank Chris Dunn for his immense support and guidance through my time at the
University, for introducing me to this project, for helping develop the experimental
design, preparing and executing the prescribed burns, and providing guidance through the
analysis.
I would also like to thank a number of individuals who helped make the study
possible: Liz Cole, for your generous time helping with identification, herbiciding, and
burning; Mike Newton, for graciously providing and applying the fall herbicide treatment;
Brent Klumph, for his substantial and accommodating logistic and equipment support;
Ryan Brown, for assistance communicating the prescribed burns; Beatrice SerranoMartinez, for the countless hours of sometimes tedious tasks; Ariel Muldoon, for offering
her statistical expertise; Jim Ervin and the Oregon State University Greenhouse Staff, for
being so accommodating and always helpful; Tom Kaye once again and the Institute for
Applied Ecology for providing valuable additional greenhouse space; Allison Blair and
the Oregon Department of Forestry, for their constant willingness to provide guidance,
equipment, and assistance; and the Pyromaniacs, for their incredible enthusiasm and
efforts throughout the prescribed burns.
I also thank the College Forests for not only providing the site for this study, but
for being so accommodating to the multiple herbicide and prescribed burn treatments,
and for funding this research.
Finally, I would like to thank my family and friends for their constant support and
generous encouragement.
CONTRIBUTION OF AUTHORS
Chris Dunn assisted with the experimental design and implementation of the
prescribed fire included in the second and third chapters of this thesis, Prescribed Fire
and Herbicide Treatment Options for Controlling Brachypodium sylvaticum and Effects
of Prescribed Burning and Herbicides on Plant Communities Invaded by Brachypodium
sylvaticum.
TABLE OF CONTENTS
Page
1
Introduction ................................................................................................................... 1
1.1
Brachypodium sylvaticum: Native Range, Morphology, and Life History ....2
1.1.1
Associations and Natural Enemies.................................................. 4
1.2
Brachypodium sylvaticum as an Invasive .......................................................5
1.3
Controlling Brachypodium sylvaticum ...........................................................8
1.3.1
Mechanical Control Methods.......................................................... 8
1.3.2
Biological Control Methods.......................................................... 11
1.3.3
Chemical Control Methods ........................................................... 12
1.3.4
Prescribed Burning Control Methods ........................................... 13
1.4
Study Site ......................................................................................................16
1.5
Research Goals, Questions, and Objectives..................................................17
2 Prescirbed Fires and Herbicide Treatment Options for Controlling Brachypodium
sylvaticum ......................................................................................................................... 20
2.1
Introduction ...................................................................................................20
2.2
Methods.........................................................................................................23
2.3
2.2.1
Study Site ...................................................................................... 23
2.2.2
Experimental Design..................................................................... 23
2.2.3
Field Measurements ...................................................................... 25
2.2.4
Seed Bank Experiment.................................................................. 26
Results ...........................................................................................................27
2.3.1
Field Experiment........................................................................... 27
2.3.2
Seed Bank Experiment.................................................................. 28
2.4
Discussion .....................................................................................................29
2.5
Management Implications.............................................................................31
3 Effects of Prescribed Burning and Herbicides on Plant Communities Invaded by
Brachypodium sylavticum ................................................................................................. 38
3.1
Introduction ...................................................................................................38
3.2
Methods.........................................................................................................41
3.3
3.4
3.5
4
3.2.1
Experimental Design and Measurements...................................... 41
3.2.2
Statistical Analyses ....................................................................... 42
Results ...........................................................................................................44
3.3.1
Total Plant Community Response ................................................ 44
3.3.2
Community Composition Response ............................................. 46
Discussion .....................................................................................................48
3.4.1
Total Plant Community Response ................................................ 48
3.4.2
Community Composition Response ............................................. 50
Management Implications.............................................................................53
Conclusion .................................................................................................................. 65
4.1
Research Summary .......................................................................................65
4.2
Directions for Future Research .....................................................................66
Bibliography ..................................................................................................................... 69
Appendix ........................................................................................................................... 80
LIST OF FIGURES
Figure
Page
Figure 1.1. Map of the 12 study blocks on the McDonald Forest near the Oak Creek
entrance. ..................................................................................................................... 19
Figure 2.1. Treatment and measurement plot design, showing one of 12 blocks total..... 35
Figure 2.2. Plot describing the mean percent surface area scorched per prescribed burn
treatment. .................................................................................................................... 35
Figure 2.3. Plot describing the ratio of the relative median B. sylvaticum percent cover
compared to the control plots. .................................................................................... 36
Figure 2.4. Plot describing the mean difference of number of viable B. sylvaticum seeds
per 1 m2 in the greenhouse for samples collected in (A) November and (B) February
compared to the control samples. ............................................................................... 37
Figure 3.1. Plot describing the ratio of the relative median plant community, excluding B.
sylvaticum, percent cover compared to the control plots. .......................................... 60
Figure 3.2. Plot describing the ratio of the relative median number of viable seedlings in
the plant community, excluding B. sylvaticum, for seed bank samples collected in (A)
November and (B) February compared to the control samples. ................................ 61
Figure 3.3. 2-dimensional NMS ordination of the post-treatment field data using
Euclidean distances of treatment plots in species space. ........................................... 62
Figure 3.4. 2-dimensional NMS ordination of the November seed bank samples using
Euclidean distances of treatment plots in species space. ........................................... 63
Figure 3.5. 2-dimensional NMS ordination of the February seed bank samples using
Euclidean distances of treatment plots in species space. ........................................... 64
LIST OF TABLES
Table
Page
Table 2.1. Prescribed fire dates in 2013, dry temperature, and relative humidity (RH). .. 33
Table 2.2. Median post-treatment B. sylvaticum percent cover estimates compared to the
control plots with Bonferroni adjusted 95% confidence intervals. ............................ 33
Table 2.3. Mean number of viable B. sylvaticum seeds per 1 m2 germinated in the
greenhouse for November and February samples with Bonferroni adjusted 95%
confidence intervals.................................................................................................... 34
Table 3.1. Collective 4-letter species codes, scientific names, and common names of all
species identified in the field post-treatment and in the seed bank assays................. 55
Table 3.2. Median post-treatment plant community, excluding B. sylvaticum, percent
cover estimates compared to the control plots with Bonferroni adjusted 95%
confidence intervals.................................................................................................... 56
Table 3.3. Median number of viable community seeds per 1 m2 , excluding B. sylvaticum,
germinated in the greenhouse for November and February samples with Bonferroni
adjusted 95% confidence intervals. ............................................................................ 56
Table 3.4. Mean species richness and Shannon’s diversity index for pre-treatment, posttreatment field, November seed bank samples, and February seed bank samples. .... 57
Table 3.5. NMS ordination summary of the correlation coefficients of each species with
each axis for post-treatment field data. ...................................................................... 58
Table 3.6. NMS ordination summaries of correlation coefficients of each environmental
variable by each axis. ................................................................................................. 58
Table 3.7. NMS ordination summary of the correlation coefficients of each species with
each axis for November and February seed bank data. .............................................. 59
1
LIST OF APPENDIX TABLES
Table
Page
Table A - 1. Number of viable seeds of each species per treatment to germinate from
November seed bank samples. ................................................................................... 81
Table A - 2. Number of viable seeds of each species per treatment to germinate from
February seed bank samples....................................................................................... 82
1
TREATMENT OPTIONS FOR CONTROLLING BRACHYPODIUM SYLVATICUM
AND IMPACTS ON NATIVE VEGETATION
1
INTRODUCTION
The negative ecological and socioeconomic effects of non-native plant invasions
have motivated widespread investigation and experimentation on invasive plant control
methods. Many of such studies have demonstrated promising results in managing existing
invasive plant populations as well as limiting the plants’ dispersal via individual control
techniques (Judge et al. 2005; Paynter and Flanagan 2004; Simmons et al. 2007).
Comparing management methods for individual invasive plant species between studies is
often difficult due to the specificity of studies’ sites and treatment application conditions.
Flory and Clay (2009) encouraged scientists to explore multiple invasive removal
methods within single studies to allow for direct comparisons of efficacy of methods in
removing the targeted plant.
Although there has been much research surrounding the effects of various control
methods on targeted invasive vegetation (Judge et al. 2005; Paynter and Flanagan 2004;
Simmons et al. 2007), less attention has been dedicated to the effects on the native plant
community (Zavaleta et al. 2001). Furthermore, few studies have investigated multiple
control methods and their impact on the native plant community (Biggerstaff and Beck
2007; Holmes et al. 2000; Mason and French 2007). Single studies exploring multiple
control methods have the ability to make conclusions on how various removal methods
affect the community and compare between methods, which could provide much
guidance to land managers affected by the same invasives (Flory and Clay 2009). Such
2
studies can greatly aid in plant community, and further, ecosystem restoration efforts
(Díaz et al. 2003; Hulme 2006). This research aimed to evaluate how multiple individual
and combined invasive plant removal techniques affect the abundance of invasive
Brachypodium sylvaticum (Huds.). P. Beauv. as well as the native plant community in
western Oregon foothills.
1.1
Brachypodium sylvaticum: Native Range, Morphology, and Life History
Brachypodium sylvaticum, or false brome, is a cespitose, perennial bunchgrass
native to Europe, Asia, and North Africa (Catalán and Olmstead 2000; Roy 2010). In its
native habitat, the grass can be found primarily in shaded woodland areas. However, B.
sylvaticum habitats are fairly diverse, and also include unshaded environments,
particularly upland areas (Grime et al. 1988). The bunchgrass is widely distributed in the
United Kingdom, residing primarily in calcareous or base-rich soils (Davies and Long
1991). B. sylvaticum has been found in habitats as extreme as sea cliffs (Burnett 1964)
and fixed sand dunes (Salisbury 1952).
The grass’ shoots stand erect while the leaves are linear (Grime et al. 1988).
Leaves, nodes, and ligules are all pubescent (Grime et al. 1988; Roy 2010). Leaf blade
color is described as apple green, but B. sylvaticum plants growing in open sites with full
sun exposure experience photo-bleaching, and may appear more yellow than neighboring,
shaded B. sylvaticum plants. The plant’s foliage can grow as tall as 35 cm while flowers
can reach nearly 1 m in height (Grime et al. 1988). Sterile shoot height reaches its
maximum in June, while fertile shoots reach their maximum by the end of July, when
flowering begins (Szujkó-Lacza and Fekete 1974).
3
B. sylvaticum seedlings generally do not flower until they reach their second year
(Roy et al. 2011). Flowers can develop from both sexually produced tillers and asexually
produced tillers (Roy 2010). The flowers are green, hermaphroditic, self-compatible and
wind-pollinated. Often as many as 100 flowers can be found grouped in spike-like
inflorescences of 8-16 spikelets (Grime et al. 1988). In fact, it is these spikelets that
distinguish B. sylvaticum from its most closely resembled genus Bromus, and most
notably, Bromus pubescens Muhl. ex Willd. Both species have pubescent leaves and
spikelets; however, in B. sylvaticum, the spikelets arise singly from the rachis whereas
they are found as branched panicles in Bromus species. In addition, B. sylvaticum exhibits
open leaf sheaths while leaf sheaths are closed in Bromus species. These slight
morphological differences inspired the origin of B. sylvaticum’s common name of false
brome (Miller et al. 2011).
By the end of August, B. sylvaticum seeds fall and disperse (Szujkó-Lacza and
Fekete 1974). Seeds are distributed primarily by animals, particularly wild ungulates in
the grass’ native habitat. B. sylvaticum seeds possess long awns that latch to the fur of
animals and can travel lengthy distances (Heinken and Raudnitschka 2002). Also, the
grass can grow along rivers and streams, and therefore can be carried long distances by
currents (Bor and Guest 1968; Davis 1988). B. sylvaticum seeds do not survive the
digestive tract of sheep, but whether the seed can viably pass through other animals is yet
unknown (Scholz 2007).
After dispersal of seed, plants begin to senesce. However, this process is generally
delayed in B. sylvaticum compared to most other woodland plants. Many B. sylvaticum
shoots are able to continue photosynthesizing through the middle of winter (Roy 2010).
4
Tiller production then resumes in the beginning of May (Szujkó-Lacza and Fekete 1974).
A demographic study in Finland revealed that B. sylvaticum plants increase in size
continuously year after year, and may live to at least 20 years (Hæggström and Skytén
1996).
1.1.1
Associations and Natural Enemies
In its native habitat, B. sylvaticum can be nearly universally found with a host-
specific endophyte Epichloë sylvatica Leuctm. & Schardl (Bucheli and Leuchtmann
1996). The relationship between the grass and this endophyte ranges from mutualistic to
pathogenic (Meijer and Leuchtmann 1999). The fungus E. sylvatica can negatively affect
the grass by “choking” the tillers in which infected tillers exhibit white patches caused by
the reproducing fungus and will not flower (Roy 2010). However, not all B. sylvaticum
plants that play host to this endophyte are detrimentally affected. Plants vary from
asymptomatic, to completely choked, or a mixed symptom type where not every tiller
hosts the fungus (Meijer and Leuchtmann 1999). This variation in severity of symptoms
is due to different strains of E. sylvatica. The sexually reproducing state is referred to as
Epichloë, and the asexually reproducing state is referred to as Neotyphodium. Epichloë
chokes B. sylvaticum, but Neotyphodium does not; hence the variety of symptoms
between plants infected by the same endophyte (Bucheli and Leuchtmann 1996; Meijer
and Leuchtmann 2001). The majority of B. sylvaticum plants play host to Neotyphodium
strains and are asymptomatic, while Epichloë infected plants are generally restricted to
small clusters (Meijer and Leuchtmann 1999).
5
In addition to the Epichloë sylvatica endophyte, B. sylvaticum is subject to a
broad group of pathogens and herbivores in its native range that regulate its populations
along with other grasses. However, these organisms do not attack B. sylvaticum
specifically. Rather, the pathogens that attack the invasive are primarily grass generalists,
and the herbivores are non-specific (Halbritter et al. 2012).
1.2
Brachypodium sylvaticum as an Invasive
B. sylvaticum was originally introduced to the continental U.S. in three separate
events occurring in Corvallis, OR, Eugene, OR, and San Francisco, CA. It is
hypothesized that the grass was initially introduced to these locations by the United
States Department of Agriculture with the purpose of testing for a new, more productive,
range grass (Rosenthal et al. 2008). The earliest known sighting of B. sylvaticum occurred
in 1939 near Eugene, OR. By 1966, B. sylvaticum was thoroughly naturalized in
Oregon’s Willamette Valley (Chambers 1966). Beyond the western U.S., B. sylvaticum is
steadily spreading across North America. Washington, Oregon, and California have
quarantined the species (CDFA 2009; NWCB 2009; ODA 2009), but the grass has been
found east in Missouri, Virginia, New York, and Ontario (Daniel and Werier 2010; Miller
et al. 2011; Roy 2010).
Like in its native habitat, B. sylvaticum can spread by its seed attaching to animal
fur. This invasive grass seed therefore can also latch to socks, shoes, and clothes, the
owners of which then unintentionally disperse the plant (Boersma et al. 2006), increasing
its presence in well-recreated parks and nature preserves (Roy 2010). In addition,
commercial logging also promotes long-distance spread of B. sylvaticum seeds (Boersma
6
et al. 2006). B. sylvaticum is also gaining popularity as a model organism due to its selffertility, short generation time, and close relationship to the annual model Brachypodium
distachyon (L.) P. Beauv. (Steinwand et al. 2013). This practical research use naturally
increases the possibility of the plant accidentally escaping from scientific environments.
B. sylvaticum is capable of forming dense monocultures under forested canopies
in North America (Boersma et al. 2006; Severns and Warren 2008). Such invasions can
detrimentally affect the ecological functions and processes of these ecosystems. As with
many invasive vegetative populations, B. sylvaticum competes with native plants for
resources, leading to stress or mortality of the native vegetation (Holmes et al. 2010). B.
sylvaticum readily outcompetes native grasses under shady, high nutrient conditions,
including Festuca roemeri (Pavlick) E. B. Alexeev (Roemer’s fescue) and Elymus
glaucus Buckley (blue wildrye), and even another aggressive invasive grass Schedonorus
arundinaceus (Schreb.) Dumort., nom. cons. (tall fescue) (Roy 2010). This competitive
advantage has been linked to its relative rapid growth rate and ability to leave persistent
leaf litter (Alonso et al. 2001; Grime et al. 1988; Hæggström and Skytén 1996).
In addition to negatively impacting native grasses, B. sylvaticum invasions can
also threaten the recovery of rare plants, and consequently, organisms that interact with
these plants (Severns and Warren 2008). For example, Icaricia icarioides fenderi
(Fender’s blue butterfly) is a federally listed endangered species. This butterfly uses
Lupinus sulphureus spp. kincaidii (Kincaid’s lupine) as its primary host plant, which is a
federally listed threatened species. Substantial loss of Kincaid’s lupine and Fender’s blue
butterfly is largely due to prairie habitat loss; many prairies that play host to these two
species have recently experienced B. sylvaticum invasions (FWS 2006). Another federal
7
candidate endangered butterfly species, Euphydryas editha taylori (Taylor’s
Checkerspot), is also experiencing a reduction in prairie habitat loss due to B. sylvaticum
encroachment (Severns and Warren 2008). These B. sylvaticum invasions can reduce
plant quality and diversity, and therefore lead to a trophic cascade in which a variety of
herbivores and many other organisms can be negatively affected (Burghardt et al. 2009;
Zuefle et al. 2008) but which have gone largely unexplored.
Competitive qualities of B. sylvaticum invasions can not only decrease herbaceous
diversity, but can also decrease tree seedling germination in forest ecosystems (Roy
2010). Although research has not established a direct relationship between B. sylvaticum
invasions and a decrease in conifer seedling regeneration, there are many studies that link
a negative effect on conifer germination, growth, and survival due to grass competition in
general (Kruse et al. 2004; Lehmkuhl 2002; Powell et al. 1994).
Such changes in plant communities can also alter forest fire regimes (Anzinger
and Radosevich 2008; Roy 2010). B. sylvaticum builds up thatch through the years,
which could increase fire risk or generate more intense/severe fires (Anzinger and
Radosevich 2008; Poulos 2013). However, B. sylvaticum does not senesce until about the
middle of winter, which is much later than most other grasses and forbs (Roy 2010). This
may actually promote the opposite effect and decrease fire risk due to its persistent live,
moist biomass (Anzinger and Radosevich 2008; Poulos 2013). Poulos (2013) has initiated
the study of the interaction between fire and B. sylvaticum in the Willamette National
Forest, and she suggests that B. sylvaticum does not affect prescribed fire intensity or
severity. However, further research needs to be conducted, because B. sylvaticum
8
invasions have great potential to alter disturbance regimes (D’Antonio and Vitousek
1992).
In addition to ecological impacts, B. sylvaticum invasions can economically
impact the region in which it invades. In the Northwestern U.S., public lands such as the
National Forest System, the Bureau of Land Management (BLM), and city, county, state,
and national parks are already spending money on control efforts. For example, a support
organization (the Friends of Buford Park) has spent at least $50,000 per year to manually
and chemically control B. sylvaticum in County Park (956 hectares) in Lane County, OR.
Private landowners such as private logging companies and The Nature Conservancy
generally already use chemicals to manage their lands from unwanted vegetation, so there
are few extra costs associated with targeting B. sylvaticum with herbicides. However,
current vegetation management practices may not be appropriate for controlling B.
sylvaticum, so additional costs are often required. In 2009, The Nature Conservancy spent
roughly $2,667 to specifically control this invasive grass with herbicides in the Philomath
Prairie, Philomath, OR (Roy 2010).
1.3
1.3.1
Controlling Brachypodium sylvaticum
Mechanical Control Methods
Prevention is the first step in controlling the spread of B. sylvaticum and starts
with educating the public about the invasive grass. This could include posting fliers at
trailheads and installing boot/shoe-cleaning stations in public parks and trails that are
known to be invaded, particularly along roads and trails. In addition, all vehicles, whether
they are recreational or logging vehicles, that have been in B. sylvaticum invaded areas
9
should be inspected and thoroughly cleaned before moving to a new area (FBWG 2009).
However, complete containment and prevention is nearly impossible, as B. sylvaticum
seeds not only attach to humans and vehicles, but wildlife and domestic pets (Heinken
and Raudnitschka 2002).
Once introduced to an area, several mechanical methods have been explored to
reduce B. sylvaticum populations (extent and cover) as well as limit its spread.
Conventional methods include hand pulling, mowing, and mulching. Hand pulling can be
successful in removing present B. sylvaticum if the plants’ roots are also removed.
However, hand pulling must be continued another one or two years after to eliminate
seedlings. It is also pertinent to hand pull before the plant goes to seed, otherwise,
individuals hand pulling may act as vectors for the spread of B. sylvaticum. Unfortunately,
hand pulling is only feasible to control small infestations, as it requires much physical
effort and time. Though expensive and marginally effective, this method is a great way to
involve the community by educating local individuals as to the ecological and economic
threat B. sylvaticum poses while having them volunteer to manually remove the grass
(Dennehy et al. 2011).
Mowing has had less empirical success in controlling B. sylvaticum populations.
For this method, the time of treatment is also imperative. Mowing must take place before
seeds begin to develop so as to not spread the seeds while mowing. Also, mowing must
not begin too early in the year, for the grass will re-sprout and flower despite earlier
mowing (Blakeley-Smith and Kaye 2008; Dennehy et al. 2011). Additionally, this
method does not decrease B. sylvaticum competitive advantage relative to other plants,
10
because all adjacent vegetation is similarly affected by the mowing process (Dennehy et
al. 2011).
Mulching can be used as a supplement to mowing, but should not be used alone.
Mulching after mowing with straw or wood chips can greatly reduce abundance and
suppress seed production for at least one year following application compared to solely
mowing (Blakeley-Smith and Kaye 2008; Dennehy et al. 2011). The False Brome
Working Group (FBWG) (2009) suggests mulching with blue wildrye seed and straw is
effective in establishing that species while the straw inhibits establishment of B.
sylvaticum.
A new mechanical method that has shown to be successful in reducing B.
sylvaticum abundance and spread is hot foam treatment. In October 2002, the Eugene
BLM and the Institute for Applied Ecology investigated the efficacy of this treatment on
B. sylvaticum. Results indicated an 88% reduction in mean B. sylvaticum percent cover
when comparing hot foam treated plots to control plots one year after application.
Although successful in reducing the abundance of B. sylvaticum, hot foam treatments are
much more expensive than traditional mechanical (or chemical) control treatments. The
Eugene Waipuna equipment used for the Eugene BLM and Institute for Applied Ecology
research required rental of the Waipuna unit at $700/month and use of their foaming
agent at $900/208 liters. Additionally, the hot foam treatment is only practical on
roadsides (FBWG 2009).
11
1.3.2
Biological Control Methods
Biological controls are not feasible options for controlling B. sylvaticum for a
variety of reasons. Firstly, B. sylvaticum is closely related to many agriculturally
important species such as Triticum aestivum L. (common wheat) (Catalán and Olmstead
2000; Opanowicz et al. 2008; Rathore and Shekhawat 2009). Therefore, if a specific
control agent were to be found and applied, it is probable that the agent would jump to
these significant agricultural species (Roy 2010). B. sylvaticum’s host-specific E.
sylvatica endophyte could be used to choke the North American populations; however,
only the asexual strain (Neotyphodium) is found on North American B. sylvaticum
populations (Halbritter 2009), so theoretically, introducing the sexual strain may be
effective in reducing the grass’ abundance. However, it is ill advised to introduce this
sexual strain to North America as it also has the possibility to jump to a different host
(Brem and Leuchtmann 2003). Plus, E. sylvatica is not commonly found in B.
sylvaticum’s native range, which suggests that it might not survive or be effective in
North America (Roy 2010). Lastly, many grass endophytes produce compounds that are
toxic to insects and common grazing mammals such as sheep and cattle (Brem and
Leuchtmann 2001; Clay 1990). When ingested, these toxins frequently induce higher
abortion rates and neurological disorders (Brem and Leuchtmann 2001; Clay 1996).
Common grazing mammals do not naturally eat B. sylvaticum; however, when exposed to
the grass early in life, sheep will graze on the plant as they grow older (Scholz 2007).
12
1.3.3
Chemical Control Methods
Chemical methods are most commonly used to control B. sylvaticum in North
America. Several studies have been conducted testing the efficacy of various herbicides
on the invasive grass (Blakeley-Smith 2007; Clark et al. 2004). Hurst and John (1999)
demonstrated that glyphosate significantly reduces the abundance of the closely related
Brachypodium pinnatum (L.) P. Beauv. in its native habitat in the United Kingdom one
year after application. However, B. pinnatum regained its dominance after this first year,
and it is proposed that this is due to its rhizomatous regeneration strategy. B. sylvaticum
does not reproduce rhizomatously, and therefore may be successfully controlled with
herbicides. However, Blakeley-Smith (2007) experienced similar results with B.
sylvaticum in Butterfly Meadows, Benton County, OR, as a significant reduction in B.
sylvaticum abundance was observed one year after seven different herbicide
combinations, but no difference in the grass’ abundance in the treated and control plots
two years after application. Glyphosate alone or in combination with hexazinone and
grass-specific herbicides such as fluazifop has also been shown to reduce B. sylvaticum
by over 90% when observed one year after application (Dennehy et al. 2011). Glyphosate
is generally recommended to be applied in the summer as it is a foliar-herbicide, but since
it is also a non-selective herbicide, it poses the risk of damaging desirable, native
vegetation (Hurst and John 1999).
It is often difficult to specifically target the invasive species while simultaneously
avoiding injury to the native plant community (Erickson et al. 2006; Freemark and Boutin
1995; Jobin et al. 1997; Kleijn and Snoeijing 1997). Continuous herbicide use can move
chemicals far from the site of application and alter nutrient regimes (DiTomaso et al.
13
2006; Donald et al. 2001). Plus, without a follow-up removal method of the biomass,
dead vegetation often makes it difficult for shade-intolerant seedlings to emerge
(Biggerstaff and Beck 2007). The phenology of the targeted plant is important to consider
when applying an herbicide with the intent of eliminating a targeted invasive species and
promoting native plant diversity. Herbicide prescriptions and rates can be customized and
timed to optimally damage the invasive species with minimal damage to other species
that do not share the same life history traits (Crone et al. 2009).
1.3.4
Prescribed Burning Control Methods
Prescribed burning can control invasive vegetation if applied in a way and time
that detrimentally affects the targeted invasive species more than the native species
(Keeley 2006). However, fire is more commonly associated with promoting the
introduction and persistence of invasive vegetation and particularly grasses (Grace et al.
2001; Harrod and Reichard 2001; Lesica and Martin 2003). Many native bunchgrasses
re-sprout vigorously after fire and increase flower production (Glenn-Lewin et al. 1990;
Keeley 1981; Young and Miller 1985). In 1998, prescribed fire treatments in Kings
Canyon National Park to reduce fuels were put on hold due to an apparent increase in the
invasive Bromus tectorum L. (cheatgrass) (Caprio et al. 1999). Additionally, there are
numerous forest restoration activities occurring in many western U.S. ponderosa pine
forests, which involve burning slash. These treatments have increased both the diversity
and abundance of non-native plant species (Dodson 2004; Griffis et al. 2001; Wienk et al.
2004).
14
Studies that have experienced success in reducing the abundance of invasive
grasses in the U.S. report that favorable results are primarily due to careful timing of
prescribed burning. Fall prescribed burns are much more feasible to execute as they are
associated with moderate fire behavior due to higher fuel moisture. Also, fire season is
normally complete by this time, so more management resources are available for burning.
However, with low to moderate fire behavior, not all thatch and seedlings are guaranteed
to be consumed. Plus, prescribed fire at this time of year will affect different plants
indiscriminately, as all will have released their seed and have begun to senesce. Late
spring burns which are executed after seed set, but before seed dispersal of the targeted
plant, have the potential to experience more intense fire behavior, eliminating the present
population (Pollak and Kan 1998).
Confirming previous observations, Pollak and Kan (1998) suggest that prescribed
burning that occurs in conjunction with seed production of Taeniatherum caput-medusae
(L.) Nevski (medusahead) eliminates the invasive grass’ seed production. This in turn
controls the treated population due to the grass’ non-dormant seeds (Evans and Young
1989). Therefore, if timed correctly, one prescribed fire treatment will be sufficient to
eliminate a medusahead population (Pollak and Kan 1998). However, not all invasive
plants have such vulnerable seeds, and therefore, a follow-up program should be
implemented to prevent escape and regeneration (DiTomaso et al. 2006).
As with chemical control methods, minimizing injury to the native community
while controlling the targeted invasive is often difficult to accomplish with prescribed
burns. Selectively controlling an invasive perennial grass is optimal in the presence of a
heavy thatch to increase fire intensity. The burn should also be timed so that the tillers of
15
the grass are elongated, but the native species are still dormant. Generally, species that
complete their life cycle before a prescribed burn are selected for, whereas species that
flower and seed after the burn are negatively impacted (Ditomaso et al. 2006). Most
studies that do yield an increase in species richness and diversity after a prescribed burn
are attributed to an increase in forbs rather than a decrease in the targeted invasive
species (DiTomaso et al. 1999). Additionally, prescribed burning is accompanied by
many added benefits, including reduction of fuel loads, restoration of historical
disturbance regimes, and improvement of forage and habitat (DiTomaso et al. 2006).
It is rare that one treatment of prescribed burning will effectively control an
invasive population and meet restoration objectives, so it is regularly recommended to
incorporate other control methods into the management strategy (Kyser and DiTomaso
2002). These could include any number of mechanical, chemical, or biological control
methods. Commonly, herbicide applications are paired with prescribed burning. After a
burn, some seeds are stimulated to germinate. One can then apply an herbicide to
eliminate these newly germinated seedlings (Biedenbender et al. 1995). In contrast,
herbicide treatments can precede prescribed burning. In this case, herbicides can be used
to increase the amount of dry dead fuels and promote a more intense burn (Glass 1991).
One of the added benefits of prescribed burning for invasive vegetation control
strategies is a decreased reliance on herbicides. Although herbicides are nearly
universally utilized for weed control, they cannot always provide long-term control when
used alone (Bussan and Dyer 1999). Some of the negative effects of extensive use of
herbicides include: movement of chemicals off the intended site, long-term selection for
herbicide-resistant vegetation, unintended harm to non-targeted species, and alterations in
16
the nutrient regimes. Integrating prescribed burning into traditionally herbicide-only
control strategies could decrease the amount of herbicides and number of applications
required to effectively control a targeted species (DiTomaso et al. 2006).
Using prescribed fire to control B. sylvaticum populations, however, is still in
need of thorough investigation. Poulos (2013) explored the relationship between fire and
B. sylvaticum and suggested that high-intensity fires can potentially control the species as
well as limit its dispersal, but low-intensity fires may only strengthen the infestation. This
study is the first to directly study the effects of fire on B. sylvaticum in a well-replicated
design, both with and without chemical treatments.
1.4
Study Site
The research occurred on Oregon State University’s McDonald Forest (Figure
1.1). The forest is located just north of Corvallis, OR, on the western edge of Oregon’s
Willamette Valley and on the eastern foothills of the Cascade Range. Elevation within the
forest ranges from 50 to 657 meters, but study blocks were all located below 260 meters.
This forest is one of the College of Forestry’s research forests and is used primarily for
university research and education. The McDonald Forest has been used to examine many
forest management regimes, including even-aged, two-storied and uneven-aged, plus
reserve old-growth stands. The forest consists mainly of Douglas-fir (Pseudotsuga
menziesii (Mirb.) Franco) with a small grand fir (Abies grandis (Douglas ex D. Don)
Lindl.) and bigleaf maple (Acer macrophyllum Pursh) component. According to
measurements taken in 2006, 1,048 hectares (23% of the total 4,552 hectares) of the
McDonald-Dunn Forest were invaded with B. sylvaticum (OSUCF 2011).
17
The McDonald Forest is an appropriate study site for researching methods of
controlling B. sylvaticum populations as it is easily accessible and has large areas that are
moderately to heavily invaded by the grass. Many of the heavily invaded areas have near
monocultures of B. sylvaticum in the understory. In addition, many of the heavily invaded
sites are also heavily shaded by a Douglas-fir overstory. As B. sylvaticum thrives in
shaded areas, the McDonald Forest serves as an ideal site for studying control methods of
the grass (Grime et al. 1988). If the B. sylvaticum invasion in the McDonald Forest is
allowed to persist uncontrolled, the ecological and educational functions of the forest
may be compromised.
1.5
Research Goals, Questions, and Objectives
Prescribed burning alone and in combination with herbicides has not been
thoroughly investigated for large-scale control of B. sylvaticum and native community
recovery. Given its ecological flexibility, this grass could pose a threat to a variety of
ecosystems regarding the maintenance of their biodiversity and ecological services.
This research will be used to develop and refine efficient techniques for
controlling B. sylvaticum populations in the Oregon Coast Range, and potentially
throughout the western United States. Similarly, it will also be used to develop methods
to protect native vegetation from loss by B. sylvaticum invasions. In order to complete
these goals, the following research questions were examined:
1. Is the abundance of B. sylvaticum in the McDonald Forest reduced by herbicide
and prescribed burning treatments in combination and separately?
18
2. Is the abundance and diversity of native vegetation impacted by herbicide and
prescribed burning treatments in sites invaded by B. sylvaticum in the McDonald
Forest?
These research questions were addressed through four objectives:
1. Determine the most effective treatment for reducing B. sylvaticum abundance
in the field.
2. Evaluate how the various treatments alter plant community cover in the field.
3. Determine the most effective treatment in maintaining and/or promoting a
diverse, species rich native plant community in the field.
4. Assess the residual seed bank following herbicide and prescribed burning
treatments.
19
Figure 1.1. Map of the 12 study blocks on the McDonald Forest near the Oak Creek
entrance. Red rectangles represent study blocks, and white lines and numbers
represent forest roads.
20
2
2.1
PRESCRIBED FIRE AND HERBICIDE TREATMENT OPTIONS FOR
CONTROLLING BRACHYPODIUM SYLVATICUM
Introduction
The negative ecological and socioeconomic effects of non-native plant invasions
have motivated widespread investigation and experimentation of invasive plant control
methods. Many of such studies have demonstrated promising results in managing existing
invasive plant populations as well as limiting the plants’ dispersal via individual control
techniques (Judge et al. 2005; Paynter and Flanagan 2004; Simmons et al. 2007).
Comparing management methods for a certain invasive plant between studies is often
difficult due to the specificity of studies’ sites and treatment application conditions (Flory
and Clay 2009). This study aimed to evaluate how multiple individual and combined
invasive control techniques affect the abundance of invasive Brachypodium sylvaticum
(Huds.). P. Beauv. in western Oregon foothills.
Brachypodium sylvaticum, or false brome, is a perennial bunchgrass native to
Europe, Asia, and North Africa (Catalán and Olmstead 2000; Roy 2010). The grass was
first spotted in North America in 1939 just outside of Eugene, OR, and had been
naturalized to Benton County, OR by 1966 (Chambers 1966). B. sylvaticum has since
spread beyond Oregon and is considered a quarantined invasive plant in Washington,
California, and Oregon (CDFA 2009; NWCB2009; ODA 2009). However, it has been
sighted as far east as Missouri, Virginia, New York, and Ontario (Daniel and Werier
2010; Miller et al. 2011; Roy 2010). B. sylvaticum seeds are readily spread by attaching
to animal fur, socks, shoes, and clothes. Furthermore, commercial logging and other off-
21
road traffic promote the long-distance spread of B. sylvaticum seeds (Boersma et al.
2006).
In its native habitat, B. sylvaticum is found primarily in shaded woodlands, but its
potential habitats are vast and varied, including unshaded prairies (Grime et al. 1988), sea
cliffs (Burnett 1964), and fixed sand dunes (Salisbury 1952). The grass can be found at
elevations ranging from sea level to 1,600 m in Europe (Long 1989) and 4,000 m in the
Himalayas (Roder et al. 2007). In North America, B. sylvaticum populations are capable
of developing dense monocultures in both heavily shaded forests as well as areas with
full sun exposure (Boersma et al. 2006; Severns and Warren 2008). This habitat
amplitude provides a robust competitive advantage against other vegetation, particularly
in its non-native habitat. Additionally, the grass is characterized by a rapid growth rate
and persistent thatch, allowing it to readily outcompete other grasses and native
herbaceous vegetation (Alonso et al. 2001; Grime et al. 1988; Hæggström and Skytén
1996). B. sylvaticum also detrimentally affects its inhabited ecosystems by threatening
the recovery of rare species (Severns and Warren 2008), decreasing tree seedling
germination (Roy 2010), and altering forest fire regimes (Anzinger and Radosevich 2008;
Roy 2010).
Many traditionally used invasive vegetation removal methods have been
examined with B. sylvaticum. However, most treatments such as mowing, mulching, hand
pulling, and hot foam have proven unsuccessful, too costly, too labor-intensive, and/or
impractical given limited accessibility to effectively control B. sylvaticum populations
(Blakeley-Smith and Kaye 2008; Dennehy et al. 2011; FBWG 2009). Single applications
of herbicides however, have shown consistent promise in immediately controlling B.
22
sylvaticum populations given ease and cost. Blakeley-Smith (2007) saw a significant
reduction in B. sylvaticum abundance in Butterfly Meadows, Benton County, OR one
year after seven different herbicide combinations. However, two years after application,
there were no longer any significant differences in B. sylvaticum abundance between the
control and treated plots. Poulos (2013) only recently examined the effect of fire intensity
on B. sylvaticum abundance in the Willamette National Forest. Her results indicated that
high-intensity fires can potentially control invasive populations of the grass and limit its
dispersal, but low-intensity fires will only promote the growth of B. sylvaticum.
Incorporating multiple control methods into invasive species research allows
inferences as to how various control methods affect the targeted species and comparisons
among removal methods rather than drawing conclusions between different studies at
different sites and times (Flory and Clay 2009). A common control pairing is prescribed
burning and herbicide treatments. Fire can stimulate some seeds to germinate, and an
application of herbicides following this fire can eliminate newly germinated seedlings
(Biedenbender et al. 1995). When herbicides precede prescribed burns, the herbicide can
increase the amount of dry fuels to create a more intense burn (Glass 1991). Also, pairing
prescribed burning with herbicides to control invasive vegetation can decrease
dependence on herbicides (Bussan and Dyer 1999), reducing movement of chemicals off
the intended site, selection for resistant vegetation, unintended harm to non-targeted
species, and alterations in the nutrient balance (DiTomaso et al. 2006).
The goal of this study was to develop and refine efficient techniques for
controlling B. sylvaticum populations in the Oregon Coast Range, and potentially
throughout the western United States. The specific objectives were to: 1) determine the
23
most effective treatment in reducing B. sylvaticum percent cover in the field and 2) assess
the residual seed bank following herbicide and prescribed burning treatments. Treatments
included the use of two herbicides and prescribed burning in various combinations, for a
total of nine treatments and a no-treatment control.
2.2
2.2.1
Methods
Study Site
The study blocks were located in Oregon State University’s McDonald Forest,
just north of Corvallis, OR, on the western edge of Oregon’s Willamette Valley and on
the eastern foothills of the Coast Range. The forest consists primarily of Douglas-fir
(Pseudotsuga menziesii (Mirb.) Franco) with a small grand fir (Abies grandis (Douglas
ex D. Don) Lindl.) and bigleaf maple (Acer macrophyllum Pursh) component. According
to measurements taken in 2006, 1,048 hectares (23% of the total 4,552 hectares) of the
McDonald-Dunn Forest were invaded with B. sylvaticum (OSUCF 2011). Study blocks
were all below 260 meters elevation on multiple aspects with slopes less than 20%.
2.2.2
Experimental Design
The study included 12 blocks, each 25x50 m and established in sites with at least
50% canopy cover (established with visual estimates). In addition, plots were situated in
areas that would be logistically reasonable for fire personnel and equipment to access for
small prescribed burn treatments. Study blocks adhered to a split-plot design. Each block
was divided into five equally sized plots with the following treatments randomly assigned
to each subunit: control, summer herbicide (SH), summer herbicide/summer burn (SHSB),
24
summer herbicide/fall burn (SHFB), and fall burn (FB). These plots were then divided
into equal halves with one half of each plot receiving an additional fall herbicide
treatment, yielding five additional treatments: fall herbicide (FH), summer herbicide/fall
herbicide (SHFH), summer herbicide/summer burn/fall herbicide (SHSBFH), summer
herbicide/fall burn/fall herbicide (SHFBFH), and fall burn/fall herbicide (FBFH) (Figure
2.1). A minimum 2 m buffer was maintained between spray and burn plots. We
established four permanent quadrats measuring 0.5x2 m within each subunit as
measurement quadrats. Thus, each of the ten treatments had a total of 48 measurement
quadrats distributed over 12 blocks.
Summer herbicide treatment was applied June 3, 2013 with a backpack sprayer.
We applied glyphosate in the form of Roundup Pro Concentrate (5.6 l/ha) with Razor Pro
(5.8 l/ha) and sulfometuron-methyl in the form of Sulfomet (175 ml/ha) at a rate of 93.5
liters per hectare using water as a carrier. This broad-spectrum herbicide was selected to
both kill the preexisting B. sylvaticum and also provide dry fuels for the subsequent
prescribed burning. The summer prescribed burn treatments followed on July 1-3, 2013.
Fall prescribed burning treatments occurred over three days on October 18, 22-23, 2013
(Table 2.1). Fall herbicide treatments followed shortly after on October 28, 2013 also
with a backpack sprayer. We applied sulfometuron-methyl in the form of Oust (280 ml/ha)
and Dyne-Amic (560 ml/ha) at 74.8 liters per hectare using water as a carrier. This
herbicide targets perennial and annual grasses and broad-leaf weeds and was selected to
ensure fatality of B. sylvaticum but also minimize damage of the native species.
25
2.2.3
Field Measurements
The percent cover of B. sylvaticum within each quadrat was visually estimated to
the nearest one percent during May and June 2013 (pre-treatment) and June 2014 (first
growing season). Quadrat measurements were then averaged over each treatment plot.
We also measured environmental variables including elevation, slope, aspect, and canopy
cover for each plot. Following the prescribed burns, scorch measurements were taken by
visually estimating percent scorch to the nearest one percent in each quadrat then
averaging over each treatment plot.
To determine which treatment was most effective at reducing B. sylvaticum, we
compared the average percent cover of B. sylvaticum in the treatment plots to the control
plots using a linear mixed model to describe the data collected. Average pre-treatment
percent cover of B. sylvaticum per treatment was added as a covariate to create a parallel
lines model. For all linear mixed models in this study, random effects included study
blocks and the residual error term and fixed effects included treatments. Observations
with an average percent cover of B. sylvaticum response of zero were removed (only four
observations), and then the response was natural log-transformed to produce normal
residuals of the percent cover of B. sylvaticum by treatment. To ensure a Type I error rate
of 5%, we performed a Bonferroni adjustment where the number of planned comparisons
was nine. Treatment means for percent surface area scorched were also compared using a
linear mixed model with Bonferroni adjusted 95% confidence intervals. All analyses
were performed using RStudio version 0.98.490 (2013).
26
2.2.4
Seed Bank Experiment
Using a hand-held bulb planter measuring 5 cm in diameter x 5 cm in depth, one
soil sample was collected from each quadrat in late November 2013 (Figure 2.1). This
allowed enough time for the herbicide to fully take effect while minimizing capturing the
effect of post-treatment seed dispersal. Samples were then temporarily stored in a cold
room at 4° C until further processing. We prepared the samples by removing all
preexisting vegetative material (excluding seeds) and sprinkled them over one half of
33x23 cm plastic trays prepared with one layer of sterilized sand and then one layer of
potting soil (both 2 cm in depth). Soil sample trays, including 12 additional control trays,
were randomly placed throughout a greenhouse, which was kept at 21° C during the day
and 16° C at night with no artificial light provided, and watered daily. Emerging B.
sylvaticum seedlings were counted for each tray over three months. This procedure was
repeated with soil samples collected in early February 2014 to allow for seeds to
experience cold stratification in the field to break dormancy for germination (Baskin and
Baskin 1988).
Similar to the field experiment, for each set of soil samples, a linear mixed model
was used to describe the data collected with average pre-treatment percent cover of B.
sylvaticum per treatment as a covariate to create a parallel lines model. This allowed us to
determine which treatment was most effective at reducing B. sylvaticum viable seeds by
comparing the average number of viable B. sylvaticum seeds in the treatment plots to the
control plots. The model was constructed to allow different variances for each treatment.
Treatment SHSBFH yielded no viable B. sylvaticum seedlings from the November
27
samples, and therefore was removed from analysis, as there were no data to estimate. Soil
sample units were converted to number of seeds per 1 m2 to a depth of 5 cm. Bonferroni
adjustments were applied as with the field data analysis.
2.3
2.3.1
Results
Field Experiment
Mean percent surface area scorched for all treatments including a summer
herbicide were all above 30% whereas the treatments without a summer herbicide yielded
a mean percent scorch of 21% (Figure 2.2). This indicates a greater fire intensity
produced by the dry, dead fuels generated by the summer herbicide. When examining
pairwise differences between treatments, only SHSBFH and FB were significantly
different.
Pre-treatment mean B. sylvaticum cover was the same for all treatments (F9,99 =
0.59, P = 0.80), and pre-treatment control mean B. sylvaticum cover was the same as
post-treatment control mean B. sylvaticum cover (F1,22 = 0.82, P = 0.38). We compared
post-treatment control plots to the treated post-treatment plots to answer the question: Is
the abundance of B. sylvaticum in the McDonald Forest reduced by herbicide and
prescribed burning treatments singly and/or in combination? After accounting for pretreatment mean percent cover of B. sylvaticum, there is strong evidence that the median B.
sylvaticum cover between the control plots and the treated plots is not equal (F9,94 =
123.48, P < 0.0001). The control plots yielded a median of 3.5% cover over all blocks
(Bonferroni adjusted 95% CI:[1.93, 6.37]) (Table 2.2). When examined individually
against the control plots, all treatments were significantly different than the control plots,
28
with the exception of the FB treatment, which actually demonstrated a slight increase in
relative median B. sylvaticum percent cover of 23% (Bonferroni adjusted 95% CI:[0.62,
2.43]) (Figure 2.3). FBFH and FH treatments exhibited moderate reductions in relative
median B. sylvaticum cover, decreasing by 62% and 74%, respectively (Bonferroni
adjusted 95% CI:[0.19, 0.75], [0.13, 0.51]) (Figure 2.3). All treatments that included a
summer herbicide more dramatically and rather uniformly reduced median cover of B.
sylvaticum relative to controls. The greatest reduction in median B. sylvaticum cover
compared to the controls was exhibited by the SHFH treatment, decreasing in relative
median B. sylvaticum cover by 98.8% (Bonferroni adjusted 95% CI:[0.0059, 0.024])
(Figure 2.3).
2.3.2
Seed Bank Experiment
After accounting for pre-treatment mean percent cover of B. sylvaticum, there is
strong evidence that the differences in mean average B. sylvaticum seedlings between the
control samples and the treated samples collected in both November and February are not
equal to zero (F8,98 = 5.82, P < 0.0001; F9,109 = 6.81, P < 0.0001). The control plots from
the November samples yielded a mean of 559.47 viable B. sylvaticum seeds per 1 m2
(Bonferroni adjusted 95% CI:[67.06, 1051.88]), while the control plots from the February
samples yielded slightly less at a mean of 302.19 B. sylvaticum seeds per 1 m2
(Bonferroni adjusted 95% CI:[113.18, 491.21]) (Table 2.3). For both germination
samples, only treatments involving a summer herbicide were significantly different to the
controls (Figure 2.4). In contrast, February FB and FH samples yielded slightly more
viable B. sylvaticum seeds compared to the controls with estimates of 20 and 95 more
29
seeds respectively (Bonferroni adjusted 95% CI:[-302.77, 341.84], [-286.42, 475.68])
(Figure 2.4).
2.4
Discussion
Summer herbicide treatments were consistently effective in controlling B.
sylvaticum populations. Summer herbicide treatments were applied before B. sylvaticum
seeds fully developed and were released, thereby impacting both current and future plant
populations; fall treatments were all applied after this critical period. These results were
similar to those found by Blakeley-Smith (2007) and Hurst and John (1999). However,
those authors hypothesized that an herbicide treatment alone would eliminate the existing
B. sylvaticum, but not the remaining seed bank. Our seed bank assays indicated otherwise
as the SH treatment alone was equally effective as the other treatments including a
summer herbicide at reducing mean B. sylvaticum number of seeds, with only possessing
a small component of pre-emergent chemicals. This also may be due to spring drought in
2012, the previous year, because B. sylvaticum seed production is strongly dependent on
climate (Roy 2010). The state of Oregon experienced its second driest summer period on
record in 2012 (OCS 2014; OSUNRC 2012). This drought event may be responsible for
reducing the amount of viable seeds available before the application of treatments in our
study in 2013, resulting in relatively few seedlings produced by 2014. B. sylvaticum seed
banks are short-lived (Grime et al. 1988), so presence of even older viable seeds is
unlikely. Future studies examining the effectiveness of various treatments at reducing a
short-lived seed bank such as B. sylvaticum are recommended to collect pre-treatment
soil samples as well compare pre-treatment and post-treatment results.
30
Studies examining the effects of herbicide on B. sylvaticum have had success in
significantly reducing the invasive grass presence after one growth season, but have
observed that the results are short-lived, and that B. sylvaticum abundance returns to that
of the controls by the next growth season (Blakeley-Smith 2007). Such rapid
reestablishment and dominance of invasive species after treatment is unfortunately
common in many restoration projects (Sveinson and McLachlan 2003; Travnicek et al.
2005; Wilson et al. 2004). To prevent this from occurring, exclosures are often suggested
to reduce the amount of wildlife moving through study plots and dispersing B. sylvaticum
seeds. This will determine if reestablishment is due to existing, surviving B. sylvaticum
seeds and vegetation or from outside recruitment.
Fall prescribed burning alone does not appear to immediately or effectively
reduce B. sylvaticum abundance. In fact, it may even promote the presence of B.
sylvaticum. This may be due to low fire intensity, and the heat simply could not eliminate
the existing plants and/or the seed bank (Poulos 2013). Given B. sylvaticum’s unusual
phenology of photosynthesizing well into the winter, the plant had barely senesced by the
time of the fall prescribed fire. Fire intensity was greater in the fall prescribed burn with a
previous summer herbicide compared to the fall prescribed burn with no previous
herbicide, but we cannot separate the more intense fire from the herbicide since a summer
prescribed burn alone is not reasonable due to high fuel moistures. Burning with
sufficient intensity to kill growth points below the soil surface and stored seed seems
problematic given concerns over fire spread and associated vegetation mortality. Fire
typically favors grass communities (D’Antonio and Vitousek 1992).
31
The addition of a fall herbicide does not hold promise for B. sylvaticum control. In
this study, it reduced the abundance of B. sylvaticum in the field, but it was not nearly as
effective as treatments with a summer herbicide and the number of viable B. sylvaticum
seeds was unchanged. Low application rates may have been responsible for the relatively
poor performance of the herbicide alone and in combination with the fall prescribed burn,
when compared to the summer herbicide. We did not use the same herbicide prescription,
so direct comparisons cannot be made. Also, the day following the herbicide application
reached temperatures as low as -2° C, which possibly top-killed the existing vegetation,
leaving foliar uptake of the herbicide compromised and relying primarily on root uptake.
Proper timing of treatments could become a regular issue due to inclement weather
conditions, immediate lack of equipment, or lack of personnel (Harvey et al. 1986; Rawn
et al. 1999; Simmons et al. 2007).
2.5
Management Implications
Treatments with an aggressive, foliar summer-applied herbicide can reduce both
existing B. sylvaticum plants as well as viable seeds one year later. Long-term
observations should be made to thoroughly understand the effects of these individual
treatments on both B. sylvaticum and the species composition. Additionally, repeated
treatment applications should be explored to determine how many seasons of herbicides
and/or prescribed burning are necessary to attain the desired plant community. Given the
grass’ short viable seed life (Grime et al. 1988), it is possible that only one or two seasons
of optimal treatments will be required to control B. sylvaticum. This would potentially
save money and labor on herbicide treatment efforts.
32
Prescribed burning preceded by an aggressive summer-applied herbicide did not
exhibit any negative effects such as increasing B. sylvaticum cover and/or seed
abundance. However, without the summer-applied herbicide, a fall prescribed burn may
even stimulate B. sylvaticum abundance, likely due to lack of fire intensity (Poulos 2013).
To prepare the fuel bed and manage the necessary fire intensity, one must apply a broadspectrum herbicide prior to the prescribed burn. Plus, landowners may achieve additional
objectives with a prescribed burn such as reducing hazardous fuels, improving wildlife
habitat, and preparing sites for seeding or planting (DiTomaso et al. 2006). Although this
study did not differentiate the beneficial effects of summer herbicides with and without
subsequent prescribed burns, managers on the McDonald Forest may consider
incorporating prescribed burns into their B. sylvaticum management agenda. The
McDonald Forest is used extensively for educational purposes and is highly recreated.
Prescribed burns at small scales to control B. sylvaticum could serve an educational
purpose for students, expose the public to the benefits of prescribed fires, and begin
restoration of historical disturbance regimes.
33
Table 2.1. Prescribed fire dates in 2013, dry temperature, and relative humidity
(RH). Wind speeds were negligible across all burns.
Block
1
2
3
4
5
6
7
8
9
10
11
12
Summer Prescribed Burn
Day
Temp. (F)
RH (%)
1-Jul
82
58
1-Jul
84
55
3-Jul
73
39
2-Jul
83
58
1-Jul
78
66.5
3-Jul
80
40
3-Jul
77.5
40
2-Jul
81
64
2-Jul
83.5
57
2-Jul
82
60
1-Jul
78.5
61
1-Jul
81
64
Fall Prescribed Burn
Day
Temp. (F)
RH (%)
18-Oct
60
63
18-Oct
60
63
18-Oct
63
59
18-Oct
63
59
22-Oct
66
74
23-Oct
63
78
23-Oct
63
78
22-Oct
70
59
23-Oct
65
74
23-Oct
65
74
22-Oct
68
66
22-Oct
68
66
Table 2.2. Median post-treatment B. sylvaticum percent cover estimates compared to
the control plots with Bonferroni adjusted 95% confidence intervals. Treatments
significantly different from the control are marked with a *.
Treatment
Control
FB
FBFH
FH
SH
SHFB
SHFBFH
SHFH
SHSB
SHSBFH
Estimate
3.51
4.31
1.34
0.91
0.080
0.076
0.048
0.034
0.056
0.042
*
*
*
*
*
*
*
*
Field
Lower CI
1.93
2.36
0.73
0.50
0.044
0.042
0.027
0.017
0.030
0.022
Upper CI
6.37
7.89
2.44
1.66
0.14
0.14
0.088
0.068
0.10
0.078
34
Table 2.3. Mean number of viable B. sylvaticum seeds per 1 m2 germinated in the
greenhouse for November and February samples with Bonferroni adjusted 95%
confidence intervals. Treatments significantly different from the control are marked
with a *.
Seed Bank - November
Treatment
Control
FB
FBFH
FH
SH
SHFB
SHFBFH
SHFH
SHSB
SHSBFH
1
Estimate
559.47
504.20
282.37
356.66
39.96
18.20
01
5.55
01
0
*
*
*
*
*
Lower CI
67.06
129.03
-143.45
106.58
-40.24
-60.53
-85.27
-73.66
-74.61
-
Upper CI
1051.88
879.37
708.19
606.74
120.15
96.93
59.93
84.76
45.64
-
Seed Bank - February
Estimate
302.19
321.73
269.47
396.82
01
01
01
01
25.60
01
*
*
*
*
*
*
Lower CI
113.18
59.76
68.36
65.26
-54.05
-31.89
-50.01
-60.88
-50.30
-60.81
Upper CI
491.21
583.70
470.57
728.38
22.47
20.62
40.32
51.49
101.50
40.53
These estimates are actually computed to be negative values due to parallel lines model
generated with pre-treatment percent cover of B. sylvaticum covariate, but are represented
as 0.
35
!!!!!"#"$!!!!!!!!!!!!!!!!!!!!!!!!!!%$"$ !!!!!!!!!!!!!!!!!!!!!!!!%$"#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!%$%#!!!!!!!!!!!!!!!!!!!!!!!!!&'()*'+
!!
!
,!-!
.!-!
!!!!"#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!%$
!!!!! !!!!!!!!!!!%$"#"$!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!%$%#"$!!!!!!!!!!!!!!!!!!!!!!!!!!!"$!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Figure 2.1. Treatment and measurement plot design, showing one of 12 blocks total.
Measurement plots are represented by the 4 small rectangles within each treatment
plot. Blue dots at one corner of each measurement plot represent location at which
soil samples were collected for the seed bank assays.
Figure 2.2. Plot describing the mean percent surface area scorched per prescribed
burn treatment. Whiskers represent Bonferroni adjusted 95% confidence intervals
36
Figure 2.3. Plot describing the ratio of the relative median B. sylvaticum percent
cover compared to the control plots. Whiskers represent Bonferroni adjusted 95%
confidence intervals. Solid horizontal line at 1.0 represents the same median percent
cover of B. sylvaticum to that of the control plots.
37
A
B
Figure 2.4. Plot describing the mean difference of number of viable B. sylvaticum
seeds per 1 m2 in the greenhouse for samples collected in (A) November and (B)
February compared to the control samples. Whiskers represent Bonferroni adjusted
95% confidence intervals. Solid horizontal line at 0 represents no difference between
mean number of viable B. sylvaticum seeds compared to the control samples.
38
3
3.1
EFFECTS OF PRESCRIBED BURNING AND HERBICIDES ON PLANT
COMMUNITIES INVADED BY BRACHYPODIUM SYLVATICUM
Introduction
Many studies investigating invasive plant control methods have demonstrated
promising results in managing existing populations as well as limiting dispersal via a
range of individual control techniques (Judge et al. 2005; Paynter and Flanagan 2004;
Simmons et al. 2007). However, little attention has been allocated to determining how
invaded native plant communities respond to such treatments (Biggerstaff and Beck 2007;
Holmes et al. 2000; Mason and French 2007). Such research can greatly aid in both plant
community and ecosystem restoration efforts (Díaz et al. 2003; Hulme 2006). This study
aimed to evaluate how prescribed burning and herbicide treatments, singly and in
combination, affect the plant community invaded by Brachypodium sylvaticum (Huds.). P.
Beauv. in western Oregon foothills.
Brachypodium sylvaticum, or false brome, is a perennial bunchgrass native to
Europe, Asia, and North Africa (Catalán and Olmstead 2000; Roy 2010) that reaches its
maximum growth height in early summer and sets seed at the end of summer (SzujkóLacza and Fekete 1974). In North America, B. sylvaticum populations are capable of
developing dense monocultures in both heavily shaded forests as well as areas with full
sun exposure (Boersma et al. 2006; Severns and Warren 2008). The grass possesses great
habitat amplitude, which provides a robust competitive advantage against other
vegetation, particularly in its non-native habitat. Additionally, the grass is characterized
by a rapid growth rate and persistent thatch, allowing it to readily outcompete other
grasses and native herbaceous vegetation (Alonso et al. 2001; Grime et al. 1988;
39
Hæggström and Skytén 1996). B. sylvaticum also detrimentally affects its inhabited
ecosystems by threatening the recovery of rare species (Severns and Warren 2008),
decreasing tree seedling germination (Roy 2010), and altering forest fire regimes
(Anzinger and Radosevich 2008; Roy 2010).
A common invasive vegetative control pairing is prescribed burning and herbicide
treatments. Fire can stimulate some seeds to germinate, and an application of herbicides
following this fire can eliminate newly germinated seedlings (Biedenbender et al. 1995).
When herbicides precede prescribed burns, the herbicide can increase the amount of dry
fuels to create a more intense burn (Glass 1991). Also, pairing prescribed burning with
herbicides to control invasive vegetation can decrease dependence on herbicides (Bussan
and Dyer 1999), reducing movement of chemicals off the intended site, selection for
resistant vegetation, unintended harm to non-targeted species, and alterations in the
nutrient balance (DiTomaso et al. 2006). Herbicides have shown consistent short-term
promise in controlling B. sylvaticum populations given ease and cost (Blakeley-Smith
2007). Poulos (2013) only recently examined the effect of fire intensity on B. sylvaticum
abundance in the Willamette National Forest. Her results indicated that high-intensity
fires can potentially control invasive populations of the grass and limit its dispersal, but
low-intensity fires will only promote the growth of B. sylvaticum.
Herbicides are more frequently being applied with the intent of promoting native
plant diversity rather than for the sole purpose of eliminating the targeted invasive
species (Marrs 1984; Marrs 1985; Rice et al. 1997; Travnicek et al. 2005). However, it is
often difficult to specifically target the invasive species while avoiding injury to the
native plant community, both directly and indirectly (Erickson et al. 2006; Freemark and
40
Boutin 1995; Jobin et al. 1997; Kleijn and Snoeijing 1997). Potential damage to nontargeted species is of particular consideration when the application site contains rare or
endangered species. Additionally, continuous herbicide use can move chemicals far from
the site of application and alter nutrient regimes (DiTomaso et al. 2006; Donald et al.
2001). Plus, without a follow-up removal, dead vegetation will remain aboveground,
which may make it difficult for shade-intolerant seedlings to germinate (Biggerstaff and
Beck 2007). Despite the concerns about herbicide applications, they can be advantageous
in that they leave root structures intact, which can prevent soil erosion. Also, the
phenology of the targeted plant is important to consider, for an herbicide can be
customized and applied at a time to optimally damage the invasive species with minimal
damage to other species that do not share the same life history traits (Crone et al. 2009).
Prescribed burning is a control method that is unfortunately more commonly
associated with introducing non-native species, rather than controlling them (Becker
1989). However, there are many instances of correctly timed prescribed burns that have
successfully removed perennial grasses (Becker 1989; Curtis and Partch 1948; Engle and
Bultsma 1984). Selective control is optimal in the presence of a heavy thatch to increase
fire intensity and timed so that tillers are elongated on the targeted species, but the native
species are still dormant. Generally, species that complete their life cycle before a
prescribed burn are selected for, whereas species that that flower and seed later in the
year are negatively impacted (DiTomaso et al. 2006). Studies usually demonstrate an
increase in species richness and diversity after a prescribed burn primarily due to an
increase in forbs rather than a reduction in the targeted invasive species (DiTomaso et al.
1999). Additionally, prescribed burning is accompanied by many added benefits,
41
including reduction of fuel loads, restoration of historical disturbance regimes, and
improvement of forage and habitat (DiTomaso et al. 2006).
The goal of this study was to examine the effects of prescribed burning and
herbicides, used as invasive species control techniques on native vegetation communities
in the Oregon Coast Range, and potentially throughout the western United States.
Although a removal method may be successful in eradicating the targeted invasive plant,
the method itself might not allow for the ecosystem to recover and reestablish (Zavaleta
et al. 2001). Our aim was to minimize B. sylvaticum abundance while simultaneously
maximizing native plant biodiversity. The specific objectives of the study were to: 1)
compare how different treatments alter total plant community cover, excluding B.
sylvaticum, after one growing season 2) describe the compositional changes in the plant
communities following control treatments, and 3) assess residual seed bank following
prescribed treatments. Treatments included the use of two herbicides and prescribed
burning in various combinations, for a total of nine treatments and a no-treatment control.
3.2
3.2.1
Methods
Experimental Design and Measurements
For a description of the study site and experimental design, please reference
Chapter 2 sections 2.2.1 and 2.2.2. Pre-treatment measurements included identifying B.
sylvaticum and all other vascular plants found at or below 0.5 meters in height and
visually estimating the percent cover to the nearest one percent of each species in each
quadrat. Percent cover readings were recorded during May and June 2013 (pre-treatment)
and June 2014 (first growing season after treatment). Quadrat measurements for each
42
species were then averaged over each treatment plot. We also measured environmental
variables including elevation, slope, aspect, and canopy cover for each plot. Following
the prescribed burns, scorch measurements were taken by visually estimating percent
scorch to the nearest one percent in each quadrat, then averaging over each treatment plot.
Seed bank experiments were similarly conducted as in Chapter 2 section 2.2.4. Emerging
seedlings were identified and counted for each tray over three months (Tables A-1, A-2).
A total of 53 species were identified in the field after one growing season and in the seed
bank experiment (Table 3.1).
3.2.2
Statistical Analyses
We compared the total percent cover of the plant community, excluding B.
sylvaticum, in the treatment plots to the control plots using a linear mixed model.
Average pre-treatment percent cover of the plant community was added as a covariate to
create a parallel lines model. For all linear mixed models in this study, random effects
included study blocks and the residual error term and fixed effects included treatments.
The response was natural log-transformed to produce normal residuals of the percent
cover of the plant community by treatment. To ensure a Type I error rate of 5%, we
performed a Bonferroni adjustment where the number of planned comparisons was nine.
Both the November and February seed bank sample data were analyzed as the
post-treatment field data. This allowed us to compare the total number of the plant
community’s viable seeds, excluding B. sylvaticum, in each treatment plot to the control
plots. Only one observation yielded an average total number of the plant community’s
viable seeds of zero, and was therefore removed from analysis. Treatment means for
43
percent surface area scorched, species richness, and species diversity (Shannon’s index)
were compared using a linear mixed model. All univariate analyses were performed using
RStudio version 0.98.490 (2013).
Multivariate statistics were used to evaluate how treatments impacted the overall
plant community. The field species matrix (120 treatment plots x 45 vascular plant
species) contained the average percent cover of each species over the 120 treatment plots.
The November and February seed bank sample species matrices contained 22 and 26
vascular plant species, respectively. The field environmental matrix (120 treatment plots
x 5 environmental variables) contained treatment, average percent cover of pre-treatment
B. sylvaticum, elevation, canopy cover, and potential direct incident radiation, which was
calculated using slope, aspect, and latitude with Equation 3 (McCune and Keon 2002).
Prior to analyses, we adjusted all (field, November soil samples, and February soil
samples) species data with a generalized logarithm (base 10) transformation to help
reduce the disproportionate influence of the most abundant species. Relativizations were
considered, but were not used to avoid amplifying noise by inflating weights given to rare
species. To further reduce overall noise, species that only occurred in one treatment plot
were deleted from the matrix (McCune and Grace 2002). Blocked multi-response
permutation procedure (MRBP) with Euclidean distance measures was used to test the
null hypothesis of no significant difference in species composition between treatments. A
priori groups were defined as the ten treatment types.
To graphically examine the relationship between species composition and
treatment type, we performed ordinations of treatment plots in species space using nonmetric multidimensional scaling (NMS; Kruskal 1964; Mather 1976; McCune and Grace
44
2002). NMS ordination was selected because the pairwise comparison of both species
percent cover and environmental variables yielded non-linear relationships. All
ordinations were performed using Euclidean distance measures with the autopilot option
set to medium, which represents a compromise between speed and thoroughness
(maximum of 200 iterations and an instability criterion of 0.00001) and no penalization
for ties (McCune and Grace 2002; McCune and Mefford 2011). This approach also
included Monte-Carlo (randomization) tests to determine whether the extracted axes are
stronger than expected by chance. In addition, all NMS ordinations began with a random
starting configuration. All ordinations were rotated to maximize the absolute value
correlation between post-treatment percent cover of B. sylvaticum or number of B.
sylvaticum seedlings and axis 1.
To evaluate the congruence between the two seed bank sample ordinations, we
performed a Mantel test using Euclidean distance measures (Mantel 1967). Mantel’s
asymptotic approximation was the default method for evaluating the test statistic. All
multivariate analyses were performed with PC-ORD version 6.12 (McCune and Mefford
2011).
3.3
3.3.1
Results
Total Plant Community Response
For a description of the percent area scorched and univariate B. sylvaticum
response analyses, please reference Chapter 2 section 2.3. Pre-treatment mean
community percent cover, excluding B. sylvaticum, was the same for all treatments (F9,99
= 1.24, P = 0.28). After accounting for pre-treatment mean community percent cover,
45
there is strong evidence that the median community percent cover between the control
plots and the treated plots was not equal (F9,98 = 31.72, P < 0.0001). When examined
individually against the control plots, all treatments’ relative median percent cover was
significantly less than the control plots, with the exception of the FB and FH treatments
(Figure 3.1) The FBFH treatment exhibited moderate reductions in median community
percent cover, decreasing to 3.42% cover (Bonferroni adjusted 95% CI:[1.22, 9.58])
(Table 3.2). All treatments that included a summer herbicide more dramatically and
uniformly reduced the ratio of relative median community percent cover to the controls.
The greatest reduction in relative median community cover was demonstrated by the
SHFBFH treatment, decreasing down to 0.87% to that of the controls (Bonferroni
adjusted 95% CI:[0.0026, 0.029]) (Figure 3.1).
Considering seed bank germination, after accounting for pre-treatment
community percent cover excluding B. sylvaticum, there is no evidence that the
differences in median average community seedlings between the control samples and the
treated samples collected in November are not equal to zero (F9,98 = 1.10, P = 0.37).
However, each treatment’s ratio of relative median total number of seedlings is below
that of the control (Figure 3.2).
In contrast, after accounting for pre-treatment community percent cover, there is
strong evidence that the differences in median average community seedlings between the
control samples and the treated samples collected in February are not equal to zero (F9,97
= 3.34, P = 0.0013). The control plots from the February samples yielded a median of
3786 viable seedlings, excluding B. sylvaticum, per soil sample (Bonferroni adjusted 95%
CI:[1526.82, 9381.89]) (Table 3.3). Only FBFH, FH, and SHFH treatments were
46
significantly different to the controls, with FBFH demonstrating the greatest reduction in
relative median number of community seedlings, decreasing down to 32% of the controls
(Figure 3.2).
3.3.2
Community Composition Response
Species richness in the field was greatly reduced by all treatments involving a
summer herbicide (Table 3.4). The November seed bank sample data also saw a
significant decrease in richness across all treatments except FB. The February seed bank
sample richness was a little more varied in that only SH, SHFBFH, SHFH, and SHSBFH
richness was significantly reduced. Shannon’s diversity was not as influenced by the
treatments; only SHFBFH significantly decreased in diversity compared to the controls in
the February seed bank assays. It should also be noted that the diversity in the pretreatment SHFB plots was significantly different from the controls. Consistent with this,
MRBP of the field data revealed that treatments differed in species composition (A =
0.20, P < 0.0001). MRBP of the greenhouse data sets exhibited no evidence that the
treatments differed in seed bank species composition (November samples: A = 0.066, P <
0.0001; February samples: A = 0.077, P < 0.0001).
Ordination of the field data converged on a 2-dimensional solution (Figure 3.3;
final stress = 14.71, final instability < 0.00001, iterations = 71, P = 0.0196). The two axes
cumulatively accounted for 89.6% of the overall variation (axis 1 r2 = 0.720, axis 2 r2 =
0.176). Post-treatment percent cover of B. sylvaticum was positively correlated with axis
1 (r = 0.76) (Table 3.5). The NMS ordinations show treatments appear to separate along
axis 1 according to their respective percent cover of B. sylvaticum. Plots of the control
47
treatment are found on the most positive side of axis 1 in the field study (Figure 3.3).
Nearby other widely distributed plots in species space are treatments FB, FH, and FBFH.
Treatment blocks with significantly less percent cover of B. sylvaticum are shown on the
negative side of axis 1, all of which include a summer herbicide treatment. Of the 41
species of plants in the adjusted data set, over half were also positively correlated with
axis 1; ten of these species showed at least moderate (r > 0.30) positive correlation with
axis 1. The species with the strongest positive correlation included: trailing blackberry
(Rubus ursinus Cham. & Schltdl.), poison oak (Toxicodendron diversilobum (Torr. & A.
Gray) Greene), and yerba buena (Clinopodium douglasii (Benth.) Kuntze). The only
species to be moderately negatively correlated with axis 1 is an unidentified dicotyledon.
None of the environmental variables were considered moderately correlated with either
axis (Table 3.6).
The NMS ordination for November seed bank sampling data, like the field data,
converged on a 2-dimensional solution (Figure 3.4; final stress = 15.94; final instability <
0.0001; iterations = 53; P = 0.0196) but showed no shift in species composition due to
treatments. The two axes cumulatively accounted for 86.7% of the overall variation (axis
1 r2 = 0.368, axis 2 r2 = 0.499). Post-treatment percent cover of B. sylvaticum was
positively correlated with axis 1 (r = 0.74) (Table 3.7). Of the 17 species in the adjusted
data set, over half were positively correlated with axis 1. Only two of these showed
moderate (r > 0.30) positive correlation with axis 1. These included bristly dogstail grass
(Cynosurus echinatus L.) and St. Johnswort (Hypericum perforatum L.). Of the species
that were negatively correlated with axis 1, all were weakly correlated (r < 0.30). None of
48
the environmental variables were considered moderately correlated with either axis
(Table 3.6).
Finally, the February seed bank data ordination also converged on a 2dimensional solution (Figure 3.5; final stress = 12.68; final instability < 0.0001; iterations
= 101; P = 0.0392) again showing no shift in species composition due to treatments. The
two axes cumulatively accounted for 88.5% of the overall variation (axis 1 r2 = 0.163;
axis 2 r2 = 0.722). Post-treatment percent cover of B. sylvaticum was positively correlated
with axis 1 (r = 0.89) (Table 3.7). Of the 19 species in the adjusted data set, about half
were positively correlated with axis 1. However, none showed even moderate correlation
either positively or negatively with axis 1. None of the environmental variables showed
moderate correlation with axis 1, but incident radiation and pre-treatment percent cover
of B. sylvaticum showed moderate positive correlation with axis 2 (Table 3.6). The two
greenhouse NMS ordinations were found to be statistically similar to one another (Mantel
r = 0.29; P < 0.0001; 8.50% redundancy).
3.4
3.4.1
Discussion
Total Plant Community Response
While summer herbicide treatments dramatically decrease plant community cover
in the field, fall herbicide treatments only slightly decrease plant community cover, if at
all. The summer herbicide used was a broad-spectrum, non-selective systemic herbicide
and was applied during the active growing season, so it is not unusual to see such a
severe reduction in plant community cover (Clark et al. 2004; Simmons et al. 2007). The
fall herbicide is primarily used to control a wide range of annual and perennial grasses as
49
well as broad-leafed weeds, with pre- and post-emergence uses (Harvey et al. 1985;
SERA 2004; Trubey et al. 1998). Its purpose in this study was to eliminate B. sylvaticum
seedlings that quickly germinated after the previous treatments, with minimal damage to
the rest of the plant community compared to the more broad-spectrum summer herbicide.
The fall herbicide treatment alone did succeed in maintaining the plant community’s
cover, but as discussed in Chapter 2, this treatment was not effective in reducing B.
sylvaticum cover in the field. The generally poor performance of the fall herbicide alone
in significantly reducing any vegetative cover in the field may be due to low application
rates when compared to the summer herbicide. We did not use the same herbicide
prescription, so direct comparisons cannot be made.
There is potential to maintain the plant community post-treatment through the
seed bank. Seeds collected in November showed no difference in number of viable seeds
compared to the controls, whereas, differences between treatments were demonstrated in
the February samples. This suggests that immediately following these treatments the
community seed bank is still intact, possibly due to lack of time for competition between
seedlings to occur in the field. Of the February samples, only FBFH, FH, and SHFH
showed any significant reduction in the plant community seed bank, all of which included
the pre-emergent fall herbicide. The use of a fall pre-emergent herbicide may reduce the
number of viable community seeds the first year.
Prescribed underburning in this range of intensity and seasonality does not
negatively affect the abundance of seed associated with the native plant community.
When a grassland is burned, generally, seeds are not exposed to lethal temperatures
(Daubenmire 1968). To eliminate seeds, burning should be conducted before the seeds
50
have dispersed and have fully cured (Brooks 2001; Ditomaso et al. 2006). The summer
burns were conducted before the 2013 B. sylvaticum seeds were dispersed. B.
sylvaticum’s seed banks are exceptionally short-lived, so the past year’s seed bank may
have been present, but beyond that is unlikely (Grime et al. 1988). Many other seeds of
the plant community with longer-lived seed banks that had fallen in seasons prior had
likely accumulated and left unharmed by both prescribed burns. Although the fall
prescribed burn was conducted after the dispersal of B. sylvaticum seeds, it was likely not
sufficiently intense to eliminate any seeds that had already fallen.
Although treatments with an aggressive summer herbicide demonstrated dramatic
reductions in the plant community cover one year after treatments, the number of viable
community seeds was maintained with the exception of the SHFH treatment. These
summer treatments also are most effective at reducing both B. sylvaticum cover in the
field and number of viable B. sylvaticum seeds one year after treatments (see Chapter 2).
Despite the severe reduction in cover in this study and others (Clark et al. 2004; Simmons
et al. 2007), the community seed bank is still present, and nearly absent of B. sylvaticum
seeds. These treatments therefore show great promise in controlling B. sylvaticum
populations while managing the recovery of the plant community.
3.4.2
Community Composition Response
Summer herbicide applications have immediate profound effects on native plant
community composition. In this study, species richness in the field and both greenhouse
samples was greatly reduced by herbicide application. Shannon’s diversity was not as
affected; although, the SHFBFH February seed bank sample was the only treatment to
51
decrease compared to the controls. There were also no identifiable species that were even
moderately negatively correlated with B. sylvaticum. This may indicate that the plants
associated with the treatments resulting in a decrease in B. sylvaticum require more time
than one growth season to reestablish. Blakeley-Smith (2007) saw an increase in native
species after three growing seasons after various herbicide applications to remove B.
sylvaticum in Butterfly Meadows, Benton County, OR. However, his study also
experienced a significant increase in introduced species in half of the 14 herbicide
treatments studied. If we were to sample the community again in the following years, and
allow the plant community to grow and develop, we would be able to draw more
substantial conclusions as to which species flourish after each treatment with a significant
reduction in B. sylvaticum.
The lack of native species’ viable seeds associated with a decrease in B.
sylvaticum may be due to limited recruitment. Commonly, introduced species will
recover and reestablish by the second growing season after a control treatment. These
species often have well-stocked seed banks and are relatively tolerant to control measures
(Wilson et al. 2004). Since the McDonald Forest had been dominated by B. sylvaticum
and other introduced species for many years, these study sites were likely saturated with
this species’ seeds. After treatments, the seed bank assays should have shown what native
plant seeds were still viable in these sites. However, since only non-native seeds showed
any positive association with B. sylvaticum, this indicates that either the native seeds are
more susceptible to the treatments, or that there simply was not a large viable native seed
bank to begin with. This is possibly due to recruitment limitations. Seeding grassland
study sites with native species have demonstrated that native species are strongly
52
recruitment limited (Tilman 1997; Seabloom et al. 2003a; Seabloom et al. 2003b). There
is also evidence that repeated applications of the control treatments are all that is
necessary to eliminate invasives while allowing natives to reestablish (Annen et al. 2005;
Randall 1996; Rice et al. 1997). Other studies encourage a more integrated approach that
requires both controlling the invasive while strengthening natives (Hurst and John 1999;
MacDougal and Turkington 2005; Wilson et al. 2004).
After one growing season, however, the resulting community, despite treatment,
does not show promise for a future diverse community. The species most strongly
associated with B. sylvaticum in the field after treatments were trailing blackberry, poison
oak, and yerba buena, all of which are native species to the area. Trailing blackberry and
poison oak commonly form dense, dominant patches from root suckers and rhizomes,
respectively, after a disturbance, and yerba buena is often associated with trailing
blackberry (Finn and Wennstrom 2003; LPN 2014; UCANR 2009). In the greenhouse,
dogstail grass and St. Johnswort were most associated with B. sylvaticum, both of which
are introduced species to the western U.S.
There was little environmental difference across this experiment to add variability.
None of the environmental variables were consistently moderately associated either axis
over all data sets, so little inference should be made regarding elevation, radiation,
percent canopy cover, pre-treatment B. sylvaticum percent cover, and number of dead
seedlings in seed bank assay. Moreover, range of elevation within the blocks was small
(171 feet to 260 meters), as were radiation, percent canopy cover, and pre-treatment B.
sylvaticum percent cover. Some of the species patterns seen may be driven by other
environmental factors not taken into account such as soil type and water availability.
53
3.5
Management Implications
Treatments with an aggressive, foliar summer-applied herbicide reduce existing B.
sylvaticum plants as well as viable seeds one year after treatment; however, such
treatments also immediately reduce native species cover, richness, and, in the case of
SHFBFH, diversity. Although the total number of viable seeds in the community seed
bank after all treatments (except FH, FBFH, and SHFH) are maintained compared to that
of the control, species richness results and NMS ordinations indicate that the resulting
community will not immediately consist of diverse, native species. In addition, a fallapplied pre-emergent herbicide may reduce the number of viable community seeds.
These results are similar to those found in herbicide only study (Blakeley-Smith 2007);
however, B. sylvaticum reestablished after the first growing season in that study.
Treatments without the summer herbicide did not reduce B. sylvaticum after one
growth season, but they did maintain species richness and diversity. Although, the
species strongly associated with these treatments were primarily dominant shrubs or
introduced weeds. Prescribed burning preceded by an aggressive summer-applied
herbicide did not directly exhibit any negative effects on the plant community. However,
without the summer-applied herbicide, a fall prescribed burn may stimulate B. sylvaticum
abundance (Poulos 2013, Chapter 2). To manage for the necessary fire intensity, one
must apply a broad-spectrum herbicide prior to the prescribed burn to provide sufficient
dry fuels. Plus, landowners may achieve additional objectives with a prescribed burn such
as reducing hazardous fuels, improving wildlife habitat, and preparing sites for seeding or
planting. Fire, and repeated fire, is known to stimulate rich plant community responses
(Becker 1989; Smith and Knapp 1999; Smith and Knapp 2001).
54
Long-term observations should be made to thoroughly understand the effects of
these individual treatments on species composition in the Oregon Coast Range.
Additionally, repeated treatment applications should be explored to determine how many
seasons of herbicides and/or prescribed burning are necessary to attain desired plant
communities in terms of cover and composition. Given grass’ short viable seed life, it is
possible that only one or two seasons of optimal treatments will be required to control B.
sylvaticum without detrimental impacts of native plant communities. This would
potentially save money and labor on herbicide treatment efforts and minimize other longterm ecosystem changes.
55
Table 3.1. Collective 4-letter species codes, scientific names, and common names of
all species identified in the field post-treatment and in the seed bank assays.
Code
ACMA
ACSP
ADBI
ALSP
AMAL
ANMA
BRSY
CABU
CANU
CASP
CIAR
CISP
CIVU
CLDO
COCA
COCO
COHE
CYEC
EPCI
FESP
FRPU
FRVE
GASP
GOOB
HYPE
HYRA
Scientific Name
Acer macrophyllum
Acer spp.
Adenocaulon bicolor
Alnus spp.
Amelanchier alnifolia
Anaphalis margaritacea
Brachypodium sylvaticum
Calypso bulbosa
Cardamine nuttallii
Carex spp.
Cirsium arvense
Cirsium spp.
Cirsium vulgare
Clinopodium douglasii
Conyza canadensis
Corylus cornuta
Collomia heterophylla
Cynosurus echinatus
Epilobium ciliatum
Festuca spp.
Frangula purshiana
Fragaria vesca
Galium spp.
Goodyera oblongifolia
Hypericum perforatum
Hypochaeris radicata
Common Name
bigleaf maple
maple species
American trailplant
alder species
Saskatoon serviceberry
western pearly everlasting
false brome
fairy slipper
palmate toothwort
sedge species
Canada thistle
thistle species
bull thistle
yerba buena
Canadian horseweed
California hazelnut
variableleaf collomia
bristly dogstail grass
fringed willowherb
fescue species
Cascara buckthorn
woodland strawberry
bedstraw species
western rattlesnake plantain
St. Johnswort
hairy cat's ear
Code
LEVU
LOHI
LOMI
MIDE
MYMU
NEPA
OECE
OESA
OSBE
POMU
PSME
PTAQ
QUGA
RAOC
ROGY
RUAC
RUUR
SACR
SESY
SYAL
TODI
UGR1
UNK1
UNK2
UNKC
VIGL
VISP
Scientific Name
Leucanthemum vulgare
Lonicera hispidula
Lotus micranthus
Mimulus dentatus
Mycelis muralis
Nemophila parviflora
Oemleria cerasiformis
Oenanthe sarmentosa
Osmorhiza berteroi
Polystichum munitum
Pseudotsuge menziesii
Pteridium aquilinum
Quercus garryana
Ranunculus occidentalis
Rosa gymnocarpa
Rumex acetosella
Rubus ursinus
Sanicula crassicaulis
Senecio sylvaticus
Symphoricarpos albus
Toxicodendron diversilobum
Viola glabella
Vicia spp.
Common Name
oxeye daisy
pink honeysuckle
desert deervetch
coastal monkeyflower
wall-lettuce
smallflower nemophila
Indian plum
water parsley
sweetcicely
western swordfern
Douglas-fir
western brackenfern
Oregon white oak
western buttercup
dwarf rose
common sheep sorrel
California blackberry
Pacific blacksnakeroot
woodland ragwort
snowberry
Pacific poison oak
unknown grass 1
unknown 1
unknown 2
unknown cotyledon
pioneer violet
vetch species
56
Table 3.2. Median post-treatment plant community, excluding B. sylvaticum, percent
cover estimates compared to the control plots with Bonferroni adjusted 95%
confidence intervals. Treatments significantly different from the control are marked
with a *.
Treatment
Control
FB
FBFH
FH
SH
SHFB
SHFBFH
SHFH
SHSB
SHSBFH
Estimate
15.94
11.75
3.42
5.31
0.65
0.24
0.14
0.37
0.42
0.24
*
*
*
*
*
*
*
Field
Lower CI
5.69
4.12
1.22
1.83
0.22
0.076
0.045
0.12
0.14
0.081
Upper CI
44.64
33.48
9.58
15.41
1.90
0.74
0.42
1.14
1.23
0.69
Table 3.3. Median number of viable community seeds per 1 m2 , excluding B.
sylvaticum, germinated in the greenhouse for November and February samples with
Bonferroni adjusted 95% confidence intervals. Treatments significantly different
from the control are marked with a *.
Treatment
Control
FB
FBFH
FH
SH
SHFB
SHFBFH
SHFH
SHSB
SHSBFH
Seed Bank - November
Estimate
Lower CI
Upper CI
5051.24
1799.14
14181.77
3513.45
1230.16
10034.74
2389.65
850.59
6713.48
2921.90
1004.62
8498.28
3089.75
1059.68
9008.89
2004.38
639.27
6284.59
2515.06
820.17
7712.46
2107.65
684.73
6487.52
3158.84
1060.82
9406.13
2053.76
698.01
6042.78
Seed Bank - February
Estimate
Lower CI
Upper CI
3785.77
1526.82
9381.89
2742.19
1093.49
6876.69
1193.61 * 481.31
3622.36
1426.76 * 561.97
2960.07
2316.36
910.81
5890.93
2992.61
1119.57
7999.25
2205.45
826.55
5884.66
1543.84 * 584.96
4074.54
2729.75
1058.07
7043.54
2386.28
932.53
6106.33
57
Table 3.4. Mean species richness and Shannon’s diversity index for pre-treatment,
post-treatment field, November seed bank samples, and February seed bank
samples. Numbers in parentheses are standard deviations. Treatments that are
significantly different from the control are marked with a *.
Treatment
Control
FB
FBFH
FH
SH
SHFB
SHFBFH
SHFH
SHSB
SHSBFH
Pre-treatment
4.69 (1.56)
4.58 (1.56)
4.75 (1.37)
4.56 (1.50)
4.98 (1.79)
4.60 (1.43)
4.92 (1.44)
4.42 (1.30)
4.21 (1.16)
4.10 (0.96)
Treatment
Control
FB
FBFH
FH
SH
SHFB
SHFBFH
SHFH
SHSB
SHSBFH
Pre-treatment
1.25 (0.30)
1.18 (0.37)
1.25 (0.39)
1.18 (0.39)
1.15 (0.43)
0.97 (0.44) *
1.29 (0.41)
1.10 (0.30)
1.09 (0.45)
1.08 (0.39)
Species Richness
Post-treatment
Seed Bank - Nov.
5.06 (1.43)
2.17 (0.58)
4.56 (1.48)
1.88 (0.60)
4.06 (0.87)
1.28 (0.68) *
4.15 (1.12)
1.52 (0.66) *
2.92 (0.79) *
1.44 (0.56) *
2.92 (0.72) *
1.21 (0.53) *
2.04 (1.08) *
1.06 (0.30) *
1.96 (0.73) *
1.23 (0.52) *
3.50 (0.83) *
1.35 (0.60) *
2.63 (0.71) *
1.15 (0.36) *
Seed Bank - Feb.
2.04 (0.90)
1.90 (0.55)
1.52 (0.61)
1.71 (0.68)
1.35 (0.29) *
1.52 (0.64)
1.06 (0.61) *
1.06 (0.48) *
1.65 (0.46)
1.21 (0.44) *
Shannon's Diversity Index
Post-treatment
Seed Bank - Nov.
1.33 (0.32)
0.72 0.41
1.21 (0.32)
0.78 0.32
1.28 (0.48)
0.68 0.37
0.99 (0.47)
0.57 0.35
1.06 (0.51)
0.48 0.31
1.35 (0.45)
0.55 0.61
1.00 (0.52)
0.34 0.35
0.89 (0.50)
0.48 0.48
1.44 (0.36)
0.40 0.35
1.31 (0.42)
0.60 0.43
Seed Bank - Feb.
0.84 (0.59)
0.86 (0.58)
0.88 (0.42)
0.81 (0.41)
0.65 (0.53)
0.58 (0.51)
0.37 (0.47) *
0.49 (0.51)
0.81 (0.55)
0.54 (0.46)
58
Table 3.5. NMS ordination summary of the correlation coefficients of each species
with each axis for post-treatment field data. Species are labeled by their four-letter
species code.
Axis
Species
ACMA
ACSP
ADBI
ALSP
AMAL
BRSY
CABU
CANU
CISP
CLDO
COCO
COHE
CYEC
FESP
FRVE
GASP
GOOB
HYPE
LOHI
LOMI
MYMU
Field
1
2
Axis
Correlation Coefficient
Species
-0.121
-0.022
NEPA
0.117
-0.082
OECE
0.102
0.052
OESA
0.121
0.109
OSBE
0.217
0.218
POMU
0.758
0.021
PSME
-0.089
-0.102
PTAQ
-0.053
0.157
QUGA
-0.236
-0.026
RHPU
0.718
-0.067
ROGY
0.386
-0.023
RUUR
-0.088
0.020
SACR
-0.043
-0.127
SESY
-0.171
-0.166
SYAL
0.241
0.059
TODI
0.193
0.163
UNK1
-0.162
-0.053
UNK2
0.116
-0.096
UNKC
0.517
-0.260
VIGL
-0.076
-0.052
VISP
0.131
0.167
1
2
Correlation Coefficient
-0.038
-0.070
0.319
-0.011
0.269
-0.307
0.493
-0.079
0.087
0.758
-0.109
-0.041
0.445
0.136
0.093
-0.138
0.087
-0.081
0.360
-0.106
0.866
0.324
0.170
-0.0269
-0.212
0.017
0.454
-0.219
0.861
0.029
-0.091
-0.02
-0.029
0.082
-0.347
-0.043
0.053
0.123
-0.089
0.000
Table 3.6. NMS ordination summaries of correlation coefficients of each
environmental variable by each axis.
Field
Axis
1
2
Environmental Variable
Correlation Coefficient
Elevation
-0.234
-0.231
Radiation
-0.124
-0.224
Pre-treatment B. sylvaticum
-0.151
-0.125
Canopy cover
-0.160
-0.004
Seed Bank - November
1
2
Correlation Coefficient
-0.147
-0.159
0.109
0.172
0.170
0.21
-0.191
-0.083
Seed Bank - February
1
2
Correlation Coefficient
0.169
-0.154
-0.008
0.476
0.077
0.355
0.008
-0.015
59
Table 3.7. NMS ordination summary of the correlation coefficients of each species
with each axis for November and February seed bank data. Species are labeled by
their four-letter species code.
Seed Bank - November
Axis
1
2
Species
Correlation Coefficient
ANMA
0.115
-0.095
BRSY
0.735
0.160
CIAR
-0.138
0.053
CISP
0.038
0.157
CIVU
0.200
-0.022
COCA
-0.049
-0.278
CYEC
0.362
0.131
EPCI
0.03
-0.021
GASP
-0.058
-0.082
HYPE
0.623
0.968
HYRA
0.007
-0.115
LEVU
0.174
0.189
MIDE
0.097
0.024
RUUR
-0.133
-0.019
SESY
-0.224
-0.112
UGR1
-0.041
0.039
VISP
0.017
0.080
Seed Bank - February
Axis
1
2
Species
Correlation Coefficient
ACSP
0.010
-0.026
ANMA
0.009
0.004
BRSY
0.892
-0.044
CASP
0.205
-0.131
CIAR
0.249
-0.071
CISP
-0.075
0.086
CIVU
-0.152
0.084
COCA
0.026
0.110
COHE
-0.046
-0.162
CYEC
0.221
0.043
EPCI
0.109
-0.181
HYPE
-0.163
0.995
LEVU
-0.057
0.105
LOMI
-0.181
-0.065
RUUR
-0.017
-0.372
SESY
0.151
-0.128
UNK1
0.092
-0.166
VISP
-0.174
0.101
UNKC
-0.120
-0.153
60
Figure 3.1. Plot describing the ratio of the relative median plant community,
excluding B. sylvaticum, percent cover compared to the control plots. Whiskers
represent Bonferroni adjusted 95% confidence intervals. Solid horizontal line at 1.0
represents the same median percent cover of the plant community to that of the
control plots.
61
A
B
Figure 3.2. Plot describing the ratio of the relative median number of viable
seedlings in the plant community, excluding B. sylvaticum, for seed bank samples
collected in (A) November and (B) February compared to the control samples.
Whiskers represent Bonferroni adjusted 95% confidence intervals. Solid horizontal
line at 1.0 represents the same median number of viable seedlings in the plant
community to that of the control plots.
62
Figure 3.3. 2-dimensional NMS ordination of the post-treatment field data using
Euclidean distances of treatment plots in species space. Treatment plots that are
closer to each other are more similar with respect to species composition than those
farther apart.
63
Figure 3.4. 2-dimensional NMS ordination of the November seed bank samples
using Euclidean distances of treatment plots in species space. Treatment plots that
are closer to each other are more similar with respect to species composition than
those farther apart.
64
Figure 3.5. 2-dimensional NMS ordination of the February seed bank samples using
Euclidean distances of treatment plots in species space. Treatment plots that are
closer to each other are more similar with respect to species composition than those
farther apart.
65
4
4.1
CONCLUSION
Research Summary
Controlling invasive plant species like B. sylvaticum to preserve the integrity and
productivity of a forest can be costly and time-consuming. Detailed prescriptions are
often required to meet specific objectives of the forest managers. Herbicides and
prescribed burning have been widely used as restoration tools to control existing and
future invasive species populations; however, they can also promote the immediate
growth of other non-native species and/or otherwise alter the plant community in
undesirable ways. This could potentially alter the ecosystem’s ecological functions,
productivity, and/or disturbance regimes (Brooks et al. 2004; Cowling 1987; DiTomaso
et al. 2005).
One aim of this thesis was to determine if herbicides and prescribed burning
singly or in combination could successfully control B. sylvaticum populations in the
McDonald Forest. Through field and seed bank assays, it was determined that treatments
with an aggressive, broad-spectrum, foliar herbicide applied in the summer were most
effective in reducing not only the existing B. sylvaticum, but also the residual seed bank
one year after application. This success can be partly attributed to the strength of the
herbicide as well as its timing, for the herbicide was applied before the B. sylvaticum
plants had set seed, thereby eliminating any production of seeds for the current growth
season. Although the prescribed burns that followed the summer herbicide treatments
demonstrated no added benefit in controlling B. sylvaticum in this study, they have the
potential to eliminate a more persistent residual seed bank.
66
The second aim of this thesis was to determine how the herbicide and prescribed
burn treatments might have a larger effect on the plant community. Such findings can be
greatly beneficial for defending weed management objectives and promoting restoration
efforts, for particular removal methods may not be conducive to allowing native
communities to recover and reestablish itself. In the McDonald Forest, all treatments
involving a summer herbicide resulted in plant communities with very low species
richness, nearly no change to the diversity index, and a notable shift in species
composition. The treatments without a summer herbicide showed greater species richness,
but the remaining species were primarily dominant shrubs or non-native weeds. A second
growth season to allow the plant community to establish itself may shed more light on
how the individual treatments affect the plant community.
4.2
Directions for Future Research
Herbicide treatments to control B. sylvaticum are well studied; however, this
research project can kick-start an investigation of controlling the invasive grass with
prescribed burning treatments alone or in combination with herbicides. The primary goal
of this research was to explore how the herbicide and prescribed burning treatments
impact B. sylvaticum and the native plant community. It also provides a template for
longer-term monitoring of site development and reinvasion.
Although this research initiates the exploration of the relationship between the
cost-effective control methods and the invaded plant community, long-term observations
are necessary to thoroughly understand the effects of the treatments on both B. sylvaticum
and the species composition. Other experimental herbicide control studies have observed
67
significant reductions of B. sylvaticum cover in the field after one growing season, but
cover returned to levels of the controls by the second (Blakeley-Smith 2007; Hurst and
John 1999). However, these studies did not examine the residual seed bank or seed
recruitment. Without seed recruitment, our study indicates that treatments with a summer
herbicide can effectively control B. sylvaticum for longer than one growing season. To
further examine the length of effectiveness, future studies should monitor seed
recruitment with exclosures to reduce the amount of wildlife moving through study plots
and dispersing B. sylvaticum seeds. This will help determine if reestablishment is due to
existing, surviving B. sylvaticum seeds and vegetation or from outside recruitment. When
not carried by animals, B. sylvaticum seeds fall directly below the parent plant (Heinken
and Raudnitschka 2002), so exclosures in addition to summer-applied aggressive
herbicides may provide long-term control of the invasive grass.
Additionally, repeated treatment applications can be explored to determine how
many seasons of herbicides and/or prescribed burning are necessary to attain the desired
plant community. Due to B. sylvaticum’s short viable seed life, it is possible that only one
or two season of optimal treatments will be require to control the existing invasive grass,
but again, recruitment will have to be monitored or controlled.
Lastly, my study design can be improved in several ways for the purpose of
repeating the experiment. Ideally, the study blocks should be randomly established
throughout the study site to make stronger inferences as to the effectiveness of the
treatments. Also, pre-treatment soil samples for the seed bank assay should be collected
to assess the existing seed bank prior to treatments. In our study, only post-treatment soil
samples were collected with the intention of comparing treated soil samples with control
68
soil samples. However, we were left to speculate as to why the summer herbicide only
treatment significantly reduced number of B. sylvaticum seeds when a residual seed bank
should be present. Finally, fire intensity in addition to measures of severity should be
monitored during prescribed burns to better quantitatively examine the relationship
between intensity and abundance of B. sylvaticum and the plant community. Temperature
sensitive paints were placed in each quadrat of each prescribed burn plot to quantitatively
account for fire intensity. Unfortunately, the paints were largely ineffective and did not
capture fire temperatures either due to extremely low fire intensity or that the paints used
were too old. Videos of each prescribed burn were taken to visually record fire intensity,
but can only be used for comparing relative fire intensity and behavior between each
prescribed burn.
This research and future similar studies can be used to develop and refine efficient,
cost-effective techniques for controlling B. sylvaticum populations and protecting native
vegetation in the Oregon Coast Range, and potentially throughout the western United
States. This may lead to improved forest productivity and maintenance of natural
ecosystem functioning in B. sylvaticum invaded sites.
69
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80
APPENDIX
81
Table A - 1. Number of viable seeds of each species per treatment to germinate from
November seed bank samples. Number of seeds was converted from number per soil
sample to number per 1 m2 to a depth of 5 cm. See Table 3.1 for scientific and
common names of the 4-letter species codes.
Code
ACSP
ANMA
BRSY
CIAR
CISP
CIVU
COCA
CYEC
EPCI
GASP
HYPE
HYRA
LEVU
MIDE
NEPA
PSME
RAOC
RUUR
SESY
UGR1
UNKC
VISP
Control
0
10.61
594.33
137.97
31.84
53.07
21.23
10.61
31.84
0
5327.73
0
42.45
0
0
0
0
84.90
31.84
21.23
0
0
FB
0
31.84
541.26
116.74
10.61
53.07
0
42.45
53.07
10.61
3650.87
0
53.07
10.61
0
0
10.61
21.23
10.61
10.61
0
0
FBFH
0
21.23
318.39
31.84
0
53.07
10.61
127.36
10.61
10.61
2642.64
0
10.61
0
0
0
0
31.84
21.23
0
10.61
10.61
FH
0
10.61
392.68
53.07
0
10.61
21.23
159.20
10.61
0
4202.75
0
63.68
0
0
10.61
0
0
21.23
0
0
0
SH
0
10.61
74.29
106.13
10.61
84.90
0
21.23
10.61
21.23
3841.91
21.23
42.45
10.61
0
0
0
31.84
31.84
10.61
0
0
SHFB SHFBFH SHFH
0
0
0
10.61
10.61
21.23
53.07
21.23
53.07
116.74
31.84
63.68
10.61
0
0
21.23
42.45
10.61
0
0
21.23
0
0
42.45
31.84
10.61
10.61
0
10.61
0
3396.16 4001.10 2451.60
0
0
10.61
10.61
10.61
42.45
0
0
0
0
0
0
0
0
0
0
0
0
31.84
10.61
10.61
74.29
63.68
21.23
0
0
0
0
0
0
0
0
10.61
SHSB SHSBFH
10.61
0
0
10.61
21.23
0
180.42
63.68
31.84
10.61
21.23
191.03
0
10.61
10.61
21.23
0
0
0
0
4521.14 3353.71
0
10.61
31.84
53.07
0
0
0
10.61
0
0
0
0
31.84
0
10.61
42.45
53.07
0
0
0
10.61
0
82
Table A - 2. Number of viable seeds of each species per treatment to germinate from
February seed bank samples. Number of seeds was converted from number per soil
sample to number per 1 m2 to a depth of 5 cm. See Table 3.1 for scientific and
common names of the 4-letter species codes.
Code
ACSP
ANMA
BRSY
CASP
CIAR
CISP
CIVU
COCA
COHE
CYEC
EPCI
GASP
HYPE
HYRA
LEVU
LOMI
PSME
RUAC
RUUR
SESY
TODI
UGR1
UNK1
UNK2
UNKC
VISP
Control
0
10.61
329.00
106.13
127.36
21.23
53.07
10.61
10.61
31.84
21.23
0
5126.08
0
31.84
0
0
0
31.84
95.52
0
0
0
0
0
0
FB
10.61
0
350.23
84.90
169.81
21.23
21.23
0
0
0
21.23
0
2982.26
0
42.45
0
10.61
31.84
53.07
0
0
21.23
0
0
10.61
0
FBFH
0
21.23
297.16
0
95.52
10.61
42.45
10.61
0
21.23
31.84
0
1337.24
0
10.61
0
0
0
10.61
53.07
0
0
0
0
0
0
FH
0
0
424.52
42.45
74.29
10.61
63.68
21.23
0
21.23
10.61
0
1889.12
0
106.13
0
0
0
63.68
10.61
0
0
0
0
0
0
SH
0
21.23
10.61
10.61
63.68
53.07
42.45
10.61
0
0
21.23
0
2939.80
0
21.23
10.61
0
0
10.61
74.29
0
0
0
0
10.61
10.61
SHFB SHFBFH SHFH
0
0
0
0
21.23
10.61
21.23
21.23
31.84
31.84
21.23
10.61
127.36
31.84
21.23
31.84
0
21.23
10.61
53.07
53.07
0
0
0
10.61
0
0
0
0
10.61
21.23
10.61
31.84
0
0
0
3343.10 3067.16 2303.02
0
0
0
0
0
31.84
10.61
0
0
0
0
0
0
0
0
63.68
31.84
21.23
42.45
10.61
21.23
0
10.61
0
0
0
0
10.61
0
0
0
0
0
10.61
0
0
0
0
0
SHSB SHSBFH
10.61
10.61
0
0
53.07
21.23
95.52
42.45
148.58
84.90
95.52
10.61
42.45
10.61
21.23
0
0
10.61
0
10.61
31.84
0
10.61
0
4001.10 3374.94
0
0
0
21.23
0
0
0
0
0
0
53.07
74.29
0
10.61
0
0
0
0
31.84
0
10.61
0
0
0
21.23
10.61